KEK Report 2010-1
October 2010
H

Belle II Technical Design Report

Belle

Edited by: Z. Doležal and S. Uno

High Energy Accelerator Research Organization

BelleKEK Report 2010-1

Copyright notice
Copyright c 2010, Belle II Experiment
Permission is granted to reproduce this document for internal use only.
Belle II Secretariat
Belle group, Physics Division I,
KEK(High Energy Accelerator Research Organization)
Institute of Particle and Nuclear Studies
1-1 Oho, Tsukuba-shi, Ibaraki-ken, 305-0801, Japan
Phone : +81-298-64-5342
Fax : +81-298-64-5340
Version: 1.5
October 28, 2010.
Edited by: Z. Doležal and S. Unoi

T. Abe,55 I. Adachi,13 K. Adamczyk,37 S. Ahn,23 H. Aihara,55 K. Akai,13 M. Aloi,30 L. Andricek,29 K. Aoki,13
Y. Arai,13 A. Arefiev,20 K. Arinstein,3, 40 Y. Arita,31 D. M. Asner,42 V. Aulchenko,3, 40 T. Aushev,20 T. Aziz,51
A. M. Bakich,50 V. Balagura,20 Y. Ban,44 E. Barberio,30 T. Barvich,22 K. Belous,18 T. Bergauer,17 V. Bhardwaj,43
B. Bhuyan,14 S. Blyth,35 A. Bondar,3, 40 G. Bonvicini,59 A. Bozek,37 M. Bračko,28, 21 J. Brodzicka,37
O. Brovchenko,22 T. E. Browder,11 G. Cao,16 M.-C. Chang,6 P. Chang,36 Y. Chao,36 V. Chekelian,29
A. Chen,34 K.-F. Chen,36 P. Chen,36 B. G. Cheon,10 C.-C. Chiang,36 R. Chistov,20 K. Cho,23 S.-K. Choi,9K. Chung,49 A. Comerma,1 M. Cooney,11 D. E. Cowley,42 T. Critchlow,42 J. Dalseno,29, 52 M. Danilov,20
A. Dieguez,1 A. Dierlamm,22 M. Dillon,30 J. Dingfelder,2 R. Dolenec,21 Z. Doležal,4 Z. Drásal,4 A. Drutskoy,5
W. Dungel,17 D. Dutta,14 S. Eidelman,3, 40 A. Enomoto,13 D. Epifanov,3, 40 S. Esen,5 J. E. Fast,42 M. Feindt,22
M. Fernandez Garcia,46 T. Fifield,30 P. Fischer,12 J. Flanagan,13 S. Fourletov,2 J. Fourletova,2 L. Freixas,1A. Frey,8 M. Friedl,17 R. Frühwirth,17 H. Fujii,13 M. Fujikawa,33 Y. Fukuma,13 Y. Funakoshi,13 K. Furukawa,13
J. Fuster,57 N. Gabyshev,3, 40 A. Gaspar de Valenzuela Cueto,45 A. Garmash,3, 40 L. Garrido,1 Ch. Geisler,8I. Gfall,17 Y. M. Goh,10 B. Golob,26, 21 I. Gorton,42 R. Grzymkowski,37 H. Guo,48 H. Ha,24 J. Haba,13 K. Hara,31
T. Hara,13 T. Haruyama,13 K. Hayasaka,31 K. Hayashi,13 H. Hayashii,33 M. Heck,22 S. Heindl,22 C. Heller,29
T. Hemperek,2 T. Higuchi,13 Y. Horii,54 W.-S. Hou,36 Y. B. Hsiung,36 C.-H. Huang,6 S. Hwang,23
H. J. Hyun,25 Y. Igarashi,13 C. Iglesias,47 Y. Iida,13 T. Iijima,31 M. Imamura,31 K. Inami,31 C. Irmler,17
M. Ishizuka,33 K. Itagaki,54 R. Itoh,13 M. Iwabuchi,60 G. Iwai,13 M. Iwai,13 M. Iwasaki,13 M. Iwasaki,55
Y. Iwasaki,13 T. Iwashita,33 S. Iwata,56 H. Jang,23 X. Ji,16 T. Jinno,31 M. Jones,11 T. Julius,30 T. Kageyama,13
D. H. Kah,25 H. Kakuno,55 T. Kamitani,13 K. Kanazawa,13 P. Kapusta,37 S. U. Kataoka,32 N. Katayama,13
M. Kawai,13 Y. Kawai,13 T. Kawasaki,38 J. Kennedy,11 H. Kichimi,13 M. Kikuchi,13 C. Kiesling,29
B. K. Kim,23 G. N. Kim,25 H. J. Kim,25 H. O. Kim,25 J.-B. Kim,24 J. H. Kim,23 M. J. Kim,25 S. K. Kim,49
K. T. Kim,24 T. Y. Kim,10 K. Kinoshita,5 K. Kishi,33 B. Kisielewski,37 K. Kleese van Dam,42 J. Knopf,12
B. R. Ko,24 M. Koch,2 P. Kodyš,4 C. Koffmane,29 Y. Koga,31 T. Kohriki,13 S. Koike,13 H. Koiso,13
Y. Kondo,13 S. Korpar,28, 21 R. T. Kouzes,42 Ch. Kreidl,12 M. Kreps,22 P. Križan,26, 21 P. Krokovny,3, 40
H. Krüger,2 A. Kruth,2 W. Kuhn,7 T. Kuhr,22 R. Kumar,43 T. Kumita,56 S. Kupper,21 A. Kuzmin,3, 40
P. Kvasnička,4 Y.-J. Kwon,60 C. Lacasta,57 J. S. Lange,7 I.-S. Lee,10 M. J. Lee,49 M. W. Lee,25 S.-H. Lee,24
M. Lemarenko,2 J. Li,11 W. D. Li,16 Y. Li,58 J. Libby,15 A. Limosani,30 C. Liu,48 H. Liu,16 Y. Liu,36 Z. Liu,16
D. Liventsev,20 A. Lopez Virto,46 Y. Makida,13 Z. P. Mao,16 C. Mariñas,57 M. Masuzawa,13 D. Matvienko,3, 40
W. Mitaroff,17 K. Miyabayashi,33 H. Miyata,38 Y. Miyazaki,31 T. Miyoshi,13 R. Mizuk,20 G. B. Mohanty,51
D. Mohapatra,58 A. Moll,29, 52 T. Mori,31 A. Morita,13 Y. Morita,13 H.-G. Moser,29 D. Moya Martin,46 T. Müller,22
D. Münchow,7 J. Murakami,33 S. S. Myung,49 T. Nagamine,54 I. Nakamura,13 T. T. Nakamura,13 E. Nakano,41
H. Nakano,54 M. Nakao,13 H. Nakazawa,34 S.-H. Nam,23 Z. Natkaniec,37 E. Nedelkovska,29 K. Negishi,54
S. Neubauer,22 C. Ng,55 J. Ninkovic,29 S. Nishida,13 K. Nishimura,11 E. Novikov,20 T. Nozaki,13 S. Ogawa,53
K. Ohmi,13 Y. Ohnishi,13 T. Ohshima,31 N. Ohuchi,13 K. Oide,13 S. L. Olsen,49, 11 M. Ono,13 Y. Ono,54
Y. Onuki,54 W. Ostrowicz,37 H. Ozaki,13 P. Pakhlov,20 G. Pakhlova,20 H. Palka,37 H. Park,25 H. K. Park,25
L. S. Peak,50 T. Peng,48 I. Peric,12 M. Pernicka,17 R. Pestotnik,21 M. Petrič,21 L. E. Piilonen,58 A. Poluektov,3, 40
M. Prim,22 K. Prothmann,29, 52 K. Regimbal,42 B. Reisert,29 R. H. Richter,29 J. Riera-Babures,45 A. Ritter,22
A. Ritter,29 M. Ritter,29 M. Röhrken,22 J. Rorie,11 M. Rosen,11 M. Rozanska,37 L. Ruckman,11 S. Rummel,27
V. Rusinov,20 R. M. Russell,42 S. Ryu,49 H. Sahoo,11 K. Sakai,38 Y. Sakai,13 L. Santelj,21 T. Sasaki,13 N. Sato,13
Y. Sato,54 J. Scheirich,4 J. Schieck,27 C. Schwanda,17 A. J. Schwartz,5 B. Schwenker,8 A. Seljak,21 K. Senyo,31
O.-S. Seon,60 M. E. Sevior,30 M. Shapkin,18 V. Shebalin,3, 40 C. P. Shen,11 H. Shibuya,53 S. Shiizuka,31 J.-G. Shiu,36
B. Shwartz,3, 40 F. Simon,29, 52 H. J. Simonis,22 J. B. Singh,43 R. Sinha,19 M. Sitarz,37 P. Smerkol,21 A. Sokolov,18
E. Solovieva,20 S. Stanič,39 M. Starič,21 J. Stypula,37 Y. Suetsugu,13 S. Sugihara,55 T. Sugimura,13 K. Sumisawa,13
T. Sumiyoshi,56 K. Suzuki,31 S. Y. Suzuki,13 H. Takagaki,56 F. Takasaki,13 H. Takeichi,31 Y. Takubo,54
M. Tanaka,13 S. Tanaka,13 N. Taniguchi,13 E. Tarkovsky,20 G. Tatishvili,42 M. Tawada,13 G. N. Taylor,30
Y. Teramoto,41 I. Tikhomirov,20 K. Trabelsi,13 T. Tsuboyama,13 K. Tsunada,31 Y.-C. Tu,6 T. Uchida,13
S. Uehara,13 K. Ueno,36 T. Uglov,20 Y. Unno,10 S. Uno,13 P. Urquijo,30 Y. Ushiroda,13 Y. Usov,3, 40 S. Vahsen,11
M. Valentan,17 P. Vanhoefer,29 G. Varner,11 K. E. Varvell,50 P. Vazquez,47 I. Vila,46 E. Vilella,1 A. Vinokurova,3, 40
J. Visniakov,47 M. Vos,57 C. H. Wang,35 J. Wang,44 M.-Z. Wang,36 P. Wang,16 A. Wassatch,29 M. Watanabe,38
Y. Watase,13 T. Weiler,22 N. Wermes,2 R. E. Wescott,42 E. White,5 J. Wicht,13 L. Widhalm,17 K. M. Williams,58
E. Won,24 H. Xu,16 B. D. Yabsley,50 H. Yamamoto,54 H. Yamaoka,13 Y. Yamaoka,13 M. Yamauchi,13 Y. Yin,48

ii

H. Yoon,23 J. Yu,23 C. Z. Yuan,16 Y. Yusa,58 D. Zander,22 M. Zdybal,37 Z. P. Zhang,48 J. Zhao,48 L. Zhao,48
Z. Zhao,48 V. Zhilich,3, 40 P. Zhou,59 V. Zhulanov,3, 40 T. Zivko,21 A. Zupanc,22 and O. Zyukova3, 40
1

Universidad de Barcelona, Barcelona (not a member of the Belle II collaboration)2
Physikalisches Institut der Universität Bonn, Bonn
3
Budker Institute of Nuclear Physics, Novosibirsk
4
Faculty of Mathematics and Physics, Charles University, Prague
5
University of Cincinnati, Cincinnati, Ohio 45221
6
Department of Physics, Fu Jen Catholic University, Taipei
7
Justus-Liebig-Universität Gießen, Gießen
8
Georg-August-Universität Göttingen, Göttingen
9
Gyeongsang National University, Chinju
10
Hanyang University, Seoul
11
University of Hawaii, Honolulu, Hawaii 96822
12
Institut für Technische Informatik der Universität Heidelberg
13High Energy Accelerator Research Organization (KEK), Tsukuba
14
Indian Institute of Technology Guwahati, Guwahati
15
Indian Institute of Technology Madras, Chennai
16
Institute of High Energy Physics, Chinese Academy of Sciences, Beijing
17
Institute of High Energy Physics, Vienna
18
Institute of High Energy Physics, Protvino
19
Institute of Mathematical Sciences, Chennai
20
Institute for Theoretical and Experimental Physics, Moscow
21
J. Stefan Institute, Ljubljana
22
Institut für Experimentelle Kernphysik, Karlsruher Institut für Technologie, Karlsruhe
23
Korea Institute of Science and Technology Information, Daejeon
24
Korea University, Seoul
25
Kyungpook National University, Taegu
26
Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana
27
Ludwig Maximilians University and Excellence Cluster Universe, Munich
28
University of Maribor, Maribor
29
Max-Planck-Institut für Physik, Munich
30
University of Melbourne, School of Physics, Victoria 3010
31
Nagoya University, Nagoya
32
Nara University of Education, Nara
33
Nara Women’s University, Nara
34
National Central University, Chung-li
35National United University, Miao Li
36
Department of Physics, National Taiwan University, Taipei
37
H. Niewodniczanski Institute of Nuclear Physics, Krakow
38
Niigata University, Niigata
39
University of Nova Gorica, Nova Gorica
40
Novosibirsk State University, Novosibirsk
41
Osaka City University, Osaka
42
Pacific Northwest National Laboratory, Richland, Washington 99352
43
Panjab University, Chandigarh
44
Peking University, Beijing
45
Universitat Ramon Llull, Barcelona (not a member of the Belle II collaboration)
46
Instituto de Fisica de Cantabria, Santander (not a member of the Belle II collaboration)
47
Universidad de Santiago de Compostela, Santiago de Compostela (not a member of the Belle II collaboration)48
University of Science and Technology of China, Hefei
49
Seoul National University, Seoul
50
School of Physics, University of Sydney, NSW 2006
51
Tata Institute of Fundamental Research, Mumbai
52
Excellence Cluster Universe, Technische Universität Munich, Garching
53
Toho University, Funabashi
54
Tohoku University, Sendai
55
Department of Physics, University of Tokyo, Tokyo
56
Tokyo Metropolitan University, Tokyo
57
IFIC, CSIC-UVEG, Valencia (not a member of the Belle II collaboration)
58
IPNAS, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061
59
Wayne State University, Detroit, Michigan 48202
60
Yonsei University, Seoul

iii

Contents
1 Motivation and Overview
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Physics Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3 The Belle II overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1
1
2
14

2 SuperKEKB
2.1 Machine Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Lattice Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Magnets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4 RF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5 Beam instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Vacuum System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.7 Injector Linac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.8 Damping Ring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.9 Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.10 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19
19
24
29
33
39
41
45
49
51
52

3 IR design
3.1 Interaction Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Beam-induced background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 IP-chamber design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Vibration measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

56
56
64
67
71

4 Pixel Detector (PXD)
76
4.1 Layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.2 DEPFET Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.3 Electronics (ASICs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4.4 Module Description and Interconnections . . . . . . . . . . . . . . . . . . . . . . 89
4.5 Radiation Hardness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.6 Quality Control and Assurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.7 Data Acquisition and Slow Control . . . . . . . . . . . . . . . . . . . . . . . . . . 103
4.8 Mechanical Support and Cooling . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
4.9 Interface to Belle II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
4.10 Test beam results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
4.11 Expected Performance of the PXD . . . . . . . . . . . . . . . . . . . . . . . . . . 124
4.12 Project Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4.13 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134

iv

5 Silicon Vertex Detector (SVD)
139
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
5.2 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
5.3 Mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
5.4 Electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.5 Environmental Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
5.6 Power Supplies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
5.7 Prototyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
5.8 Expected Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
5.9 Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
5.10 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
6 Central Drift Chamber (CDC)
202
6.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
6.2 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
6.3 Gas system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
6.4 Readout electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
6.5 Beam Test for a Prototype readout board . . . . . . . . . . . . . . . . . . . . . . 213
6.6 Expected performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
7 Particle Identification - Barrel
220
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
7.2 Detector configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221
7.3 Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
7.4 Prototype test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
7.5 Expected performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
8 Particle Identification: End-cap
250
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250
8.2 Basic Detector Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
8.3 Mechanical Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
8.4 Cabling and Other Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
8.5 R&D Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
8.6 Expected Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274
8.7 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
9 Calorimeter (ECL)284
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284
9.2 The Belle electromagnetic calorimeter . . . . . . . . . . . . . . . . . . . . . . . . 284
9.3 Performance with increasing luminosity . . . . . . . . . . . . . . . . . . . . . . . 285
9.4 General electronics upgrade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287
9.5 Options for the endcap upgrade . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297
10 KL0 and µ detection (KLM)
313
10.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313
10.2 Resistive Plate Chambers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
10.3 Muon and KL identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318
10.4 Backgrounds in the endcap RPCs . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
10.5 Scintillator Endcaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330v

11 Detector Solenoid and Iron Structure347
11.1 Iron Yoke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
11.2 Solenoid Magnet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
11.3 Cryogenic System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348
11.4 Possible rotation of the Belle II structure . . . . . . . . . . . . . . . . . . . . . . 351
12 Trigger
358
12.1 CDC 2D Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
12.2 CDC 3D Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364
12.3 ECL Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369
12.4 Barrel PID Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
12.5 KLM Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379
12.6 GDL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380
13 Data Acquisition System383
13.1 Global Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383
13.2 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
13.3 Timing distribution and handshake . . . . . . . . . . . . . . . . . . . . . . . . . . 386
13.4 Belle2Link . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388
13.5 Detector front-end interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392
13.6 COPPER Readout System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393
13.7 Event Builder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402
13.8 Data Processing Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404
13.9 High Level Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407
13.10Slow control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
13.11PXD integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
13.12Data reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412
14 Computing and Software
416
14.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416
14.2 Computing Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
14.3 Distributed Computing and Data Management . . . . . . . . . . . . . . . . . . . 422
14.4 Offline Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436
14.5 Resource Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456
14.6 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464
15 Organization469
15.1 Collaboration members and organization . . . . . . . . . . . . . . . . . . . . . . . 469
15.2 Cost and schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469

viChapter 1

Motivation and Overview
1.1

Introduction

By November 2009, the Belle detector [1], operating at the asymmetric electron positron collider KEKB [2], had accumulated a data sample with an integrated luminosity of 1000 fb−1 .
This achievement completes all of the technical milestones put forward in 1999 for Belle and
KEKB. In a decade of operation, measurements arising from KEKB and Belle have offered important insights into the flavor structure of elementary particles, especially the violation of CP
symmetry in the quark sector. Numerous results of the Belle collaboration, and its companion collaboration BaBar [3], operating at the PEP-II B-meson factory at SLAC, have confirmedwith good precision the theoretical predictions of the Standard Model. These experimental tests
culminated in the 2008 Nobel Prize for physics awarded to M. Kobayashi and T. Maskawa for
their theory of CP violation [4].
With the much larger data sample that will become available at SuperKEKB, a Super B factory
level upgrade of the KEKB collider, a new panorama of measurements in heavy flavor physics
will be possible. These studies will provide an important and unique source of information on
the details of new physics processes that are expected to be uncovered at hadron colliders in the
coming years. An upgrade of the Belle experiment, Belle II, was first presented in a detailed
Letter of Intent in March 2004 [5], followed by a supplemental report in October 2008 [6]. After
receiving strong encouragement from the KEK management and its review committees, the BelleII collaboration was formed in December 2008 and a formal management structure (describedin Chapter 15) was implemented in July 2009.
This document gives a full account of the detector design details and illustrates the progressand changes since the 2008 report. The document is structured as follows. In the remainderof this overview, we will give a short description of the Belle II physics motivation and reach,and introduce the highlights of the Belle II detector. Chapter 2 discusses the SuperKEKB accelerator design. The remaining chapters describe the detector components in detail. Emphasis
is placed on the detector construction, and on the changes in detector component performance,background levels and physics performance as compared to the Letter of Intent and its 2008
supplement. Finally, there are chapters devoted to the time schedule, and to the management
structure of the experiment.

1

CHAPTER 1. MOTIVATION AND OVERVIEW

1.2

Physics Motivation

1.2.1

Moving beyond the Standard Model

The Standard Model (SM) of interactions among elementary particles is—at the current level ofexperimental precision and at the energies reached so far in man-made particle accelerators —one of the best verified physics theories. Despite its tremendous success in describing the basic
forces of nature — recognized by several Nobel prizes — many fundamental questions remainunanswered within the SM.
It is unclear why there should be only three generations of elementary fermions. Considering only
its known content, there is a prejudice that the SM has too many free parameters. The masses
and mixing parameters of the SM bosons and fermions are apriori unknown and must therefore
be determined experimentally. The origin of mass is resolved within the SM by spontaneous
breaking of the electroweak symmetry, resulting in a yet-unobserved neutral Higgs boson. In
order to preserve the unitarity of the theory its mass should lie at or below the TeV energy scale.
This, however, requires an unnatural cancellation (fine tuning) among the parameters of the SM.
Several solutions for this hierarchy problem are proposed, the best known being the existenceof new supersymmetric particles with masses on the TeV scale, or the existence of unobserved
extra spatial dimensions. In these and other New Physics (NP) scenarios, new generations, newparticles and new processes arise quite naturally.
Studies of symmetries have often illuminated our understanding of nature. For example, there isan observed hierarchy in the fermion masses and some NP models have attempted to exploit newsymmetries to explain this hierarchy. At the cosmological scale, there is a serious unresolved
problem with the matter-antimatter asymmetry in the universe. While the violation of CP
symmetry is a necessary condition for the evolution of a matter-dominated universe, as was
first noted by A. Sakharov in 1967 [7], the observed CP violation within the quark sector thatoriginates from the complex phase of the Cabibbo-Kobayashi-Maskawa (CKM) matrix is manyorders of magnitude too small to explain the dominance of matter in the universe. Hence, there
must exist undiscovered sources of the CP asymmetry responsible for the matter-dominated
Universe. As a final example, the elements of the CKM matrix, describing the fractions ofcharged W ± boson decays to quarks of specific flavors, exhibit a roughly diagonal hierarchy,
even though the SM does not require this. This may indicate the presence of a new mechanism,
such as a flavor symmetry, that exists unbroken at a higher energy scale.
Considering the open questions that in the SM remain unanswered, it is fair to conclude thatthe present theory is an extremely successful but phenomenological description of subatomic
processes at the energy scales up to O(0.1 TeV).
The future experiments in high energy physics are designed to address the above questions
through searches of NP using complementary approaches. One approach is at the energy frontierwith the main representatives being the ATLAS and the CMS experiments at the Large Hadron
Collider (LHC) at CERN. The second is the rare/precision frontier, exemplified by the LHCb
experiment at the LHC, the BESIII experiment at the BEPCII charm factory, the planned
SuperB factory in Italy, and the Belle II experiment at SuperKEKB.
At the energy frontier, the LHC experiments will be able to discover new particles produced inproton-proton collisions at a center-of-mass energy of up to 14 TeV. Since the constituent gluons
or quarks interact in these collisions, only a fraction of the center-of-mass energy is available toproduce such new particles, and the mass reach is limited to O(1 TeV/c2 ). Sensitivity to thedirect production of a specific new particle depends on the cross section and on the size of thedata sample (i.e., on the luminosity of the accelerator and performance of the detector).

2

CHAPTER 1. MOTIVATION AND OVERVIEW

MNP[TeV]At the rare/precision frontier, observable signatures of new particles or processes can be obtained
through measurements of flavor physics reactions at lower energies and evidence of a deviationfrom the SM prediction. (Here, “rare” and “precision” refer to processes that are strongly
suppressed or allowed, respectively, in the SM.) An observed discrepancy can be interpreted interms of NP models. This is the approach of Belle II.
Apart from being a complementary approach to the direct high energy searches, the precision frontier has unprecedented sensitivity to the effects of NP. The sensitivity depends on thestrength of the flavor violating couplings of the NP. The mass reach for new particle/process effects can be as high as O(100 TeV/c2 ) if the couplings are enhanced compared to the SM. In themost pessimistic Minimal Flavor Violation case, where the NP flavor violating processes (suchas neutral meson oscillations) are a consequence of the same Yukawa couplings as in the SM,
SuperKEKB and Belle II would still be able to observe the effects of so far unknown particles
up to O(1 TeV/c2 ) [8]. Again, sensitivity to the contribution of a new particle or process to aparticular flavor physics reaction depends on the NP model and on the size of the data sample.
The reach of various colliders in searching for NP is illustrated in Fig. 1.1.

SuperKEKB

10 2

10

KEKB
LHC
1

Tevatron
10

-1

1

10

10
(gNP/g)2

2

Figure 1.1: Illustrative region of sensitivity to NP as a function of the flavor violating couplings(relative to the SM) in the indirect searches at KEKB and SuperKEKB, and direct searches at
LHC and Tevatron.
The value of the high-energy and rare/precision frontiers is associated with the complementary
direct vs. indirect nature of the contribution of new particles or processes to the ensemble ofavailable measurements and the distinct predictions from NP models in these two regimes. The
processes in which unknown particles are expected to be observed are different in most of thecases between the energy and precision frontier experiments.
Belle II and SuperKEKB, described in this report, will exploit our strengths at the rare/precision
frontier by moving beyond a simple observation of a NP effect to its detailed characterization
through overconstraining measurements in several related flavor physics reactions. This is also
the reason for the existence of several experiments in the precision frontier with, to a large
extent, non-overlapping and thus complementary programs. In Sec. 1.2.3.2, we briefly address
3CHAPTER 1. MOTIVATION AND OVERVIEW

the complementarity between the LHCb and Belle II.

1.2.2

NP-sensitive physics at Belle

To illustrate the expected sensitivity of Belle II and SuperKEKB to New Physics phenomena,
we examine some of the major scientific breakthroughs at the Belle experiment and then identify
where Belle II can extend our reach.
• 2002: Belle observed mixing-induced time-dependent CP violation (TCPV) in the systemof neutral B mesons and provided a measurement of one of the angles of the unitarity
triangle (UT) sin 2φ1 [9] through a careful analysis of B 0 → J/ψK 0 and related decays.
Since then, the determination of this parameter has become a precision measurement(5.5% relative accuracy, which is further reduced by averaging measurements performedby different experiments in different decay modes).
• 2003: Belle presented evidence of TCPV in B 0 → π + π − decays and a measurement of the
UT angle φ2 [10]. Nowadays, φ2 is also measured precisely (19% relative accuracy in the
B 0 → ρ+ ρ− decay mode, which is further reduced by averaging measurements performedby different experiments in different decay modes).
• In the same year, Belle measured TCPV in the penguin-dominated modes B 0 → φKS ,K + K − KS and η ′ KS and observed that the parameter sin 2φ1 deviated somewhat from thevalue measured in tree-dominated B 0 → J/ψK 0 decays [11]. The discrepancy has becomeless significant with more data, but is still statistically limited. The greater sensitivity of
Belle II will permit us to discern the presence of NP effects in these penguin modes.
• In 2003 Belle discovered a new resonance named X(3872) [12], produced in B decays ina similar manner as charmonia, but exhibiting properties that made its classification as aconventional meson quite difficult. Many properties and decay modes of the X(3872) state
have since been measured, and it has been joined by a large number of other interesting
new particles with similar puzzling properties. Studies of these states at Belle II, as wellas possible discoveries of new ones, will help to extend our understanding of quantum
chromodynamics.
• 2004: Data revealed for the first time direct CP violation (DCPV) in B decays to π + π −and K + π − [13, 14].
• In the same year, Belle collaborators performed the first measurement of the last of theunitarity triangle angles, φ3 , using a new method: a time-independent measurement of the
Dalitz distribution in B → D (∗) K decays [15]. This approach has proven to be the mostsensitive method to determine φ3 and will be exploited by Belle II.
• 2005: The first measurements of TCPV in B 0 → K ∗0 γ were reported [16], where theconstituent b quark decays into an s quark and a photon. The CP asymmetry in this decay
is strongly suppressed by fermion helicity conservation in the SM, but can be dramaticallyenhanced in some NP models. Measurements with improved precision will be an important
tool in the search for new processes with Belle II.
• 2006: The purely leptonic decay B + → τ + ντ , was observed for the first time [17]. The
branching fraction is sensitive to the value of the least well known CKM matrix element,
Vub and the wavefunction overlap of the B meson at the origin. In NP scenarios, it can beenhanced by the contribution of a charged Higgs boson.
4CHAPTER 1. MOTIVATION AND OVERVIEW• 2007: Belle and BaBar found the first evidence for the phenomenon of mixing in the systemof neutral charmed mesons D 0 [18, 19]. The large rate can be accomodated by NP but
may also be explained by difficult to calculate long-distance strong interaction effects in
the SM. In contrast, CP violation in the D meson system with a magnitude comparable tothe current experimental sensitivity is an unambiguous signature of NP. With the sample
of charmed meson decays collected by Belle II it will be possible to clarify the situation.
• 2008: A measurement of the branching fraction and photon energy spectrum for fully
inclusive B → Xs γ decays was performed with an energy threshold of 1.7 GeV [20]. This
result is in agreement with the SM and provides strong constraints on charged Higgs
bosons. The shape of the spectrum helps in the determination of the b quark mass and|Vub |.
• In the same year, a measurement of DCPV in B + → K + π 0 proved it to be different than
the same quantity in B 0 → K + π − decays [21], contrary to the naive SM expectation. In
combination with other B → Kπ measurements and with the larger Belle II data set, thevalidity of the SM can be tested in a model-independent way.
• 2009: Rare B → K ∗ ℓ+ ℓ− penguin decays were measured with improved precision [22].
The forward-backward asymmetry of the leptons is a sensitive probe of possible NP contributions. With current data samples, the asymmetry appears to deviate from the SM
expectation, but the difference is statistically limited. The greater sensitivity of Belle II
will resolve whether the discrepancy is due to NP effects or not.

1.2.3

NP-sensitive physics at Belle II







 


















Figure 1.2: The SM contribution (left) and the gluino–down squark contribution (right) to theb → ss̄s transition.
Here, in order to illustrate the unprecedented sensitivity to the presence of NP effects at therare/precision frontier that the improved performance of the Belle II detector and the muchlarger data set will offer, we expand on few of the above examples of measurements: b → ss̄s,
b → sγ, B → τ ν, and B → Kπ decays.
The examples presented are just a few examples in the broad physics program of Belle II,
which brings the searches of New Physics performed at the existing B factories to a completely
new level of sensitivity, and significantly extends the reach of present experimental efforts in a
way complementary to the energy frontier experiments. The real value of the Super B factory
is in its ability to perform measurements in all fields of heavy flavor physics, extending from(∗)
B 0(±) meson decays to Bs meson decays, charm physics, τ lepton physics, spectroscopy, andpure electroweak measurements. A large number of planned measurements will over-constrain
the parameter space of the SM as well as its extensions and will shed light on the nature of5CHAPTER 1. MOTIVATION AND OVERVIEW

NP signatures that may be observed directly at the LHC. A detailed study of correlations
among various observables, sensitivities and expected physics output can be found in Ref. [23].
Tables 1.1 and 1.2 summarize these studies.
1.2.3.1b → ss̄s decays

The value of sin 2φ1 as measured in B 0 → φKS and similar b → s transitions differs slightly
from the value measured in B → J/ψKS decays, the current world average difference being
J/ψK 0S∆S ≡ sin 2φφK
− sin 2φ1
= 0.22 ± 0.17 [25]. The former decays proceed through b → sss̄1
underlying quark process, possible only through the loop processes shown in Fig. 1.2 (left), andthe latter through the b → csc̄ tree diagram. While the CKM matrix elements included in theamplitudes of these decays are approximately real, the possibility of B 0 − B̄ 0 mixing before thedecay introduces an additional factor (Vtb∗ Vtd )2 ∝ e−2iφ1 . Hence, the decay time distribution ofboth decays is sensitive to sin 2φ1 , and the difference in the value measured in the two decays is
0.01
expected to vanish within small corrections, ∆S = 0.03 ± 0.04
[26]. However, NP particles can0contribute in the loop of B → φKS , as illustrated in Fig. 1.2 (right), and change the expectationfor ∆S.
In B → K + K − KS decays, φKS is one of several intermediate resonant contributions to the final
S
state. In order to determine the value of sin 2φφK
, one has to perform a decay time dependent
1+
Dalitz plot analysis, where the accuracy of K K − KS vertex determination and the particle
identification for the suppression of backgrounds are crucial. These are achieved in Belle II withthe vertex detector (Chapters 4 and 5) and the particle identification system (Chapters 7 and 8).
The expected dependence on integrated luminosity of the ∆S sensitivity from these and related
decays is shown in Fig. 1.3 [23]. With L = 10 ab−1 of data, the experimental and theoreticaluncertainties will be comparable.

Figure 1.3: Expected precision of ∆S measurements as a function of integrated luminosity [23].

6CHAPTER 1. MOTIVATION AND OVERVIEW

1.2.3.2b → sγ decays

δS

Radiative decays b → sγ are sensitive probes of right-handed weak currents, which are absent
by fiat in the SM. The helicity structure of the effective Hamiltonian that describes this loop
process allows only for bR → sL γL and bL → sR γR decays, where the subscript denotes thehandedness of the particle. The amplitude of the former (latter) process depends on the helicity
flip and is proportional to mb (ms ). In mesons the bL → sR γR transition, for example, canproceed directly or via B̄ 0 → B 0 mixing; the interference leads to a small time dependent CP
asymmetry that is proportional to ms /mb . In various NP models (e.g. Left-right symmetricmodels) the right-handed currents are not suppressed and can lead to a sizable CP asymmetry.
A prominent example of such radiative quark transitions is the decay B 0 → KS π 0 γ. Within
the SM, the decay time dependent CP asymmetry in this decay is estimated to be S ≈−2(ms /mb ) sin 2φ1 ≈ −0.04; some SM predictions allow for a value of |S| up to 0.1 [27, 28]. On
the other hand, in L-R symmetric models, the asymmetry can be as large as S ≈ 0.67 cos 2φ1 ≈0.5.
The decay-time dependence in B 0 → KS π 0 γ is measured through reconstruction of the B
meson decay vertex using only pions from KS → π + π − decay that are constrained to the e+ e−interaction region profile. The Belle II vertex detector (Chapters 4 and 5) will improve thevertex position resolution and, more importantly, increase the reconstruction efficiency of KS
decays with charged pion hits in the silicon detectors.
The expected accuracy of the S(KS π 0 γ) measurements is shown in Fig. 1.4 [23]. With a data
set corresponding to 50 ab−1 , the sensitivity of the measurement will reach the SM value andthus cover a range of NP predictions.

1

10

-1

10

-1

1

10

-1

L(ab )

Figure 1.4: Expected precision of the TCPV asymmetry measurements for B → K ∗0 (982)γ(green), other KS π 0 γ (blue) and all KS π 0 γ final state (red) as a function of integrated luminosity [23].

The measurement of the S(KS π 0 γ) also nicely illustrates the complementarity among the precision frontier experiments, specifically between Belle II and LHCb. The sensitivity of Belle II
for the S(KS π 0 γ) measurement cannot be reached by the LHC experiment. On the other hand7

CHAPTER 1. MOTIVATION AND OVERVIEW(neglecting the possibility of dedicated longer data taking periods at the Υ(5S) resonance), the
LHCb experiment can perform a much more precise measurement of the Bs → µ+ µ− decay rate.
When interpreting both measurements within the Minimal Supersymmetric Standard Model inthe mass insertion approximation (MIA), the contours of the MIA parameter and tan β areshown in Fig. 1.5 [23]. While the measurement of the B(Bs → µ+ µ− ) at the level of 10−9 yields
a rather loose constraint on the MIA parameter, a combination with the measurement of the
S(KS π 0 γ) with a precision of 0.1 results in a tight constraint in both dimensions.

d ) and tan β from the measurement of the
Figure 1.5: Constraints on the MIA parameter Re(δRL
0+−
S(KS π γ) and B(Bs → µ µ ) [23]. Contours of S(KS π 0 γ) are shown in the intervals of 0.1.

1.2.3.3

B → τν

One of the outstanding problems in particle physics is the question of the origin of masses andthe related Higgs boson(s). The SM incorporates a single neutral Higgs boson. The Higgs sectorof various extensions of the SM is richer, with charged Higgs bosons possible as well. In the TypeII Two Higgs Doublet Models (2HDM-II), the charged Higgs boson H ± behaves like the charged
weak bosons W ± apart from its couplings to fermions, which are proportional to their masses.
The contribution of H ± can thus be expected in all charged weak current processes, especiallythose involving heavy fermions. A typical example is the purely leptonic decay of charged B
mesons, B + → τ + ντ , where, in the 2HDM-II models, the contribution of H + is expected to belargest due to the masses of the τ lepton and the b quark.
The effect of a possible charged Higgs boson on the partial leptonic decay width of B mesons isgiven byΓ(B + → τ + ντ ) = ΓSM (B + → τ + ντ )[1 − (m2B /m2H ) tan2 β]2 ,(1.1)
where ΓSM (B + → τ + ντ ) denotes the SM partial decay width, and tan β denotes the ratio ofthe vacuum expectation values of the two Higgs fields and is a free parameter of the models.
The leptonic decay width can thus be suppressed or — if the H ± contribution is dominant —enhanced compared to the SM value.
8

CHAPTER 1. MOTIVATION AND OVERVIEW

Experimentally, of the leptonic branching fraction measurement [17] consists of (partial) reconstruction of the accompanying B meson in the event, called the tagging B meson (Btag ).
Btag can be fully reconstructed in a number of hadronic decays (hadronic tagging) or partiallyreconstructed in semileptonic decays (semileptonic tagging), where the hadronic system (andthe charged lepton) of the final state is detected while the neutrino escapes the detection. The
hadronic tagging method has better purity in the Btag sample, but suffers from a lower efficiency compared to semileptonic tagging. The remaining particles in the event are assigned
to the signal B meson (Bsig ); if they are consistent with a possible τ decay, the undetectedpart of the event consists of one or more neutrinos from (semi)leptonic decays. The signatureof such event is thus a little or no residual energy detected in the electromagnetic calorimeter, after removing the contributions from the particles used in the reconstruction of Btag andthe τ from Bsig → τ ντ . The resulting distribution of the residual calorimeter energy for themeasurement based on the semileptonic tagging [29] is shown in Fig. 1.6 (left). The peaking
component at low energy is the signal of B → τ ντ . The leptonic branching fraction is found to
0.35−4
be B(B → τ ντ ) = (1.65 ± 0.38
0.37 ± 0.37 ) × 10 .
1000

800

2

Events/ 0.05 GeV
H Mass (GeV/c )

600

400

±

Events / 0.05 GeV

400
350 (a)
300
250
200
150
100
50
0
0 0.25 0.5 0.75 1
EECL (GeV)

200
Tevatron Run I
LEP
0
0

20

40

60

80

100

tan β

Figure 1.6: Left: Distribution of residual energy in the calorimeter for semileptonically tagged
B → τ ντ candidate events [29]. The dashed histogram represents the background, and the solid
red histogram the result of the fit that includes a signal component peaking at null value. Right:
5 σ discovery sensitivity region for the charged Higgs boson from B → τ ντ branching fraction
measurement at an integrated luminosity of 5 ab−1 (red). Other colored regions denote thepresently excludedcurrent exclusion regions.
Excellent performance of the electromagnetic calorimeter is crucial for the described measurement. The Belle II calorimeter (Chapter 9) maintains this performance even with the more
severe backgrounds expected at SuperKEKB.
The statistical and systematic uncertainty of the result are almost equal in magnitude. However, the main sources of the systematic error—statistics of the control samples for the shape ofthe residual energy distribution and efficiency of the tagging—will decrease with the increased
integrated luminosity of the available data sample. Assuming the theoretical uncertainties on
the CKM element |Vub | and B meson decay constant fB will be reduced to 5% in a few years, we
obtain the five standard deviations discovery sensitivity region at L = 5 ab−1 in the (tan β, mH )plane shown in Fig. 1.6 (right).
9

CHAPTER 1. MOTIVATION AND OVERVIEW

1.2.3.4

B → KπCharmless 2-body B meson decays are another example of rare SM processes in which thepossible contribution of NP could be large enough to be observed in the future. The decays
B → Kπ proceed through a tree diagram depicted in Fig. 1.7 (left) but are suppressed by
the small CKM matrix element |Vub |. Thus, the contribution of the loop penguin diagram isof similar magnitude. The interference of the two leads to a direct CP asymmetry of AfCP =[Γ(B̄ → f¯)−Γ(B → f )]/[Γ(B̄ → f¯)+Γ(B → f )]. As suggested in diagrams of Fig. 1.7 (left), themain processes underlying the B → Kπ decays are the same and equal for neutral and charged
B mesons. Neglecting additional diagrams contributing to B + decays only (and expected to be
K + π 0 in B ± → K ± π 0 decays
much smaller than the shown contributions), the asymmetries ACP
K + π − in B 0 (B̄ 0 ) → K ± π ∓ decays are expected to be the same. However, a precise
and ACPK + π0 −measurement by Belle [21] showed a significant difference between the two, ∆A = ACP
K + π − = 0.164±0.035±0.013. The asymmetry in the number of reconstructed signal decays canACP
be observed visually in Fig. 1.7 (right). The difference could be due to the neglected diagrams
contributing to charged B meson decays, for which the theoretical uncertainty is still rather
large, or to some unknown NP effect that violates isospin. In Ref. [30], the author proposes a
test of sum rule for NP free of theoretical uncertainties. The sum rule reads
+
+ 0
0
0 0
B(B + → K 0 π + )τB 0
0 π 0 2 B(B → K π )K + π 0 2 B(B → K π )τB 0
= ACP
+AK
,
CP
0
+
−
0
+
−
0
+
B(B → K π )τB +
B(B → K π )τB +
B(B → K π − )(1.2)
where B(B → f ) denotes the corresponding branching fraction and τB 0 (B + ) lifetimes of neutral
and charged B mesons.
+ −

0 +

K π
π
ACP
+AK
CP

a K–p+

b K+p–

c K−p0d K+p0

750

a

u
W
b

B+ , B0
u, d

b

s, d
u
p0, p–u, dW

K+, p+

B+, B0s, d K+, p+ugup0, p–u, du, dEntries per 2 MeV/c2

500

b

250

0
300

200

100

0
5.2

5.25

5.2
Mbc (GeV/c2)

5.25

Figure 1.7: Left: Tree and penguin diagrams contributing to B → Kπ decays [21]. Right: Thereconstructed signal of B̄ 0 → K − π + (top left), B 0 → K + π − (top right), B − → K − π 0 (bottom
left) and B + → K + π 0 (bottom right) [21].
By measuring all the observables in the above equation, one can test the prediction of the SM.
Using the current world average values for the corresponding quantities [25], the isospin sum rule
0 π0
0 π+
can be presented as a diagonal band in the plane of AK
vs. AK(see Fig. 1.8 (left)). The
CP
CP
slope of this dependence is determined by the precisely known branching fractions and lifetimes,
K + π 0 and to a much lesser extent to AK + π − .
and the uncertainty of the offset is mainly due to ACP
CP10

CHAPTER 1. MOTIVATION AND OVERVIEW
0π0

AKmeasured

−0.05

su
m

0.05
measured

0.05 0.10 0.15 0.20 0.25 0.30 AK 0 π +

−0.05

−0.05

0.05 0.10 0.15 0.20 0.25 0.30 AK 0 π +−0.10

expected(sum rule)

expected(sum rule)0.05
measured

−0.05

−0.10
−0.15

00000000000000000000000000000000
11111111111111111111111111111111
11111111111111111111111111111111
00000000000000000000000000000000
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111
00000000000000000000000000000000
11111111111111111111111111111111

0.10

ru
le

0.10

K+ π 0 )
σ (A

)
ru
le

σ (A

1111111111111111111111111111111111
0000000000000000000000000000000000
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111
0000000000000000000000000000000000
1111111111111111111111111111111111

0π0

su
m

K+ π 0measured

AK

−0.15

0 0

0 +

π dependence on AK π . The
Figure 1.8: Left: Sum rule from Eq. 1.2 [30] shown as AKCP
CPexperimental values of various observables are taken from Ref. [25] and the hatched region
represents the expectation from the sum rule. Right: The same sum rule with the current
central values of observables and the accuracies expected with L = 50 ab−1 .

Several measurements must be accomplished in order to perform the above test. The mostdemanding is the measurement of the all-neutral final state K 0 π 0 . In the decay-time dependentmeasurement, the vertex reconstruction is based on charged pions from the neutral kaon decays(as in B 0 → KS π 0 γ decays) and depends crucially on a vertex detector with a large radial
acceptance. Reconstruction of the neutral pion (π 0 → γγ) requires very good electromagnetic
calorimetry. For the final states with charged kaons and pions, an excellent separation between
the two particle species must be provided by the particle identification system.
The main systematic uncertainty contributions (tag side interference) in the recent measurementof B 0 → K 0 π 0 [31] are expected to be reduced as the data sample increases. The expected sensitivity of the sum rule test with the integrated luminosity of 50 ab−1 is illustrated in Fig. 1.8 (left).
We have conservatively scaled only statistical uncertainties on CP asymmetries of K 0 π + andK + π 0 final states. If one assumes the current central values of observables and the expected
accuracy a discrepancy in the expectation of Eq. 1.2 can be clearly established.

1.2.4

Expected sensitivities for various observables

The summary of the expected sensitivities for individual observables at selected integrated luminosities is shown in Tables 1.1 and 1.2. A more detailed overview of physics program to be
fulfilled at the SuperKEKB can be found in Ref. [23].

11CHAPTER 1. MOTIVATION AND OVERVIEW

Observable

Belle 2006(∼0.5 ab−1 )Hadronic b → s transitions∆SφK 00.22∆Sη′ K 0
0.11∆SKS0 KS0 KS0
0.33∆Aπ0 KS0
0.15
AφφK +
0.17
f
φef
1 (φKS ) Dalitz
Radiative/electroweak b → s transitions
SKS0 π0 γ
0.32
B(B → Xs γ)
13%
ACP (B → Xs γ)
0.058
C9 from AF B (B → K ∗ ℓ+ ℓ− )C10 from AF B (B → K ∗ ℓ+ ℓ− )C7 /C9 from AF B (B → K ∗ ℓ+ ℓ− )RK††
B(B + → K + νν)< 3 BSM0∗0††
B(B → K ν ν̄)< 40 BSM
Radiative/electroweak b → d transitions
Sργ
B(B → Xd γ)
Leptonic/semileptonic B decays
B(B + → τ + ν)
3.5σ††B(B + → µ+ ν)< 2.4BSM
B(B + → Dτ ν)
B(B 0 → Dτ ν)
LFV in τ decays (U.L. at 90% C.L.)
B(τ → µγ) [10−9 ]45
B(τ → µη) [10−9 ]
65
B(τ → µµµ) [10−9 ]21Unitarity triangle parameterssin 2φ10.026
φ2 (ππ)11◦◦
φ2 (ρπ)68 < φ2 < 95◦
φ2 (ρρ)62◦ < φ2 < 107◦
φ2 (combined)
φ3 (D(∗) K (∗) ) (Dalitz mod. ind.)20◦(∗)
φ3 (DK ) (ADS+GLW)
φ3 (D(∗) π)
φ3 (combined)|Vub | (inclusive)
6%|Vub | (exclusive)
15%
ρ̄
20.0%
η̄
15.7%

Belle II/SuperKEKB(5 ab−1 )(50 ab−1 )
0.073
0.038
0.105
0.072
0.05
3.3◦

0.029
0.020
0.037
0.042
0.014
1.5◦

0.10
7%
0.01
11%
13%

0.03
6%
0.005
4%
4%
5%
0.02
30%
35%

0.07

0.3
24% (syst.)

LHCb†(2 fb ) (10 fb−1 )
−1

0.14
-

-

-

-

-

7%
0.043
-

-

-

-

-

0.15

10%
3%
4.3 ab−1 for 5σ discovery
8%
3%
30%
10%
10
5
3

5
2
1

-

-

0.016
10◦
3◦
3◦
2◦
7◦
16◦
18◦
6◦
5%
12% (LQCD)

0.012
3◦
1.5◦
1.5◦
. 1◦
2◦
5◦
6◦
1.5◦
3%
5% (LQCD)
3.4%
1.7%

∼0.02
10◦
10◦
8◦
5-15◦

∼0.01
4.5◦
4.5◦

4.2◦
-

2.4◦
-

Table 1.1: Summary of sensitivity studies (I) [23]. Branching fraction limits in the table are atthe 90% confidence level. † Values for LHCb are statistical only and are taken from Ref. [24] unlessotherwise stated. †† BSM represents the expected branching fraction in the SM; BSM = 5 × 10−6
for B(B + → K + νν), 7 × 10−6 for B 0 → K ∗0 ν ν̄ and 7.07 × 10−7 for B(B + → µν) are used inthis table.

12CHAPTER 1. MOTIVATION AND OVERVIEW

Observable

Belle

Belle II/SuperKEKB
−1

(2 fb
Bs physics
B(Bs → γγ)(∗) (∗)∆ΓCPs /Γs (Br(Bs → Ds Ds ))∆Γs /Γs (Bs → fCP t-dependent)
φs (with Bs → J/ψφ etc.)
B(Bs → µ+ µ− )φ3 (Bs → KK)
φ3 (Bs → Ds K)
Υ decays
B(Υ(1S) → invisible)
Charm physics
D mixing parameters
x
y
δKπ
|q/p|
φ
AD
New particlesℵ
γγ → Z(3930) → DD̄∗B → KX(3872)(→ D0 D̄∗0 )B → KX(3872)(→ J/ψπ + π − )B → KZ + (4430)(→ ψ ′ π + )e+ e− → γISR Y (4260)(→ J/ψπ + π − )Electroweak parameterssin2 ΘW(25 fb−1 )< 8.7 × 10−6
3%
−1
(3 fb )
< 2.5 × 10−3(∼0.5 ab−1 )‡

0.25%
0.16%
10◦
0.16
0.13 rad2.4%-(5 ab−1 )0.25 × 10−6
1% (model dependency)
1.2%-(500 fb−1 )< 2 × 10−4
(5 ab−1 )(50 ab−1 )

0.12%
0.10%
6◦
0.1
0.08 rad
1%

0.09%
0.05%
4◦
0.05
0.05 rad
0.3%

LHCb†
)
(10 fb−1 )

0.02
0.01
6 fb−1 for 5σ discovery
7-10◦
13◦

0.25%††
0.05%††> 3σ
400 events
1250 events
1000 events
3000 events(∼10 ab−1 )3 × 10−4

Table 1.2: Summary of sensitivity studies (II) [23]. † Values for LHCb are taken from Ref. [24]unless otherwise stated. ‡ For D mixing parameters the world average of results from [25] isquoted. †† LHCb sensitivities on x and y are estimated from sensitivities on x′2 , y ′ and yCP[32] assuming x = y = 0.80% and δKπ = 25◦ ± 6◦ . ℵ Due to a large number of various possible
measurements we only list expected signal yields for a few interesting processes.

13

CHAPTER 1. MOTIVATION AND OVERVIEW

1.3

The Belle II overview

Figure 1.9: Upgraded Belle II spectrometer (top half) as compared to the present Belle detector(bottom half).
The design of the Belle II detector follows to a large extent the scheme discussed in the Letterof Intent [5] and its 2008 supplement, Design Study Report [6], with one notable exception: apixel detector now appears in the innermost part of the vertex detector. Other modifications are
due to the change in the accelerator design from the high current version to the “nano-beam”
collider, and are associated with the larger crossing angle, the need to have the final quadrupoles
as close as possible to the interaction point, and the smaller beam energy asymmetry (7 GeV/c
on 4 GeV/c instead of 8 GeV/c on 3.5 GeV/c).
For the Belle II detector, our main concern is to maintain the current performance of Bellein an environment with considerably higher background levels. As discussed in detail in the2008 Design Report [6], we evaluate the possible degradation of the performance in a highbackground environment by extrapolating from the present operating conditions of KEKB andBelle by accounting for the scaling of each component of background with the higher currents,
smaller beam sizes and modified interaction region. From these studies, we assume a conservative
factor of twenty increase in the background hit rate. The physics event rate will be about 50
times higher.
The following changes to Belle will maintain a comparable or better performance in Belle II:• just outside the beam pipe, the silicon strip detector is replaced by a two-layer silicon pixel
detector based on the DEPFET technology;• the silicon strip detector extends from just outside the pixel detector to a larger radius
14CHAPTER 1. MOTIVATION AND OVERVIEW

than in Belle;• the readout of the silicon strip detector is based on the APV25 chip with a much shorter
shaping time than the present read-out based on the VA1TA chip;• the central tracking device—a large volume drift chamber—has smaller drift cells thanin Belle, starts just outside the expanded silicon strip detector, and extends to a larger
radius;• the completely new particle identification devices—higher performance yet more compact—
in the barrel and endcap regions are of the Cherenkov imaging type, with very fast read-out
electronics;• the electronics of the electromagnetic calorimeter is of the wave-form-sampling type; areplacement of the endcap scintillator crystal (CsI(Tl)) with a faster and radiation tolerant
version (e.g. pure CsI) is considered as an upgrade option;• the barrel part of the muon and KL detector is still equipped with RPCs, but with someinner layers perhaps operating in proportional mode, while the endcap part is replacedwith scintillators instrumented with silicon photomultipliers;• the new data acquisition system meets the requirements of a considerably higher event
rates.
In several aspects, Belle II will offer considerably better performance than Belle:• the vertex resolution is improved by the excellent spatial resolution of the two innermost
pixel detector layers;• the efficiency for reconstructing KS decays to two charged pions with hits in the silicon
strip detector is improved because the silicon strip detector occupies a larger volume;• the new particle identification devices in the barrel and endcap regions extend the very
good pion/kaon separation to the kinematic limits of the experiment;• the new electronics of the electromagnetic calorimeter considerably reduce the noise pileup, which is of particular importance for missing-energy studies.
The expected performance of the upgraded spectrometer is summarized in Table 1.3. In Chapters 4–12, we discuss the details for each individual component.

15

Table 1.3: Expected performance of components of the Belle II spectrometer.
Component
Beam pipeType
Beryllium
double-wall

Configuration
Cylindrical, inner radius 10 mm,
10 µm Au, 0.6 mm Be,
1 mm coolant (paraffin), 0.4 mm Be
Sensor size: 15×100 (120) mm2
pixel size: 50×50 (75) µm2
2 layers: 8 (12) sensors
Sensors: rectangular and trapezoidal
Strip pitch: 50(p)/160(n) - 75(p)/240(n) µm
4 layers: 16/30/56/85 sensors
56 layers, 32 axial, 24 stereor = 16 - 112 cm- 83 ≤ z ≤ 159 cm

Readout

Performance

PXD

Silicon pixel(DEPFET)

10 M

impact parameter resolution
σz0 ∼ 20 µm(PXD and SVD)

SVD

Double sided
Silicon strip

CDC

Small cell
drift chamberTOP

RICH withquartz radiator

16 segments in φ at r ∼ 120 cm
275 cm long, 2 cm thick quartz bars
with 4x4 channel MCP PMTs

8k

ARICH

RICH withaerogel radiator

78 k

ECL

CsI(Tl)(Towered structure)

KLM

barrel: RPCs

4 cm thick focusing radiatorand HAPD photodetectors
for the forward end-cap
Barrel: r = 125 - 162 cm
End-cap: z =-102 cm and +196 cm
14 layers (5 cm Fe + 4 cm gap)
2 RPCs in each gap
14 layers of (7 − 10) × 40 mm2 strips
read out with WLS and G-APDs

end-caps:
scintillator strips

245 k

14 k

6624
1152 (F)
960 (B)
θ: 16 k, φ: 16 k
17 k

σrφ =p
100 µm, σz = 2 mm=
σpt /p
(0.2%pt )2 + (0.3%/β)2pt
σpt /pt = (0.1%pt )2 + (0.3%/β)2 (with SVD)
σdE/dx = 5%
Np.e. ∼ 20, σt = 40 ps
K/π separation :efficiency > 99% at < 0.5% pion
fake prob. for B → ργ decays
Np.e. ∼ 13
K/π separation at 4 GeV/c:
efficiency 96% at 1% pion fake prob.
σE
0.2%
1.6%
√
1.2%
E = E ⊕ 4E ⊕√σpos = 0.5 cm/ E(E in GeV)
∆φ = ∆θ = 20 mradian for KL∼ 1 % hadron fake for muons∆φ = ∆θ = 10 mradian for KL
σp /p = 18% for 1 GeV/c KLReferences[1] Belle, A. Abashian et al.,9002(01)02013-7.

Nucl. Instrum. Meth. A479, 117 (2002),

10.1016/S0168-[2] S. Kurokawa et al., Nucl. Instrum. Meth. A499, 1 (2003), 10.1016/S0168-9002(02)01771-0.
[3] BABAR, B. Aubert et al., Nucl. Instrum. Meth. A479, 1 (2002), hep-ex/0105044,
10.1016/S0168-9002(01)02012-5.
[4] Nobelprize.org,
The
Nobel
Prize
in
Physics
http://nobelprize.org/nobel_prizes/physics/laureates/2008/.

2008,[5] S. Hashimoto, M. Hazumi, J. Haba, J. Flanagan, and Y. Ohnishi, editors, Letter of Intent
for KEK Super B Factory (KEK Report 2004-04, 2004), http://belle2.kek.jp/.
[6] sBelle Design Group, I. Adachi et al., (2008), 0810.4084.
[7] A. D. Sakharov, Pisma Zh. Eksp. Teor. Fiz. 5, 32 (1967).
[8] T. E. Browder, T. Gershon, D. Pirjol, A. Soni, and J. Zupan, (2008), 0802.3201.
[9] Belle, K. Abe et al., Phys. Rev. D66, 032007 (2002), hep-ex/0202027, 10.1103/PhysRevD.66.032007.
[10] Belle, K. Abe et al., Phys. Rev. D68, 012001 (2003), hep-ex/0301032, 10.1103/PhysRevD.68.012001.
[11] Belle, K. Abe et al., Phys. Rev. Lett. 91, 261602 (2003), hep-ex/0308035, 10.1103/PhysRevLett.91.261602.
[12] Belle, S. K. Choi et al., Phys. Rev. Lett. 91, 262001 (2003), hep-ex/0309032, 10.1103/PhysRevLett.91.262001.
[13] Belle, K. Abe et al., Phys. Rev. Lett. 93, 021601 (2004), hep-ex/0401029, 10.1103/PhysRevLett.93.021601.
[14] Belle, Y. Chao et al., Phys. Rev. Lett. 93, 191802 (2004), hep-ex/0408100, 10.1103/PhysRevLett.93.191802.
[15] Belle, K. Abe et al., (2004), hep-ex/0411049.
[16] Belle, Y. Ushiroda et al.,Phys. Rev. Lett. 94, 231601 (2005), hep-ex/0503008,
10.1103/PhysRevLett.94.231601.

17

REFERENCES[17] Belle, K. Ikado et al., Phys. Rev. Lett. 97, 251802 (2006), hep-ex/0604018, 10.1103/PhysRevLett.97.251802.
[18] Belle, M. Staric et al., Phys. Rev. Lett. 98, 211803 (2007), hep-ex/0703036, 10.1103/PhysRevLett.98.211803.
[19] BABAR Collaboration, B. Aubert et al.,10.1103/PhysRevLett.103.211802.

Phys. Rev. Lett. 103, 211802 (2009),[20] Belle, K. Abe et al., AIP Conf. Proc. 1078, 342 (2009), 0804.1580, 10.1063/1.3051954.
[21] Belle, S.-W. Lin et al., Nature 452, 332 (2008), 10.1038/nature06827.
[22] Belle, J. T. Wei et al., Phys. Rev. Lett. 103, 171801 (2009), 0904.0770, 10.1103/PhysRevLett.103.171801.
[23] S. Hashimoto, M. Hazumi, and B. Golob, editors, Physics at Super B Factory (KEK Report
2009-12, 2009), arXiv:1002.5012[HEP-EX], http://belle2.kek.jp/physics.html.
[24] O. Scheider, talk given at the 1st LHCb Collaboration Upgrade Workshop, Jan. 11-12, 2007
, http://www.nesc.ac.uk/action/esi/contribution.cfm?Title=729, 2007.
[25] Heavy Flavor Averaging Group, E. Barberio et al., (2008), 0808.1297, online updates at
http://www.slac.stanford.edu/xorg/hfag.
[26] H.-Y. Cheng, C.-K. Chua, and A. Soni, Phys. Rev. D72, 014006 (2005), hep-ph/0502235,
10.1103/PhysRevD.72.014006.
[27] D. Atwood, M. Gronau, and A. Soni, Phys. Rev. Lett. 79, 185 (1997), hep-ph/9704272,
10.1103/PhysRevLett.79.185.
[28] B. Grinstein, Y. Grossman, Z. Ligeti, and D. Pirjol, Phys. Rev. D71, 011504 (2005),
hep-ph/0412019, 10.1103/PhysRevD.71.011504.
[29] Belle, I. Adachi et al., (2008), 0809.3834.
[30] M. Gronau, Phys. Lett. B627, 82 (2005), hep-ph/0508047, 10.1016/j.physletb.2005.09.014.
[31] Belle, I. Adachi et al., (2008), 0809.4366.
[32] G. W. P. Spradlin and F. Xing, A study of D 0 → hh′ decays for D 0 − D̄ 0 mixing measurements (LHCb public note LHCb-2007-049, 2007).

18

Chapter 2

SuperKEKB
2.1

Machine Parameters

2.1.1

Nano-Beam Scheme

The KEKB B-Factory will be upgraded to SuperKEKB using the same tunnel as KEKB [1]. The
upgrade is based on the “Nano-Beam” scheme, which was first proposed for the Super B factory
in Italy [2]. The basic idea of this scheme is to squeeze the vertical beta function at the IP(βy∗ ) by minimizing the longitudinal size of the overlap region of the two beams at the IP, which
generally limits the effective minimum value of βy∗ through the “hourglass effect.” Figure 2.1
shows a schematic view of the beam collision, which is a plane figure, in the Nano-Beam scheme.
The size of the overlap region d, which is considered to be the effective bunch length for the
Nano-Beam scheme, is much smaller than the bunch length (σz ). The length d is determinedby the horizontal half crossing angle (φ) and the horizontal beam size at the IP (σx∗ ) via thefollowing equation:
d∼
=

σx∗
.
φ

(2.1)

The hourglass condition in the Nano-Beam scheme is expressed asβy∗ > d,(2.2)

instead of that for a usual head-on collision ofβy∗ > σz .

(2.3)

To shorten the length d, a relatively large horizontal crossing angle and extremely small horizontal emittances and horizontal beta functions at the IP for both beams are required.
The luminosity of a collider is expressed by the following formula, assuming flat beams and equalhorizontal and vertical beam sizes for two beams at the IP:
γ±
L=
2ere

I± ξy±
∗
βy±

!

RL
Rξy



,

(2.4)

where γ, e and re are the Lorentz factor, the elementary electric charge and the electron classicalradius, respectively. The suffix ± specifies the positron (+) or the electron (−). The parameters
19CHAPTER 2. SUPERKEKBFigure 2.1: Schematic view of beam collision in the Nano-Beam scheme.

Energy (GeV) (LER/HER)ξyβy∗ (mm)I (A)Luminosity (1034 cm−2 s−1 )KEKB Achieved
3.5/8.0
0.129/0.090
5.9/5.9
1.64/1.19
2.11

SuperKEKB
4.0/7.0
0.090/0.088
0.27/0.41
3.60/2.62
80

Table 2.1: Fundamental parameters of SuperKEKB and present KEKB.
RL and Rξy represent reduction factors for the luminosity and the vertical beam-beam parameter,
which arise from the crossing angle and the hourglass effect. The ratio of these parameters
is usually not far from unity. Therefore, the luminosity is mainly determined by the threefundamental parameters; i.e. the total beam current (I), the vertical beam-beam parameter(ξy ) and the vertical beta function at the IP (βy∗ ). The choice of these three parameters, thebeam energy and the luminosity is shown in Table 2.1 together with those of present KEKB.
For the vertical beam-beam parameter ξy , we assume the same value of 0.09 as has been achieved
at KEKB. The vertical beta functions at the IP for SuperKEKB are smaller by almost by afactor of 20 than those of the present KEKB owing to the adoption of the Nano-Beam scheme.
Assuming these parameters, we need to double the total beam currents compared with thoseof the present KEKB to achieve the luminosity goal of SuperKEKB, 8 × 1035 cm−2 s−1 . The
machine parameters of SuperKEKB including the three fundamental parameters are shown in
Table 2.2. In the following, it is shown how these parameters are determined.

2.1.2

Machine parameters of SuperKEKB

2.1.2.1

Emittance, crossing angle, beta functions at the IP

To realize the Nano-Beam scheme, the effective bunch length d(= σx∗ /φ) should be small. Of
the two parameters of σx∗ and φ, having a smaller σx∗ is more important than having a larger
φ, since it becomes difficult to obtain the design beam-beam parameter if we decrease d only
by enlarging φ. In the Nano-Beam scheme, each particle in a bunch interacts with only a small
portion of the other colliding bunch. To obtain the design value of ξy , extremely small horizontal
and vertical beam sizes are needed.
In the optics design of SuperKEKB, we have made efforts to decrease the horizontal emittance
while preserving as much as possible of the present lattice . The design values of the horizontal
emittance shown in Table 2.2, which are smaller by a factor 5 or 10 than those of the present
KEKB, include some enlargement due to intra-beam scattering. We are continuing the process

20

CHAPTER 2. SUPERKEKBBeam Energy
Half Crossing Angle
Horizontal Emittance
Emittance ratio
Beta Function at the IP
Horizontal Beam Size
Vertical Beam Size
Betatron tune
Momentum Compaction
Energy Spread
Beam Current
Number of Bunches/ring
Energy Loss/turnTotal Cavity Voltage
Synchrotron Tune
Bunch Length
Beam-Beam Parameter
LuminosityEφεxεy /εxβx∗ /βy∗σx∗σy∗νx /νy
αc
σε
I
nb
U0
Vc
νs
σz
ξy
L

LER (e+)4

HER (e-)7
41.5

3.2(2.7)
2.4(2.3)
0.40
0.35
32 / 0.27
25 / 0.41
10.2(10.1)
7.75(7.58)
59
59
45.530/45.570
58.529/52.570
2.74 × 10−4
1.88 × 10−4
8.14(7.96) × 10−4 6.49(6.34) × 10−4
3.60
2.62
2503
2.15
2.50
8.4
6.7
-0.0213-0.0117
6.0(4.9)
5.0(4.9)
0.09000.087535
8 × 10

units
GeV
mrad
nm
%
mm
µm
nm

A
MeV
MV
mm
cm−2 s−1

Table 2.2: Machine Parameters of SuperKEKB. Values in parentheses denote parameters at zero
beam currents.

Beam Energy
Half Crossing Angle
Horizontal Emittance
Emittance ratio
Beta Function at the IP
Horizontal Beam Size
Vertical Beam Size
Betatron tune
Momentum Compaction
Energy Spread
Beam Current
Number of Bunches/ring
Energy Loss/turnTotal Cavity Voltage
Synchrotron Tune
Bunch Length
Beam-Beam Parameter
LuminosityEφεxεy /εxβx∗ /βy∗σx∗σy∗νx /νy
αc
σε
I
nb
U0
Vc
νs
σz
ξy
L

LER (e+)4

HER (e-)7

41.5
3.2(2.3)
5.1(5.0)0.27
0.25
32 / 0.27
25 / 0.31
10.2(10.1)
11.2(11.1)
48.3
61.8
45.530/45.570
45.530/43.570
3.28 × 10−4
4.36 × 10−4−4
8.23(7.96) × 10
5.85(5.77) × 10−4
3.60
2.60
2500
2.13
2.07
9.64
12.0
-0.0250-0.0245
6.0(5.0)
5.0(4.9)
0.08860.0830
8 × 1035

units
GeV
mrad
nm
%
mm
µm
nm

A
MeV
MV
mm
cm−2 s−1

Table 2.3: Example of further optimization of machine parameters. Values in parentheses denoteparameters at zero beam currents.

21

CHAPTER 2. SUPERKEKB

of optimizing machine parameters, such as the horizontal emittance, etc., as shown in Table 2.3.
The optics of the IR are also undergoing further optimization.
The horizontal beta functions at the IP are also very small compared with those of the present
KEKB, the typical value of which is 1.2 m. Even with the very small horizontal emittances andthe horizontal beta functions at the IP, a rather low x − y coupling of approximately 0.25-0.4 %is needed to obtain ξy of 0.09.
The half crossing angle φ is 41.5 mrad, which is about 4 times larger than that of the present
KEKB. This choice of φ also contributes to decreasing the effective bunch length d. However, thedesign value of φ is determined mainly by considerations related to the optics of the interaction
region (IR), magnet design, and the detector background. With a large crossing angle, thefinal focus quadrupole magnets can be independent for the two beams, which has the meritof reducing the detector background due to synchrotron radiation. Another merit of a larger
crossing angle is that the final focus quadrupole magnets can be placed closer to the IP, which
contributes to widening the dynamic aperture.
Dynamic aperture is one of the most serious issues for SuperKEKB in the Nano-Beam scheme.
A narrow dynamic aperture shortens the beam lifetime from the Touschek effect and the lostparticles cannot be replenished by the injector if the lifetime is too short. With the parametersin Table 2.2, the effective bunch length d is ∼ 0.25 mm and ∼ 0.19 mm for the LER and the
HER, respectively. From the viewpoint of the hourglass condition, values of βy∗ even smaller
than those in Table 2.2 are possible . However, the achievable values of βy∗ in SuperKEKB are
restricted more strictly by dynamic aperture than by the hourglass effect.
2.1.2.2

Beam energy

In SuperKEKB, the beam energies have been changed from the present values of 3.5 and 8.0 GeV
to 4.0 and 7.0 GeV. In the Nano-Beam scheme, emittance growth due to intra-beam scatteringand the short beam lifetime due to the Touschek effect are very serious problems, particularlyin the LER. The increase in the beam energy of the LER from 3.5 to 4.0 GeV helps mitigate
these problems. In addition, the decrease in the beam energy of the HER from 8.0 to 7.0 GeV
is beneficial in obtaining a lower emittance. The impact of this change of the beam energy
asymmetry on the physics sensitivity is discussed elsewhere in this report.
2.1.2.3

Beam-beam parameterAs a design value for ξy , we assumed the value of 0.09, which was actually achieved at KEKB.
This value was achieved by using the crab cavities, which effectively enable a head-on collisionat the IP with beams crossing at an angle. On the other hand, SuperKEKB will adopt a large
crossing angle. Therefore, we need a careful study of the effect of the crossing angle on theachievable value of ξy .
In the case of a large crossing angle, there exists another kind of hourglass effect. A particle
with a finite horizontal offset at the IP collides with (the center of) the other beam at the place
where the vertical beta function βy is larger than its minimum value βy∗ . The difference of βyfrom its minimum value depends on the horizontal offset. This shift of the collision point fromthe vertical waist position depending on the horizontal offset creates another kind of hourglass
effect. This secondary hourglass effect could possibly degrade the beam-beam performance andlower the achievable value of ξy . It is known that this effect can be avoided by using the so-called“crab waist” scheme [2].
The crab waist scheme shifts the vertical waist position using sextupole magnets so that thevertical waistline of one beam is aligned along the trajectory of the other beam at the IP. Beam22

CHAPTER 2. SUPERKEKB

beam simulations have been done based on a strong-weak model to investigate the beam-beamperformance in the Nano-Beam scheme.
The simulations showed that the effectiveness of the crab waist scheme depends on the machineparameters, and that the luminosity improvement with the crab waist scheme is only about
10% with the SuperKEKB parameters in Table 2.2, as shown in Fig. 2.2. The simulation also
showed that the design value of 0.09 for ξy is achievable with the design parameters without the
crab waist scheme. A tune survey was also done in the beam-beam simulations to find the best
working point. The fractional parts of the betatron tunes shown in Table 2.2 were determined by
the simulation to maximize ξy . The optimum horizontal tune is not as close to the half integer
as is the case in KEKB.

Figure 2.2: The strong-weak beam-beam simulation with and without crab waist.

In the present design of SuperKEKB, we do not employ the crab waist scheme. However, we arestill considering the crab waist scheme as a backup option, because the simulation has predictedthat use of the crab waist scheme gives larger tolerances for machine errors and larger choicesof tunes. To give a more realistic estimation of the beam-beam performance, a strong-strong
simulation is underway.
2.1.2.4

Beam current and beam current related parameters

To achieve the target luminosity of 8 × 1035 cm−2 s−1 with the design values of βy∗ and ξy in
Table 2.2, beam currents of 3.60 and 2.62 A are needed for the LER and HER, respectively.
These currents are about twice as high as those in KEKB. We have been conducting R&D on
hardware components, such as the vacuum system and the RF system, assuming the even higher
beam currents of 9.4 A and 4.1 A in the LER and HER, respectively. These currents had been
assumed before we adopted the Nano-Beam scheme. The designs resulting from this long-term
R&D program can also be used at the relatively low currents that are now required.
The number of bunches per ring (nb ) is 2503, which implies that every other RF buckets is filledwith beam. If we decrease nb while maintaining the total beam currents, which implies higher
bunch currents, then we can obtain the same luminosity with a larger x-y coupling. This will
somewhat reduce the difficulty of the optics design or relax the requirement for the x−y couplingcorrection in actual beam operation. However, higher bunch currents bring other problems suchas difficulty in handling higher HOM power, single bunch instabilities such as the micro-wave
23

CHAPTER 2. SUPERKEKB

instability or emittance growth due to intra-beam scattering. With the design value of nb inTable 2.2, it has been determined that these problems are manageable.
As for the bunch length σz , a shorter bunch is preferable, since with a longer bunch length weneed to decrease the x-y coupling or increase the bunch currents to compensate for lower particle
densities in the beam overlap region at the IP. However, several bunch lengthening effects, suchas potential-well distortion, micro-wave instability and intra-beam scattering, prevent us fromachieving a short bunch length. The calculations of σz considering these effects with a wakefieldthat includes the effect of the coherent synchrotron radiation (CSR) showed that the design
values of σz in the Table 2.2 are attainable. The RF voltages in Table 2.2 were adjusted sothat the design value for σz is obtained at the design bunch currents with the effects mentioned
above.
We have also calculated the effect of the micro-wave instability at the design bunch currents toasses the impact on the energy spread σε . Although some enlargement of σε is expected, it isstill tolerable.

2.2

Lattice Design

2.2.1

Beam-optical parameters

As shown in Table 2.2 of Section 2.1.2, low emittances and small beta functions at the IP arenecessary to achieve the design luminosity of 8×1035 cm−2 s−1 . Two rings of 4 GeV and 7 GeV
have been designed to achieve the low emittance. A new Final Focus (FF) section with local
chromaticity correction sections has also been designed to strongly squeeze the colliding beams
in both the horizontal and vertical planes at the IP.
The LER has 4 arcs and 4 straight sections. Each arc is approximately 540 m long and consistsof 6 normal cells and one modified cell. The FF section is placed in the Tsukuba straight section,
containing the IP. A vertical chicane to transport one beam over the other ring is placed in thestraight section diametrically opposite the IP, the Fuji straight section. This straight section is
also utilized to adjust betatron tunes. RF cavities are also placed in the Fuji straight section.
The wiggler magnets, which adjust the emittance and damping time, are placed in the othertwo straight sections (Oho and Nikko), and RF cavities are also installed on the upstream sideof each wiggler section.
The geometry of the HER is the same as that of the LER. The straight section on the opposite
side of the IP is utilized to adjust betatron tunes. RF cavities are placed in the other two
straight sections and there are no wiggler magnets in those sections.
The quadrupole magnets from KEKB are reused as much as possible. However, the main dipole
magnets are replaced by new ones in order to achieve low emittance. To reduce the emittanceone order of magnitude below that of KEKB, the arc cells of both rings have been redesigned.
The emittance is analytically given byI
Cq γ 2
Hds,
(2.5)
εx =
2πρ20 Bendwhere
H = γx ηx2 + 2αx ηx ηx′ + βx ηx′2 .

(2.6)

In the case of the LER, the length of the main dipole magnet is changed from 0.89 m to 4 m to
make the bending radius longer. The wiggler sections have also been redesigned along with the24CHAPTER 2. SUPERKEKB

arc cells. The period of the wiggler magnets is reduced to half of that of KEKB by adding new
wiggler magnets.
In the case of the HER, the number of cells for each arc is increased from 7 to 9 to keep thehorizontal dispersion small and to reduce the emittance. The main dipole magnets, which are
5.9 m long, are replaced with ones 3.8 m long. Other straight sections outside the IR are almost
identical to those of KEKB.
The bunch length at zero beam current (nominal) is expressed ass
αp E 3
Cαp
σδ ∝
,
(2.7)
σz =
2πνs
Vc
where
σδ = γ
νs ∝

s

r

Cq
2ρ

(2.8)

αp Vc
.
E

(2.9)

Since the design of arc cells is dedicated to achieve extremely low emittance, the momentum
compaction factor, αp , cannot easily be used to adjust the bunch length. Therefore, the total
RF voltage, Vc , is adjusted to achieve the design bunch length. The nominal bunch length isdetermined by the luminosity requirement, with bunch lengthening due to intra-beam scattering,
the wake field effects from the ring impedance, and the effect of CSR at the design beam current.
Skew sextupole magnets have also been considered to correct chromatic x − y coupling at theIP, due to their demonstrated effectiveness in improving the luminosity at KEKB [3, 4]. This
technique is expected to give a dynamic aperture larger than that achievable without skew
sextupoles.

2.2.2

Arc cell

The arc lattice consists of 2.5π unit cells. Each arc cell includes two non-interleaved sextupolepairs for the chromaticity correction. Two sextupole magnets in a pair are connected with apseudo −I transform,


−1
0
0
0
 m21 −100 .
(2.10)
 0
0
−1
0 
0
0 m43 −1

In principle, nonlinearities in the sextupole magnets are cancelled in each pair. The arc unit
cells in the LER and HER are shown in Figs. 2.3 and 2.4, respectively. There are 7 families ofquadrupole magnets in a cell in the LER and 6 families in the HER with 6 constraints: 4 forthe pseudo −I conditions of two sextupole pairs, and 2 to adjust εx and αp by adjusting thehorizontal dispersion at the dipole magnets. We reduced the number of quadrupole families in
the arc cell for the HER in order to reduce the number of new magnets to be installed as muchas possible.

25

CHAPTER 2. SUPERKEKB

(b)

(a)

Figure 2.3: Arc unit cell in the LER. (a) KEKB-LER and (b) SuperKEKB-LER.

(b)

(a)

Figure 2.4: Arc unit cell in the HER. (a) KEKB-HER and (b) SuperKEKB-HER.

2.2.3

Interaction region

The FF section is designed to achieve very small beta functions at the IP, small nonlinearities
with non-interleaved sextupole pairs, and corrections of the large chromaticity generated in the
IR. The nominal values for the beta functions at the IP are 32 mm in the horizontal plane and270 µm in the vertical plane for the LER, 25 mm in the horizontal plane and 410 µm in thevertical plane for the HER, respectively.
To squeeze the beta functions, doublets of vertical focusing quadrupole magnets (QC1s) andhorizontal focusing quadrupole magnets (QC2s) are utilized. The distance between the centerof the first quadrupole and the IP is 0.92 m for QC1LP and 0.91 m for QC1RP in the LER and1.46 m for QC1LE and 1.38 m for QC1RE in the HER. The beams in the LER and HER collide
at the IP with a horizontal crossing angle of 83 mrad.
In the FF section, bending magnets are placed on both sides of the IP to make dispersion in
the region of the local chromaticity corrections (LCC). One family of sextupole pairs in thevertical plane (Y-LCC) or two families of sextupole pairs both in the horizontal and verticalplanes (X-LCC and Y-LCC) are used. A chicane type of LCC is adopted in the LER to increase
geometrical flexibility. In the case of the HER, a chicane type is adopted for the X-LCC and an

26

CHAPTER 2. SUPERKEKB

arc type is adopted for the Y-LCC to suppress the emittance generation at the LCC region.
The betatron phase advance between the center of QC1 and the closest sextupole magnet to
the IP in a Y-LCC pair is π in the vertical plane and the phase advance between QC2 and theclosest sextupole magnet to the IP in X-LCC is 2π in the horizontal plane. When the LCC
scheme is Y-LCC only, the closest sextupole pairs (SF2TL and SF2TR) to the IP in the arc
section are used in anway similar to that of X-LCC. The IR lattice is shown in Figs. 2.5, 2.6,
and 2.7.
The solenoid field of Belle II is fully compensated with compensation solenoids on each side of
the IP:Z
Bz (s)ds = 0.
(2.11)IP

The remaining x − y coupling components, and the horizontal and vertical dispersions are corrected to be zero at the IP, and are localized in the IR on each side of the IP. In order to makethis possible, skew quadrupole magnets, as well as horizontal and vertical dipole magnets areused to adjust these optical parameters and to satisfy geometrical constraints.
The beam trajectory becomes a three-dimensional twist. Therefore, the x−y axis rotates aroundthe beam axis along the beam trajectory. The rotation angle can be calculated asZ
1
Bz (s)ds.
(2.12)
θ=
2Bρ IP
Final focusing quadrupole magnets (QC1 and QC2) within the solenoid field also rotate aroundthe beam axis and the optical parameters can be optimized to eliminate x − y coupling at the
IP. The angle between the solenoid axis and each beam axis of the LER and HER is 41.5 mrad,
which is optimized by the vertical emittance due to synchrotron radiation coming from the fringe
field of the solenoid magnet. The vertical emittance is estimated approximately as 2 Zpεy ∝H(s)ds ∝ Bx4 (s),(2.13)
ρwheresφx
Bx (s) ≃ − Bz′ (s) ≃ − Bz′ (s).
22(2.14)To reduce the vertical emittance due to the solenoid fringe field, the half crossing angle, φ and/or
the rate of change of Bz should be decreased.

2.2.4

Dynamic aperture

The dynamic aperture is defined by requiring stability in 1000 turns with synchrotron oscillation and without radiation damping, which gives almost the same result in one transverse
damping time with radiation damping. The dynamic aperture is estimated numerically with
six-dimensional tracking simulations using SAD[5], which is an integrated code for optics design
and particle tracking. In the case of the Nano-Beam scheme, the dynamic aperture will be reduced because of the nonlinear fringe and kinematic terms in the IR, and also strong sextupole
magnets. The aperture for the initial action Jy0 is written as [6]
Jy0 =

βy∗2
(1 − 32 Kl∗2 )l∗
27

A(µy ),(2.15)

CHAPTER 2. SUPERKEKB

(b)

(a)

Figure 2.5: One family of sextupoles in LCC. (a) LER lattice design in the IR and (b) theregion for adjusting of x − y coupling and dispersions.

(b)

(a)

Figure 2.6: Two families of sextupoles in LCC. (a) LER lattice design in the IR and (b) theregion for adjusting of x − y coupling and dispersions.

28

CHAPTER 2. SUPERKEKB

(b)

(a)

Figure 2.7: Two families of sextupoles in LCC. (a) HER lattice design in the IR and (b) theregion for adjusting of x − y coupling and dispersions.
where K is a magnetic-field strength and the sign of K is negative for the final quadrupole
magnet. This equation implies that the dynamic aperture decreases as the beta function at the
IP is squeezed and as the distance (l∗ ) between the IP and the final quadrupole is increased.
The dynamic aperture affects both Touschek lifetime and injection efficiency of the beams. The
target Touschek lifetime is 600 sec for the LER and HER. The beam lifetime must be larger than
181 sec for the LER and 105 sec for the HER at least, which is calculated from the injection
rate assuming 100% injection efficiency. The requirements for dynamic aperture for betatron
injection is shown in Table 2.4. The lattice optimization for the dynamic aperture is still inprogress for both LER and HER.
Table 2.4: Required transverse apertures (Ax and Ay ) and momentum aperture (∆p/p0 ) for
betatron injection.
LER
HER
Unit
Beam Energy
E
4
7
GeV
Horizontal
Ax
5.11×10−7
3.77×10−7m−7−7injection error 2Jx
4.19×10
3.32×10m
VerticalAy
1.10×10−8
1.46×10−8minjection error 2Jy00mLongitudinal
∆p/p0
0.21
0.24
%

2.3

Magnets

2.3.1

Magnet replacements

A major change in the magnet system will be required. The main dipole magnets in the LER
and HER will be replaced. The LER dipoles become longer (from an effective length of 0.89 m
to ∼4 m) and the HER dipoles become shorter (from 5.91 m to 3.8 m). More dipole, quadrupole29

CHAPTER 2. SUPERKEKB

and sextupole magnets are needed in the HER since the number of cells in the arc sections isby about 30% larger than in the KEKB lattice, as shown in Fig. 2.8. More wiggler magnets,
with shorter pole lengths, are needed in the Nikko and Oho straight sections. The layout of
the wiggler section magnets will change as shown in Fig. 2.9. Vertical steering magnets need tobe replaced by new magnets with wider gaps to account for the antechambers. The magnetic
properties of the steel used for the magnets should be the same as that used for the KEKB
magnets, as some of the magnets will be reused.
There may be a need for new, stronger sextupole magnets. One way to increase the field is toreplace the power supplies and run the magnets at higher currents. The excitation curve of a
KEKB sextupole magnet is shown in Fig. 2.10, where the integrated sextupole field is plottedagainst the current. Since a clear saturation is seen, replacement by new sextupole magnets ispreferable to achieve much higher fields.

Figure 2.8: Magnet layout in the north arc section. The present KEKB magnet layout andthe new magnet layout are represented with black and grey lines, respectively. The LER dipole
magnets (B2Ps) become longer while the HER dipole magnets (B2Es) become shorter. The
HER arc lattice changes result in more cells and more magnets being needed.

2.3.2

Field measurements

Precise magnetic field measurements need to be performed for all new magnets. Some of therecycled magnets also need to be measured, as they will be operated at higher currents thanin KEKB. A new flip-flop coil system needs to be made for measuring the new dipole magnets.
The probes of the two harmonic coil systems need refurbishment, most likely to be replacedby new sensors. The total number of magnets to be measured is estimated to be close to one
thousand. The tolerances on the multipole errors are expected to be the same as those of the
KEKB magnets [7].

2.3.3Magnet installation and alignment

First, almost all of the magnets will need to be removed from the beam line; whether they
will be moved to outside of the tunnel depends of the construction scenario. Most of the HER30

CHAPTER 2. SUPERKEKBFigure 2.9: Wiggler section layouts for KEKB (left) and SuperKEKB (right).

Figure 2.10: The excitation curve of the KEKB sextupole magnet.

31

CHAPTER 2. SUPERKEKB

quadrupole magnets will be reused, at new positions in the tunnel. Most of the base-plates,
which support the magnets in the arc sections, will also be removed. A survey of monuments
for the magnet alignment will follow the floor refurbishment.
Though the LER arc lattice does not change, the LER magnet positions are shifted toward theoutside of the tunnel to compensate for the circumference change, which comes from the neworbit in the interaction region. Realignment of all the magnets will be necessary in both the
LER and the HER. The alignment network is expected to be improved with more monuments
being added to the tunnel walls. Alignment of the magnets and mechanical stability of magnets
will be very important to approach single-beam emittance coupling values of 0.3-0.4%. The
movers of the sextupole magnets might be replaced by more rigid supports to reduce vibration.

2.3.4

Utilities and facilities

A larger capacity water cooling system is required to operate the increased number of magnets.
The number of water pump systems will be doubled from the present four to eight, as is indicatedin Fig. 2.11. The plumbing work outside and inside the tunnel will be arranged and carried out
by the Facilities Department.

Figure 2.11: Cooling water system.

2.3.5

Power supplies

More power supplies are needed, as the number of magnet families increases. A request for more
space in the power supply buildings has been made. There will be more cables from the buildings
32

CHAPTER 2. SUPERKEKB

to the tunnel, which may require adding more thru holes from the power supply building to
the tunnel. New power supplies are needed to run at higher currents and/or with different
specifications, which include the power supplies for the new IR superconducting magnets. The
design work of the new power supplies can start when the magnet design is fixed, after themachine lattice is finalized. Some very old power supplies need to be replaced: most likely thepower supplies for the LER and HER dipole magnets will be replaced. Cabling in the tunnel
needs to be (mostly) removed and reorganized.
Since the amount of work and effort of redoing the magnet and power supply systems forSuperKEKB is massive, the magnet workload may become the critical path item for the project’sschedule.

2.4

RF

2.4.1

RF Overview

The present RF system for KEKB consists of 20 ARES cavities for the LER and 12 ARES and 8
superconducting (SC) cavities for the HER, powered by 25 klystrons in total [8]. Beam currents
of up to 2.0 A in the LER and 1.45 A in the HER have been stored.
Table 2.5 gives the RF-related machine parameters and the design RF parameters for SuperKEKB. In each ring the design beam current is twice that of the present KEKB, and therequired beam power in the LER is three times larger. On the other hand, the total RF voltage
is low, particularly in the HER, about half that of the KEKB HER. The low RF voltage withhigher beam current and larger beam power makes beam-loading effects much more serious in
SuperKEKB. If the present RF system is used with the current configuration, several problems
arise. First, the input coupling of the ARES needs to be increased to an unacceptably high levelto obtain the optimum coupling at the design beam current. Second, the input couplers of the
SC cavities also need to be replaced with more strongly coupling ones to reduce the loaded-Q
values by a factor of three or four. This work can cause possible air dust contamination on
the SC cavity surface. The tips of the couplers also may have heating problems. Third, thedetuning frequency of the SC cavities will become comparable with the revolution frequency,
which makes the growth time of the -1 mode longitudinal coupled-bunch instability associatedwith the accelerating mode on the order of 100 microseconds.
To solve these problems, two measures will be taken. One is that the RF system configuration
with the ARES cavities will be changed from the present scheme where one klystron drives two
ARES cavities to a different scheme where one klystron drives one ARES. For this, we add
klystrons, but remove some of the ARES cavities. The high power RF and LLRF system layout
will be changed accordingly. Each RF station will be operated at around 800 kW, well below
the saturation level of the klystrons. At this power the klystrons, power supplies and high-power
RF system can be operated stably. In this way the power delivered by each ARES cavity to thebeam can be increased from 220 kW up to 600 kW, while the total RF voltage is kept low.
Another measure is to introduce a new operation scheme for the SC stations, the so-called“Reverse Phase Operation (RPO).” Figure 2.12 shows a phasor diagram of the cavity voltage
for RPO scheme. The phase of a part of SC cavities are set on the time-rising side (reverse
phase), while others on the time-descending side (normal phase). With this scheme a low total
RF voltage is obtained, while each cavity can be operated at a high voltage. Beam power isshared by all cavities, including the reverse-phase ones. Merits of the RPO scheme are: (1) noneed to change the input coupling, (2) the detuning frequency is kept sufficiently small, and (3)the impedance of the reverse-phase cavities cancels that of normal phase ones. The -1 mode
33

CHAPTER 2. SUPERKEKBTable 2.5: RF parameters for SuperKEKB.
LER
HERBeam energy
4.0
7.0
Beam current
3.60
2.62
Number of bunches
2503
2503
Energy loss/turn
2.15
2.50
Momentum compaction
2.74
1.88
Radiation loss
7.74
6.55
Total loss factor
25
40
Parasitic loss
1.30
1.10
Total beam power
9.04
7.65
Total RF voltage
8.4
6.7
Cavity type
ARES ARES+ SCC
Number of cavities18
8
8(3 for RPO† )RF voltage/cavity
0.467
0.48
1.3
Wall loss/cavity
131
139
Beam power/cavity
502
556
400
Input coupling
4.84
5.01
Loaded Q value
1.9
1.8
∼5
Klystron output
677
744
428
Detuning frequency
28.1
18.4
47.4
† Reverse Phase Operation (RPO)

unit
GeV
A
MV
× 10−4
MW
V/pC
MW
MW
MV

MV
kW
kW
× 104
kW
kHz

Figure 2.12: Phasor diagram of the reverse phase operation.
instability growth rate becomes acceptably small. Harmful gap transient effects also cancel out.
By changing to the 1:1 scheme for the ARES stations and introducing the RPO for the SC
stations, the required beam parameters can be satisfied, as shown in Table 2.5. The system
configuration change is summarized in Table 2.6.
In the HER, another scheme with 14 ARES cavities alone without SC cavities would also work.
34

CHAPTER 2. SUPERKEKB

However, we choose the SC and ARES hybrid system as the baseline scheme for the following
reasons: (1) the existing SC cavities and cryogenic system can be used without large changes.
(2) We can continue progress on KEK’s world-leading technology and maintain experience with
SC cavities for high current applications; KEKB-type cavities have been successfully operatingin BEPC-II at IHEP, and are also being considered for adoption at other laboratories. (3) The
RPO scheme has been tested at KEKB, and no serious problem with this scheme has been foundso far. Thus we consider the 14 ARES scheme as a back-up option. Details of the beam test
results for RPO will be given in Section 2.4.3.
Table 2.6: Reinforcement of RF stations by changing to 1:1 configuration. (Numbers listed arenumber of klystrons/number of cavities.)
Building
KEKB
SuperKEKB Change
LER HER LER HER(ARES cavity stations)
D4
3/6
6/6
add 3 klystrons
D5
4/6
6/6
add 2 klystrons, convert from HER to LER
D7
5/10
6/6
add 1 klystron, remove 4 ARES
D8
5/10
6/6
add 1 klystron, remove 4 ARESD11
2/2
add 2 klystrons, install 2 ARES(SC cavity stations)
D10
4/4
4/4
no change
D11
4/4
4/4
no change

2.4.1.1

Bunch gap transient

In KEKB, owing to the high stored energy of the ARES and SC cavities, transient phase modulation and longitudinal position shift along the bunch train due to an abort gap is small, about
3 to 5 degrees. No luminosity degradation along a train related to this effect has been observed.
Calculation and measurements show good agreement [9]. In SuperKEKB, since the beam current is twice as high, the gap length has to be reduced to less than half, from 500ns to 200ns, tokeep the transient phase modulation as small as in KEKB. For this, the rise time of the abort
kicker needs to be shortened.
2.4.1.2

Coupled-bunch instabilities

Table 2.7 shows a summary of growth time of coupled-bunch instabilities related with the RF
cavities. The fastest growth time of longitudinal instabilities caused by HOM in the ARES
cavities is 15 ms, which is faster than the radiation damping time. A longitudinal bunch-bybunch feedback system is needed for SuperKEKB, in addition to the transverse feedback. The-1 mode instability will be safely cured by the -1 mode damper implemented in the RF system.
2.4.1.3

RF system for Damping Ring

According to the design parameters of the Damping Ring, the required RF voltage and beam
power is 0.261 MV and less than 10 kW, respectively. This can be provided by one RF station
with a klystron output power of less than 150 kW. The HPRF and LLRF components can becompatible with those of the LER and HER. However, because of tight space constraints in the35

CHAPTER 2. SUPERKEKBTable 2.7: Instability due to RF cavities and cure.
Ring
Cause
Frequency Growth time Cure
(MHz)
(ms)
Longitudinal LER
ARES-HOM
1850
15
BbyB FB
ARES-zero/pi
504
29
BbyB FB-1 mode508.795-1 mode damper
Longitudinal HER
ARES-HOM
1850
75
slower than τrad,L †SCC-HOM
1018
58
slower than τrad,L-1 mode508.7911-1 mode damper
Transverse
LER
ARES-HOM
633
9
BbyB FB
Transverse
HER
ARES-HOM
633
48
slower than τrad,T ††SCC-HOM
688
14
BbyB FB†τ††
rad,L and τrad,T are longitudinal and transverse radiation damping times, respectively.
Direction

tunnel and no need for the energy-storage cavity, a new accelerating cavity based on the ARES
design, but without a storage cavity, will be used.

2.4.2

ARES cavity

The ARES cavity is a three-cavity system operated in the π/2 mode, in which an accelerating
cavity is resonantly coupled with an energy storage cavity via a coupling cavity between [10].
The name “ARES” stands for “Accelerator Resonantly coupled with Energy Storage,” which
represents its RF schematic. Fig. 2.13 shows a schematic 3D view of the ARES cavity developed based on a conceptual demonstrator named ”ARES96” [11], together with an equivalent
kinematic model consisting of three coupled pendulums.
The energy storage cavity, corresponding to the left-side pendulum with the very large mass,is operated in the TE013 mode and functions as a kind of electromagnetic flywheel to stabilize
the π/2 accelerating mode against heavy beam loading on the accelerating cavity, which corresponds to the right-side pendulum. The accelerating cavity itself is a HOM-damped structure,
carefully designed to be smoothly embedded into the whole ARES scheme. Four rectangular
waveguides are directly brazed to the upper and lower sides of the accelerating cavity. Each
HOM waveguide is terminated with two bullet-shaped SiC ceramic absorbers directly cooled bywater flowing inside. The beam pipes at both ends of the accelerating cavity are Grooved Beam
Pipes (GBPs) [12] with two grooves at the upper and lower sides of each circular pipe. In eachgroove, eight SiC tiles are arranged in a line and are brazed to a water-cooled copper plate.
Details of the HOM absorbers for the ARES cavity system are found in [13]. The coupling
cavity, corresponding to the central pendulum, is the keystone of the ARES cavity system, andis equipped with an antenna-type coupler [14] to damp the parasitic 0 and π modes. RF poweris fed through an input coupler [15] installed on the storage cavity, being transferred from arectangular waveguide, via a doorknob transformer, through a coaxial line with an RF window,
and finally to a coupling loop at the end.
At present, there are 32 ARES cavities being stably operated in KEKB, 20 for the LER and 12
for the HER, respectively. With our experience accumulated through KEKB machine operations
so far, we are reasonably confident that the present ARES cavity system can be operated, even
without upgrades to the ARES cavity itself, for SuperKEKB using the Nano-Beam scheme. In
SuperKEKB, 26 out of the 32 ARES cavities will be reused, 18 for the LER and 8 for the HER,
36

CHAPTER 2. SUPERKEKBFigure 2.13: A schematic 3D view of the ARES cavity.
respectively, where every ARES cavity is fed with RF power up to 800 kW at maximum fromone klystron capable to deliver 1 MW CW.
However, the increased HOM power for SuperKEKB is our primary concern. Table 2.8 summarizes the HOM power projections for the ARES cavity when being operated in the SuperKEKB
LER, together with the results of calorimetric measurements in the KEKB LER. The total HOM
power per cavity is estimated to be 17 kW for the design total beam current of 3.6 A consistingof 2503 bunches with a bunch length of 6 mm. As for the HOM waveguide, the estimated poweris 3.3 kW per waveguide, which is 66 % of the handling capability of 5 kW determined based on
the results of high power tests with an L-band klystron. As for the GBP, the estimated power
is 0.93 kW per groove, which is close to the power handling capability of 1 kW with a marginof about 8 % left.
Table 2.8: HOM power projections for SuperKEKB LER.
KEKB LER SuperKEKB LER Verified††
Sep. 21,2004
Beam current [A]
1.6
3.6
Number of bunches
1293
2503
Bunch length [mm]76†Loss factor [V/pC]
0.40 (0.39 )0.44
PHOM /ARES [kW]
5.4†
17
†
PHOM /HWG [kW]
1.05
3.3
5.0
PHOM /Groove [kW]
0.3†
0.93
1.0
† Calorimetric measurement.
†† RF power handling capability verified at 1.3 GHz.

37

CHAPTER 2. SUPERKEKB

As for the input coupler, the power handling capability over 800 kW has already been demonstrated at a high-power test stand [16]. However, multipactoring discharge in the coaxial section
has been observed in about 10% of the input couplers in use in KEKB. To eliminate this concern
for the high power operation of the couplers for SuperKEKB, fine circumferential grooving has
been applied to the inside of the outer conductor, and successfully tested on the high-power test
stand, and used in actual KEKB operation [17]. In addition, the input coupling factor needs to
be increased up to 6 for SuperKEKB, about two times as large as in the current type, and has
been demonstrated over 6 up to 8 in low power tests. Currently, a prototype coupler is underfabrication, and will be tested on the high-power test stand in April 2010. It will be installedon an operational ARES cavity for May.

2.4.3

Superconducting cavity

Eight superconducting accelerating cavities in KEKB-HER have been operated stably for morethan ten years. These cavities will be reused in SuperKEKB. Two major modifications areneeded to satisfy the requirements for SuperKEKB. One is to improve the HOM dampers toabsorb higher HOM power. The other is introducing Reverse Phase Operation (RPO), describedin Sec. 2.4.1.
2.4.3.1

HOM damper

The design bunch length, 5 mm in the HER, generates 46 kW of HOM power in one cavity at 2.6
A with 2500 bunches. The HOM power has to be absorbed in the ferrite HOM dampers attachedto the two beam pipes on either side of the cavity. The most serious issue is the outgassing fromthe ferrite material. The outgassing condenses on the cavity wall and can trigger a breakdown.
To suppress outgassing, the surface temperature of the ferrite material must be decreased. Two
improvements are being developed for this. One is a thinner ferrite damper with a thicknessof 3 mm (the present damper is 4 mm thick). A prototype of the 3 mm thick damper was
fabricated and high-power tested. The surface temperature was reduced by 25%. Another is adouble cooling channel structure for more efficient cooling of the ferrite surface. A prototype
damper with a double cooling channel structure is being fabricated, and will be tested. This is
expected to further reduce the surface temperature by 17%. With these improvements, the HOM
damper is expected to absorb the required HOM power without generating serious outgassing.
2.4.3.2

Beam test for the Reverse Phase Operation

Feasibility studies for the RPO scheme were conducted in KEKB several times in 2009. The
parameters related to the RF voltage and the synchronous phase, such as the synchrotron tune,
the bunch length and the beam loading in the reversed cavity, were measured. The results
showed that the total RF voltage obtained was as expected by calculation. Transient behaviorof the cavity voltage, tuner phase, the input power and reflected power were measured when oneof the cavities tripped. The transient behaviors are well understood by taking the beam-loading
effects into account, and the beam was normally aborted by the abort system. The increase of
the cavity voltage and the reflected power before the beam abort were acceptable.
After the dedicated machine studies, the RPO scheme was tried in beam collision operation
during the physics run for five days. A beam current of up to 1.2 A was stored, and an RF
power of more than 300 kW was delivered to the beam in each cavity. The RPO scheme operated
stably during this period. Thus the feasibility of the RPO scheme was demonstrated, and thisscheme will be used in SuperKEKB.
38CHAPTER 2. SUPERKEKB

2.5

Beam instrumentation

2.5.1

Beam position monitor system

About 510 beam position monitors (BPMs) will be installed in the HER and 460 in the LER.
The BPM system will have four functions based on discussions so far: 1) precise slow orbit
measurement with a repetition rate of several Hz, 2) fast orbit measurement for orbit stabilization
feedback with a repetition rate of several kHz, 3) turn by turn orbit measurement of a pilot bunchthat is located at the end of a bunch train for the optics measurement during collision and 4)
orbit measurement near the interaction point to maintain stable collision.
We need to take into account the following factors for the system design: 1) a large beam current,
about twice that of KEKB, which could cause poor electrical contact of a button electrode, large
signal power to a detector and movement of the BPM due to thermal deformation of the beamchamber, 2) use of antechambers whose lowest cut-off frequency of about 900 MHz is below
the detection frequency of the present KEKB system, and 3) maximal use of the existing BPM
system to minimize costs. Based on the above considerations the following efforts are in progress.
A button type pickup electrode with a small diameter of 6 mm was developed. It has a pin type
inner conductor to ensure tight electrical connection. The electrode is attached to the beamchamber with a flange for ease of removal in case of problems with the electrode, and for ease ofTiN coating of the chamber. It has already been tested at KEKB. No problem has been foundso far.
A narrow-band super-heterodyne detector with a detection frequency of 509 MHz is underdevelopment based on a detector used at KEKB. Switch modules can be used in front of thedetector to cover four electrodes with one detector.
A medium-band detector with a repetition rate of 5 kHz is also being developed for orbit stabilization feedback and optics measurement during collision. It has two signal paths: detectionof 509 MHz frequency component via direct sampling followed by a digital filter, and log-ratio
detection with a fast gate for optics measurement. Cost is a factor limiting full use of themedium-band detector. It will be evaluated in detail after a prototype of the medium-band detector is tested. A combination of narrowband detectors together with medium-band detectors
could be a good compromise of cost and performance. For example, the medium-band detectors
can be used for BPMs near sextupoles where optics will be sensitive to orbit deviations.
A special detector for the orbit measurement for the collision feedback is also being developed.
A displacement sensor that measures the displacement between a quadrupole or a sextupole anda nearby BPM caused by movement of a chamber will be used in SuperKEKB. About 230 sensors
are already installed in KEKB. A special reference target and sensor arms made of ceramic witha very low thermal expansion coefficient of less than 3 × 10−6 K−1 is under development for use
at positions where the optics are sensitive to the orbit position.

2.5.2

Bunch-by-bunch feedback system

The following considerations are taken into account to design the bunch-by-bunch feedback
system that damps coherent betatron and synchrotron oscillations: 1) a longitudinal feedback
system, which is not used in routine operation at KEKB, is required in the LER of SuperKEKB
because the growth time of longitudinal coupled-bunch instabilities caused by higher order modesof the ARES cavities is estimated to be 15 ms, which is shorter than the longitudinal radiation
damping time of 19 ms, 2) noise in the transverse feedback system should be minimized toreduce the blowup of the beam size during collision as suggested by beam-beam simulation, and39

CHAPTER 2. SUPERKEKB

3) vacuum components such as kickers, power cables, feedthroughs and BPM electrodes shouldwithstand large beam currents.
Two sets of short strip line kickers will be installed in each ring for the transverse feedback
system. The maximum kicker voltage is 8.9 kV in both rings. The expected damping time is0.27 ms for the LER and 0.45 ms for the HER for a maximum oscillation amplitude of 0.3 mm.
The expected damping time is comparable to the estimated instability growth time of electron
cloud instability (ECI) in the LER and fast ion instability (FII) in the HER. The study of ECIand FII has just started. More study is needed to determine target values of the damping time.
The results of further study might have an impact on the design of the feedback system. A
simulation and a recent beam study at KEKB showed that the noise signal in the transverse
feedback system affected the luminosity. Considering the very small beam size at the IP, thefeedback noise should be reduced as much as possible. Development of low-noise front-end
electronics with comb filters has started.
Two DAFNE type kickers will be installed in the LER for the longitudinal feedback system.
The total kicker voltage is 3.2 kV. The expected damping time is 10 ms for an energy deviationof 4x10−4 .
The iGp digital signal processing system will be used in both the longitudinal and transverse
feedback systems. The system is developed under US-Japan collaboration between KEK and
SLAC. FIR filters with maximum 8 taps are available. It has a down-sampling function forthe longitudinal feedback system. Transient analysis of the bunch oscillation is possible for the
study of beam instabilities. The system was tested successfully at KEKB, the KEK-PF andother laboratories.

2.5.3

Synchrotron light monitor

2.5.3.1

Visible light monitor

The vertical beam size at the monitor source point is about 20 µm in both LER and HER.
Measurement of the size is possible with interferometers, though it is at the limit of the resolution.
An extraction mirror is installed in an antechamber slot to reduce the impedance. The limitationon the resolution is due to interferometer slit separation, which is limited by the slot height of
the antechambers; this appears difficult to increase due to the presence of upstream quads.
Heat load at high beam currents causes distortion of the extraction mirrors. Input power to themirrors is about 50% higher than that in KEKB if the bending radius of the light source bendin the LER is doubled. Investigation of new mirror structures, e.g. thin Be on thin water-cooled
Cu plate, is underway in order to reduce the distortion further.
Several options for the visible light monitors, e.g., a standard interferometer using σ polarization,
an interferometer using π polarization and a vertical polarization monitor as used at PSI, areconsidered for applicability to different types of measurements. The longitudinal bunch profiles
will be measured by streak-cameras.
2.5.3.2

X-ray beam size monitor

An X-ray beam size monitor will be introduced to provide high-resolution bunch-by-bunch measurement capability. The system has no extraction mirror; thus, low beam current dependenceof the measurement is expected. We are developing a system based on coded aperture imaging, which was developed by X-ray astronomers, using a mask to modulate the incoming light.
The large open-aperture of the mask of 50% gives high flux throughput for bunch-by-bunchmeasurements. The X-ray sources will be the last arc-bends located immediately upstream of40

CHAPTER 2. SUPERKEKB

the straight section (LER: Fuji, HER: Oho). Research and development of the monitors is inprogress under collaboration with Cornell University, University of Hawaii and SLAC. Beamsize measurements down to 10-15 µm have been demonstrated so far at CesrTA at Cornell.
2.5.3.3

Beamstrahlung Monitor

We have a plan to install a beamstrahlung monitor developed by G. Bonvicini originally for
use at CESR. The monitor uses the relative strengths of horizontal and vertical polarization
components of wide-angle beamstrahlung to diagnose the quality of collisions, allowing a direct
evaluation of parameters such as beam separation and relative beam sizes at the collision point.
Estimation of signal and background level shows that a much stronger signal than that seen at
CESR is expected.
2.5.3.4

Direct detection X-ray monitor

This monitor is under consideration for supplementary size measurement. The basic principleof the monitor is to use X-rays penetrating the chamber walls downstream of bends directly
to measure beam emittance. The system is very simple, with no optics elements required. It
requires a small thin region (∼1 mm thick) on the outer wall of the antechamber to extract the Xrays. Candidate locations for the monitor are found in the local chromaticity correction sections
around the interaction point with huge beta functions and no overlap light from upstream bends.

2.5.4

Gated measurement system for tune, orbit and longitudinal phase of abunch

The measurement of tune, orbit and longitudinal phase of a bunch proved to be a very usefuldiagnostics tool in KEKB. It is used for tune stabilization feedback, the measurement of tune
shift along a train due to electron clouds, the estimation of beam-beam kick and so on. The
system will also be used in SuperKEKB. A fast gate module has already been developed to
select individual bunch signals separated by one RF bucket of 2 ns. A test to excite betatronoscillation of a particular bunch was successfully carried out with a phase-locked loop. As afeasibility test of the optics measurement during collision, the turn-by-turn orbit of a bunch
located 6 ns after a bunch train was measured with a gated circuit. The experiment showedthat the system had the sensitivity needed to measure x − y coupling parameters near the IP.

2.6

Vacuum System

2.6.1

Issues for vacuum system

The design of the vacuum system for SuperKEKB is based on our operational experiencesat KEKB, but also introduces some novel concepts at the same time, in order to meet thechallenging beam parameters to achieve an unprecedented luminosity.
The first major issue for the vacuum system comes from the high beam currents. The synchrotron
radiation (SR) power and the photon density are consequently high, and the resultant heat andgas loads are also large. Another issue comes from the high bunch current and the short bunch
length. Higher order modes (HOM) are likely to be excited and the loss factors of various
vacuum components need to be minimized to keep the HOM power losses as low as possible.
Beam impedance is also a key issue for maintaining small beam emittances. The electron cloud
effect in the positron ring (LER) and the fast ion effect in the electron ring (HER) are more
41

CHAPTER 2. SUPERKEKB

severe than before. Described here are the basic vacuum system designs mainly for arc sectionsof the rings. A design for the IR will be presented elsewhere.

Figure 2.14: Beam chamber with antechambers for the LER.

2.6.2

Beam chamber

Beam chambers for the arc sections have an antechamber structure [18]. A beam chamberconsists of a beam channel and two antechambers at both sides. A schematic view of an antechamber for the LER is shown in Fig. 2.14 . The beam goes through a beam channel, and theSR passes through an antechamber located at the outside of the ring (SR channel) and hits theside wall of the antechamber. The beam chamber should be nearly circular in order to minimize
the incoherent tune shift due to the image charge.
Pumps are provided in an antechamber (pump channel) at the inside of the ring. The pumpchannel is connected through a screen with many small holes. Two cooling channels are provided
on the outside of the antechambers. A beam position monitor (BPM) section will be fabricatedin a block, as in the present KEKB, with the same cross section as that of the beam chamber.
When a single-pipe chamber is used in some sections, in a straight section for example, tapers
are required at the transitions from an antechamber structure to a single-pipe one. The crosssection, as shown in Fig. 2.14, fits within the present magnets except for vertical correctors.
One advantage of the antechamber scheme is that the power density of the SR can be reduced.
Since the incident point of SR on the side wall is far from the emitting point, the incident SR
power density is diluted. The antechamber scheme also has the advantage of a small beam
impedance. Since the pumping channels are located in the antechamber, the pumping holes
have little effect on the beam. Photon masks are also placed in the SR channel. For the LER,
the antechamber structure is very important in reducing the effects of the photoelectrons, as
described later.
In the case of the HER, if an antechamber structure with a horizontal half-width of 90 mm isused, the maximum SR power density at a beam current of 2.62 A is approximately 11 kW/m
(19 W/mm2 ), which is almost the same level to the case of the present KEKB HER (1.4 A).
42

CHAPTER 2. SUPERKEKBThe wiggler section in the LER also requires the antechamber structure to reduce the SR power
density down to 20 kW/m (20 W/mm2 ) by using a beam chamber with a half-width of 110 mm.
Copper (Oxygen free copper, OFC) is therefore a suitable material in these cases. No leadshielding is required for copper. Copper beam chambers with antechambers can be formed by acold-drawn method.
On the other hand, for the LER arc section, the SR power density is approximately 2.6 kW/m
(2.5 W/mm2 ) at a beam current of 3.6 A for a beam chamber with a half width of 110 mm. In
this case, an aluminum-alloy beam chamber can be used. Manufacturing and welding are easierthan for copper. Aluminum-alloy will be also used for special and complex chambers in straightsections. Such beam chambers with antechambers can be formed by an extrusion method.

2.6.3

Electron cloud issues in the LER

Here the countermeasures against the electron cloud issue in the LER are discussed. The single
bunch instability due to the electron cloud is a serious problem for SuperKEKB, and morethorough countermeasures than ever before are required [19]. From simulation, the average
electron density should be less than approximately 1 × 1011 electrons/m3 . The antechamber
scheme is effective in reducing the photoelectrons in a beam duct, which are seeds of the electron
cloud.
In the high bunch-current regime, however, the secondary electrons due to electron impact playa major role in forming the electron cloud. Copper is said to have a relatively low secondary
electron yield (SEY), but realizing the target electron density will be hard with the use of only
copper beam chambers. A solenoid field is very effective at preventing multipactoring, and has
been used successfully at KEKB [20]. The electron density around the beam is decreased byseveral orders of magnitude when the solenoid field is applied to a copper beam chamber. The
solenoid, however, is usable only in a drift region (field free region).
Another way to suppress the secondary electron emission is to coat the inner surface with somematerials having a low SEY, such as TiN, NEG or graphite. These coatings are usable for bothdrift regions and inside magnets. A TiN coating has been used in the LER beam chamber of
PEP-II [21] and the coating technique is well developed. The measured electron densities forbeam chambers with TiN coatings decreased to one half or one third of that for a bare copper
beam chamber [22]. It should be noted that a bare aluminum alloy has a much higher SEY thancopper and any coatings are indispensable if aluminum-alloy beam chambers are used.
Recently, it was found that a grooved surface and a clearing electrode (Fig. 2.15) are very useful
to suppress the electron cloud, especially in the dipole field of a bending magnet or a wiggler
magnet [23, 24]. The former reduces SEY geometrically, and the latter absorbs the electrons
around the beam orbit with a static electric field. They can reduce the electron density by one
or two orders of magnitude compared to that for a bare copper beam chamber. The current
plan will use clearing electrodes in wiggler magnets, where the beam chamber is straight. The
application of the grooved surface in a bending magnet is under consideration. Impedance issues
have to be considered carefully for both cases.

2.6.4

Pumps

The target vacuum pressure in the ring is on the order of 10−7 Pa on average, which guarantees
a beam lifetime determined by the vacuum pressure longer than the luminosity lifetime, andsufficiently long to be compatible with the injection scheme. From the viewpoint of ion instabilities in the electron ring (HER), an acceptable pressure is also on the order of 10−7 Pa on

43

CHAPTER 2. SUPERKEKBFigure 2.15: Clearing electrode in a beam chamber.
average, but is less than 10−6 Pa locally. A pressure of less than 1×10−7 Pa will be requiredaround the IR, especially just upstream of Belle II.
To achieve the target pressure, a linear pumping speed of approximately 0.1 m3 s−1 m−1 is required, assuming a photo-desorption coefficient of 1×10−6 molecules photon−1 . To evacuate
the long, narrow beam chambers effectively, a distributed pumping scheme will be adopted [25].
The main pump is a strip-type non-evaporable getter (NEG), ST707 (SAES GETTERS Co.
Ltd.). To evacuate non-active gases and to assist evacuation at relatively high-pressure regimes,
sputter ion pumps are provided as auxiliary pumps. The rough-pumping system consists of aturbo-molecular pump and a dry pump. The system is completely oil-free. Ports for sputter ion
pumps or rough pumps are located at the bottom of the pump channel.

2.6.5

Other components

Bellows chambers are installed between adjacent beam chambers to ease beam chamber installation and to absorb any thermal deformation. Since the beam current is large, heating of bellows
due to HOM, especially TE-mode-like HOM, will become a serious problem. The present designis equipped with a comb-type RF-shield structure that has a higher thermal strength and alower impedance than that used before [26]. The RF shield consists of thin, interlocking combteeth. This shield is applicable to various cross sections of the beam chamber. The comb-type
RF-shield will also be used for gate valves (Fig. 2.16).
An MO-type flange will be used as a connection flange [27]. The flange has a square edge
to maintain a smooth current flow across a copper gasket as well as vacuum tightness for an
ultra-high vacuum. Adaptation to a complicated cross section is possible. A copper-alloy andan aluminum-alloy flange are now available, which make the manufacturing process of beamchambers simple and also relaxes the heating problems of flanges due to wall losses.
To protect Belle II from damage due to spent particles and to reduce the background noise, amovable mask (collimator) system will be installed in each ring. The first issue for the movablemask is the HOM generated at the mask head. A chamber-type movable mask that has beenused in KEKB, which has a trapped-mode-free structure, will be employed for SuperKEKB
44

CHAPTER 2. SUPERKEKBFigure 2.16: Comb-type RF shield for gate valves.
in the commissioning stage, at least [28]. HOM dampers will have to be included with the
movable mask system. Another problem is the development of grooves on the mask head. An
effective way to avoid the production of grooves is to use a light material as the mask head, suchas graphite, with a thickness of about one radiation length. A new, improved movable mask
system will be required to handle high current beams in the future.
The design of the control and monitoring system follows that of the present system. Vacuum
gauges are cold cathode gauges (CCG) and are positioned about every 10 m. The compressed
air system will also be reused to actuate the gate valves. The flow rates of the cooling waterand the temperatures of the vacuum components must be monitored. Highly reliable alarm andinterlock systems are required.
The cooling power should be improved since the total SR power increases by a factor of two.
The power loss in both rings is estimated to be approximately 14 MW in total. On the other
hand, the present cooling capacity is about 8 MW in total for the vacuum system. The lengthof one cooling loop in the tunnel or the layout of the loop should also be optimized.

2.7

Injector Linac

2.7.1

Requirements and upgrade strategy

The present KEKB injector linac supplies 8.0 GeV electrons to the HER and 3.5 GeV positrons
to the LER. The electron beam for the HER (1 nC, 2 bunches) is generated in the pre-injector
at the beginning of the linac. Electrons for positron production (10 nC, 2 bunches) are also
generated in the same pre-injector and accelerated up to 4 GeV to irradiate a tungsten target
located in the middle of the linac to generate positrons. The positrons (1 nC, 2 bunches) are
extracted by a capture section and accelerated up to 3.5 GeV in the latter half of the linac. The
HER and LER injections are switched pulse-by-pulse to keep the stored currents constant.
After the transition of the SuperKEKB design strategy from the high current option to thenano-beam (low-emittance) option, the upgrade scheme of the injector linac has been revised tomeet the new requirements of the storage rings. Table 2.9 shows a comparison of KEKB and
45

CHAPTER 2. SUPERKEKBSuperKEKB machine parameters concerning the injector upgrade. The most significant changes
are the beam emittance and the intensity. More than one order of magnitude lower emittances
are required for both electrons and positrons. Due to the doubled stored currents and the beam
lifetimes as short as 10 minutes in SuperKEKB, injection beam intensities should be increased.

Beam energy (GeV)Stored current (mA)
Beam lifetime (min)Bunch charge (nC)
Number of bunches
Beam emittance γǫ(1σ) (µm)
Energy spread σE /E (%)
Bunch length σz (mm)

KEKB
e+
e−
3.5
8.0
1600
1200
150
200
10.0/1.0 1.0
2
2
2100
300
0.125
0.05
2.6
1.3

SuperKEKB
e+
e−
4.0
7.0
3600
2620
10
10
10.0/4.0 5.0
2
2
10
20
0.07
0.08
0.5
1.3

Table 2.9: KEKB/SuperKEKB machine parameters

Figure 2.17: SuperKEKB injector
To achieve this smaller emittance and higher intensity of the electrons, we adopt a photocathodeRF gun in a new pre-injector. A low-emittance and short-pulse beam will be generated byirradiating a small-size cold cathode with short-pulse laser photons. This beam is accelerated to
7.0 GeV in the linac and injected into the HER. For primary electrons that are used to generate
positrons, the present pre-injector will be used. This is because the required electron intensity
for positron production is much higher than the injection beam and it is difficult to achievewith a photocathode RF gun. Thus, these two pre-injectors will be switched pulse-by-pulse forelectron and for positron injections.
46

CHAPTER 2. SUPERKEKB

To increase positron beam intensity, we adopt a new matching device and a L-band capture
section to increase positron acceptance. By replacing the existing matching device (air-core
pulse coil) with a flux concentrator or a superconducting solenoid, a wider positron energy
acceptance will be achieved. Replacing the present S-band (2856 MHz) capture section with an
L-band (1298 MHz) will give us a larger beam aperture in the accelerating structure and longer
RF wave length for larger phase space acceptance. To obtain low emittance positrons, we willbuild a damping ring to reduce the emittance with radiation damping. The damping ring will
be constructed in a location where 1 GeV positrons can be injected from the linac. Positrons are
re-injected from the damping ring to the linac two-beam pulse period after the injection to makethe emittance sufficiently low. Details of the damping ring are described elsewhere (Section 2.8).

2.7.2

Positron Source Upgrade

Since the positrons for the LER are produced as secondary particles from the converter target, the emittance is much larger than the electron beam and the intensity is limited by theacceptance of the capture section. We will enlarge the acceptance to increase the intensity for
SuperKEKB. The emittance of the positrons from the capture section will be larger than that
required for injection in the nano-beam scheme. To compensate for this, a damping ring (DR) is
introduced. The beam energy at the DR is designed to be 1.0 GeV. The DR will be located on
one side of the linac, between Sectors 2 and 3, as shown in Fig. 2.17, where there is suitable space
to construct beam transport lines from and to the DR. To increase the energy margin for DR
injection, considering the lower acceleration field in the L-band modules, the positron station
including the target and the capture section will be moved approximately 50 meters upstream
to have a longer positron acceleration region. Low emittance positrons after the damping in
the DR are re-injected into the linac and accelerated up to 4.0 GeV in Sectors 3, 4 and 5. To
increase the energy margin for LER injection, a second C-band accelerator module will be addedin the Sector 4 in 2010.
In the present capture section, a short air-core pulse solenoid (2 T) is used as a matching device
to focus positrons and an S-band accelerating field captures them in a long DC solenoid (0.4 T).
With a short and sharp field distribution of the pulse solenoid, this matching device has a monochromatic energy acceptance. We will replace the present solenoid with an adiabatic matching
device that has a wider energy acceptance, with a higher peak field and a more gradual field
distribution. One of the candidates for this device is a flux-concentrator type of pulse solenoid,
which can yield a very high field by an intense induced current inside a copper conductor. We
are developing a prototype in collaboration with BINP in Russia, which has already achieved
10 T as a peak field strength. The solenoid has a certain amount of non-axial field component
that kicks positrons and creates beam loss. The observed field distribution of the prototype
is rather sharp and the energy acceptance was not sufficiently wide. Positron yield includingthese effects will be evaluated by a simulation study and by a beam study with the prototype,which will be installed in the KEKB linac in 2010. The other candidate is a super-conducting
solenoid. Though it has the merit that an ideal adiabatic field distribution can be created by anappropriate coil design, quenching of the magnet by heating with particles from the target canbe a problem in operation. Preliminary irradiation test of a sample super-conducting solenoidwith KEKB linac beams has shown that the quenching is not sensitive to the very high heatdensity of the pulsed beams. Thus we can design a super-conducting solenoid for SuperKEKB
with a quench limit determined by the average heating from the beams and by the field strength
in the coil wire. A design study of a prototype solenoid is underway and beam irradiation studies
will be performed with the prototype. Final decision on the matching device will be done after

47

CHAPTER 2. SUPERKEKB

the evaluation of the studies and the tests of the flux-concentrator and the super-conducting
solenoid.
To enlarge the positron acceptance, we will introduce L-band accelerating structures in thecapture section. By replacing the present S-band accelerating structures with the L-band structures, we will enlarge the aperture diameter from 20 mm to 30 mm, which corresponds to 2
times larger transverse phase-space acceptance. Though the acceleration field gradient is lower
in the L-band (10 MV/m) compared to the S-band (14 MV/m), a longer capture section cancompensate for this. Since the wave length of the L-band RF is twice as long as that of the
S-band, the longitudinal acceptance will increase as well. The positron intensity is expected toincrease by more than a factor of four by introducing the adiabatic matching device and the
L-band capture section. The L-band system is also introduced in the three subsequent accelerator modules for the quadrupole focusing system to have comparable transverse acceptance tothe capture section. Development work on components for the L-band modules is underway. A
klystron of 40 MW output power and the first prototype L-band accelerating structure are underfabrication and high-power tests will be performed in a test stand. Accelerating structures in asolenoidal field and in intense radiation from a converter target are sensitive to RF breakdowns.
After studies to investigate the breakdown properties of the structures, the final design of the
L-band accelerating structures will be decided.

2.7.3

Electron Source Upgrade

In the present KEKB linac pre-injector, a triode-type thermionic electron gun with a dispenser
cathode of 200 mm2 size generates an electron beam. Electrons are extracted from the cathodeby a electric field of 200 kV accelerating voltage. A minimum pulse length (typically 1 ns) of thebeam from the cathode is limited by a grid pulser signal and the beam intensity is controlled
by a grid pulse and a DC bias voltage. The electron beam pulse is compressed by RF buncher
cavities (two sub-harmonic bunchers of 114 MHz, 571 MHz, a pre-buncher and a buncher of2856 MHz) to yield a single bunched beam of 10 ps length (FWHM) with no satellite bunches,
to fulfill the longitudinal acceptance requirement of the HER and LER. To double the injection
current to the rings, a second beam pulse is generated 96 ns after the first pulse by a grid pulse
signal from a second pulser. This second beam pulse is also compressed by the RF bunchers
into a single bunch. These two bunches, at a 96 ns interval, are accelerated in the same RF
pulse. Bunch intensities are switched for each operation mode, with 1 nC for the HER injection,
10 nC for positron generation and 0.1 nC for synchrotron facilities (PF and AR). The typicalnormalized emittance of electrons from the pre-injector is 100 µm or less.
For HER injection in SuperKEKB, the electron emittance is required to be less than 20 µm. In
addition, the bunch intensity is required to be 5 nC, which is five times the present value. To
fulfill the emittance and the intensity requirements, we will develop a new pre-injector with aphotocathode RF gun. For generating a low-emittance beam, the cathode size should be small
as 7 mm2 to make a low intrinsic emittance, and the acceleration field gradient should be high(more than 100 MV/m) to suppress space charge effects in the low velocity region. An RF field
in a cavity is used to achieve this high gradient instead of a static field. To make a compact new
pre-injector that can generate single bunch beams without RF buncher cavities, a photoemission
cathode with a short laser pulse of 10 ps order is used. Eliminating bunchers is advantageous
in avoiding emittance growth as well.
To achieve the specified beam intensity with this small cathode size, a sufficiently high intensity
laser should be used considering a quantum efficiency of the cathode material. Taking a photocathode in KEK-ATF as an example [29], a Cs2 Te cathode of 1% quantum efficiency and a48

CHAPTER 2. SUPERKEKB

266 nm laser of 3 µJ/bunch intensity are used to generate a 1.6 nC/bunch beam. Considering
the short lifetime of the Cs2 Te cathode, a more tolerant material like copper is preferred forlong-term operation in SuperKEKB. Yet, since the quantum efficiency of copper is very low(3 × 10−5 ), the laser intensity should be very high. For the SLAC-LSLC injector [30], a 255 nm
laser of 500 µJ/bunch is used to irradiate a copper cathode to generate a beam with 1 nC/bunch
intensity. To achieve 5 nC beam in this scheme, 2500 µJ/bunch laser is required and it is beyond the power level of lasers available now. Our idea to overcome this difficulty is improve thequantum efficiency by two orders of magnitude by adopting 205 nm wavelength instead of 260
nm, as suggested by the test data of wavelength dependence measured at CERN [31]. A higher
field gradient in the RF cavity helps to enhance the quantum efficiency. In this wavelength withan assumed 170 MV/m field gradient, the required laser power is expected to be less than 100µJ/bunch.
According to an estimation of contributions to the beam emittance by thermal effects, rf field
effects and space charge effects, it is suggested that the space charge effect is dominant for typicaldesigns of RF gun cavities. This effect can be suppressed with a higher field gradient. Thus
we adopt a SPring8-type half-cell cavity [32] which can yield the highest field gradient among
candidate cavity designs. This type of cavity, operated at an S-band frequency, is expected toachieve a 170 MV/m field gradient.
Even though the new pre-injector can yield a low-emittance beam, wake field effects during
acceleration can degrade the emittance. Care should be taken with the longitudinal charge
distribution in the beam bunch and of the design of the beam focusing system to suppress theemittance growth.
Detailed design study and prototype development of the photocathode RF gun will be performedin the coming few years.

2.8

Damping Ring

The injection aperture of the LER is 0.5 µm. Assuming a septum width of 4 mm and a beta
function at the injection point of 120 m, the emittance of the injected beam must be less than
4 nm. The emittance of the positron beam, which is generated with a conventional target, is aslarge as 2.1 µm at an energy of 1 GeV. Thus a damping ring is necessary to reduce the emittanceby a factor of 130.
The intensity of the injected beam, on the other hand, has to be larger than 4 nC per Linac-pulse
in order to maintain the current of the LER, whose lifetime is expected to be as short as 600
sec. For a high-intensity positron beam, the Damping Ring (DR) therefore serves as a collector
ring that accepts the beam with a large energy spread and a large transverse emittance.
The DR is placed at the end of Sector 2 of the Linac, at an energy of 1 GeV. Parameters of
the incoming beam to the DR are shown in Table 2.10. One of the nice features is an energy
compression system (ECS) incorporated in the injection line to the DR. The ECS reduces theenergy spread of the beam from ±5% to ±1.5 %, which is the acceptance of the DR.
Parameters of the DR are shown in Table 2.11. We adopt a FODO cell with a reverse bend as
the arc cell. This structure allows us to get low momentum compaction while preserving theshort damping time. The injected bunches stay for two Linac pulses (40 ms) before extraction.
We assume 8 nC per bunch as the design intensity, which gives us a great operability in the caseof shorter life time in the LER. The bunch length of the extracted beam is compressed from 5
mm to 0.5 mm by the BCS system incorporated in the RTL line.
The dynamic aperture is vitally important to accommodate the large emittance and large energy
spread of the beam. Figure 2.18 shows the results of a tracking simulation.
49

CHAPTER 2. SUPERKEKBTable 2.10: Parameters of the injected beam.
before ECS after ECS
Energy(GeV)
1.050
Repetition frequency(Hz)
Emittance
(µm)
2.1
±5
± 1.5
Energy spread*
(%)
± 8.7
± 28.2
Bunch length*(mm)
Number of bunches per pulse
2
98
Bunch spacing(ns)
Bunch charge(nC)
8* Full width

Table 2.11: Parameters of the Damping Ring
Energy1.0
135Circumference
Number of bunch trains2
2
Number of bunches/train
Maximum stored curent*
70.8
0.0714
Energy loss per turn
12.66
Horizontal damping time
Injected-beam emittance
2.1
0
35.4
70.8
Stored current
Equilibrium emittance
11.7
13.0
14.0
10
Coupling
Emittance at ejection(hor.)
15.3
16.6
17.6
4.8
5.0
5.1
Emittance at ejection(ver.)
Energy band-width of injected beam
±1.5
0.0526 0.0535 0.0542
Energy spread
5.2
5.3
5.4
Bunch length
Momentum compaction factor
0.00191
0.257
Cavity voltage for 1.5 % bucket-heightRF frequency
509
32
Inner diameter of chamber
44
Bore diameter of magnets* 8 nC.bunch

GeV
m

mA
MV
ms
µm
mA
nm
%
nm
nm
%
%
mm
MV
MHz
mm
mm

In Fig. 2.18(a), relative-strength errors of quadrupoles (1 × 10−3 ) and sextupoles (2 × 10−3 ),transverse misalignments of quadrupoles/sextupoles (0.15 mm), rotation error (0.3 mrad), andBPM offset of 0.15 mm are assumed. In Fig. 2.18(b), the systematic high-order allowed multipole
error of quadrupoles and sextupoles are added, where the strength of the multipole field errorof 0.06% and 0.23% at the radius of 22 mm were assumed for the first allowed multipole andhigher multipoles, respectively. The dynamic aperture is sensitive to the systematic high-ordermultipoles. They can be corrected by end-shimming after field measurement.
The electron cloud density near the beam is estimated to be 0.7 × 1014 m−2 , which is close to50

CHAPTER 2. SUPERKEKBa)b)

Figure 2.18: Tracking results of dynamic aperture. The horizontal axis is the initial momentum
deviation and the vertical axis is the maximum action of the survived particle after 4000 turns.
The green line corresponds to the injected beam. The thick red line is the result for the case ofno machine error while the thin red lines are for the case of machine errors. (a) Machine errors
include relative strength error of quads (1×10−3 ) and sexts (2×10−3 ), transverse misalignmentsof quads/sexts (0.15 mm), rotation error (0.3 mrad), and BPM offset of 0.15 mm. (b) Systematic
higher-order allowed multipole error of quads and sexts are added to the errors of (a).
the threshold of electron-cloud instability of 1.57 × 1014 m−2 , assuming a secondary electron
emission coefficient δ of 1.2. Methods for mitigation of the effect is under investigation.

2.9

年 月

Control

日木曜日

The design of the control system for SuperKEKB
is basicallyan extension of the present KEKB
年 月日木曜日
control system. Its software is based on EPICS (Experimental Physics and Industrial Control
System). EPICS is an open source software toolkit used to construct distributed control systems
mainly for accelerators and other large physics experiments. In the EPICS system, the control
system hardware consists of the OPI (Operator Interface) and IOC (Input Output Controller).
The OPI is a workstation which can run various EPICS tools. The IOC is a frontend computer
which has interfaces to the various components of the accelerator. Many IOCs and OPIs areconnected each other through a LAN (local area network).
In the present control system, VME board computers with VxWorks realtime operating systems
are mainly used as the IOCs. There are roughly 90 VME IOCs for the LER, HER and beamtransport lines. Because these VME computers were installed more than 10 years ago and havebecome outdated and are expected to be hard to maintain for the next decade, we have thefollowing plans.
1. Upgrade the VME CPU board
2. Introduce new type IOCs other than VME-based one
Most of the current VME CPU board are Force PowerCore-6750. We are planning to replacethem with Emerson MVME5500 (or MVME4100). The replacements have already started partially. We are continuing the replacements. At the same time it is necessary to upgrade VxWorks

51

CHAPTER 2. SUPERKEKB

and EPICS for these IOCs. VxWorks will be upgraded from 5.3 to 5.5 (or 6.7 or higher, which
we are evaluating). EPICS will be upgraded from R3.13.1 to R3.14.
It is also required to replace the outdated field buses, especially the CAMAC system, which has
been used for more than 20 years and has become hard to maintain. ARCNET has been usedin the magnet power supply control system. The PSICM (Power Supply Interface Controller
Module) was designed with the ARCNET interface in the present system. The number ofmagnet power supplies is expected to increase in SuperKEKB. Thus, we have started developing
ePSICM (Ethernet-based Power Supply Interface Controller Module) for the additional magnet
power supplies. The ePSICM is the newer version of the PSICM using an Ethernet interface
instead of ARCNET.
We are developing various types of EPICS IOC-embedded equipment. In our new configuration,
EPICS software is installed more on the frontend side. It makes the controlled equipment itself
being IOC. In our design plan the following new type of IOCs are being developed.
1. F3RP61, a CPU module running Linux for YOKOGAWA FA-M3 PLC;
2. EPICS embedded oscilloscope, which is a Tektronix DPO7104 with Windows embedded;
3. The prototype of the ePSICM with EPICS embedded;
4. Embedded EPICS on micro-TCA cards for new LLRF system.
The F3RP61 is the key product of the new control system. Generally speaking, most of thecontrol system does not require high speed nor complicated data processing, but it needs tohandle various kinds of equipment. For such purpose the F3RP61 is suitable. We have installed
EPICS on it to be a light weight IOC. Compared to the VME IOC it is cheaper, smaller andless power consuming. It has no fans and is sufficiently reliable. It reduces not only hardware
cost but also the cost of software development. User space programming on Linux and simple
synchronous I/O access make software development much easier. Although graceful handlingof high-density signal cable is required, we are considering the F3RP61 as the first candidate of
the VME/CAMAC alternatives.
Fast control is also expected to be required in some cases. We are preparing for such requirementswith a new event-based control system. The OPIs and network are going to be upgraded. We are
introducing Linux Blade Servers as OPI. The replacement of the network core switch and edge
switches are planned and partially in progress. In the new network system we are introducing
redundant configuration, VLAN, and potentially 10Gbps connections for future purposes.

2.10

Schedule

A tentative schedule for the SuperKEKB construction is shown in Fig. 2.19. The Injector
upgrade and Damping Ring construction are shown in the upper part of the figure, and theMain Ring construction is shown in the lower part. The construction will start after the final
run of the present KEKB operation, which runs through June, 2010. The commissioning ofSuperKEKB will begin in April 2014.

52

CHAPTER 2. SUPERKEKBFigure 2.19: Schedules for injector upgrade and damping ring (upper) and Main Ring (lower).

53

References[1] S. Kurokawa and E. Kikutani, Nucl. Instrum. Meth. A 499, 1 (2003), DOI: 10.1016/S01689002(02)01771-0.
[2] P. Raimondi,
talk given at the 2nd SuperB workshop,
Frascati,
http://www.lnf.infn.it/conference/superb06/talks/raimondi1.ppt, 2006.
[3] Y. Ohnishi et al., Phys. Rev. ST Accel. Beams 12, 091002 (2009),
RevSTAB.12.091002.

10.1103/Phys-[4] D. Zhou et al., Phys. Rev. ST Accel. Beams 13, 021001 (2010),
RevSTAB.13.021001.

10.1103/Phys-[5] K. Oide, Nucl. Instrum. Meth. A 276, 427 (1989), DOI: 10.1016/0168-9002(89)90567-6.
[6] K. Oide and H. Koiso, Phys. Rev. E 47, 2010 (1993), 10.1103/PhysRevE.47.2010.
[7] KEK-REPORT-95-7.
[8] K. Akai et al., Nucl. Instrum. Meth. A 499, 45 (2003), DOI: 10.1016/S0168-9002(02)017734.
[9] T. Ieiri, Y. Funakoshi, T. Kawamoto, M. Masuzawa, and M. Tobiyama, Phys. Rev. ST
Accel. Beams 8, 124401 (2005), 10.1103/PhysRevSTAB.8.124401.
[10] Y. Yamazaki and T. Kageyama, Particle Accelerators 44, 107 (1994).
[11] T. Kageyama et al., Talk given at 17th IEEE Particle Accelerator Conference (PAC 97):
Accelerator Science, Technology and Applications, Vancouver, Canada, 12-16 May 1997.
[12] T. Kageyama, Y. Morozumi, Y. Yamazaki, and K. Yoshino, Talk given at the Linear
Accelerator Conf., Albuquerque, NM, Sep 10-14, 1990.
[13] Y. Takeuchi et al., Talk given at 17th IEEE Particle Accelerator Conference (PAC 97):
Accelerator Science, Technology and Applications, Vancouver, Canada, 12-16 May 1997.
[14] T. Naito et al., Talk given at Asian Particle Accelerator Conference, Tsukuba, Japan, 1998.
[15] T. Naito et al., Talk given at 17th IEEE Particle Accelerator Conference (PAC 97): Accelerator Science, Technology and Applications, Vancouver, Canada, 12-16 May 1997.
[16] H. Sakai, T. Abe, T. Kageyama, and Y. Takeuchi, Prepared for Particle Accelerator Conference (PAC 05), Knoxville, Tennessee, 16-20 May 2005.

54

REFERENCES[17] T. Abe, T. Kageyama, H. Sakai, and Y. Takeuchi, Talk at the European Particle Accelerator
Conference (EPAC 06), Edinburgh, Scotland, 26-30 Jun 2006.
[18] Y. Suetsugu, K. Shibata, H. Hisamatsu, M. Shirai, and K. Kanazawa, Vacuum 84,
694 (2009), Proceedings of the 4th Vacuum and Surface Sciences Conference of Asia
and Australia (VASSCAA-4) - Sessions on Vacuum Science and its Application, DOI:
10.1016/j.vacuum.2009.06.027.
[19] K. Ohmi and F. Zimmermann,
RevLett.85.3821.

Phys. Rev. Lett. 85, 3821 (2000),

10.1103/Phys-[20] H. Koiso et al., Present Status of the KEKB B-Factory, in Particle accelerator. Proceedings,
8th European Conference, EPAC 2002, Paris, France, June 3-7, 2002, edited by J.-L.
Laclare, (ed. ), pp. 341–343, 2002.
[21] K. Kennedy et al., TiN coating of the PEP-II low-energy ring aluminum arc vacuum
chambers, in Proceedings of the 17th IEEE Particle Accelerator Conference (PAC 97):
Accelerator Science, Technology and Applications, Vancouver, Canada, 12-16 May 1997,
pp. 3568–3570.
[22] Y. Suetsugu, K. Kanazawa, K. Shibata, and H. Hisamatsu, Nucl. Instrum. Meth. A 578,
470 (2007), DOI: 10.1016/j.nima.2007.06.015.
[23] Y. Suetsugu, H. Fukuma, M. Pivi, and L. Wang, Nucl. Instrum. Meth. A 604, 449 (2009),
DOI: 10.1016/j.nima.2009.03.011.
[24] Y. Suetsugu et al.,Nucl. Instrum. Meth.
10.1016/j.nima.2008.08.154.

A 598,

372(2009),

DOI:[25] Y. Suetsugu, K. Shibata, and M. Shirai, Nucl. Instrum. Meth. A 597, 153 (2008), DOI:
10.1016/j.nima.2008.09.023.
[26] Y. Suetsugu et al.,10.1063/1.2723747.

REVIEW OF SCIENTIFIC INSTRUMENTS 78 (2007),[27] Y. Suetsugu et al., JOURNAL OF VACUUM SCIENCE & TECHNOLOGY A 27, 1303
(2009), 10.1116/1.3237149.
[28] Y. Suetsugu, T. Kageyama, K. Shibata, and T. Sanami, Nucl. Instrum. Meth. A 513, 465(2003), DOI: 10.1016/j.nima.2003.06.003.
[29] N. Terunuma et al., SLAC AARD Technical Note ARDB367, , 2004.
[30] D. H. Dowell et al., SLAC-PUB-12951, , 2007.
[31] E. Chevallay, J. Durand, S. Hutchins, G. Suberlucq, and M. Wurgel, Nucl. Instrum. Meth.
A 340, 146 (1994), DOI: 10.1016/0168-9002(94)91293-9.
[32] T. Taniuchi et al., 25th Linear Accelerator Meeting in Japan, Himeji 2000.

55

Chapter 3

IR design
3.1

Interaction Region

The 7 GeV electrons stored in the high-energy ring (HER) and the 4 GeV positrons in the
low-energy ring (LER) collide at one interaction point (IP) with a non-zero crossing angle of
83 mrad. The large crossing angle helps to separate the two beams quickly and allows the final
quadrupole magnets to be closer to the IP in order to achieve small β-functions at the IP. Somepertinent parameters are listed in Table 3.1.
Table 3.1: Beam parameters of SuperKEKB.
LERHEREnergy4.0
7.0∗∗
32 / 0.27
25 / 0.41
βx / βyǫx / ǫy
3.2 / 12.8
2.4 / 8.4
Coupling
0.4
0.35
Horizontal beam size at IP
10.2
7.75
Vertical beam size at IP
0.059
0.059
Beam-beam parameter
0.09
0.0875
Bunch length
65Beam current
3.6
2.6
Betatron tune (νx /νy )45.53 / 45.57 58.53 / 52.57
Synchrotron tune
-0.023-0.012
Number of bunches
2503
Crossing angle
83
Luminosity
8 × 1035

GeVmm
nm / pm
%
µm
µm
mm
A

mrad
cm−2 s−1

A schematic layout of the beam line near ithe IP is shown in Fig. 3.1. This figure shows five superconducting quadrupole magnets (QC1LP, QC1LE, QC1RP, QC1RE and QC2RP) and three
permanent quadrupole magnets (QC2LP, QC2LE and QC2RE). The final vertical and horizontal
focusing fields will be provided by the QC1 and QC2 magnets in each ring, respectively. These
superconducting magnets overlap with the solenoids (S-L and S-R) to compensate for the 1.5 T
field created by the Belle solenoid. The field axis of the compensation solenoids is aligned to thedetector solenoid. The superconducting quadrupole and solenoid magnets on each side of the
IP are contained in a common cryostat, respectively. These magnets have a warm bore vacuum56

CHAPTER 3. IR DESIGN

Figure 3.1: Schematic layout of the magnets and beam line near the interaction point.

chamber connected to the cryostats via bellows. QC2LP, QC2LE and QC2RE, which are locatedoutside of cryostats, are designed as Halbach-type permanent magnets. The cryostats will besmall and the assembly of the vacuum chamber is simplified by using permanent magnets. The
parameters for these magnets are summarized in Table 3.1.
The inclination of the HER and LER orbits relative to the solenoid axis, which is 41.5 mrad,respectively, is chosen to minimize the vertical emittance degradation for the HER in the fringe
field of the anti-solenoid. Because it is not easy to rotate the HER orbit without degradation of
its performance, rotation of the detector is under consideration at present.
Table 3.2: Locations of the magnet center from IP, effective length, field gradients, magnet typeof final focus magnets and inner diameters of vacuum chamber are shown.

Magnet
QC2LE
QC2LP
QC1LE
QC1LP
QC1RP
QC1RE
QC2RP
QC2RE

z
(m)
-2.90
-1.98
-1.46
-0.92
0.91
1.38
1.94
2.93

Leff
(m)
0.6
0.35
0.36
0.39
0.28
0.36
0.35
0.4

Field gradient
(T/m)
23.6
31.3
72.3
58.7
80.1
72.8
31.2
32.3

Focus
Horiz e−Horiz e+Vert e−Vert e+Vert e+Vert e−Horiz e+Horiz e−Type
Permanent
Permanent
S.C.
S.C.
S.C.
S.C.
S.C.
Permanent

I.D. of vac. ch.
(mm)
70
60
30
20
20
30
60
70

The beam stay-clear for the QC1 and QC2 magnets has been determined by considering therequirements for injection. The acceptance required for beam injection is assumed as 2Jx =5 × 10−7 (m) for the horizontal direction and 2Jy = 2 × 10−8 (m) for the vertical direction.
Dynamic effects are ignored because the nominal horizontal betatron tune is far from the halfinteger resonance. The inner diameter of the vacuum chamber is 20 mm for QC1RP and QC1LP
and 30 mm for QC1RE and QC1LE.
57

CHAPTER 3. IR DESIGN

3.1.1

IR magnets

The final focusing system for the two beams consists of five superconducting quadrupoles, three
permanent quadrupoles, two superconducting compensation solenoids, and 32 superconducting
corrector coils. In the following sections, the magnet designs and specifications are described.
QC1RP and QC1LP
QC1RP and QC1LP have the most stringent space constraints since these magnets are locatedclosest to the IP with a narrow gap of the two beams. They provide the final focusing for the
LER (e+ ) beam. The cross section of QC1RP is shown in Fig. 3.2. The magnets QC1RP and
QC1LP have the same cross section. The design parameters of these quadrupoles are listed inTable 3.3. The magnet inner radii are 22 mm, and the magnetic lengths of QC1RP and QC1LP
are 0.2967 m and 0.3695 m, respectively. QC1RP and QC1LP generate integral field gradients of
22.43 and 22.91 T at the operating currents of 1510.7 A and 1232.3 A, respectively. Combining
their magnetic fields together with the solenoid and the compensation solenoids, the maximum
fields in the magnets are calculated to be 2.70 T and 3.98 T for QC1RP and QC1LP. These
operating points correspond to 66% and 80% of the critical conditions for superconductivity,
respectively.

Figure 3.2: Cross section of QC1RP and the cancel corrector coils of the QC1RP leakage field.
Within the magnet bore, the beam pipe is located and should be kept at room temperature in
the vacuum of the cryostat. Since the distance between the beam pipe and the helium vessel
at 4.5 K is only 3.5 mm, the cryostats must be fabricated accurately and have good thermal
performance.
Inside the magnet bores, four types of superconducting corrector coils are designed. The skew
and normal dipoles (a1 and b1 in Fig. 3.2) align the magnetic centers of QC1R/LP. The skew
quadrupole is for the alignment of the mid-plane of the quadrupole. The octupole (b4 ) is required
to improve the dynamic aperture.
Since QC1RP and QC1LP are iron-free magnets, their magnetic fluxes pass also through theneighboring HER beam line. These leakage fields have a harmful influence on the beam dynamics
of the electron beam, and consist mainly of dipole, quadrupole and sextupole components (b1 ,58

CHAPTER 3. IR DESIGN

Table 3.3: Design parameters of QC1RP and QC1LP
QC1RP QC1LP
Coil inner radius, mm
22.00
Coil outer radius, mm
27.55
Spec. of integral field, T
22.43
22.91
Field gradient, T/m
75.61
62.00
Effective magnetic length, m
0.29670.3695Magnet current, A
1510.71232.3Magnetic field by Belle and comp. sol., T
1.2
3.0
Max. field in the coil without solenoid field, T
2.24
1.84
Max. field in the coil with solenoid field, T
2.70
3.98
Operating point with respect to Bc at 4.4 K
66%
80%

b2 and b3 ). To cancel out these fields, the correction coils b1 , b2 and b3 for the electron beamline have been designed, as shown in Fig. 3.2.
QC1RE, QC1LE and QC2RP
The design concepts for QC1RE and QC1LE shown in Fig. 3.3 are the same as for QC1RP and
QC1LP. They are designed to operate under nearly the same solenoid fields of 1.2 T and 1.0 T,
respectively, and have identical magnet configurations. Their parameters are listed in Table 3.4.
The inner radii and the effective magnetic lengths are 28.25 mm and 0.3596 m, respectively. To
generate the field gradients of 72.91 T/m and 72.38 T/m in QC1RE and QC1LE, the operating
currents are designed to be 1814.6 A and 1801.4 A. These operating points correspond to 76% and
75% of the critical conditions, respectively. The field correction scheme for QC1RE/QC1LE is
the same as for QC1R/LP; it consists of 7 superconducting multi-pole coils. The design concept
for QC2RP is same as QC1 magnets, and thus it is assembled in a common cryostat with QC1RP
and QC1RE.

Figure 3.3: Cross section of QC1RE and the cancel corrector coils of the QC1RE leakage field.
QC2RE, QC2LP and QC2LE
59

CHAPTER 3. IR DESIGN

Table 3.4: Design parameters of QC1RE and QC1LE.
QC1RE QC1LE
Coil inner radius, mm
28.25
Coil outer radius, mm
33.80
Spec. of integral field, T
26.22
26.03
Field gradient, T/m
72.91
72.38
Effective magnetic length, m
0.3596
0.3596
Magnet current, A
1814.61801.4Magnetic field by Belle and comp. sol., T
1.2
1.0
Max. field in the coil without solenoid field, T
2.89
2.87
Max. field in the coil with solenoid field, T
3.28
3.15
Operating point with respect to Bc at 4.4 K
76%
75%

QC2RE, QC2LP and QC2LE are designed as permanent magnets, and are located behind thecryostats. Their parameters are listed in Table 3.5. The field strength required for the permanentmaterial is at most 0.9 T, and Samarium-Cobalt was selected due to its reduced sensitivity toradiation. The remnant field of Samarium-Cobalt ranges from 1.04 to 1.12 T. Study of thepermanent magnet design is on-going.

QC2RE
QC2LP
QC2LE

Table 3.5: Design parameters of QC2RE, QC2LP and QC2LE
IntegralMagnetRequired
Beam pipe
Field atfield gradient length field gradient outer radius coil inner
(T)
(m)
(T/m)
(m)
radius (T)
12.91
0.6
21.52
0.04
0.86
10.96
0.45
24.36
0.035
0.85
14.13
1.0
14.13
0.04
0.57

Compensation solenoids
From recent studies of beam dynamics, it is found that the fringe fields of the compensation
solenoids, S-R and S-L, increase the vertical beam emittance. To reduce this effect, the compensation solenoids are designed to be segmented into small coil pieces. The solenoids housesuperconducting quadrupoles and correctors in their magnet bore, and their axes are coincident
with the solenoid axis, as shown in Fig. 3.4. The coil pieces have gradually decreasing numberof turns along the axis from the IP to have a slow gradient of the solenoid fringe field along thesolenoid axis, shown in Fig. 3.5. According to these field profiles, the compensation coils are
subject to repulsive electro-magnetic forces of 31.2 kN and 26.2 kN against the solenoid field.
These forces are at the same level as that of the KEKB S-L magnet, and they will be taken careof in the cryostat and the support structure designs. The peak fields with the solenoid, ESR
and ESL, are -2 T and -3 T, respectively. These peak fields overlap with the fields of QC1R/LP,
and the operating points of S-R/S-L are calculated with these field profiles.

3.1.2

Vacuum chamber and IR assembly

The vacuum system for the region within 4m of the IP has to fulfill some prescribed conditions.
The inner diameter of the beam duct in the region of the QC1 magnet is 2 cm. The inner surface60

CHAPTER 3. IR DESIGN

Figure 3.4: Compensation solenoids in the cryostats.

Figure 3.5: Solenoid field profile along the solenoid axis.
of the beam ducts must be plated with 50 µm of gold. The beam ducts next to the IP chamber
are inside a cryostat and have a small (insulation-vacuum) gap to the liquid helium vessel.
The essential components to be incorporated in the beam ducts are:1. Beam position monitors to control the beam orbit. These must have a clearly defined
position reference to provide reliable information;
2. Bellows units that tolerate an independent motion between the various units of the vacuum
chamber and absorb engineering errors in the fabrication and also deformations duringassembly and operation;
3. Vacuum pumps to realize the local pressure without affecting the overall average pressureof the ring;61

CHAPTER 3. IR DESIGN

4. A structure to provide cooling of synchrotron radiation and heating due to the wall currents
etc. so that the temperatures of the ducts are acceptable for the duct itself as well as
outside components.
Figure 3.6 shows a rough sketch of the vacuum system for the right hand side. The center ofthe ring is towards the bottom of the page. The dimension of the cryostat is determined bycryogenic considerations. At the end of the IP chamber, the ducts for the positron beam andthe electron beam are completely separated. The inner diameter of the beam duct is designed
so as not to trap the electromagnetic field created by the circulating beams, especially at the
Y-shaped structure of the IP chamber. The presently adopted diameter for the central partof the IP chamber is 2 cm. The inner diameter of the beam duct increases from 2 cm after
the QC1RP magnet region to 3 cm in the QC1RE region, and to 6 cm in the QC2LP region.
The inner surface of the duct will have small masks to prevent scattered photons from reaching
the IP. The material of the beam duct in the cryostat is OFC clad with stainless steel outside.
Details of the IP chamber are discussed in Sec. 3.3.
#1.

#FMMPXT

#1.

2$3&

#FMMPXT

2$3&

*1

"



2$31

#

2$31
$





#FMMPXT

1VNQ

&MFDUSPO

1PTJUSPON

Figure 3.6: Sketch of the vacuum system for the right hand part of the IR (top view).
Possible locations of the beam position monitor (BPM) are outside the ends of each cryostat. In
the front position, the BPM will be placed on the IP chamber. A trial model pick-up electrodefor the small diameter duct is shown in Fig. 3.7. In the rear position, the BPM will be placedon the beam ducts just outside of the cryostat. Bellows for the beam ducts are inserted between
the IP chamber and the cryostat ducts, and between the cryostat ducts and the outer beamducts. Bellows are also used to connect the cryostat ducts to the body of the cryostat. There isno space for vacuum pumps until the end of the cryostat. The pumping speed of the pump will
be typically 0.05 m3 s−1 , which is limited by geometrical constraints. The distance of the pumps
from the IP and their pumping speed are not so different from the present KEKB situation.
However, the very small conductance of new beam pipes produces a large pressure difference
between the IP and the pump. The heat load due to synchrotron radiation from the last bend
and the ohmic loss of the wall current is estimated along the beam duct for the incoming positronin Table 3.6. The sections A, B, and C given in the table are shown in Fig. 3.6. There is anadditional heat load due to the electromagnetic wave produced by the non-uniform structure of
the duct. The amount of this heat is 100 W and distributed along the ducts. For the section
A, the heat load is about 0.5 kW. If we allow a temperature rise of 2 K for the cooling waterwith a velocity of less than 2 ms−1 , a cross section of the cooling channel of more than 30 mm262CHAPTER 3. IR DESIGN

is necessary. Figure 3.8 shows a cross section through the beam pipe with the water channels
indicated. However, the temperature rise of the duct must be checked for realistic water flow
conditions.

Figure 3.7: Test model of a pick-up electrode for the beam position monitor at the IP chamber.









8BUFS$IBOOFM0'$
4UBJOMFTT4UFFM

Figure 3.8: Cross section of the cryostat beam duct close to the IP (see text).

Table 3.6: Heat loads and ohmic losses along the beam duct.
SectionA
B
C
Length (m)1.14 0.5 1.12
ID (cm)2
3
6
SR Power (W)240 340 395
Ohmic loss (Au) (W) 250
72
81

The pressure around the IP is estimated for sections A, B, and C of the beam duct. The maingas load is due to photon-desorption by synchrotron radiation. The pressure around the IP isdetermined mainly by this part of the beam duct. An approximate estimate of the pressure can63CHAPTER 3. IR DESIGN

be made by considering a model pipe where both ends, one at IP and the other at the pump
port, are closed. The pressure at the pump is determined by the total gas load in the pipe andthe pumping speed. The pressure difference between the IP and the pump is determined by thegas load and the conductance of each segment and is independent of the pressure at the pump.
Assuming a sufficiently scrubbed value of the photo-desorption coefficient of 10−5 , the pressure
at the IP and at the pump is estimated as 6 × 10−5 and 6 × 10−6 Pa, respectively, for the design
current. Though the pressure is acceptable from the view point of the detector backgroundaccording to recent studies at KEKB, the pressure is high enough to affect the average pressurein the ring. A sketch of the left hand side vacuum system is shown in Fig. 3.9. The design
is similar to the right hand side (see Fig. 3.6). However, in this case, the space between thecryostat and the QC2LP magnet is very tight. Further iteration is necessary to design this part.
#FMMPXT

1PTJUSPO&MFDUSPO

#1.

#FMMPXT

2$-1

2$-1

#1.

*1
2$-&



1VNQ

#FMMPXT



2$-&





Figure 3.9: Sketch of the vacuum system for the left hand side of the IR (top view).
The connection between the IP chamber and the cryostat duct is a difficult issue to be solved.
One idea is to fabricate the cryostat so that it provides channels in the body for tightening rods
to access the screws on the connecting flanges (Fig. 3.10). For this purpose, the liquid helium
vessel has narrow open tubes for the rods and the body of the cryostat has holes that can beclosed. This idea necessarily prefers a symmetrical design of the cryostat with respect to thebeam orbits. In this case, the bellows between the IP chamber and the cryostat chamber are
located on the cryostat chamber. Another idea for the connection is described in Sec. 3.3. The
type of connection has some impact on the design of the IP chamber.

3.2

Beam-induced background

In SuperKEKB, the expected luminosity will be 40 times higher than at KEKB, due to thehigher beam currents and smaller interaction point (IP) beam sizes. These features cause higher
beam-induced background in the Belle II detector. To assure stable detector operations atsuch high luminosity, an interaction-region (IR) design based on beam background estimations
inferred from the present level is important.
In this section, we discuss the expected beam-induced background at SuperKEKB. Note that
all expectations strongly depend on the beam optics. We expect to update the numerical results
below after fixing the beam optics and the interaction region design.

64

CHAPTER 3. IR DESIGN

4DSFXTFBM

4DSFXTFBM*%QBUIJOUIF)FMJVNKBDLFU

Figure 3.10: Suggested modification of the cryostat to tighten screws for the flanges in front of
the cryostat (side view).

3.2.1

Evaluation of possible beam-induced backgrounds

In this section, we describe the possible background sources in SuperKEKB: synchrotron radiation (SR) from the high energy ring (HER) upstream direction, backscattering of SR from HER
downstream, scattering of the beam on residual gas,1 Touschek scattering, radiative Bhabha
scattering, and electron-positron pair production via the two photon process e+ e− → e+ e− e+ e− .
• SR from upstream (SR Upstream)
It is important to evaluate the upstream SR background to design the IP chamber to protect
the inner detectors (PXD and SVD). Here we design the IP chamber to avoid direct SR hits
from the HER in the detector. Since the SR background level depends on the HER current,
beam-optics (magnet positions, magnetic field strength, and beam orbits), and the geometry of
the IR components, we perform GEANT4-based beam-line simulations. We find no direct SR
hits from HER are expected with the current beam optics and IP chamber design.2• Backscattering of SR from downstream (SR Backscattering)
The final focusing magnet for the HER downstream side is called QCS-R, where R stands forthe right hand side in the schematic drawing. The magnet QCS-R provides the final focusingof the LER beam. In the current KEKB case, it also works as a bending magnet to separate
the outgoing HER beam from the LER. Strong SR is then emitted because of this bending.
On the other hand, in the SuperKEKB case, two separate quadrupole magnets are located on
both the R and L sides, and beam orbits of both incoming and outgoing beams are on centerin the magnets. We therefore expect much lower background than at KEKB. Based on the
optics calculations, we expect 1/800 of the current KEKB backscattering SR at SuperKEKB.
To confirm this, careful simulation studies will also be necessary after fixing the beam optics.
1

In what follows, we will use the expression ‘beam-gas scattering’ or just ‘beam-gas’ for this kind of scattering.
Recently, we find there are direct SR hits from HER to the IP chamber. We have developed an IP chamber
design to take care of these SR hits.
265

CHAPTER 3. IR DESIGN• Beam-Gas scattering
Beam-gas scattering (bremsstrahlung and Coulomb scattering) changes the momenta of beam
particles, which then hit the walls of vacuum chambers and magnets. Shower particles areproduced and are one of the major sources of the beam-induced background. The size of thisbackground depends on the beam current, the vacuum pressure in the ring, and the strength ofthe magnets.
In SuperKEKB, the beam currents will be ∼2 times higher than in KEKB. Except for the IR,
the vacuum and the overall magnet-field strength will be the same as the current levels. We
therefore expect the same order of magnitude (a few times higher) beam-gas background dose.
However, the vacuum level at the IR (±2 m from IP) will be 100 to 1000 times higher thanat present, and the magnetic fields of the final focus magnets are much higher; therefore, it
is important to evaluate these effects. In addition, in the SuperKEKB IR, due to the limited
space around the IP, the thickness of the IP chamber mask that shields the shower particle
backgrounds arising from beam-gas and Touschek will be only 1-2X0 , so a careful beam-gas
background evaluation is necessary.
• Touschek scattering
Touschek scattering is intra-bunch scattering. It changes the momenta of beam particles so thatthey hit the vacuum chamber and magnet walls. Shower particles are then produced. Thisbackground is proportional to the beam bunch current, the number of bunches, and the inverseof the beam size. In SuperKEKB, the beam size will be ∼1/20 of that at present, therefore theTouschek background is expected to be the major background source.
The contribution from the HER can be ignored, because the rate of Touschek scattering is
proportional to E −3 , where E is the beam energy, and also to the bunch current density, whichis less than in the LER because the HER current is smaller than the LER current.
Based on the expected beam lifetime, we expect the Touschek background from the LER to be
20-30 times that of KEKB. A detailed Touschek background estimation based on the beam-line
simulation is important.
• Radiative Bhabha scattering
The rate of the radiative Bhabha events is proportional to the luminosity. Photons from theradiative Bhabha scattering propagate along the beam axis direction and interact with the iron of
the magnets. In these interactions, neutrons are copiously produced via the giant photo-nuclear
resonance mechanism [1]. These neutrons are the main background source for the outermost
detector, the KL and muon detector (KLM) in the instrumented return yoke of the spectrometer.
Detailed simulation studies are important to design the IR.
In addition, in a radiative Bhabha event, both electron and positron energies decrease. If weemploy the shared QCS magnets for incoming and outgoing beams as in KEKB, the scatteredparticles are over-bent by the QCS magnets. The particles then hit the wall of magnets where
electromagnetic showers are generated. In the SuperKEKB case, we use two separate quadrupole
magnets and both orbits for incoming and outgoing beams are centered in the Q-magnets. We
therefore expect the radiative Bhabha background due to over-bent electrons and positrons will
be small. Based on a beam optics calculation, we estimate 1/40 of the current KEKB backgroundin SuperKEKB.

66

CHAPTER 3. IR DESIGN• Electron-positron pair production via two photon process
In SuperKEKB, we locate the pixel detector close to the IP. Therefore, we need to evaluate thevery low momentum electron-positron pair backgrounds produced via the two-photon processe+ e− → e+ e− e+ e− .
Based on MC simulations, we estimate that there are 900 to possibly 14000 e+ e− pairs in each
event in the first layer of the PXD, 1.3 cm from IP. The rate drops roughly as 1/r 2 . These
tracks will result in an occupancy of between 0.1 and 1.5% for the first layer of the PXD. Here
we assume the number of pixel in the first layer to be 3.2M and an integration time of 20 µs. The
cluster size is 3 pixels per track. These track numbers translate to a track rate of 700 kHz/cm2
to 10 MHz/cm2 . For the first PXD layer, we expect a hit rate of 45 M to 670 M tracks per
second.
The estimation strongly depends on how the MC simulations are done. In the last part of the2010 KEKB/Belle run we carried out a series of tests to measure this background.
To understand the particle shower background features, we performed background studies during
the 2009 fall and 2010 spring Belle runs. To evaluate the beam-gas scattering, we carried out
vacuum bump studies, in which we changed the vacuum level of each section of the ring. To
study the Touschek effect, we vary the overall beam size. In these studies, we use either single
LER or HER beams.
• Vacuum Bump study
To study beam-gas background, we vary the vacuum level of one of the sections in the HER
or LER ring. We compare the SVD PIN diode current, CDC current, or TOF hit rate andvacuum level for each section. All of the above sub-detector background levels depend on thevacuum level of the last arc or the straight sections just upstream. However, there is no strong
correlation between the detector background level and vacuum levels in other sections. This
study shows that the vacuum level between the last arc and the upstream straight section of the
IR determines the beam-gas background level.
We also vary the vacuum level of the IP in this background study. Figure 3.11 shows the resultsfor (a) CDC current, (b) SVD PIN diode, (c) HER beam life time, and (d) vacuum level ofthe IP. This study indicates that a bad IP vacuum level affects the beam lifetime, but does notdegrade the detector background level.
• Touschek study
To study the Touschek effect, we vary the HER or LER beam size. Figure 3.12 shows scatterplots of (a) 1/beamsize vs 1/lifetime, and (b) 1/lifetime vs CDC current. Since CDC current is
proportional to the lifetime, we estimate the expected Touschek background level based on the
expected beam lifetime, as shown in Sec. 3.2.1.

3.3

IP-chamber design

Figure 3.13 shows a rough sketch of the current IP chamber design for SuperKEKB. As shownin the figure, there are crotch structures on both the left and right sides, since there are two
separate QCS magnets. The radius of the IP chamber is 10 mm, to avoid a resonant cavity
structure, since the radius of the QCS beam-pipe is 10 mm. The central part is made withdouble-walled beryllium, and the crotch parts is tantalum, to shield against particle shower

67

CHAPTER 3. IR DESIGN(a) CDC current(b) SVD PIN diode(c) HER Life-time(d) Vacuum near IP (HER down stream)

Figure 3.11: Beam backgrounds for various vacuum conditions at the IP.

68CHAPTER 3. IR DESIGN(a) 1/beamsize vs 1/lifetime

1/τ

ICDC (b) 1/lifetime vs CDC current

0.022

40

0.02

35

0.018
30
0.016
25

0.014
0.012

20
0.01
0.008

15

0.006

10

0.004
5
0.002
0

0.35

0.4

0.45

0.5

0.55

0.6

0
0

0.002 0.004 0.006 0.008

0.01

0.012 0.014 0.016 0.018

1/σy

0.02

1/τ

Figure 3.12: Results of the LER Touschek background study. (a) 1/beamsize vs 1/lifetime, and(b) 1/lifetime vs CDC current.
Table 3.7: Basic parameters for the central Be part of the IP chamber.
Gold plate
Thickness
10 µ mInner Be pipe
Inner radius 10.0 mm
Thickness
0.6 mm
Gap for coolant Thickness
1.0 mmOuter Be pipe
Outer radius 12.0 mm
Thickness
0.4 mmbackgrounds. Table 3.7 summarizes the current basic parameters for the IP chamber Be-partdesign.
Cooling of synchrotron radiation (SR) and the heat due to wall current etc. is also necessary. The
central beryllium part and crotch tantalum parts are cooled with paraffin and water, respectively.
In the SuperKEKB IP chamber, beam-position monitors are mounted for fast and precise beam
feedback.
In the Belle IP chamber, there are SR masks to prevent direct SR hits the central IP chamber
part. In SuperKEKB, the polarity of the last bend is designed so that the SR fan from the bend
does not directly hit the central part of the IP chamber, as shown in Fig. 3.14. Therefore we do
not have a mask structure, because the SR is blocked by the crotch.
As described in Sec. 3.1.2, the connection between the IP chamber and the QCS cryostat is oneof the key issues in the IR design. In KEKB, the IP chamber and the QCS beam pipes without
QCS cryostat ducts were directly connected first; the QCS beam pipes and QCS cryostat ducts
were then connected. In SuperKEKB, due to the limited space in the IR, the QCS cryostat
ducts and the QCS beam pipes are integrated. Therefore we must connect the IP chamber and
QCS cryostat ducts directly. Some possibilities for this connection are discussed in Sec. 3.1.2.
Another idea to connect the IP chamber and QCS cryostat ducts is shown in Fig. 3.15. Here,
we use a quick disconnect system to connect the IP chamber and cryostat ducts via universal
joints. It is important to test these IR assembly methods for the IR design.

69

CHAPTER 3. IR DESIGN

Figure 3.13: Picture of IP chamber.

NSB





E











#BDLXBSE'PSXBSE

Figure 3.14: SR fan and IP chamber structure.

*1&MFDUSPO

43GBO1PTJUSPO

Figure 3.15: SR fan and IP chamber structure.

70

CHAPTER 3. IR DESIGNAs the central part is made of thin beryllium tubes, special care is necessary. The synchrotron
radiation from the HER and LER will not hit this part directly. We minimize the HOM (higherorder-mode) heat generation with a smooth transition from the crotch to the beryllium part.
The largest heat source in this section is caused by the image current. Based on the calculation
in Ref. [2], the generated heat values by LER and HER beam currents are 217 and 149 W/m,
respectively. As the length of the beryllium part is 22 cm, the total heat will be 81 W.
Since beryllium is reactive, we would like to avoid cooling by water. Instead, a normal paraffinliquid such as C10 H22 is the candidate coolant. As the heat capacity of C10 H22 is around
2 J/K/g, we need to flow about 300 cm3 /min of paraffin to keep the temperature rise below
10◦ C. To ensure a safety margin, we need to design the cooling system so that a paraffin flowof 1000 cm3 /min is allowed. In addition, the pressure drop of the liquid should be less than
0.1 MPa to avoid breakdown of the cylinder. According to experience with the IP chamber in
KEKB, this flow rate can be realized with a 1 mm gap between the inner and outer cylinders.
The liquid flow speed amounts to 10 m/s and the flow should be turbulent to allow efficientheat exchange between the wall and the liquid. The paraffin liquid should be dehydrated andthe water contamination should be monitored in order to avoid corrosion.
Temperature monitor sensors should be distributed over the chamber and the interlock systemshould work during accelerator operations. Depending on the HOM mode, there could be large
amounts of heat dissipation in certain limited locations. Such temperature rises should be
detected by the temperature monitor to prevent fatal accidents.

3.4

Vibration measurements

Because the beam size of SuperKEKB is expected to be very small, beam oscillation amplitudes
must be kept much smaller than are required at present. A large vibration amplitude results inluminosity degradation. In order to evaluate the present vibrations around the IP, measurements
were carried out on the KEKB tunnel floor, on some of the magnets in the interaction region(IR), on magnet supports, on movers and on the Belle detector.
Servo accelerator sensors, MG-102, made by Tokkyokiki Corporation, were used for the vibration
measurements. An output of 1 V corresponds to 1 gal with our setup. The frequency range ofthe sensors is from 0.1 to 400 Hz.
Several kinds of measurements were carried out. They are:
1. Vibration measurement at the Belle detector;
2. Vibration measurement around the IR region in the KEKB tunnel;
3. The effect of the air conditioner mounted on the Belle electronics hut;
4. Coherence between the two sides of the KEKB tunnel at the IP.
Vibration measurement on the Belle detector
Measurement locations include the floor just under the Belle detector, the Belle support table,
the middle and the top positions of the Belle end-yoke and the top of the barrel-yoke. Threeaxes of vibration, North-South (NS), East-West(EW) and Up-Down (UD), were measured simultaneously using three sensors.
Power spectral densities (PSD) at the floor and the top of the end-yoke are shown in Fig. 3.4.
Some typical resonant peaks were measured on the floor. There are resonances at 0.3–0.4 Hz
71

CHAPTER 3. IR DESIGN

Figure 3.16: Measurement results at the Belle detector: (a) Vibration on the floor, and (b)Vibration on the top of the end-yoke.
due to the effect of micro-seismic motions in the horizontal direction and at around 3 Hz due tothe resonance of gravel soil in the vertical direction.
All measurement data show a unique resonant peak at 4 Hz, mainly in the horizontal direction.
This resonance becomes larger when going from the bottom of the end yoke toward the top.
The vibration on the top of the barrel yoke is almost the same level as at the top of the end
yoke. This indicates that the Belle detector is oscillating horizontally. Though the integrated
amplitude above 1 Hz is around 60 nm on the floor, the integrated amplitude in the horizontal
direction grows to about 250nm to 350nm at the top of the end yoke. The amplitude in thevertical direction does not show a large difference. The larger vibration on the top can probably
be explained by the support configuration of the end yoke and the Belle detector.
Vibration measurements in the KEKB tunnel
Vibrations of the KEKB IR magnets were also measured. Measurement positions are the QC
magnets placed on the support table called the “QCS boat,” the QCS boat itself, the QCS
movable table and the KEKB tunnel floor. The QCS boat is placed on the QCS movable table.
The QCS movable table is mounted on rails that are fixed to the floor.

Figure 3.17: Measurement results around the KEKB. (a) Vibration on the floor, and (b)Vibration on the QC1RE.
A unique resonant peak at 8 Hz was measured with other two typical resonances at 0.3 Hz and72

CHAPTER 3. IR DESIGN

3 Hz, as shown in Fig. 3.4. The vibration amplitude is larger than that on the floor. This 8 Hz
resonance was confirmed by a hammering test where all components were vibrating horizontallywith the same phase.
The integrated amplitude in the horizontal direction was measured to be around 60 nm on thefloor, growing to about 240 nm on the QC1 magnet. The amplitudes of the vibrations are similaron the B4 floor and the KEKB tunnel floor.
Other measurements
Coherence between the two sides of the Belle detector was measured (Fig. 3.4). Sensors wereplaced on the left and right sides of the KEKB tunnel and data were taken simultaneously on
both sides. The distance between the two locations was about 8 m. The result showed nocoherence between the left and right sides, except for resonant frequencies of around 0.3 Hz and
3 Hz.
The effect of the air conditioner (AC), which is mounted on the Belle electronics hut, was also
investigated. Vibrations were measured at both sides of tunnel with the air conditioner turnedon and off. The effect of the AC turned out to be small.

Figure 3.18: Vibration coherency between left and right sides in Tsukuba Hall.

Summary
Vibrations of the Belle detector, the tunnel floor, and the magnets and their supports are
summarized in Table 3.4. The floor vibration is magnified by the Belle detector and becomesas large as ∼300 nm at the top of the Belle detector. There is no coherence between the left
and right sides of the IP. The effect of the AC being turned on was measured to be small. The
influence of the helium flow in the cryogenic system is scheduled to be measured.
A collision orbital feedback system, similar to the “iBump” feedback [3] is required to maintain
good collision conditions. In order to monitor the collision, vertical and horizontal beam-beamkicks are monitored using BPM data. The new “iBump” system will probably be configured
with iron core magnets, and with faster BPM readouts. The target rate of the new system is 50
Hz, which should be sufficient to compensate for the vibration measured at the KEKB tunnel
floor and magnets.

73

CHAPTER 3. IR DESIGN

Table 3.8: Integrated vibration amplitudes
Integrated amplitude (nm)
> 1Hz
> 10Hz
Perpend Beam Vertical Perpend Beam
Barrel Top
196
301
93
18
12
End-yoke Top
248
354
80
25
17
Endyoke Middle
204
254
121
14
27
Belle stand
105
69
71
13
11
B4 floor
50
46
67
4
3
KEKB floor
55
45
68
10
5
Magnet table
90
50
76
12
16
QCS boat
250
60
118
15
21
QC1RE
241
77
112
52
50

74

Vertical
9
20
19
13
9
9
19
30
46

References[1] Particle Data Group, C. Amsler
10.1016/j.physletb.2008.07.018.

et

al.,

Phys.

Lett.

B667,

[2] A. Piwinski, DESY-HERA-92-11.
[3] M. Masuzawa et al., Proceeding of EPAC 2000, Vienna, Austria (2000).

75

1(2008),

Chapter 4

Pixel Detector (PXD)
At the high luminosities envisaged for SuperKEKB, the detectors close to the beam pipe are facedwith extremely high hit rates, caused by beam-related background—for example, the Touschek
effect—and by low-momentum-transfer QED processes. Beam-related backgrounds are discussed
in detail in Chapter 3, and the QED backgrounds (mostly photon-photon reactions) are discussed
below. Such backgrounds need to be considered carefully when designing the first few layers ofthe vertex detector.
In the nano-beam option chosen for the SuperKEKB machine (Chapter 2), the beampipe radiusin the interaction region will only be about 10 mm. This is good news for the physics related tovertex reconstruction, but is a challenge for the vertex detector itself because the backgroundincreases roughly with the inverse square of the radius. The innermost layers of a high precisionvertex detector can no longer be realized by strip detectors due to the large occupancy, definedas the fraction of channels hit in each triggered event: the large strip occupancy at SuperKEKB
luminosities makes the reconstruction of the B-decay vertices impossible. The solution is to use
pixel sensors rather than strips for the innermost layers, which have a much larger number ofchannels and therefore a much smaller occupancy. Strip detectors are safe at radii beyond 40
mm at SuperKEKB luminosities.
This scheme—pixels followed by strips—has been successfully applied for the detectors at the
LHC. However, at the lower energies of the SuperKEKB machine, the LHC silicon detectors are
too thick: the relatively large amount of material necessary to make these pixel sensors work
(thick sensors for large signals, equipped with amplifier electronics and digital logic for the signal
extraction located above the sensors, requiring active cooling) would cause too much multiple
scattering for a precise reconstruction of B-decay vertices at our energies.
For Belle II, we therefore propose a different pixel detector concept, the PXD, based on the
DEPFET (DEPleted Field Effect Transistor) technology which allows for very thin (50 micron)sensors. In this concept, the readout electronics, which needs active cooling, are located outside the acceptance region and will therefore not contribute to the multiple-scattering material
budget. The sensors themselves will consume very little power so that air cooling is sufficient.
Radiation hardness clearly is an issue, but our irradiation tests show that the DEPFET can beengineered in an inherently radiation-hard technology.
After a general description of the layout of the PXD in Sec. 4.1, we describe the individualcomponents of this detector. These are the DEPFET sensors (Sec. 4.2), the readout ASICs
mounted on the ends of the sensors (Sec. 4.3), and the construction and assembly of an entire
module including the readout electronics (Sec. 4.4). We then address the studies on radiation
hardness, pointing towards a refined technology step with thin oxides (Sec. 4.5). Quality controlof the sensors, electronics and modules are described in Sec. 4.6, and the foreseen scheme for the76

CHAPTER 4. PIXEL DETECTOR (PXD)

data acquisition is sketched in Sec. 4.6. The mechanical support of the sensors and the coolingof the ASICs is engineered in an integral design, described in Sec. 4.8, followed by a discussion
on the necessary interfaces to the rest of the detector and the services to the PXD (Sec. 4.9).
The DEPFET sensors, initially planned for experiments at a future linear collider, have been
qualified intensively in high-energy test beams (Sec. 4.10), and the expected performance in theenvironment of SuperKEKB is shown in Sec. 4.11. Finally, in Sec. 4.12, we describe the work
packages attributed to the various collaborating institutions and sketch the schedule for realizing
the PXD up to the commissioning phase at the accelerator. We conclude this chapter with asummary.

4.1

Layout

The DEPFET pixel (Sec. 4.2) consists of a fully depleted silicon substrate and is equipped witha p-channel MOSFET structure with an internal gate where the electrons liberated by traversing
charged particles are collected. The internal gate modulates the current through the MOSFET
at readout time. The DEPFET pixel sensor is a monolithic structure, with current-digitizing
electronics at the ends of the sensor, outside of the acceptance region.

Figure 4.1: Schematic view of the geometrical arrangement of the sensors for the PXD. The
light grey surfaces are the sensitive DEPFET pixels, which are thinned to 50 microns and cover
the entire acceptance of the tracker system. The full length of the outer modules is 174 mm.
Due to its internal amplification, the DEPFET sensor can be made very thin (down to 50
microns), minimizing the multiple scattering (see Sec. 4.4). Since the DEPFET pixels are “on”
only during the readout, it is a low power device and no active cooling is necessary for the
pixel sensor itself. The readout electronics consists of three types of ASICs (Sec. 4.3): The“Drain Current Digitizers” (DCD), which digitize the MOSFET currents from a row of pixels;
the “Digital Handling Processor” (DHP), which does the zero-suppression of the “empty” pixels;
and the “SWITCHERs,” which switch on a pixel row to send the currents to the DCD. While
the SWITCHERs are located along the side of the DEPFET sensor on a 2 mm wide unthinned
rim, the DCD and the DHP are located at the ends of the sensors outside of the acceptanceregion (Fig. 4.10). Active cooling (Sec. 4.8) is needed for the DCDs and the DHPs.
77

CHAPTER 4. PIXEL DETECTOR (PXD)

The PXD consists of two layers of sensors, with radii at 14 mm and 22 mm. The inner radiusleaves sufficient space for possible variations of the final beampipe layout (Ch. 3). A schematic
drawing of the sensor arrangement is shown in Fig. 4.1. The inner layer consists of 8 planarsensors (“ladder”), each with a width of 15 mm, and a sensitive length of 90 mm. The outerlayer consists of 12 modules with a width of 15 mm and a sensitive length of 123 mm. The
sensitive lengths in each of the layers are determined by the required angular acceptance of the
tracker (Ch. 6), i.e., a polar angle range of 17 degrees (forward) to 150 degrees (backward).
The sensors are mounted on an integrated support and cooling structure, held by screws. The
support on the backward side can slide on the beampipe to compensate for thermal expansionof the beampipe and the beampipe supports.

Figure 4.2: Layout of the complete support structure with mounted sensor ladders and services
to the outside. The two half-shells are supported on the beampipe (shown in green). They aredisplaced from their mounting positions in the picture for clarity.
At the end of the active part of the ladder (“end-of-stave”), there is 25 mm of room on each side
for the DCD and the DHP ASICs. A total of four DCDs and four DHPs are bump-soldered oneach end-of-stave. From there, a multi-layer Kapton cable of 6 mm width guides the signals to
the “Data Handling Hybrid” (DHH) (Sec. 4.7), where the data stream is fed via optical fiber tothe data acquisition system. The PXD is read out in rolling shutter mode, with a speed of 100
ns per pixel row. Four rows are read out in parallel, so that the total readout time of 1600 pixel
rows (800 on each side) is about 20 microseconds for an entire frame. Several frames are stored
in a ring buffer within the DHP, waiting for a external trigger to initiate the frame readout.
An exploded view of the entire pixel detector, up to the end of the Kapton cable, is shown in
Fig. 4.2. There is an 16 mm radial gap between the PXD and the innermost layer of the silicon
strip detector (Ch. 5).

78

CHAPTER 4. PIXEL DETECTOR (PXD)

4.2

DEPFET Sensors

The DEPFET (DEPleted Field Effect Transistor) is a semiconductor detector concept thatcombines detection and amplification within one device. It was invented in 1987 by Josef Kemmer and Gerhard Lutz of the MPI for Physics [1]. After a period of principal investigations,the move of the MPI-Semiconductor Laboratory into new facilities provided the technologicalinfrastructure to fabricate large scale detectors. In recent years, the sensor development was
driven by an intensive R&D and prototyping for x-ray imagers [2] and the ILC vertex detector
[3].

4.2.1

Operation Principles

A cross section through the device is shown in Fig. 4.3. A p-channel MOSFET or JFET (junction
field effect transistor) is integrated onto a silicon detector substrate, which becomes fully depleted
by a sufficiently high negative voltage to a p+ contact on the back side. A potential minimum
is formed by sideward depletion [4], which is shifted directly underneath the transistor channel
at a depth of about 1 µm by an additional phosphorus implantation underneath the external
gate. Incident particles generate electron-hole pairs within the fully depleted bulk. While theholes drift to the back contact, electrons are accumulated in the potential minimum, called
the “Internal Gate.” When the transistor is switched on, the electrons modulate the channel
current. The readout is non-destructive and can be repeated many times.
FET gatep+ sourc

eclear gaten+ clear

amplifierp+ draindeep n-d
oping’internal
gate’
depletedn-Si bulk

deep p-w

ell

p+ back

contact

Figure 4.3: Operating principle of a DEPFET
The removal of the signal charge and thermally generated electrons from the internal gate iscalled “Clear.” A neighboring n+ contact is pulsed at a positive voltage providing a punchthrough into the internal gate. Any reset noise is avoided if the entire charge is removed. An
advantage of the DEPFET device is the amplification of the signal charge just above the positionof its generation, thus avoiding any lateral charge transfer where losses could occur. The mostimportant feature of the DEPFET is the very small capacitance of the internal gate, resulting
in a very low noise performance even at room temperature.
DEPFET structures can be operated individually as integrated on-chip amplifiers—for instancein the readout nodes of a silicon drift detector—or collectively as an active pixel detector.
79

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.4 shows the scheme of a DEPFET pixel matrix that is operated with a row-by-row
access via the external gates, also called “rolling shutter mode.” Here, the external gates switch
the pixel on and off while the signal amplification is achieved via the internal gate. There is no
current flow in the non-selected DEPFET rows so that the array consumes only very little power.
The readout amplifiers at the end of the columns can be connected either to the sources (source
follower) or the drains (drain readout) of the DEPFETs. For collider applications, we use thefaster drain (current) readout. A measurement cycle consists of a collection phase (Collect), thereadout (Read) and the reset of the internal gate (Clear). A pedestal subtraction is realized
either by a consecutive Read–Clear–Read sequence (double sampling) or by a faster Read–Clear
procedure (single sampling), where cached pedestal values are subtracted in the DHP readout
chip (Sec. 4.3). Only during this readout mode is the DEPFET (partially) insensitive. Hencethe dead time is only 100 ns within the 20 µs readout cycle (0.5%).

Figure 4.4: DEPFET matrix operated in rolling shutter mode
The figure of merit is the internal amplification of the DEPFET. It is defined as the current
response to an electron collected in the Internal Gate.
gq = ∆Id /e−(4.1)

Note that gq is directly proportional to the signal-to-noise (S/N ) of the system, because thenoise of the readout ASICs dominates over the noise of the DEPFET. The relationship between
gq and the technology and design parameter can be derived [5] from the simplified equation 4.2
r
Id µ
(4.2)
gq = gm /Cint = 2 3
L W Cox80

CHAPTER 4. PIXEL DETECTOR (PXD)

where gm is the conductance of the external gate, Cint is the capacitance of the internal gate,
Cox is the sheet capacitance of the gate oxide, Id the drain current, µ the carrier mobility, and
L and W are the length and width, respectively, of the gate. The gate length L has the biggest
impact on gq (see Fig. 4.5, left side). Prototypes with the standard channel geometry have a gq
of about 400 pA/e− , but DEPFETs with a scaled channel geometry show even better results.
For instance, the 128x128 test matrix H09 with 20 × 20 µm2 pixel size investigated during thelast test beam at CERN in 2009 (Sec. 4.10) has a gq of 560 pA/e− . This was achieved by amodest decrease of the DEPFET gate length L from 5 µm to 4 µm.

Clear

GclearChannelMetal 2
Metal 1
Poly 2
Poly 1n+Deep pp
Deep nFigure 4.5: (Left) Internal amplification gq vs drain current and channel length L illustrating
the scaling potential of the DEPFET [5]. (Right) Cross section through the Clear - Clear Gate
- Internal Gate simulated with Synopsis TCAD-DIOS [6] (x and y scales in µm).

4.2.2

Technology Extensions for Belle II Vertexing

For DEPFET applications in ILC and astrophysics experiments, a new double-sided DEPFET
technology was developed. This CCD-like technology was specially tailored to the functional
DEPFET requirements. It contains two polysilicon and two metal layers and is the world’s mostcomplex technology on high ohmic wafers. The cross section through the clear and channel regionof the DEPFET (Fig.4.5, right side) gives an impression of the DEPFET technology.
Two major changes must be incorporated to meet the Belle II requirements. The separately
developed thinning-technology module (Sec. 4.4) is implemented into the currently processed
DEPFET prototype run, called PXD6. PXD6 is the first technology run that produces DEPFETs
on 50 µm thick substrates. In parallel, the smaller PXD-TO project aims to optimize a radiationhard gate insulator that is able to cope with the harsh backgrounds near the Belle II beamline.
The starting point for this development is a gate dielectric that shows an acceptable flatband
voltage shift of 3 V measured on MOS capacitors after 10 MRad irradiation (Sec. 4.5). However,
PXD-TO contains not only MOS capacitors but also transistors with “DEPFET-equivalent”
doping profiles and will test a larger parameter space in order to find an even more radiationhard dielectric. The resulting technology module, “Thin Oxides,” will be implemented in the
final Belle II production. The reduction in gq expected from the increased gate capacitance will
be compensated by a slight reduction of the gate length L according to equation 4.2.
Two wafers of the PXD6 batch are produced with plasma etched polysilicon to get smootherand smaller transistor gates. If this development succeeds, we can increase the S/N by taking
81CHAPTER 4. PIXEL DETECTOR (PXD)

advantage of the scaling potential of the device (Fig. 4.5). Finally, a third metal layer, madeof copper, must be implemented to provide the under-bump metal necessary to bump-bond theASICs and to reduce the voltage drops on the all-silicon module (Sec. 4.4). The DEPFETs
for the Belle II vertex detector will be processed on wafer bonded SOI material with a specially developed technology including 18 photo-lithographic mask steps, 9 ion implantations,two polysilicon layers, and three metal layers.

4.2.3

Prototype Designs for Belle II

Due to the similar requirements, the Belle II DEPFETs are developed based on the ILC devices [7]. However, the size of the ILC pixel is in the range of only 25 × 25 µm2 while the pixel
sizes envisaged for the inner and outer layers of the Belle II vertex detector are 50 × 50 µm2 and50 × 75 µm2 , respectively. The most challenging requirement is the short frame readout timeof 20 µs, corresponding to 12.5 ns per row for 1600 pixel rows in total. Such a short readout
time would, however, be incompatible with the intrinsic settling times on the long readout lines
and control lines of the matrix and would introduce additional high-bandwidth noise. In orderto relax the speed requirement, we split the matrix to have readout electronics on both ends
and we implement in addition a high degree of parallelization: Four rows are read out simultaneously, which multiplies the number of drain lines and readout channels by the same factor(Fig. 4.6, left side). The combined factor of eight leads to a row processing time of 100 ns, which
is manageable.
The increase of pixel size over the ILC design implies an increased charge collection time, i.e.,the drift time that the charge needs to reach the internal gate. An efficient drift structure is
implemented to increase the electric field, especially at the pixel edges. Device simulations showthat drift times can be kept below 60 ns with the favored design, which should be short enoughto suppress ballistic deficits. The readout itself is more critical. Using the fast single sampling
readout mode, we must sample and reset the signal within the 100 ns window. To provide
enough time for signal settling and sampling, the reset (Clear) time must be less than 20 ns. As
in the ILC designs, a narrow channel width is needed to reduce the time for the electrons todrift from the internal gate into the clear. Therefore, the small linear basic transistor structure[7] is adopted from the proven ILC designs, while the clear and drift regions are expanded to fill
the enlarged pixel area.
The baseline design comprises a DEPFET structure with individual source and drain regions
embedded in drift and clear regions (see Fig. 4.6, right side). This approach has fast chargecollection times and is suitable for both pixel sizes to be used in Belle II. A blow-up of a
successfully tested ILC design [8] was chosen as a fall-back solution. Here, each contact region(drain, clear, source) is shared by two neighboring pixels, which leads to a very compact design.
The disadvantage is a longer collection time for the charge generated at the edge of the pixel.
Although all devices were designed by using technology and device simulations tools [6, 8, 9],
there are features that are unpredictable. In particular, production yield and radiation hardness
may be influenced drastically by minor design changes. Therefore, we will test several designs,
concepts and options. We have numerous smaller wire-bonded test matrices on the PXD6 wafer
in order to be able to select the best option based on laser and radiation tests.

4.2.4

Power consumption of a DEPFET matrix

Due to the row-wise addressing, the power consumption depends only on the number of columns:
P = 2 · Id · Vds · ncol = 2(100 µA)(5 V)(800) = 0.8 W
82

(4.3)

CHAPTER 4. PIXEL DETECTOR (PXD)

 
 











Figure 4.6: Left: Principle of 4-fold parallel readout and resulting matrix organization for the
DEPFET baseline design. Right: a single pixel.
∗
VGate
∗
VClear∗∗
VDrainCollection
3V
2V

Read
−2V
2V

Clear
−2V
15V

−5V
VClearGate
−2V
VBulk
10V
∗∗∗
VBack
−10V... − 50V∗ control lines (transferred via Switcher)∗∗ provided by DCD input stage∗∗∗ depending on detector thickness and contact mode
Table 4.1: Operation voltages of a DEPFET matrix with respect to source (0V )The factor of two results from splitting the matrix into two readout directions (Sec. 4.1). The
power necessary to ramp up and down the gate and clear lines is mainly consumed in the
SWITCHERs (Sec. 4.3). Compared with these contributions, we can neglect the power consumption caused by the leakage current: this is at most a few mW even after irradiation.

4.2.5

Matrix Operation Voltages

Table 4.1 summarizes the operating voltages of the matrices. Note that the gate and clear gate
voltages may have to be shifted to more negative values to compensate for radiation-induced
oxide damage during operation.

83

CHAPTER 4. PIXEL DETECTOR (PXD)

4.3

Electronics (ASICs)

As illustrated in Fig. 4.4, the DEPFET pixel modules are read out in a rolling shutter mode:a matrix segment consisting of four multiplexed rows (Fig. 4.6) is selected by pulling the gateline to a negative potential using the SWITCHER chip (see below). The selected DEPFET
pixels send currents to the vertically connected drain lines. These currents are processed at
the bottom of the matrix by the Drain Current Digitizer (DCD) chips. The DCD performs animmediate digitization of the current with 8 bit resolution and sends the data serially throughmany low-swing single ended lines to a third chip, the Data Handling Processor (DHP), whichbuffers and analyzes the digital data stream and performs a zero suppression. The remaining
data are then sent to the off-module data handling hybrid DHH (Fig. 4.22).
Three different ASIC types are, therefore, used for the matrix readout:• The SWITCHER chips select and clear the DEPFET four-row segments by generating
voltage swings of 10–20 V. In order to reduce the inactive module border, both functionalities are merged in a single chip, as shown in Fig. 4.7. The channel selection is doneinternally by a simple shift register. Precise timing is provided by additional STROBE
input signals.
• The DCD chips process the currents in the columns and digitize the analog values.
• The DHP chips perform data processing, compression, buffering and fast serialization andsend the data off module to the DHH.
All chips are mounted directly on the detector module using bump-bonding and flip-chip techniques, leading to all-silicon modules.

4.3.1

Readout Cycle

The readout cycle starts with the selection of a DEPFET four-row segment by a SWITCHER
chip. The corresponding SWITCHER channel is enabled by setting a single enable bit in its shift
register and by confirming the selection using the fast STROBEGATE signal. All SWITCHER
control signals are generated by a master DHP. The low voltage control signals are translated
internally to the required higher gate-on voltages that steer large MOS switches. These devices
pull the gates of a complete DEPFET row (with a capacitance of as much as 50 pF) to the
GATEON potential. The DEPFET currents flow then through the column lines into the DCDs.
The current receivers in the DCDs are based on transimpedance amplifiers. They hold thecolumn-line potentials at a constant level (virtual ground) to make the readout speed more
insensitive to the large column-line capacitances (50 pF). Since the potentials of the lines areconstant, the signal currents flow directly into the DCDs rather than charging the line capacitances. The current receivers can also amplify the current signals and act as low-pass filters to
reduce the noise. The amplified and shaped signals are then processed by current-mode cyclic
ADCs. Two are placed in each DCD channel to achieve the necessary sampling frequency ofat least 10 MHz. The shaping time and the gain of the current receivers are programmable: alarger shaping time leads to a better S/N and a lower readout speed, while a larger gain leads
to an increased S/N and a decreased input-signal dynamic range.
The currents in the columns consist of a standing current of 50–100 µA, required to operate
the DEPFET devices, and a small signal component that depends on the charge gain gq ofthe devices. Due to device mismatch in the matrix, the standing currents are not identicalfor all devices, leading to pedestal fluctuations. Digitizing signals plus the large pedestals would
84

CHAPTER 4. PIXEL DETECTOR (PXD)

require a very high resolution ADC with correspondingly high area and power consumption. The
pedestals must therefore be subtracted prior to digitization. Two methods are implemented:• Double sampling: A clear pulse sent to the DEPFETs during current readout removes
charges in the internal gate. Subtracting the current before and after this pulse leaves
only the signal component, as the pedestal is constant. This Read–Clear–Read sequence isimplemented by providing a current storage cell with a sufficient dynamic range that holds−(pedestal + signal) in the first phase. The pedestal signal after the clearing is subtracted
by simply adding the drain current and the stored value.
Because the DCD must take two samples during each readout cycle, the shaping time of
the current receiver must be below 35 ns for an 80 ns readout cycle. Using such a readout
mode simplifies the DHP design since no digital pedestal correction is needed (see below).
However, the short sampling and shaping times and the fact that two samples are taken
in each readout cycle lead to an increased readout noise that may reduce the theoreticaladvantange, in terms of 1/f noise cancellation, of the double correlated sampling.
• Single sampling: A constant current is subtracted from the drain current and the signal
is directly digitized. Clearing can be done after this. There is no need to wait for signal
settling after the clear, so that this Read–Clear procedure is faster. The ADC would still
have to accommodate the full pedestal current dispersion. To reduce the required range,a 2 bit DAC in each channel is available to subtract varying currents. If we assume a
50 µA DEPFET bias current and a conservative 20% pedestal variation among the pixels,
the required dynamic range would be 10 µA. With the highest possible gain for the DCD,
we have an ADC range of 4 µA and a full range (with DACs) of 16 µA. Note, however,that the gain of the transimpedance amplifiers in the current version of the DCD can be
programmed to lower values, yielding an even higher range of the ADCs, which can be as
high as 64 µA. The control words for these DACs can be different for each pixel. They are
stored in the DHP and are sent serially from the DHP to the DCD.
The shaping time of the current receiver can be longer in this mode. Assuming a readout
cycle of 80 ns and a clear time of 20 ns, the shaping time can be 60 ns. Under such conditions, the noise introduced by the current receiver (its input transistor) will be lower than
the noise introduced by the ADC (typically, rms(ADC) is 40 nA).
The use of two-bit pedestal correction in the DCD will not be enough to reduce the remaining part of the pedestal dispersion to a level that allows an effective signal recognitionand zero suppression. For this reason, an additional pedestal current compensation will be
performed in the DHP on the digital codes received from the DCD. The DHP will also calculate the average of the signals received from every DEPFET row-segment and subtract
this average part from the signals itself and in this way compensate for any average-signal(common mode) fluctuation. The low-frequency signal fluctuations can be eliminated by
updating the pedestal values frequently.
After the readout cycle the DEPFET is switched off till the next cycle, 20 µs later. Because ofthis frame readout mode, all signals arriving within the 20 µs between two readout cycles are
stored (integrated). However, this might cause some increased dead time due to the SuperKEKB
injection mode. Injection will be every 20 ms (50 Hz). Since the injected bunches are noisy, thetrigger will be vetoed during the passage of these bunches for a couple of µs until the noise has
calmed down about 3 ms after injection. However, due to the long integration time, it is notpossible to veto the DEPFET during the passage of the noisy bunches. In the worst case, the
DEPFET data will be flushed with noise hits during the 3 ms, corresponding to a dead time of85

CHAPTER 4. PIXEL DETECTOR (PXD)

15%. A possible solution would be to decrease the injection rate while injecting more bunches
each time.

4.3.2

SWITCHER

The SWITCHER steering chips are mounted on the ∼ 2 mm inactive rim of the module. These
chips provide fast (∼ 10 ns into 50 pF) voltage pulses of up to 20 V amplitude to activate gate rows
and to clear the internal DEPFET gates. The SWITCHER is implemented in the AMS 0.35 µm
HV technology using special design techniques to achieve radiation hardness (enclosed NMOS
gates, guard rings). One SWITCHER will be able to control 32 different DEPFET matrix
segments (row groups). Each channel provides a clear- and a gate-driver. Channels are selected
via a simple shift register with serial input to (output from) the previous (next) chip. Figure 4.7
shows a preliminary layout of the chip with an approximate size of 2 × 3.6 mm2 .
All required SWITCHER control signals and power must run on the 2 mm-wide module rim.
The number of I/O signals has therefore been minimized and an unusual bump pad geometry has
been chosen to simplify routing on the module. To simplify system design, the SWITCHERs
have a floating digital ground and use fast, low power level shifters. A JTAG interface withboundary scan logic allows for interconnectivity tests on the module.

Figure 4.7: Preliminary layout of the SWITCHER chip. The 4×16 bump pads for the gate/clear
outputs are in the center; additional 4 × 4 pads for power and control are at top and bottom.
The SWITCHER optimized for the Belle II requirements (“SWITCHERB”) has been submitted in February 2010. The existing prototype (“SWITCHER 4”) has been successfully tested.
Radiation hardness of at least 37 MRad has been demonstrated.

4.3.3

DCD

The currents generated by a selected DEPFET four-row segment are routed out via columnlines and read out by the DCD chips placed at the end of each half-module matrix. Each DCD
has 256 analog inputs. The DCD is implemented in the UMC 0.18 µm CMOS technology using
special radiation hard design techniques. The chip occupies an area of 3.2 × 5 mm2 . Chip size
and input pitch have been adapted to the Belle II requirements (“DCDB”). DCDB uses bumpbonding with bumps on the UMC technology provided by EuroPractice. Figure 4.8 shows the
DCDB layout and the organization of the pads.

86CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.8: Layout of the DCDB chip. The upper part contains the 256 inputs; the lower partcontains the digital logic and digital input / output pads.

Readout Mode
Double corr. sampling
Single sampl. w/o ped. corr.
Single sampl. with ped. corr.

Receiver√2·60 nA
25 nA
25 nA

Noise
Sampling cell
40 nA
0
0

ADC
40 nA
40 nA
10 nA

Total
102 nA
47 nA
30 nA

Table 4.2: Expected noise contributions by readout mode, for a readout cycle time of 80 ns.

Each channel consists of an input stage, two ADCs and digital logic. The analog input stage
keeps the column line potential constant (necessary for fast readout), compensates for DEPFET
pedestal current variations, amplifies the signal, and provides shaping for noise reduction. For
these purposes, the input stage offers programmable gain and bandwidth, a two-bit DEPFET
pedestal current compensation (using digital data from the DHP) and sampling of the pedestal
current. The analog signal is digitized using current-mode cyclic ADCs, two of them placedin each channel. A large synthesized digital block decodes and derandomizes the ADC raw
data, which are then transmitted in a well sorted sequence to the DHP chips using fast parallel
8-bit digital outputs. The digital timing and data protocols are tuned for rapid communication
with the DHP. Several operating modes using single sampling or double correlated sampling are
possible.
Due to the expected quite significant power dissipation of up to 600 mA per chip, voltage dropson the internal power buses are a significant concern. This is addressed by several methods: theuse of separate power buses for sensitive parts, high power supply rejection, massive decoupling,
and the use of the extra redistribution metalization of the bumping technology for additional
power routing.
The DCD chip optimized for Belle II (DCDB) has already been submitted, received and is being
characterized. A very similar prototype chip (“DCD2”) has been successfully tested and used toreadout a prototype DEPFET matrix at nearly full speed with a noise value smaller than 100 nA(see Fig. 4.9). Radiation tolerance of at least 7 MRad has been proven. Table 4.2 summarizes
the noise figures that are expected in the various readout modes for the latest version of DCD.

87

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.9: Noise when reading out a DEPFET matrix with DCD2 at 11 MHz (in ADC counts,
one ADC count corresponding to approximately 100 nA).

4.3.4

DHP

The data handling processor (DHP) reduces the data rates produced by the DCDs. This isachieved by zero-suppressing the DCD data and by reading out only triggered data. To allow
for efficient zero-suppression, the raw data is corrected for common mode noise and pedestal
fluctuations. The latter is an offset in the signal data and is not removed by the DCD whenrunning in single sampling mode (Sec. 4.3.3). These individual offset values will be continuously
updated within the DHP to compensate for low frequency fluctuations and drifts.
The common mode refers to an offset that is found in all signals sampled at the same time.
This offset is time dependent and therefore different for each sampling interval. To remove
this offset, the mean signal value of all simultaneously sampled channels is calculated inside
the DHP and subtracted from the original input signals. The zero-suppressed data, together
with a time stamp, are stored in hit buffers and selected for readout upon receipt of a trigger.
The triggered hit data are transmitted to the data handling hybrid (DHH) with high speed
links running at 1.25 Gbit/s per chip, resulting in an overall maximum data rate of 5 Gbit/s
per half-module. In addition to the data processing task, the DHP will also serve as a module
controller by generating all fast timing signals for synchronization of DCD and SWITCHER andby providing a slow control JTAG interface. The DHP chip will be implemented in the IBM
90 nm CMOS technology to accommodate the memory needed for pedestal and frame storage.

4.3.5

Bumping and Flipping

To make the module as compact as possible, all chips are bumped and flip chip mounted directly
onto the silicon substrate. This procedure requires two major steps: the bumping, i.e., thedeposition of (in our case) solder spheres onto the chip pads and the flipping, i.e., placing thechips upside down onto the substrate and melting the solder by a temperature cycle. For bothsteps, the chip/substrate surface must be suitable for soldering: they must have an under-bump

88CHAPTER 4. PIXEL DETECTOR (PXD)

metalization (“UBM”).
For the substrate, this is assured by the post-processing technology used in the MPI Halbleiterlabor, HLL, as explained in Sec. 4.4. The DCDB and DHP chips can be ordered with bumps (andUBM) being placed by the vendors or subcontracted companies. Presently, the pitch for thesebumps is limited to 200 µm, which is a serious boundary condition for the designs. The DCDB
chip was ordered with such bumps. For the SWITCHER, there seems to be no possibility to getbumped chips from the Multi-Project Wafers (MPW). We will therefore use a backup technologythat was developed in Heidelberg: In the first step, gold studs are placed on the SWITCHER
pads, acting as a UBM for the solder. In the second step, individual solder balls are placed
by a solder bumping machine (available in Heidelberg). This technique can accommodate the
SWITCHER’s pitch of 150 µm. The technology has been successfully tried out on dummy chips,with solder balls being placed by the vendor of the machine.
The flipping can be done on a manual machine with very high precision available in Heidelberg,
or with an automated machine that will be available at HLL. Other involved institutes have (orwill have) flipping capabilities as well.

4.4

Module Description and Interconnections

The DEPFET pixel array is made on thin (about 75 µm) detector grade silicon supported bya directly bonded silicon frame of about 400 µm thickness. The dimensions of the ladders andthe overall layout of the PXD are described in detail in Sec. 4.8. The readout electronics, thelines for power, data, and slow control are placed on both short sides of the ladder, outside thesensitive volume; the steering chips for the row-wise read out are attached on the thick frame
along the long side of the ladder. The circuit paths for these steering chips are integrated on
the support frame of the sensor module. Figure 4.10 shows the sketch of a module for the inner
layer of the PXD. In the following, we describe the thinning technology and the interconnection
details between sensor and read-out chip, as well as the off-ladder interconnection at the endsof the ladders.

4.4.1

Thinning Technology

Back-thinning of microelectronic chips is widely used in semiconductor industry. However, thesetechnologies are not easily applicable for fully depleted sensors with an electrically active backside. DEPFETs are FETs on fully depleted bulk with a deep-n implant under the channel. They
have a structured implant, contacts, and metalization at the back side. Conventional thinning,i.e., grinding or chemical mechanical polishing (CMP) of the back side, is usually done after
the top side processing is finished. The processing steps at the back side (implantation andlaser-assisted implant activation or diffusion) would then have to be done with a thin and fragile
wafer, a procedure that is extremely difficult and cost-intensive.
To avoid these critical steps, we have chosen another way to produce ultra thin sensors (see[10]). Figure 4.11 illustrates our approach to fabricating such thin devices with a minimumof processing steps after thinning. The feasibility of this approach has been shown with the
production of 50 µm thin PiN diodes. The volume-generated reverse current of under 100 pA/cm2
achieved with these thin devices is extremely encouraging. The mechanical stability of the diced
chips is sufficient for safe handling and mounting. There is no distortion visible on the 50 µm
thin large area silicon membrane with single-sided aluminum metalization.
The same technology of deep anisotropic etching is used to reduce the material in the supporting
frame along the long sides of the ladder. In this way, the contribution of the silicon frames can be89

CHAPTER 4. PIXEL DETECTOR (PXD)

z= 0

~75µm

Clear SW

Gate SW

~50µm

gate
clear

drainsactive areacross section

DCD Chips
DHP Chips

Figure 4.10: Sketch of a first layer module with thinned sensitive area supported by a siliconframe, illustrating the DEPFET ladder concept.
reduced by roughly 30%. Figure 4.12 shows the result of the technology simulation with a closeup of the perforated frame. The assessment of the overall material budget of the first layer is seenin Table 4.3, including all major contributions (Si, SWITCHER, bumps, Cu interconnection,and frame) and with selected thicknesses of the sensitive layer. The overall material budget in
the baseline configuration (Option 1 in Table 4.3) is 0.19% of a radiation length. The material
contributions are calculated under the following assumptions:• Sensitive area of the first ladder: 1.25 × 9 cm2• Support frame: 0.1 + 0.2 cm• Switcher-Sensor interconnect: Au stud bumps, φ = 48 µm• Cu Layer: t = 3 µm, 50% coverage in sensitive region• Switcher dimensions: 0.15 × 0.36 cm2• Number of Switchers: 8• Material reduction by frame etching: 1/3
90

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.11: The process sequence for production of thin silicon sensors with electrically active
back side implant. (a) It starts with the oxidation of the top and handle wafer and the back side
implantation for the sensor devices. (b) After direct wafer bonding, the top wafer is thinned andpolished to the desired thickness. (c) The processing of the devices on the top side of the wafer
stack is done on conventional equipment; the openings in the back side passivation define theareas where the bulk of the handle wafer will be removed. (d) The bulk of the handle wafer isremoved by deep anisotropic wet etching and the etch process stops at the silicon oxide interface
between the two wafers.

Figure 4.12: Full size electrically active samples made using the process of Fig. 4.11.
The largest contribution to the overall material budget is the support frame, as seen in the
breakdown of the various components in Fig. 4.13.

91

CHAPTER 4. PIXEL DETECTOR (PXD)

Option
1
2
3
4
5
6
7
8

Sensitive
Thickness (µm)
50
50
50
50
75
75
75
75

SwitcherThickness (µm)
500
500
200
200
500
500
200
200

Frame
Thickness (µm)
450
400
450
400
450
400
450
400

Total
Thickness (% of X0 )
0.16
0.15
0.15
0.14
0.19
0.18
0.18
0.17

Table 4.3: Material assessment of the DEPFET Ladder (L1), averaged over sensitive area.

Figure 4.13: Breakdown of the material contribution of various ladder components.

4.4.2

Low-Mass Joint Between Half-Ladders

The ladders for the second layer of the PXD are too long to fit on a 150 mm wafer. Theseladders are split into two halves that are joined using a low-mass joint that maintains mechanicalstability. As shown in Fig.4.14, the support frame is laser-cut at one end of the ladder, leaving anarrow band (≈ 250 µm) of inactive silicon as a support. In addition, there are ∨-grooves etchedin the support frame perpendicular to the laser-cut line. This etching is done simultaneouslywith the back-thinning of the handle wafer. The two half-ladders are then aligned to each otherand glued. The mechanical stability is provided by inserts (ceramic or silicon) into the ∨-grooves,again attached with the appropriate adhesive (Araldite 2011).
This technology is indispensable for the second layer. Although an entire first-layer ladder could
fit on a 150 mm wafer, yield considerations compel us to use this low-mass joint there as well.
Simulations show that the small insensitive region (≈ 500 µm) and the little extra material does
not deteriorate the overall performance of the PXD (see Sec. 4.11).

92

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.14: Perforation of the silicon frame of the ladder for further material reduction (technology simulation result, not to scale).

4.4.3

On- and Off-Ladder Interconnection

As described in section 4.3, there are three types of ASICs placed directly on the DEPFET
ladder. The interconnection between these ASICs and the DEPFET ladder is done by conventional flip-chip bonding of the solder-bumped ASICs to the landing pads on the ladder. The
bumping of DCD and DHP is done by the manufacturer using standard wafer-level bumping
technologies. The bumping of the SWITCHER chips has to be done on the chip level using asolder-jet technology provided by the company Pac-Tech.
On the other side of the DEPFET ladder, an appropriate landing pad with solder-wettable
metallurgy has to be prepared. This metallization is done during the processing of the DEPFET
wafers by the electroplating of copper and tin. This process provides a third low-impedance
wiring layer on the DEPFET ladder.
The data transmission, slow control of the ASICs, and power supply connections are realized bya three-layer impedance-controlled Kapton cable glued directly to the end of the ladder. The
electrical connections are done by conventional wire bonds from the pads on the Kapton cableto three banks of wire-bond pads on the inactive part of the sensor ladder. A PCB serves asa patch panel to connect to the more remotely located DHH (4.9). It needs some circuitry
for impedance matching of the HF signal lines to twisted pair cables upstream and overvoltage
protection for the power lines.

4.5

Radiation Hardness

To date, we have no reliable simulations of the expected irradiation level. We do not know theexact composition of the background nor the spectrum of the particles and photons. Extrapolations from Belle are difficult, since important machine parameters will change. An educatedguess would suggest 1–2 MRad/y. Pending more information, we want to assure that PXD
components survive at least 10 Mrad.
Rough estimates can be derived from the expected occupancy. Assuming an occupancy of 0.5%
from charged particles in pixels of 50 × 50 µm2 and 20 µs integration time, the absorbed doseis 2.6 Mrad in one year (107 s), assuming a particle flux of about 10 MHz/cm2 . Assuming that93

CHAPTER 4. PIXEL DETECTOR (PXD)

most of the particles are low energy electrons just above the cutoff given by the magnetic field(6 MeV), they have a damage factor of 0.08 compared to 1 MeV neutrons. Hence, the expected
NIEL damage is in the order of 1013 n/cm2 (1 MeV neutron equivalent).

4.5.1

DEPFET Irradiations

The DEPFET is a MOSFET device and suffers mainly from threshold voltage shifts due to anincrease of oxide charges and interface states in the gate oxide. In addition, some increase ofnoise due to interface traps and a reduction of the amplification is expected. NIEL damage
increases the leakage current and contributes to the shot noise. In case significant shot noise
is generated, it could be reduced by lowering the sensor temperature. Since there is no chargetransfer over long distances during the operation of DEPFET matrices, trap generation by NIEL
is of minor importance for this kind of device.
4.5.1.1

Ionizing Radiation Damage

All MOS technologies are inherently susceptible to ionizing radiation. The main total ionizing
dose effects are:
• A shift of the threshold voltage to more negative values caused by radiation induced chargebuild up in the oxide;• Build up of states at the interface between Si and SiO2 , resulting in an increased subthreshold slope and possibly a higher 1/f noise of the transistors;• Reduction of the transconductance (gm ) due to a lower mobility of the charge carriers in
the channel after irradiation.
The degradation of MOS transistors with a certain thickness of the gate dielectrics (about 200
nm in the case of the present DEPFET prototypes) for a given total ionizing dose in the oxide
depends on the technology and the biasing conditions during irradiation.
During several irradiation campaigns at an x-ray source in Karlsruhe, DEPFET devices and
MOS test structures were irradiated up to 10 MRad. During normal operation the DEPFET
is in “charge collection mode,” i.e. fully depleted bulk with empty internal gate and switched
off by applying a positive gate voltage with respect to the source. The transistors of a row
are only switched on during the short readout period. The time ratio between “off” and “on”
state ton /tof f in the vertex detector (assuming a 1600 pixel array read out at both sides) is in
the order of 0.1%. Thus, the irradiation of the test devices was done with the transistors in“off” state with an empty internal gate to test for the radiation tolerance in this most frequent
operation mode.
The dose rate of the X-ray source ranged from 73 kRad(SiO2 )/h up to 625 kRad(SiO2 )/h. The
dosimetry was provided via the generated photo current in a diode in depletion mode and using
the spectrum of the x-ray source. Also, this dosimetry was cross checked with RadFET monitoring devices. The input characteristic of the devices were measured immediately (approximately
1 min) after each irradiation period and the threshold voltage was extracted by a quadratic
extrapolation of the IDrain (VGate ) curve to IDrain = 0.
Figure 4.15 shows the threshold voltage shifts directly after irradiation. The irradiation was
stopped after 10 Mrad(SiO2 ) and the devices were annealed at room temperature. The thresholdvoltage shift after 300 h annealing at room temperature is reduced from 16.5 V to 12.5 V.

94CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.15: Threshold shift of DEPFETs irradiated up to 10 Mrad, before annealing. The red
dots indicate a device with the gate voltage adjusted to optimal transistor performance while
the blue dots show a device with 0 V gate voltage all the time.

Figure 4.16: 55 Fe spectrum taken with a linear MOS-type DEPFET. Left figure: before irradiation. Right figure: after irradiation (4 Mrad).
The most important issue is the spectroscopic performance of the DEPFET after irradiation.
Fig.4.16 shows an 55 Fe spectrum taken with a DEPFET before and after irradiation. The
equivalent noise charge of the pedestal peak changed from 2.1 e− to 4.6 e− (rms), attributed tothe increase of the low frequency noise which does not depend on the shaping time. Even after
this high total ionizing dose of 4.1 MRad(Si), the DEPFET shows only a moderate noise increaseof about 6 electrons equivalent noise charge. Hence it can be concluded that the DEPFETs are95

CHAPTER 4. PIXEL DETECTOR (PXD)

radiation tolerant to doses up to 10 Mrad. However the large threshold voltage shifts demandlarge corrections of the operation parameters. These corrections may be outside the range of thecontrol electronics. In case of inhomogeneous irradiations across a module it might be impossible
to find optimal parameters for the complete sensor. Hence it is highly desirable to reduce theselarge shifts.
4.5.1.2

Irradiation of MOS test devices with thin oxides

A well known remedy for effects of oxide damage in MOS devices is the reduction of the oxide
thickness and the addition of a nitride layer which partly compensates the damage in the oxide.
However, the thickness of the oxide is not a free parameter but it also affects properties like √theinternal amplification gq which is expected to vary depending on the oxide thickness d like d.
In order to evaluate this possibility test diodes with thinner oxides (100 nm) and Nitride layers
have been produced and irradiated up to 10 Mrad. The results are shown in Fig. 4.17.

Figure 4.17: Flatband voltage shift of diodes with thin oxide.
Indeed the shifts of the flat band voltage, which correspond to the threshold voltage shifts in
MOSFETs, are dramatically reduced. Only 3 V were observed which is reduced to 2.2 V after
500 h of annealing compared to 12 V with thick oxides. Such shifts can be compensated withthe existing SWITCHER electronics and do not pose a serious challenge for the operation of the
DEPFET sensors. Further tests are planned optimizing the oxide-nitride combination.

4.5.2

Proton and Neutron Irradiation

In addition to the already presented irradiations with photons, DEPFET devices have also been
irradiated at the LBNL Cyclotron with protons and neutrons. The protons had an energy of 30
MeV and the irradiation was carried out with all DEPFET terminals grounded. The achieved
proton fluence was 1.2 × 1012 p/cm2 and the total ionizing dose at this fluence was calculated to96CHAPTER 4. PIXEL DETECTOR (PXD)

irradiation
x-ray
neutronprotondose
10 Mrad0283 kradflux
0
2.4 × 1011 n/cm2
3 × 1012 n/cm2

∆Vth
16V
0
5V

gm
-25%
-15%

Ileak
1.4 pA
26 pA

Table 4.4: Results of DEPFET irradiations
be 283 krad(Si). For the neutron irradiation the fluence was 1.6 × 1011 n/cm2 with the energyof the neutrons ranging from 1 to 20 MeV. This is summarized in Table 4.4.
The IV characteristic of DEPFETs after these irradiations is shown in Fig. 4.18. This confirms
the shift of the threshold voltage observed after gamma irradiation. The increased subthresholdslope after ionizing radiation is due to the build-up of interface traps. Also the reduced transconductance of the proton irradiated sample suggests this interpretation. The expected higher levelof the low frequency noise is verified by the spectral analysis of the noise. The results confirm
the radiation damage models of MOS devices, which predict that neutron irradiation does notdegrade the subthreshold slope and has no influence on threshold voltage.

Figure 4.18: (a) Drain current-gain voltage characteristics of three DEPFETs before (solid lines)
and after (dashed lines) irradiation with 912 krad 60 Co (red), 1.2 × 1012 cm−2 30 MeV protons(green), and 1.6 × 1011 cm−2 1–20 MeV neutrons (blue). (b) Transconductance normalized to
W/L = 3 of the transistors before and after irradiation, using the same color code.
However, the bulk damage due to non-ionizing energy loss (NIEL) of neutrons and protons
increases the bulk generated leakage current flowing into the internal gate and hence the shotnoise of the device.
At SuperKEKB, the shot noise contribution will be proportional to the readout time of a complete matrix. The cell accumulates leakage current between two consecutive readouts. This will
97

CHAPTER 4. PIXEL DETECTOR (PXD)

Component
DCD
SWITCHER4
DHP
Optolink
DHH ASIC
Regulator

Process
UMC 180 nm
AMS 0.35 HV
IBM 90 nm

max
10 Mrad10 Mrad10 Mrad? Mrad? Mrad? MradDose
7.5 Mrad36 MradResultokokcomment
DSM CMOSDSM CMOS

Table 4.5: Irradiations of PXD electronics components
lead to an offset that can be corrected. However, the fluctuations of this contribution lead tonoise. For a readout cycle of 20 µs, the noise contribution would be 78 electrons for a NIEL
damage corresponding to a flux of 1013 n/cm2 .
4.5.2.1

Summary and Future R&D

We conclude from these results that the DEPFET, using a technology with thin oxides, isremarkably radiation tolerant beyond the doses expected at SuperKEKB. The threshold voltage
shift of only −3 V after 10 Mrad can be handled by a simple readjustment of the gate voltage
needed to switch on the DEPFET for readout. The shot noise due to leakage currents can becontrolled by the sensor temperature. Assuming a bulk leakage current of 4.9 × 10−11 A at room
temperature, corresponding to 1013 n/cm2 , a surface current of 1.2 × 10−11 A, the total noise,
including DEPFET channel noise and DCD noise, would reach 200 electrons (or a S/N of 20:1) at
a temperature of 27◦ C.1 As a next step, we plan to test various combinations of thin oxides andnitride layers to minimize the threshold voltage shift. In addition, we will perform irradiations
with low energy electrons, which are probably the dominant background at SuperKEKB.

4.5.3

Electronics

Similar to the DEPFET, the CMOS ASICs suffer from threshold voltage shifts. Fortunately,
due to the extremely thin oxides used in the deep submicron (DSM) CMOS processes used formost PXD ASICs, these shifts are very small and the ASICs turn out to be inherently radiation
tolerant [11, 12, 13]. The expected total ionizing dose at SuperKEKB does not challenge thecurrent deep sub-micron CMOS technologies as long as the designers use radiation hard layouts
for the transistors. An exception is the Belle II SWITCHER, which uses a 0.35 µm HV-CMOS
technology with rather thick oxides of the HV-transistors. The design therefore uses devices thatare based on thin oxides and uses enclosed structures and guard rings throughout. A prototypeof the Belle II SWITCHER, SWITCHER4, has been exposed to 36 Mrad with no observed
degradation.
An overview of the ASICs used for the PXD and the status of radiation tests is given in Table 4.5.
Another item is the tolerance against single event upset (SEU). Some protection is implemented
in the DHH:
1

The temperature dependence of the leakage current is


 2
Eg
Eg
T
−
exp
I(T ) = I0
T0
2kT0
2kT

(4.4)

where I0 is the current at reference temperature T0 (in Kelvins), T the operation temperature (in Kelvins), Eg
the band gap energy (1.1eV), and k the Boltzmann constant.

98

CHAPTER 4. PIXEL DETECTOR (PXD)• Configuration registers use triple redundancy with majority voting;• Data buffers have error detection and correction that is able to correct for one bit error in
a 32 bit word and detect two bit errors in a word;• The PLL is designed like the ATLAS FE-I4 chip [14], which is able to work in a much
more challenging environment than that of SuperKEKB.
The Switcher and DCD will use triple redundancy with majority voting for all configuration
bits. The SEU rate can be measured by reading back all three bits via JTAG.

4.5.4

Other Components

In principle, other components like glues or thermal grease may be subject to radiation damage.
Since members of our collaboration have experience with the construction of silicon detectors for
the LHC, the use of LHC grade materials is foreseen, thus ensuring sufficient radiation hardness.

4.6

Quality Control and Assurance

In the following section, general aspects of quality control via testing and pre-commissioning are
discussed, and the transition from wafer-level testing of matrices to pre-testing of ASICs to fullfunctionality testing is outlined. Finally, the ladder qualification and planned quality assurance
procedures are depicted.

4.6.1

Production quality characterization

4.6.1.1

Sensors

Production quality tests are done via static measurements of test structures that are homogeneously distributed over the wafer surface. Testing of the DEPFET matrices starts on the wafer
level via static measurements where the basic transistor characteristics are being measured.
Technology related defects of the matrices can be discovered this way and the structures preselected according to the static measurement results then undergo testing in a dynamic operation.
Static measurements will be done on the wafer level. A semiautomatic probe station is used
for static I/V and C/V measurements. The probe station is integrated into the semiconductor
parameterization system and the system allows the selection of structures of interest on thewafer and measurement of those in an automatic mode. Special devices designed for the characterization of the production quality assurance as well as small size matrices (128 × 16 pixels) canbe measured in this manner. Static measurement of full size module matrices can be performed
using a specially designed prober card.
4.6.1.2

ASICs

The final ASICs will be available by March 2011 and they will be subject to quality test using aprobe station. If problems are observed, there will be enough time for resubmission and retesting
without impact on the overall schedule.
Dedicated needle cards will be used to contact the I/O and power pads. The chips will be
designed in a way to allow testing of most important features using a minimal number of I/O
pads. For instance, in the case of the DCDB chip, only the pads at the outer pad-row will
be used: the JTAG pads, clock and synchronization input, eight output pads and a test signal
99

CHAPTER 4. PIXEL DETECTOR (PXD)

pad that allows emulating DEPFET input currents and testing of all analog channels without
contacted DEPFET matrix. A special needle card for the pads with bumps will be used. In thecase of the SWITCHERB chip, the clear and gate outputs of all 32 channels will be multiplexed
to a monitor pad that can be contacted by a needle card.
4.6.1.3

Belle II PXD ladders

Once the pixel layout is fixed and the final production of the Belle II PDX matrices is done, thematrices to be installed in the detector have to be selected. The static measurements will be
performed in the same way as planned for the prototype production. Since the steering and thereadout chips are to be bump-bonded onto the rim of the matrices, the characterization of thematrices as well as the chips has to be done independently so that pre-characterized chips will
be bump-bonded onto the selected matrices.

4.6.2

Dynamic tests

4.6.2.1

Sensors

Structures preselected according to the static measurements undergo testing in a dynamic operation. The test system for the DEPFET characterization has followed the evolution of the
DEPFET matrices from ILC-type to Belle II-type matrices.

Figure 4.19: View of the S3B system for testing the ILC matrices.
For the characterization of matrices for ILC applications, the S3B system was developed andmost of the measurements shown in this report have been obtained using this system (Fig. 4.19).
This system was made for the testing of the 64 × 128-pixel matrices with one CURO II readout
chip [15] and controlled by two SWITCHER III chips [15], one for the DEPFET gate control andthe second for the clear pulses. The matrix and the ASICs are housed on a PCB board or hybrid,
where the output current of the CURO is converted into a voltage signal by an external low noise
and fast transimpedance amplifier. The hybrid is connected to a second board where the voltage
signal from the hybrid is digitized by a 14-bit ADC and stored in SRAM cells for a subsequent
readout. This board contains a SPARTAN 3 FPGA that is in charge of the slow control andreadout of the chips, the timing, and the data transfer to the PC via USB. Special multi-channel
power supplies have been built to conveniently provide all voltages. LEMO connectors are used100

CHAPTER 4. PIXEL DETECTOR (PXD)

to trigger the system and to interface to the data acquisition during the beam tests. Everythingis housed in a compact metal frame with standardized supports to simplify alignment in the test
beam.
An intermediate setup is being developed for testing the Belle II prototype matrices of the
PXD6 production. This test system is schematically shown in Fig. 4.20. For the operation ofstandard 128 × 16-pixel matrices, one SWITCHER-B chip (SWB) for gate and clear control andone DCD-B and a DCDRO chip2 for the readout is used. (A description of the chips is given
in Sec. 4.3.) The matrix is bonded on a separate ceramic carrier accommodated with a pin
connector. An adapter board is designed to accommodate conversion from bump-bonded chips(SWB, DCDB and DCDRO) to wire-bonded matrices. The hybrid is connected to a readoutboard via a flat band cable. This board contains the drivers for the SWB, the memory, and a
VIRTEX4 FPGA to generate all timing and control signals. The data transfer to a PC is done
via a single USB2.0 link. A multi-pin connector is used to feed all required supply voltages.

Figure 4.20: Schematics of the planned test system for the PXD6 matrix qualification.
This system allows simple and fast exchange of small prototype matrices due to its modular
design. For testing of the half modules, adapter boards are not required since the design isintended for bump-bonded steering and readout chips. The same FPGA board or DHP chip
(Sec. 4.3) can be used for the readout of the signals from the modules.
Final testing of the ladders for the Belle II PXD detector will be performed using the final
versions of the SWB, DCDB, DHP, and DHH chips. The full DEPFET matrix characterizationis performed combining the source and the laser scan results.
4.6.2.1.1 Source tests A number of tests are necessary to characterize the DEPFET module in terms of noise, gain, etc. For an absolute measurement of the noise and gq , spectrausing a number of radioactive sources are measured (Fig. 4.21, left). The measurements areusually performed using 55 Fe, 109 Cd, and 133 Ba irradiation. A typical value measured from suchmeasurements for a thick matrix is gq = 0.280 nA/e− . This value is smaller than that usuallyobtained from measurements on single DEPFETs and small arrays with 55 Fe irradiation. Thiseffect is understood and is due to the incomplete clear process in the used test system. The
system noise was measured to be 15 ADC units for the S3B system, which corresponds to 90 nA.
As explained in Sec. 4.3, the performance of the new readout chip and steering chip should leadto an improved S/N ratio.
4.6.2.1.2 Laser tests Laser tests are done to study inhomogeneities of the matrix response
and can be performed nowadays at several collaboration institutes using laser systems with different wavelengths: 682 nm, 810 nm, and 1055 nm. The laser is triggered either by an internally2

As the DCDB has non-standard low swing single ended signal outputs, it cannot be connected directly to an
FPGA. To be able to test the chip without the foreseen DHP, the DCDRO support chip has been designed toconvert the signals to the LVDS standard.

101

CHAPTER 4. PIXEL DETECTOR (PXD)

generated signal in the S3B board or by an external pulse generator that triggers both the laser
and the acquisition system. The laser spot is focused on the matrix backplane with spot sizes
which vary, depending on the setup, from 2.5 µm to 5 µm. The DEPFET module is mounted ona motor-controlled xy-stage with steps of the order of 1 µm, allowing a full scan of the matrix
surface so that the charge collection mechanism can be studied. Figure 4.21 (right) shows anexample of the variations of the pixel signal across the matrix. Variations of about ±5% between
the mean cluster signals can be observed. The reasons for these variations in pixel gain are not

Figure 4.21: Left: Hit map for an ILC-type matrix during the source testing. The CURO chip
is located at the bottom. Right: Result of a laser scan over an ILC-type matrix, using thecommon-mode correction method. The 5 × 5 cluster signal is plotted versus the laser position(x, y). Steps are 3 µm in both directions. The CURO readout chip is located on the right side
(readout direction from left to right).
fully understood and are under investigation. Even so, they can be corrected in the analysis andtherefore pose no harm to the final performance of the detector.
4.6.2.2

Belle II PXD ladders

To perform a functionality test of the ladder, a sensor probing with the probe card is planned.
All contacts are provided via needle contacts placed onto the bump-bond pads, and the steeringof the matrix is performed via an external instrument. In this way, a full functionality test
can be done. The results of these scans can be used for the selection of the matrices for theladder construction. Bump-bonding of the chips is done sequentially with a functionality test
performed after every bonded chip. Once all the chips are in place and the flex cable connected,
the final characterization of the ladder performance occurs, using both source and laser tests.

4.6.3

Belle II PXD commissioning

Once all the pre-tests are performed and the selection of ladders to be used in the detector
is made, the ladders are mounted onto the support structure and the final commissioning is
performed using source. The source positioning tube through which the source is moved in thedefined way is placed around the PXD so that the performance of all ladders in their mountpositions can be studied. All components of the PXD system (cooling system, power supplies
and DAQ) are commissioned at this stage.

102

CHAPTER 4. PIXEL DETECTOR (PXD)

Once the detector has passed all tests, it will be disassembled and the individual ladders will
be shipped to KEK. Final commissioning of the reassembled detector will happened there. Pretesting of the individual ladders with the source irradiation is planned to check the functionalityof the ladders at KEK before final assembly. Additional tests are planned once the ladders
are mounted onto the supporting structure for the integration in the Belle II. Finally, the fullsystem test will be repeated once the detector is in place. After the test of the full Belle II PXD
detector, its commissioning together with the rest of the Belle II detector will take place.

4.6.4

Production Yield

From past experience with devices of similar size and complexity (for high energy physics andastrophysical applications) we conservatively expect a yield for the DEPFET production of 50%.
In similar semiconductor devices, the HLL MPI routinely obtains a better than 80% yield. The
expected yield of the flip chipping is high due to the relaxed pitch of the ASICs. The yieldfor the full ladder assembly is also assumed to be 50% (again conservative: for the ATLAS
pixel detector a yield of 90% was reached in the assembly procedure). In total, we count on ayield of working ladders of better than 25%. With this yield, we will produce 40 complete andfunctioning ladders (20 are needed for the PXD detector).

4.7

Data Acquisition and Slow Control

4.7.1

Overview

SWITCHER

DCD
DHP

The architecture of the PXD readout system is shown in Fig. 4.22. The patch panel is aninterface adapter card between the Kapton flex cable (≃ 20 cm length) and the differential cable(≃ 10 m length, probably LVDS). The DHH is described in Sec. 4.7.2 and the Compute Nodein Sec. 4.7.4.

FLEX Cable
Patch
Panel

LVDS Cable

Compute Node
Optical Links
DHH
Event Builder PC Farm 

ATCA

Gigabit Ethernet
FPGAs

Figure 4.22: Architecture of the PXD readout system.
103

CHAPTER 4. PIXEL DETECTOR (PXD)

4.7.2

Data Transmission - Patch Panel and Data Handling Hybrid (DHH)

The Data Transmission System is the interface of the DEPFET modules to the outside world,
i.e., power supplies and DAQ system. Each half ladder will be connected via the Kapton flex
to a small Patch Panel (PP) that, in turn, connects to the Data Handling Hybrid (DHH). The
PP will be located very close to the modules to keep the Kapton flex cable as short as possible(20 cm); this minimizes the degradation of the fast output signals from the DHP. The PP is thecable adapter for the fast signals from the DHP (4 signals with 1.25 Gbit/s). In addition, thePP performs power filtering, impedance matching and possibly over-voltage protection. Signals
and power will then be routed via shielded twisted pair copper cables to the DHH located in
the docks (or perhaps outside the detector). The DHH is connected via optical links to theCompute Nodes, to the PXD power supplies, and to the Belle II GDL (Global Decision Logic)
trigger and master clock. Its main components are an FPGA and Finisar optical transceivers.
The tasks of the DHH are the following:• generate the DHP system clock from the Belle II clock distribution system,• receive the four fast signals coming from the DHP in an AURORA Gbit link receiver,• multiplex the four DHP outputs per half-ladder to one optical link (5 Gbit/s),• provide a JTAG master for the slow control of the DHP,
• send the slow control data to the Compute Nodes via the optical link,• decode slow control commands from the external Belle II slow control panel, and• regulate the voltage.

4.7.3

Data Rate Estimate

For the following estimate, we assume a trigger rate of 30 kHz, corresponding to the highest
luminosity of L=0.8×1035 cm−2 s−1 . For an estimate of the required PXD readout data rate,
we assume 40 PXD half ladders with 250 × 800 (or 0.2 × 106 ) pixels each and 8 × 106 pixels in
total. The average cluster size is expected to be 2 pixels. Given a readout time of 20 µs, theaverage occupancy is ≃ 1%, corresponding to ≃ 8 × 104 fired pixels per frame. This occupancy
still does not take into account any background. For a frame rate of 50 kHz and a trigger
rate of 30 kHz, the expected reduction factor on the DHH can be calculated using Poisson
statistics to a factor of 2.2. This amounts to a fired-pixel rate of ≃ 1.8 × 109 Hz. Multiplying
by a data size of 4 bytes per pixel for the encoded position and ADC charge information, we
estimate a total data rate of ≃ 58 GBit/s for the complete PXD. With 40 optical links, this
implies ≃ 1.44 GBit/s (or ≃ 180 MByte/s) per optical link. However, there will be a significant
contribution to the occupancy by radiative QED events of the type e+ e− →e+ e− γ, beam gas
events, synchrotron radiation from the upstream and downstream dipoles, and the Touschek
effect. For the background, we take into account a factor of three safety margin, i.e., the system
will be prepared to cope with a maximum occupancy of 3%. If the background increases theoccupancy to values above 3%, PXD subevents will have to be truncated. Precise track vertex
reconstruction in events with such high occupancy degrades in any case because of too highcombinatorics and subsequently an increased fraction of wrong PXD hit-to-track assignments.

104

CHAPTER 4. PIXEL DETECTOR (PXD)

4.7.4

Readout System

The hardware platform for the PXD readout is the Compute Node (CN) and is shown in
Fig. 4.23 (left side). The 14-layer printed circuit board has been developed by IHEP Beijing
and the II. Physics Department of Giessen University. Each CN has five XILINX Virtex-4 FX60 FPGAs, chosen for their high computing performance and their links for high bandwidth
data transfer (RocketIO). Fig. 4.24 shows the schematic block diagram of the Compute Node.
On each board, all FPGAs are interconnected by point-to-point links (see below for details)
for event building. The programming of the FPGAs in VHDL is being done using XILINXISE (Integrated Software Environment) Vers. 10.1 framework. Each Virtex-4 FX60 FPGA has
two 300 MHz PowerPCs implemented as core; these are used for slow control purposes but
not for algorithms. In the current design, the PowerPCs run Linux 2.6.27. In addition, each
FPGA has 2 GB of DDR2 memory attached. The CN is designed as a board of the ATCA
(Advanced Telecommunications Computing Architecture) standard. The ATCA shelf is shownin Fig. 4.23 (right side). In an ATCA shelf with a full mesh backplane, point-to-point pairwise
connections between CNs are wired. This avoids any bus arbitration. In addition to the highcomputing performance, the CN also provide high bandwidth interconnections. (a) All five
FPGAs are connected pairwise (on the board) by one 32-bit general purpose bus (GPIO) and
one full duplex RocketIO link. (b) Four of the five FPGAs have two RocketIO links routed to
the front panel using Multi-Gigabit Transceivers (MGT) for optical links. (c) One of the five
FPGAs serves as a router and has 16 RocketIO links through the full mesh backplane to all theother compute nodes in the same ATCA shelf. (d) All five FPGAs have a Gigabit Ethernet Link
routed to the front panel. With the current design, the input bandwidth in one ATCA crate is≤ 35 GBit/s (14 CN, eight optical links each, operating at ≤ 2.5 Gbit/s). The slow control tasks(e.g., power negotiation) between the CN and the ATCA shelf are based upon IPMI (Intelligent
Platform Management Interface), implemented by an ATMEL ATmega2560 micro-controller on
a CN add-on card that was developed at Giessen.

Figure 4.23: Left: Photo of a Compute Node (CN) prototype. Right: Photo of an ATCA Shelf.
The performance of the compute nodes was measured in several tests:• Concerning the data input of the compute nodes, the RocketIO transmission over the optical links were operated stably in long term tests at a sustained data rate of ≃ 1.6 GBit/s,
105

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.24: Schematic block diagram of the Compute Node.
limited by the usage of the SFP transceivers. For the PXD readout, the compute nodes will
be upgraded to SFP+ transceivers, allowing to operate at the full RocketIO transmission
rate of up to 6.5 Gbit/s.
• Concerning the data output of the compute nodes, the gigabit ethernet was tested by using
the PowerPC405, which is embedded on the Virtex-4 FPGA. Data rates of ≃ 212 Gbit/s(≃ 26.5 MByte/s) from PowerPC to PC and ≃ 241 Gbit/s (≃ 30.1 MByte/s) from PC
to PowerPC were achieved. For the final readout system, the FPGA, not the PowerPC,will be used for the gigabit ethernet transmission. This requires implementation of the
UDP transmission protocols in VHDL. Tests by XILINX indicate that data rates of ≥100 MByte/s are reachable.
• As a complete system test, a readout chain for one readout channel in the sequence
data transmitter → optical link → FPGA → write to RAM → read from RAM→ gigabit ethernet → PC
was tested. For this purpose, pseudo-random data were generated on the transmitter side
and checked by a logic analyzer program on the PC. No bit error was observed during along-term test of ≃ 150 hour duration.

4.7.5

Data Reduction

The high data rate of ≃ 2.4 Gbit/s (≃ 300 MByte/s) per optical link must be reduced by abouta factor of ≃ 10 to match the gigabit ethernet bandwidth from the compute nodes to the event
builder farm and to avoid saturation of the event builder. There are at least two options for thedata reduction: First, a track finder and track fitter using the PXD and the SVD raw data will106

CHAPTER 4. PIXEL DETECTOR (PXD)

be programmed in VHDL on the Virtex-4 FPGAs. Second, the compute nodes will buffer PXD
events and wait for fitted tracks, provided by the HLT (High Level Trigger). In both options,the fitted tracks are extrapolated to the PXD modules, and hits that are not matched to any
track (generated by QED, beam-gas background, or synchrotron radiation) are discarded.
In the reduction of the raw PXD data stream by a factor of ≃ 10, data of physics interest should
be kept and only background-induced data should be discarded. Since the PXD has only twolayers, the distinction between physics and background hits relies on the extrapolation of tracks
reconstructed in the relatively quiet SVD through the PXD. Using the data from the SVD alone,a fast track finding procedure is performed. These tracks are then propagated back through the
PXD ladders. Around each intersection point of a track with a PXD ladder, a region of interest(“ROI”) in the plane of the ladder is defined. If a fired PXD pixel lies inside an ROI, it is kept;
otherwise, it is discarded.

Figure 4.25: Track-finding efficiency of the Hough transform algorithm in r–z space, based only
on the SVD information. From the tracks found, the ROIs for the PXD are constructed.
Since the SVD-only track finding has to be done early in the DAQ chain, it has to be very
fast; therefore, advanced track finding algorithms cannot be applied. In particular, a full threedimensional track finding procedure is too costly. Instead, the SVD hits are projected into r–z
space, where z is the axial coordinate of the hit and r is its distance from the z-axis. Twotypes of tracks are handled by this data reduction method: straight tracks (for particles above atunable momentum cutoff) and helical tracks (for particles below the cutoff). Straight (helical)
tracks appear then as straight lines (sine curves) in r–z space. Tests show that a reasonable
cutoff parameters is 1 GeV.
The Hough transform technique finds the tracks in r–z space. It determines the parameters of the
tracks by transforming each hit from r–z space to a two dimensional parameter space. Dependingon the track type, each SVD hit is represented by a line or a sine curve in the parameter space.
107

CHAPTER 4. PIXEL DETECTOR (PXD)

SVD hits originating from a common track are then given by the intersection of their lines/sine
curves in the parameter space. A robust method of determining these intersections is given by aspace subdivision scheme. It recursively subdivides the parameter space in smaller areas, yielding
as final output areas containing the intersections and therefore the final track parameters. Fromthese parameters, the ROIs on the PXD ladders can be calculated by transforming the Houghtransform parameters back to the track representation in r–z space. The resulting ROIs appear
in a PXD layer as complete rings in r–φ with a finite width along z. A preliminary estimateof the track-finding efficiency of the Hough algorithm is shown in Fig. 4.25. One can see thatexcellent efficiency is obtained down to very low momenta. High efficiency is essential, since all
PXD hits are removed that are not located in a ROI defined by the tracks found by the Houghalgorithm.
The data reduction factor can be improved by introducing an additional subdivision of the r–φ
plane into wedge-shaped sectors. Such a subdivision is very well suited to the parallelization of
the ROI-finding computations. Two types of sectors are considered: sectors with straight edges(for energetic particles) and with curved edges (for soft particles). An arbitrary combination of
sector types is possible to optimize the track finding efficiency. Since each sector only covers asmall part of the PXD, ring-like ROIs are avoided, resulting in a better data reduction factor.
First tests show that a reduction factor of 15-20 is achievable with this refinement.

4.7.6

Backup Solution of the PXD Readout System

In the baseline option of the PXD readout, the CN receives data from the SVD and performs
ROI-finding in the FPGA equipped on it. This approach is well suited to separate PXD readoutfrom other sub-systems as well as possible, which consequently results in a good scalability ofthe system. However, this option requires (1) a signal branching system of SVD to the mainstream and to the PXD, and (2) partial event building system of the branched signal to match
to the number of CN inputs (40). The option also requires special skill to develop and maintainthe FPGA codes for the ROI-finding.
As an fallback solution, we investigate a backup option for the ROI-finding by the FPGA with ahigh level trigger farm (HLT) consisting of O(10) units of PC farms. In this backup option, the
HLT runs the software for the ROI-finding. Figure 4.26 shows the comparison of the baseline
and the backup option.
In case of the backup option, we need to consider a latency for the HLT decision. According toour experience in Belle, the online track reconstruction on one Intel Xeon 2 × 3.4 GHz PC takes
typically less then 1 second and up to 10 seconds for harsh events. Accounting for CPU power
evolution, we expect ∼ 5 seconds for the HLT latency at most. In addition, the few PXD events
that can not be processed within 5 seconds will be accepted by default, and their full data will
be stored.
We have two sub-options for the backup option. In the following subsections, we describe eachof them. A final decision for the choice of the readout system will be made in spring 2011
based upon prototype results, in order to provide sufficient time for any required hardware
development.
4.7.6.1

ATCA-based readout system with HLT

As well as the main option, this sub-option employs the ATCA boards to read out the PXD.
The data from the PXD is read by 40 ATCA boards, which are housed in an ATCA crate. Each
ATCA board is connected to each DHH and receives data from the DHH over the RocketIO
link. The ATCA board has an Ethernet (or GbE) port to communicate with the HLT about108

CHAPTER 4. PIXEL DETECTOR (PXD)

Baseline option

Backup option

DHH #1

DHH #1
DHH #2...

PXD R/O

PXD

ROI-finding information

PXD R/O

ROI-finding information

CDC

COPPER

R/O PC

COPPER

R/O PCswitch

SVD

COPPER

R/O PCCDC

COPPER

R/O PC

COPPER

R/O PC

Higher Level Trigger

R/O PC

Higher Level Trigger

COPPER

Event builder #1

SVD

switchEvent builder #1

ROI-finding

Figure 4.26: Block diagrams of the baseline and backup options of the ROI-finding scheme.
the HLT decision. For this sub-option, the ATCA readout system needs to hold PXD data forup to 5-second HLT latency, which corresponds to 3–5 GB at most per node. There exist twosolutions for this: the first is to redesign the CN to equip the large memory, and the second isto purchase and install a commercially available memory unit of ATCA. At this stage, the firstsolution seems more feasible.
4.7.6.2

PC-based readout system with HLT

In this sub-option, the DHH outputs the data to a PC over the RocketIO link instead of the
ATCA board. An internal block diagram of the PXD-readout PC is shown in Figure 4.27. To
accommodate the 600 MB/s rate of the RocketIO input, the internal link of the PC between the
RocketIO interface and the processor should be larger than this throughput. The PCI-express(PCIe) allows 5 Gbps data transfer per link. Two or more PCIe links can be occupied by a single
PCIe card to multiply the data transfer speed. There are commercially available PC mainboards
with PCIe slots connected to 8-fold PCIe links, which enable 40 Gbps per slot in total. As for
the HLT latency, the PC can house physical memory of O(10) GB at a reasonable price. The
ROI-finding information is given to the PC from the HLT over the GbE. Data size reduction is
performed by the processor in the PC. The reduction can be realized in software, which is anadvantage of this sub-option from the viewpoint of the development cost and maintainability.
The PXD data are integrated by 40 PXD-readout PCs in total. All output from the PXDreadout PCs are transferred to the second level event builder.
A critical path of this sub-option is the development of the RocketIO card on the PCIe. Tokyo
Electron Device Ltd. provides an evaluation board of Virtex5 on the PCIe with optical link connectors [16]. The board provides 3 Gbps RocketIO link with firmware and interfacing firmware
to the PCIe. The design of our own RocketIO PCIe card with much higher link speed, using
this board as a reference, is an option.
One of the differences between the ATCA-based and the PC-based system is the different handling of the interrupts that are generated at the end of data transfers of the small incoming data
packages (≤100 kBytes). DMA of large data blocks is not an option because of non-implemented
large scale buffer on the DHH. The handling of these interrupts in the operating system of thePCs could lead to a quite high load on the processors. In the ATCA-based system, there is nooperating system, so this problem is nonexistent. A prototype system of the PC-based approach

109

Event builder

DHH #40

Event builder

DHH #40...

DHH #2PXD

CHAPTER 4. PIXEL DETECTOR (PXD)

DHH

RocketIO

processor

x8 PCIe

memoryx8 PCIe

IOH
x8 PCIe

HLT

GbE

PC

GbE

EB

Figure 4.27: The internal block diagram of the PXD-readout PC.
will provide measurements of the CPU load.
4.7.6.3

Communication with the HLT

Figure 4.28 shows data stream and communication diagram between the PXD-readout systemand the HLT.
Event records stored in the ATCA/PC memory are sorted by event number since they directly
come from the DHH. On the other hand, the HLT outputs are not sorted, since the time tomake ROI-decision by the HLT varies event-by-event. Because the event building system, which
receives data from the ATCAs/PCs, does not expect event records disordered, the outputs fromthe ATCA/PC should be sorted by event number. To sort the HLT decision by event number,
we install a ‘sorter PC’ at the final output of the HLT.
In the following, we describe successful operation and faulty operations.
• SuccessIf the HLT decision is made within the predefined HLT latency (∼ 5 seconds), the HLTdecision packet (an example is shown in Figure 4.29) is broadcast to all of ATCAs/PCs.
• Fault (event recored expiration in the sorter PC)
After the sorter PC broadcasts the n-th HLT decision successfully, the sorter PC waits forthe (n + 1)-th HLT decision. If the (n + 1)-th decision does not arrive within the HLTlatency, the sorter PC generates a special packet of the HLT decision to assume all dataas the ROI. This action will take place irrespective of the arrival of (n + 2)-th event. If
the (n + 1)-th HLT decision comes later, that decision is discarded.
• Fault (event record expiration in the ATCA/PC)
After the ATCA/PC sends out the n-th event record to the event building system successfully, the ATCA/PC waits for the (n + 1)-th HLT decision from the sorter PC. If the(n + 1)-th decision does not arrive within the HLT latency, the ATCA/PC will send theevent record to the event building system without any data size reduction. If the (n+1)-th
HLT decision comes later, that decision is discarded.
Figure 4.29 shows an example packet of the HLT decision to be broadcast to the ATCAs/PCs
from the sorter PC.

110

CHAPTER 4. PIXEL DETECTOR (PXD)

to EB

Ev#01

Ev#02

...

Ev#03

ATCA/PC#01
Ev#04

DHH#01

to EB

Ev#01

Ev#02

Ev#03

...

Ev#04

ATCA/PC#02

DHH#02

to EB

Ev#01

Ev#02

Ev#03

...

Ev#04

ATCA/PC#40

DHH#40

Network SW

HLT#02

...

Ev#02

Ev#06

HLT#10
Ev#03

HLT#09Sorter PC

Ev#01

HLT#01Figure 4.28: The data stream and communication diagram between the PXD-readout systemand the HLT.

4.8

Mechanical Support and Cooling

The mechanical structure of the PXD strongly depends on the geometry of the beamline. Since
the design of the interaction region and the beampipe for the nano-beam option is still evolving,
the PXD mechanical design has to accommodate (among other things) geometric changes in thelength of the straight part of the beampipe as well as the location and diameter of flanges thatserve as anchor points for the PXD. Therefore, the numbers given here are subject to change.
A very important parameter still under discussion is the angle of the beamline with respect
to the axis of the Belle II solenoid. In case this angle is not zero, the PXD loses its cylindrical symmetry because it has to cover the specified acceptance region. As a consequence, themechanical construction becomes more complicated and, concurrently, the active area of thedetector modules needs to be longer. On the other hand, the most important parameter for
the PXD mechanical design—the radius of the beamline at the interaction point—has settled
to a stable value (rinner = 10 mm). This means that a close-to-final mechanical design can be111

CHAPTER 4. PIXEL DETECTOR (PXD)

Grand header / event ID
DHH#01 header / word count
Extract region [000] xxx ... yyy
Extract region [001] xxx ... yyy
Extract region [002] xxx ... yyy
DHH#02 header / word count
Extract region [000] xxx ... yyy...

Extract region [001] xxx ... yyy

DHH#40 header / word cound
Extract region [000] xxx ... yyy
Extract region [001] xxx ... yyy
Extract region [002] xxx ... yyy
Grand trailer / checksum

Figure 4.29: The data stream and communication diagram between the PXD-readout systemand the HLT.
developed while keeping in mind that minor changes will surely be made as the IR design isfinalized. The dimensions of the mechanical support structure for the case that the beampipe
is parallel to the Belle II solenoid is shown in Fig. 4.30.

Figure 4.30: Overview of the detector layout.

4.8.1

General Concept

The PXD is a barrel-only system consisting of two cylindrical active detector layers coaxial withthe beam line (Fig. 4.1). These layers consist of eight or twelve detector modules which overlap
in φ in such a way that the insensitive balcony area in one module is covered by the sensitive
pixel area of the neighboring module. The overall coverage is nearly 100% within the acceptanceangle. In situ geometric alignment is done continuously using high-pt tracks that pass throughthe overlap region.
112

CHAPTER 4. PIXEL DETECTOR (PXD)

The inner layer is placed as close to the beamline as possible at r = 13 mm. The outer layer is
at a radius of r = 22 mm. The envisaged spatial resolution is ≈ 10 µm. The support structure
must be robust enough to prevent short-term spatial movement of the mounted PXD, but does
not need an absolute mounting precision of better than ≈ 0.1 mm because continuous position
calibration and monitoring will be achieved with energetic charged tracks.
An online alignment system for each module is considered to be unnecessary even though amonitoring of the position of the support structure with respect to the neighboring silicon strip
detector system is highly desirable. A system based on fiber Bragg gratings is under study.

4.8.2

Detector Modules

The detector modules consist mainly of the DEPFET silicon sensor (thickness of 400 µm) withintegrated electrical lines and pitch adaptors. All necessary chips to operate the DEPFET(switcher chips, digitizers and data processors) are bump-bonded to the wafer surface. The
sensor is thinned to 75 µm for the full sensitive area (Sec. 4.4). Only the end sections of thesensor that are outside the acceptance region exhibit the full thickness for reasons of rigidityand bondability. Each module consists of two half-modules that are connected with a joint pieceof silicon material glued to the bottom side of the module.

X/X0

Material budget studies - Belle II PXD
0.014
PXD - active + passive Si (rims, switchers)

0.012
PXD - active Si (sensors)

0.01
0.008
0.006
0.004
0.002
0
-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8
1
cos(θ)

Figure 4.31: Distribution of expected material as a function of cos(θ).

layer
1
2

radius13
22

wafer size (mm)length width
131
15
174
15

sensitive region (mm)length
width
90
12.5
123.45
12.5

no. of pixels
in z in φ
1600 250
1600 250

pixel pitch (µm)
in z
in φ
56
50
77
50

Table 4.6: PXD module parameters
In the baseline mechanical design, we attach the silicon wafers directly to the support structure,using either screws or clamps. The necessary holes in the wafer are produced by laser cutting.
Since this is a rather challenging approach, a fall-back solution is under study, wherein extension
113

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.32: (a) 3D view into the PXD detector with the integrated support and cooling structure, including the Kapton cables to the outside services. (b) View along the beampipe. (c)Detail of the support structure holding the sensors.

114

CHAPTER 4. PIXEL DETECTOR (PXD)

bars of CVD-diamond (0.4 × 7 × 30 mm3 ) are glued at both ends to the backside of the modules.
These bars are clamped to the support structure with springs.
Table 4.6 shows the main parameters of the modules. Figure 4.31 shows the amount of material
as a function of cos θ.
Electrical connections are realized with triple-layer Kapton cables, glued and wire-bonded atboth ends of the module. These cables emerge from the detector volume along the beamline(Fig. 4.32).

4.8.3

Support Structure

The support structure (Fig. 4.32) is a formidable engineering challenge. Since it must also serveas the heat sink for the detector modules, it has an integrated cooling channel that can carryevaporative CO2 as the coolant, delivering cooling capacity as close as possible to the power
dissipating chips. The many holes in the material result in suboptimal heat transport, but they
are necessary to enable the flow of cold air between the two sensor layers (Fig. 4.32 b). The
ratio between hole sizes and heat-conducting material is still being optimized. Copper is usedrather than aluminum because of its better thermal conduction and expansion coefficient.
The support structure itself is mounted to the structural parts of the beam pipe far from theinteraction point. The two end rings are not identical due to the asymmetry of the Belle IIacceptance. The support structure is designed as two half shells that are clamped together
during the installation of the detector to allow the mounting on the assembled beam pipe. The
two mechanically independent half shells are completely assembled prior to installation.
The detector modules are fixed to grooves in the support structure by springs. Precision holes
in the wafers and pins on the support structure on one side provide the required mechanicalaccuracy. On the other detector side, long holes in the wafers that can slide on pins on the
support structure enable the system to yield to thermal movements. The pressure applied by
the fixation springs is adjusted to provide the best possible thermal coupling of the modules
to the support structure while allowing thermal expansion and contraction without mechanicaldeformations. Due to the small coefficient of thermal expansion of 2.0 × 10−6 K−1 for silicon, theexpected contraction will be ≈ 50 µm when the temperature is lowered from room temperature
to the operating temperature of slightly below 0◦ C. On the other hand, when the electrical
power of the DEPFET system is turned on, the thermal expansion will be of ≈ 100 µm.
In parallel, we are evaluating an alternative solution wherein both sides of the silicon wafer are
fixed with screws and the whole support structure yields to thermal expansion.

4.8.4

The cooling concept

The cooling of the PXD system must balance the conflicting demands of robust heat dissipation
with a minimal material budget (driven by the desire for a small multiple Coulomb scattering
contribution to the charged-track vertex resolution).
• The thermal power of the PXD system amounts to a total of 360 W. The twenty detector
modules contribute with 18 W each: There are four DCD chips and four DHP chips oneach side of the module; each chip dissipates about 1 W. The DEPFET itself produces
about 1 W distributed homogeneously over the whole area. The switcher chips on thebalcony are turned off for most of the time and contribute only moderately to the heatproduction (1 W on average) (Fig. 4.33).
• The beampipe as the central part within the cylindrical pixel volume has its own coolingsystem and will probably be kept at a temperature slightly above the dew point.
115

CHAPTER 4. PIXEL DETECTOR (PXD)• There is limited available space in the innermost region of Belle II for services, tubing, etc.
• One boundary condition stems from the detector properties: the temperature of the siliconsensor should not exceed 30◦ C while the chip’s temperature should be kept below 60◦ C
to prevent electromigration.
• For simplicity and to economize on space, a common cold dry volume for both the PXDand SVD is under study. In this design, the forced convection, which is needed to cool
down the center of the ladders, is provided for both detector systems, and temperatures
below the external dew point can be operated inside this volume.

Figure 4.33: Parameters for the simulation studies. The color code shows the temperature
distribution along the ladder as a result from a finite-element simulation with a set of reasonableboundary conditions.
In our present design, the thermal power of the DEPFET sensor is dissipated by heat conduction
through the silicon material itself, supported by a moderate cold air flow (≈ −5◦ C at a speedof ≈ 1 m/s) through the full tracker volume. The thermal power produced by the readout chips
is absorbed from the support structure, which acts as a heat sink.

4.8.5

Cooling simulations and tests

The main feature of the design is the absence of any cooling-related material within the acceptance region. To verify its validity, detailed thermal simulation studies have been performed.
The full complexity of the pixel system, however, exceeds the available computing power, so
single modules have been simulated. The expected power consumption of the chips is shown in
Fig. 4.33.
The thermal models are validated with experimental studies in which the heat generation sources
are simulated with resistors and heat foils glued on silicon. These measurements give confidence
in the reliability of the simulations. Figure 4.34 shows the good agreement of simulation andexperiment.

116

CHAPTER 4. PIXEL DETECTOR (PXD)

50
simulation45

measurements40

T [°C]

35
30
25
20
15
10
5
0

20

40

60
y [mm]

80

100

120

Figure 4.34: Comparison of simulated and measured data. The diagram shows the temperature
profile along the middle axis of a DEPFET module with 2 mm CVD extension on both sides.
The ambient temperature is 20◦ C, the support structure is kept at −10◦ C.

4.9Interface to Belle II

The PXD needs the following services from the outside:• Supply voltages for the DEPFET sensors, the readout and control ASICs and auxiliaryelectronics in the DHH;
• Digital data I/O for configuration and readout, clock signals, trigger signals and readout
protocol (electrical);• Optical fibers for the readout;• Pipes for the liquid coolant;• Pipes for the air coolant.
Since the space in the IR region is very limited, only very thin cables are allowed close to thedetector. It is therefore foreseen to bring the thick power and optical IO fibers only up to a
distance of 2m from the PXD to the data handling hybrid (Sec. 4.7.2). From there, thin power
cables and thin twisted pair cables for the digital I/O go to a patch panel. From there, flat
Kapton cables are used for the last 20–50 cm. If possible, the patch panel should house only
passive components for impedance matching and overvoltage protection. These services will be
described in more detail in the following sections.

4.9.1

Kapton Links

Each module is serviced with a custom made Kapton cable connecting the ladder to a patch
panel. The Kapton cable is fixed on the module (glued and wire bonded). The cable has to bepre-shaped to follow the complicated geometry through the support structure. To fit throughthe gaps in the support structure and on the available space on the module, its width is limited
to 7 mm. The large number of electrical lines needed requires a three-layer tape. The total
length is limited by the production process (lithography) and the damping of the HF signals toapproximately 50 cm.
117

CHAPTER 4. PIXEL DETECTOR (PXD)

Nr
0
0.1
0.1.1
0.2
0.2.1
1
1.1
1.1.1
1.2
1.2.1
1.3
1.4
2
2.1
2.1.1
2.2
2.2.1
2.3
2.3.1
2.4
2.5
2.5.1
2.6
2.6.1
3
3.1
3.1.1
3.2
4
4.1
4.1.1
4.2
4.3
4.3
4.4

short namecommonDVDD 1.8
sDVDD 1.8
DGND
sDGND
DCD
AVDD DCDsAVDD DCD
AGND DCDsAGND DCD
REFIN DCD
AmpLow
SW
DVDD SW
sDVDD SW
CLEAR on SW
sCLEAR on
CLEAR off SW
sCLEAR off
sub
GATE on SW
sGATE onGATE off SW
sGATE off
DHP
DVDD DHPCOREsDVDD DHP
DVDD DHPGP
DEPFET
VSOURCEsVSOURCE
VCCG
VBULK
VBP
VGUARD

namecommon digital power
DVDD DCD, JTAG SW, DVDD IO, DHP
sense DVDD 1.8
comon digital ground
sense DGND
DCD power
DCD analog supply
sense line AVDD DCD
DCD analog ground
sense line AGND DCD
referance of memory cell
analog ground for amplifierswitcher powerswitcher digital supply
sense of DVDD SW
clear onsense line of CLEAR on
clear off
sense line of clear off
substrate
gate onsense line of gate ongate off
sense line of gate off
DHP power
DHP digital supply
sense of DVDD DHPCORE
supply for gigabit link
DEPFET sensor
sourcesense line of sourcecommon clear gate
bulk
back planeguard ring
Table 4.7: Power lines per module

118

V

Imax

1.8V

1A

0

1.4A

1.8V

2.3A

-

0

-2.3A

-

1.1V
0.35V

200 mA-1.52A

-

3.3V

4mA

17V

27mA

?
-

8V

-27mA

-

lowest4V

27mA

local?
-

13V

27mA

-

1V

500mA?

-

1.2V
7V
7V
17V
-20V

100mA

comment

CHAPTER 4. PIXEL DETECTOR (PXD)

Nr
1
2
3
4
5
6
7
8
9

short name
GCK
FCK
TRG
TMS
TCK
TDI
TDO
RST
DO(4)

name
system clock
frame clock
trigger
JTAG mode select
JTAG clock
JTAG data in
JTAG data out
resetdata out (4)42.3MHz(?)
99.2kHz10-30Hz

comment
LVDS
LVDS
LVDS
LVDS
LVDS
LVDS
LVDS
LVDS
CML

Table 4.8: I/O lines per module (DHH/patch panel/module)

4.9.2

Power Cables

The static voltages for the DEPFET biasing and control can be supplied by very thin cables(0.8 mm2 , 150 Ω/km). The same is true for the sense wires. Analog and digital power of the
ASIC has higher currents, up to 2.3 A. Here, wires of 10 mm2 (5 Ω/km) and 3.1 mm2 (20 Ω/km)
will be used. The voltage drop of up to 350 mV requires sensing and regulation in the power
supplies. The cable servicing one module has a diameter of 5 mm (a cross sectional area of
20 mm2 ), including insulation and shielding.

4.9.3

Data links and fibers

Data, trigger and clock signals are transferred from the module to the patch panel in the Kapton
tapes described above. From there to the DHH, twisted pair cables will be used. Special
attention is needed to limit damping and signal distortion in these links, either by impedance
matching in the patch panels or active repeaters. The lines needed are listed in Table 4.8. Datatransfer between the DHH and the ATCA rack and the distribution of the clock and trigger
signal to the DHH will be done optically.

4.9.4

Cooling tubes

The PXD needs dry-air cooling to cope with the power dissipated by the sensors and switcher
chips without adding extra material in the acceptance region and active cooling to remove theheat generated by the electronics (DCD and DHP) on the module ends.
4.9.4.1

Air cooling

Heat removal from the sensors and SWITCHER chips will require air cooling. The power
dissipated in the active region is about 20 W. According to simulations, the air velocity shouldbe 1 m/s with a temperature of about −5◦ C . These calculations do not include the effect ofheat radiation from one layer to the other; therefore, the required air temperature may be lower.
The PXD support structure will have 1 mm holes on top of each module support to allow the air
to flow into the active region. This will require 20 of those pipes on each side that should provide
the the required volumetric flow, which will be about 6 m3 /h. Air may need to be pumped out
on one of the sides. It is not yet clear how to bring the air into the system. Although the flowrate is modest, there are risks of vibrations, given the thickness of the sensors, and detailed
studies are being carried out.

119

CHAPTER 4. PIXEL DETECTOR (PXD)

A −5◦ C dry-air flow will presumably require a cold, dry volume that might include the SVD.
4.9.4.2

Active cooling at the module end

The PXD power dissipated on each end of the detector is 180 W. Heat removal will happen
on the support structure, which is divided into two halves, each having its own built-in coolingchannel. That means that each of the two cooling circuits has to remove 90 W.
We have chosen a two-phase evaporative cooling system based on CO2 . According to the thermal
simulations, the temperature at the module cooling contact should be 5◦ C. Simulations andmeasurements have shown that the temperature difference between the coolant and the module
end can be as high as 20◦ C, requiring a coolant temperature of less than −15◦ C. For both cooling
circuits, corresponding to the two shells of the support structure, the required mass flow would
be 0.65 g/s for CO2 with a pressure of 23 bar. In this case the required inner diameter of thepipe would be 0.9 mm, although this needs to be fine-tuned to control the pressure drop. The
return lines will need to have a larger diameter to reduce the return line pressure drop. Each halfof the support structure will, thus, be connected to a large diameter (outer diameter ≥ 6 mm)exhaust pipe and a relatively flexible capillary (outer diameter ∼ 2 mm).
One can design a warm pipe cooling system by introducing a counter-current heat exchanger
between the incoming condensed liquid and the outgoing evaporated fluid. The location of theheat exchanger is not yet determined but it would need to be as close as possible to the PXD
support structure to minimize the length of the capillaries.

4.9.5

GroundingA PXD ladder is made from two monolithic silicon modules glued together. An electrical contact
between the modules cannot be excluded. In this case, the silicon bulk would be electricallyconnected while the electronics and DEPFET transistors are serviced independently from twosides. Hence there is the danger of a large ground loop. In order to minimize this risk, themain ground of the PXD system must be close to the modules with all power lines and I/O andclock lines floating. The support structures at both ends need a solid ground connection. The
grounding scheme is not yet fully engineered; this will to be done together with the SVD and
CDC, where some interference could be expected.

4.10

Test beam results

Beam tests of DEPFET prototypes form an important complement to the laboratory test procedures described in Sec. 4.6. Their main aim is to characterize the response of DEPFET
prototypes to minimum-ionizing particles, thus validating the results obtained with source orlaser tests, and to establish the spatial resolution of the devices.

4.10.1

Testbeams of DEPFET prototypes

Since 2005, DEPFET prototypes have been submitted to multiple beam tests in a 6 GeV electron
beam at DESY, 24 GeV proton beam at the CERN PS and 120 GeV pion beam at the CERN
SPS. Sophisticated beam test infrastructure has been developed. For a detailed descriptionof these tests, the reader is referred to several published test beam reports [17, 18, 19]. The
write-up of beam tests performed in 2008 and 2009 is in progress [20].

120CHAPTER 4. PIXEL DETECTOR (PXD)

4.10.1.1

Testbeam setup

Several DEPFET devices, or modules, were prepared for each beam test and installed on remotecontrolled xy-stages in the beam area. The outermost modules constitute the beam telescoperequired to characterize the spatial resolution of the innermost devices (DUTs). All modules
are powered using custom DEPFET power supplies developed by Bonn University. A pair ofscintillators read out by photomultiplier tubes is used to generate a trigger for the readout
system.
A photo of the setup for the 2009 beam test at the H6 line of the CERN SPS is shown in
Fig. 4.35.

Figure 4.35: A photo of the DEPFET beam telescope in the H6 area at the CERN SPS.

4.10.1.2

DEPFET prototypes under test

The DEPFET active pixel sensors submitted to beam tests are read out using the S3B system,
described in Sec. 4.6 (Fig. 4.19). The PXD5 sensors tested so far are 450 µm thick DEPFET
sensors with 64 × 256 or 64 × 128 pixels. The issue of thinning will be addressed in the PXD6
production currently in progress. Typical pixel sizes in these designs for the ILC vertex detector
range from 20 × 20 µm2 to 24 × 32 µm2 , whereas the pixels on Belle II ladders are 50 × 50 µm2
and 50 × 75 µm2 . Also, the read-out system differs in several important aspects from the BelleII PXD ladders. The CURO front end ASIC [21, 22] is being phased out in favor of the DCD
chip described in Sec. 4.3 and a design iteration of the switcher is foreseen.
Prior to the beam period, all modules were characterized using source and laser tests. An
analysis of the former provides a determination of the internal gain of the first amplification
stage in the sensor (the quantum gain gq , described in Sec. 4.2). The latter gives a first idea ofthe uniformity of the charge collection over the sensor active area (Sec. 4.6).

4.10.2

Results on PXD5 prototypes

DEPFET beam tests have led to a wealth of results. A discussion of all these is beyond thescope of this document and the reader is referred to the references cited previously for a moreexhaustive discussion. Here, the most important findings are given. The focus is on two basic aspects of the DEPFET performance: signal collection and in-pixel amplification in the DEPFET
sensors and the spatial resolution of the DUTs.

121

CHAPTER 4. PIXEL DETECTOR (PXD)

4.10.2.1

Characterization of the signal collection

7

3

cluster charge (10 ADC)

cluster size (# pixels)

The most straightforward measurement is that of the signal charge distribution. Pedestalsubtracted and common-mode corrected analog data are presented to a clustering algorithmwith a seed threshold of 7σ and a neighbor threshold of 2.6σ. The resulting cluster signal(Landau) distribution is shown in Fig. 4.36 (left).

6

2

1.8
1.6

5

1.4
1.2

4
3
2

0.6

data TB2008

cluster signal

0.4

MC digitizer

1
0-1

1

0.8

seed signal
MC digitizer

0.2
0

1

2
3
4
5
incidence angle (degrees)

0-1

0

1

2
3
4
5
incidence angle (degrees)

Figure 4.36: Left: the seed (filled) and cluster signal distribution for 120 GeV pions perpendicularly incident on the small-pixel DUT. Center: cluster size vs. incidence angle. Right: seed
(open circles) and cluster signal (filled circles) vs. incidence angle. The cross markers correspondto the result of a MC model that is discussed in Sec. 4.10.3.
The distribution is found to be in excellent agreement with the most commonly-used models [23, 24, 25, 26] in the range up to several MIPs. This agreement corroborates the excellent
performance of the DEPFET system: noise and gain variations have a very small effect on
the width of the distribution. The saturation of the DEPFET internal gate for a signal of
approximately 70,000 electrons affects the high signal tail (not visible on this linear scale).
The distribution of the signal on the seed pixel is also shown in Fig. 4.36. On average, twothirds of the signal is contained in the seed pixel. For perpendicularly incident MIPs, theaverage cluster size (the number of pixels with a signal exceeding 2.6σ) is approximately 4.5.
For these small-pixel devices, charge sharing between pixels increases strongly with incidence
angle, leading to an increase in cluster size and a decrease in the fraction of the signal in theseed pixel.
The most probable signal ranges from 1600 to over 3000 ADC counts (ADU) in different sensor
designs. The noise level in these devices is approximately 13 to 14 ADU. Thus, these devices
have a very comfortable signal-to-noise ratio of well over 100. The most probable signal isused to determine in-pixel gain gq .3 The results for the most important DEPFET designs are
summarized in Table 4.9. These results are in good agreement with the expectations from thesource tests.
Two design variants tested in 2009 prove to yield a very significant increase in the in-pixel
amplification. In a DEPFET device with a modified clear-gate structure known as Capacitively
Coupled Clear Gate (CCCG), a 40% increase of the gain is observed when compared to thesame sensor design with the usual Common Clear Gate design. The measurements on a PXD5
sensor with a short gate length (Lgate = 4 µm) confirm, on a large-scale device, the strong
3

The in-pixel gain gq , in nA/e− , equals µ × (7.7 nA/ADU)/(EMP /(3.6 e− /keV), where µ is the most probablevalue in ADU, 7.7 nA/ADU corresponds to the measured gain of the CURO/S3B system, and EMP is the mostprobable energy deposition in 450 µm of silicon by 120 GeV pions: EMP = 131 keV [23, 24, 25, 26] corresponding
to 36.4 ke−

122CHAPTER 4. PIXEL DETECTOR (PXD)

Table 4.9: The in-pixel gain of different DEPFET prototypes.
sensor type, matrix & pixel size
resultsnamerow × column (µm2 ) gq (pA/e− ) noise (e− )telescope TB2008
64 × 128
32 × 24320 ± 20320 ± 20
DUT 2008
64 × 128
24 × 24360
284
telescope TB2009
64 × 25632 × 24394 ± 14290 ± 2
DUT CCCG
64 × 25632 × 24
507
225
DUT short gate
64 × 256
20 × 20655
174

dependence of the gain observed in single-pixel measurements in Fig. 4.5. This module has
shown excellent performance throughout the test beam, while operated with an 80% higher
gq than the standard sensors with a gate length of 5 µm. This increase in gain translates toa proportional enhancement of the signal-to-noise ratio, crucial to the operation of very thinsensors.
The uniformity of the response over the DEPFET sensor has been measured. A spread of 5%
is observed when comparing the response of the over 8000 pixels of a sensor. The response is,moreover, found to depend very slightly on the position inside the pixel. The RMS in this caseis approximately 3%. None of these effects is expected to affect the resolution significantly.
4.10.2.2

Spatial resolution of small-pixel DEPFETs

The spatial resolution of the DUT is evaluated by comparison with the prediction of the beam
telescope. The position of a high-momentum pion is predicted using the information of a multimodule DEPFET telescope with sub-micron precision. The resolution of the DUT is extracted
from the residual distribution using the method described in Ref. [18] that takes into accountthe finite telescope precision and multiple scattering. The spatial resolution of the 2008 DUTwith 24 × 24 µm2 pixels is thus found to be:
σx = (1.3 ± 0.2) µm,

σy = (1.2 ± 0.1) µm(4.5)

This excellent resolution establishes the DEPFET as a firm candidate for high-precision vertex
detectors.

4.10.3Comparison with a detailed DEPFET model

These tests of small-pixel DEPFET prototypes have allowed a detailed understanding of thecharacteristics of MIP signals in these devices. The test beam results are a crucial input tovalidate the model of the DEPFET response. This model, described in more detail in Sec. 4.11,
is used as the digitizer stage of Monte Carlo studies to predict the performance of Belle II vertex
detector ladders and in the Belle II physics studies.
A detailed comparison has been performed of the model predictions with test beam measurements under different incidence angles. Excellent agreement is found for the cluster size andfraction of the signal in the seed pixels, as shown in Fig. 4.36. The agreement in the η distribution4 of Fig. 4.37 (left) is an even better indication that charge sharing between neighboring
pixels is described correctly.
4

η is defined as ±SN /SN + SS , where SS and SN are the seed and highest-neighbor signal, respectively, andthe sign is positive (negative) if the highest neighbor is located to the right (left) of the seed pixel.

123

CHAPTER 4. PIXEL DETECTOR (PXD)
0.45 ×10

pdf

-3

0.018

0.4

0.016

G4 + digitizer

0.35

0.014

TB data

0.3

0.012
0.25

0.01

0.2

0.008

0.15

0.006
0.004

0.1

0.002

0.05

0
-0.5 -0.4 -0.3 -0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5
η

0
0

2

4

6

8

10
12
14
16
18
column signal (x 1000 electrons)

Figure 4.37: Comparison of measured beam test data (black) to the prediction of the digitizer(red). Left: the η distribution. Right: the column signal distribution from TB data (blackcontinuous line) and MC (red dashed line) for incidence angles of 12◦ and 36◦ with respect tothe perpendicular. (See text in Ssec. 4.10.3 for the explanation).
To measure the signal distribution for a thin sensor, data was taken with particles incident at ashallow angle. Since the particle trajectory projects onto a large number of pixel columns, thesignal collected in each column corresponds to the energy deposited along a small fraction of
the trajectory. The signal distributions in the rightmost plot of Fig. 4.37 for sensor rotations of
12◦ and 36◦ with respect to perpendicular incidence correspond to a sensor thickness of 112 µm
and 40 µm, respectively. The excellent agreement observed in both cases demonstrates that theLandau fluctuations in thin sensors are taken into account correctly by the digitizer model.
4.10.3.1

Discussion

Beam tests of DEPFET prototypes have been vital to prove the principle of DEPFET inpixel amplification. Small-pixel prototypes have demonstrated excellent signal-to-noise ratio,
achieving an in-pixel gain of over 600 pA/e− . Moreover, the DEPFET response is found to beuniform within 5% over the sensor and within the elementary pixel cell. The spatial resolutionof a single small-pixel DEPFET sensor is found to approach the micron level (Eq. 4.5).
Test beam results are a crucial input to the estimate of the DEPFET performance in Belle II. Dueto the differences in sensor design, the extrapolation must be performed by a careful Monte Carlosimulation. The measured response of the DEPFET to high-energy particles from an accelerator
has been used to validate a detailed model of the DEPFET response (the DEPFET digitizer
described in Sec. 4.11). Thus, the MC studies of the DEPFET vertex detector performance rest
on a solid empirical basis.

4.11

Expected Performance of the PXD

Here, we present the expected performance of the PXD in the harsh background environmentof SuperKEKB. The situation is particularly severe for the PXD since it is always live and thus
integrates all impinging particles during the readout interval of 20 µs.

124CHAPTER 4. PIXEL DETECTOR (PXD)

4.11.1

QED Background

According to preliminary Monte Carlo calculations (see below), the expected background arisingfrom QED processes will be very large and may even surpass in rate the background fromthe machine (beam-gas reactions, Touschek effect, and synchrotron radiation). Apart fromthe Touschek effect, the machine background is not expected to be significantly larger than at
KEKB. The main reason is that the SuperKEKB beam currents are only double those of KEKB,
whereas all processes proportional to the luminosity, such as QED reactions, will increase relative
to KEKB by a factor of 40 at design luminosity.
PT th cut Lab Energy lower partPT th cut Lab Energy lower part Electron

Entries968
Mean
0.01852
RMS
0.01462

70
60
50
40
30
20
10
0
0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Figure 4.38: Energy distribution of secondary electrons from γγ interactions (in GeV). The solid
blue line is from the KoralW generator, while the dashed red line is from the BDK generator(see text).
Several Monte Carlo generators (BDK [27], KoralW [28], and Racoon [29]) were used to estimate
the background. Since the QED processes (mostly γγ reactions) making up the background for
the PXD are very low in energy, electrons and positrons above a transverse momentum of only
6 MeV will reach the first layer of the PXD. So far, there are no direct measurements of suchlow-momentum particles in an e+ e− collider. As a consequence, the predictions from the various
generators may not all give a consistent estimate for the rate of particles into the PXD. To have aconservative estimate, the generator with the largest particle flux has been chosen. In Fig. 4.38,
the low energy part of the corresponding spectrum from electrons and positrons, limited to theBelle II acceptance (polar angles of 17◦ to 150◦ ) is shown. In the figure, the spectrum has been
cut off at a transverse momentum of 5 MeV, since charged particles with lower energy will notreach the PXD due to the 1.5 T solenoidal field. From this spectrum and the cross section for
the reaction γγ → e+ e− around a center-of-mass energy of about 10.5 GeV, the occupancy forthe first layer of the PXD is below 0.5%.

4.11.2

General Strategy

The evaluation of the performance of the PXD is carried out by simulating single track events
as well as more realistic physics benchmark processes. In the former, muons are generated
at the unsmeared e+ e− interaction point with selected values of track momenta, p, and polar
125

CHAPTER 4. PIXEL DETECTOR (PXD)

angles, θ, uniformly distributed in azimuth, φ. For an evaluation of physics events with a more
realistic track occupancy, we choose the reaction Υ(4S) → B 0 B¯0 where one of the Bs decays
via a CP eigenstate and the other through a state tagging the b− (or b̄−)quark of the entangled
B mesons. For the CP side, we choose the “golden” mode B 0 → J/ψ KS with J/ψ → µ+ µ−
and KS → π + π − , while for the tag side we simulate the decay chain Btag → D ∗± π ∓ with++
D ∗+ → D 0 πslow→ K − π + πslow. Thus, the decay muons of the J/ψ provide high momentum
tracks with a transverse momentum, pt , up to 2.5 GeV/c, while the decay particles of the D ∗±provide tracks at medium (K, π) and low (πslow ) momenta of only a few tens of MeV.
The performance of the PXD is then characterized by the track impact parameter resolution in
the rz projection, ∆z, as well as in the rφ plane, i.e., the resolution of the distance of closest
approach, ∆d0 . In addition to the track impact parameters, the full physics events are also
used to evaluate the PXD performance in terms of z-vertex resolution of the CP - and tag-side
decays. Furthermore, the full physics events allow us to evaluate the quality of the J/ψ, D ∗±and D 0 candidate reconstruction in terms of the width of the signal peak and the backgroundlevel under the peak.

4.11.3

Event Generation, Simulation and Reconstruction

For our optimization studies, we take advantage of the ILC framework, which has been developed
to guide the detector research and design for the future linear collider [30]. Thanks to its modular
design, the ILC framework proved itself to be flexible enough so that it could be adopted quickly
to the special needs for the Belle II PXD optimization study.
The event simulation is implemented in the GEANT4 [26] based Mokka package. For the single
track events, we use the built-in particle gun; for the physics events, we use our privately
developed interface to read events in HEPEvt format. In this way, the EvtGen [31] generator,
which is well established in Belle, can serve as a source of events. After EvtGen, the events areboosted according to the Belle II beam configuration, and constitute the input to our simulation
step.
Within Mokka, the generated particles are traced through the tracking volume. The full detector
simulation takes into account the interactions with the detector material, e.g., the productionof secondary particles and the energy deposition in the active volumes of the detector.
Once the simulation step is finished, the events are handed over to the Marlin program for reconstruction, which is handled by a sequence of so-called Marlin processors. The digitization step
converts the energy deposits into hit pixels (PXD), strips (SVD) and wires (CDC). The implementation of the PXD digitizer follows the procedure adopted in the simulation/reconstruction
software of the CMS experiment at the LHC.
In the simulation, a charged particle traversing the active volume of the PXD sensors has its
trajectory divided into segments (so-called ionization points) whose charge is smeared according
to the Landau distribution. Ionization points are then drifted to the electrodes, subjected to
the Lorentz shift in the presence of the Belle II magnetic field and smeared by a Gaussian
distribution to account for diffusion. For each electrode, one gets a digit, with either a vanishing
signal or non-zero signal, depending on how many ionization points contribute to the signal.
Finally, the digits are converted into real hits.
For the clustering of hit pixels, either a center of gravity or an analog head-tail algorithm (forcluster multiplicities larger than two hit pixels) is used. Before the actual start of the clustering
algorithm, the pixel sensors are populated with possible additional hits. These originate fromsignal hits from the other tracks in the event, from additional tracks due to QED background
events, or from electronic noise.

126

CHAPTER 4. PIXEL DETECTOR (PXD)

After the digitization, hits from PXD, SVD and CDC are fed into another Marlin processor that
performs the track pattern recognition and the track fitting. For the study presented here, weused the standard tracking processor as implemented in the ILC framework that is based on the
tracking software package of the Delphi Collaboration.
Once tracks are found in real physics events, they are combined to decay candidates in another
Marlin processor. In the current study, candidates of J/ψ → µµ and D 0 → Kπ decays areformed from all possible track pair combinations with a total charge of zero. No particle ID
information has been used so far. The lists of track combinations are then fed into the next
processor that fits the decay candidate vertex using the RAVE library [32] (developed for CMS).
The whole chain of the event generation, detector simulation, and reconstruction up to thereconstructed decay candidates has been verified against the the equivalent chain using the Belleexperiment’s software framework (BASF). Track impact parameter resolutions were determinedin single track events and full physics events, and are found to agree well within the LCIO for
Belle II and the BASF frameworks. For the full physics events, the track impact parameter andthe vertex resolution for J/ψ agree well.

4.11.4

Simulation Scenarios

For the baseline beam configuration, we assume that the nano-beam option 2 will be realized:
4 GeV positrons collide with 7 GeV electrons at an crossing angle of 83 mrad. The tilt angle ofthe lower energy positron beam with respect to the direction of the axis of the solenoid has a
non-vanishing component only in the horizontal plane; its value is 15.55 mrad.
Since the Delphi tracking code, as implemented in the ILC framework, only allows for rotationallysymmetric geometries with a magnetic-field axis that coincides with the z axis, we are forced toassume that the beam pipe axis and the central axis of the PXD coincide with this z axis. This
is not necessarily the case for the final design of the interaction region; however, for the detector
optimization, for which we compare the relative performance of various detector scenarios inexactly the same environment, possible tilts of the symmetry axis of the PXD and the beam
pipe with respect to the magnetic-field axis can be safely neglected.
Guided by preparatory studies, we decided upon the basic parameters of a baseline PXD thatwould have a good chance to meet the physics requirements of Belle II. This design consists of
two layers of DEPFET pixel sensors, with the inner (outer) layer containing 8 (12) ladders at
a radius of 14 mm (22 mm). Both layers have 250 × 1600 pixels, corresponding to a pixel sizeof 50 × 50 µm2 on the inner layer and 50 × 75 µm2 on the outer layer. In the outer layer only,
the ladder is built from two DEPFET pixel sensors, glued end to end (Sec. 4.8). The sensor
thickness was a parameter in the study.
The baseline scenario is evaluated against a number of scenarios in which only one of the parameters characterizing the baseline detector is varied at a time. For example, we studied the
reduction of the inner radius to 13 mm, the use of 50 or 75 µm-thick sensors, the reduction in
the number of pixel rows from 1600 to 800 (to permit the full readout of the PXD within 10 µs),
and the splitting of the inner-layer ladders into two end-to-end sensors as in the outer layer (tosimplify the final production, but at the cost of ∼ 500 µm-wide dead regions). Finally, we also
consider an “optimal” detector scenario, which might still be feasible, although difficult in lightof the mechanical considerations. In this scenario, we reduce the radius of the inner layer to
13 mm and assume 2000 pixel rows for both the inner and outer layer, while keeping the sensitive
length in each layer constant.

127

CHAPTER 4. PIXEL DETECTOR (PXD)

Sensor thickness: d = 75µm (vs. 50µm)

Radius of inner layer: r = 13mm (vs. 14mm)

3500

Variation

3000

Baseline

entries

entries

1

4000

3500

Variation

3000

Baseline

2500

2500

2000

2000

1500

1500

1000

1000

500

500

-200

-150

-100

-50

0

50

100
150
200
zVtx (Rec-Gen)[µ m]Number of pixel rows: N = 800 (vs. 1600)

-200

3500

Variation

3000

Baseline

entries

4000

100
150
200
zVtx (Rec-Gen)[µ m]Baseline

2000
1500

1000

1000

500

500
0

50

3000

1500

-50

0

Variation

2000

-100

-50

3500

2500

-150

-100

4000

2500

-200

-150

Optimistic Design vs. Baseline Desgin1

entries

4000

50

100
150
200
zVtx (Rec-Gen)[µ m]

-200

-150

-100

-50

0

50

100
150
200
zVtx (Rec-Gen)[µ m]Figure 4.39: The J/ψ z-vertex resolution of the baseline detector (blue) compared to selected
alternate scenarios (red).

4.11.5Results of the Simulation

A comparison of the z-vertex resolutions of J/ψ in the different scenarios is shown in Fig. 4.39.
A reduction of the number of pixel rows clearly worsens the resolution. A slight improvement
is found when the inner radius is reduced to 13 mm.
Surprisingly, increasing the thickness of the sensor from 50 to 75 µm does not noticeably degrade the resolution, as one might naively expect. The additional multiple scattering is outweighed by the increasing charge sharing between neighboring pixels, which reduces the fractionof single-pixel clusters whose hit-position resolution is worse than for multiple-pixel clusters.
(For multiple-pixel clusters, more advanced position reconstruction algorithms such as center-ofgravity or analog head-tail can be applied.) Hence 75 µm-thickness was chosen for the baseline
design.
Splitting the inner-layer ladders into two end-to-end sensors has no visible effect (therefore notshown in Fig. 4.39). As expected, the best performance is seen for the so-called “optimal”
detector layout.
For muons from J/ψ decays, tracks with large transverse momenta dominate the sample. As analternative, we also studied the tag-side B decay vertex that is reconstructed from the vertex andfour-momentum of the D 0 alone by extrapolating the D 0 from its decay vertex back towards
the beam line. The same trends as for the J/ψ vertex resolutions are observed, though lessprominently than in the former case due to the lower momenta of the kaons and pions. The
PXD adds only slightly more material to a particle that has already traversed the thicker beam
pipe. (The thickness of the Belle beampipe is about 0.7%X0 , while that of a single PXD layer isonly 0.19%X0 .) The conclusion obtained from the decay vertex resolutions are supported by the128CHAPTER 4. PIXEL DETECTOR (PXD)

track impact parameter resolution. Figure 4.40 shows the track z0 impact parameter resolutionsof muons from J/ψ decays. Results from single-track events are consistent with those shown inthis figure.
0

σ(z0)

120

100

80

χ2 / ndfProbab
χ2 / ndfProbab

19.03 / 22
0.643620.2 ± 0.1934
10.25 ± 0.5651
44.17 / 22
0.003374
15.92 ± 0.1736
10.65 ± 0.4493µ-(J/ ψ ): z impact parameter resolution
0

120

σ(z0)

µ-(J/ ψ ): z impact parameter resolution

100

80

60

60

40

40

20

20

0.5

1

1.5

µ (J/ ψ ): z impact parameter resolution
0

σ(z0)

120

100

80

2

2.5
3
3/2
p×β×sin(θ) [GeV]χ / ndfProbab
χ2 / ndf
Prob
a
b
2

19.03 / 22
0.643620.2 ± 0.1934
10.25 ± 0.5651
129.6 / 22
3.074e-17
30.36 ± 0.3092
13.73 ± 1.067

0

0

100

80

40

40

20

20

1

1.5

2

1.5

120

60

0.5

1

µ (J/ ψ ): z impact parameter resolution

60

0

0.5

-

σ(z0)

0
-

2.5
3
3/2
p×β×sin(θ) [GeV]

0

0.5

1

1.5

χ2 / ndfProbab
χ2 / ndf
Prob
a
b

2

2.5
3
3/2
p×β×sin(θ) [GeV]χ / ndfProbab
χ2 / ndf
Prob
a
b
2

2

19.03 / 22
0.643620.2 ± 0.1934
10.25 ± 0.5651
40.58 / 22
0.00924619.85 ± 0.1784
9.201 ± 0.5715

19.03 / 22
0.643620.2 ± 0.1934
10.25 ± 0.5651
48.81 / 22
0.0008467
18.64 ± 0.2053
9.818 ± 0.5171

2.5
3
3/2
p×β×sin(θ) [GeV]

Figure 4.40: Comparison of the track impact parameter resolution, ∆z0 . The blue open circles
and line represent the baseline detector, while the red points and line indicate the varied detector
scenarios.
To verify that the Belle II detector with the DEPFET PXD as its innermost element meetsthe physics requirements of precision reconstruction of vertices and track impact parameters,
we compared the Belle II baseline detector to a simulation of the tracking volume of the Belle
detector, both within the ILC framework. The muon-track z0 impact parameter resolution isshown in Fig. 4.41, demonstrating the superior performance of the Belle II tracking systems. At
momenta below 800 MeV, an improvement of almost a factor of two is expected for Belle II.

4.11.6

Conclusion

A simulation chain for the evaluation of various detector options has been established. We
studied both clean physics signal events and events where we mixed in the expected QED
background and electronic noise. The results of the studies with and without background leadto the same conclusions. Findings of the comparison of baseline and alternate PXD scenarios
provide a clear guideline to further improve the performance of the PXD. Already, the baseline
scenario fulfills the physics requirements, as is demonstrated by comparing the performance of
the Belle II and Belle tracking systems.

129

CHAPTER 4. PIXEL DETECTOR (PXD)

Ratio Belle-I (LCIO)/Belle-II (LCIO) σ(z ): µ +(J/ψ )0

2.5

σ (z ) / σ (z )

0

0

3

2

1.5

1

0.5

0
0

0.5

1

1.5

2

2.5
3
5/2
p ×β ×sin(θ) [GeV]

Figure 4.41: Belle over Belle II ratio of the z0 track impact parameter resolutions as function of
the pseudo-momentum, p × β × sin5/2 θ. At low momenta, the impact parameter resolution of
Belle II is about twice as good as that of Belle.

4.12

Project Organization

The institutes participating in the construction of the Belle II PXD are
1. Charles University, Prague, Czech Republic∗ (PRA)
2. Physikalisches Institut der Universität Bonn, Germany∗ (BON)
3. Institut für Kernphysik, Karlsruhe, Germany∗ (KAR)
4. II Physikalisches Institut der Universität Göttingen, Germany (GOE)
5. Max-Planck-Institut für Physik, Munich, Germany∗ (MPI)
6. Institut für Technische Informatik der Universität Heidelberg, Germany∗ (HEI)
7. Ludwig-Maximilians-Universität Munich, Germany (LMU)
8. Technische Universität, Munich, Germany (TUM)
9. II Physikalisches Institut der Universität Gießen, Germany∗ (GIE)
10. IFIC Valencia, Spain (IFV)
11. University of Barcelona, Spain (UBA)
12. University Ramon Llull, Barcelona, Spain (URL)
13. University of Santiago de Compostela, Spain (USC)130

CHAPTER 4. PIXEL DETECTOR (PXD)

Id
1.0
1.1
1.2
1.3
1.3.1
1.3.2
1.3.3
1.3.4
1.4
1.4.1
1.4.2
1.4.3
1.5
1.6
1.7
1.7.1
1.7.2
1.7.3
2.0
2.1.1
2.1.2
2.1.3
2.2
2.3
2.4
3.0
4.0

work package
DEPFET Sensors
parameter definition
sensor development
ASIC Development
Switcher
DCD
DHP
Interconnections
Module design
sensor Ladder
Kapton Flex
DHH
Mechanical design
Thermal Issues
SystemData Acquisition
Power supplies
Cooling plant
Test facilities
Test beam setup
Beam tests analysis
Lab tests
Thermal tests
Mechanical mockup
Irradiation tests
Integration
Operation Issues

lead instituteparticipants

MPI
MPI

PRA

HEI
HEI
BON
BON

UBA, MPI
MPI, USC, URL

MPI
BON
TUM
MPI
KAR

HEI, BON, IFV, CNM, IFB
LMU, URL
BON, URL
KAR, VIE, IFV, KEK
MPI, VIE, KRA, IFV, IFB

GIE
LMU
KEK

TUM, MPI, KRA, GOE, URL, KEK
KRA, KEK, USC
KAR, IFV

IFV
PRA
MPI
KAR

KAR, BON, VIE, IFV, IFC
URL, CNM, IFB, USC, MPI, HEI(all)
MPI, VIE, IFV, IFC
MPI

Table 4.10: Work packages and assignments to the collaborating institutions
14. Instituto de Fisica de Cantabria, Santander, Spain (IFC)
15. Centro Nacional de Microelectronica, Barcelona, Spain (CNM)
16. Henryk Niewodniczanski Institute of Nuclear Physics, Cracow, Poland∗ (KRA)
The institutions marked with ∗ are already members of Belle II; the other will apply once national
funding is secured. In addition the project is supported by other Belle II collaboration members
like the HEPHY, Vienna, Austria (VIE) and KEK, Japan (KEK).

131

Figure 4.42: Schedule of the PXD construction.

CHAPTER 4. PIXEL DETECTOR (PXD)

The project is led by a project leader assisted by a technical coordinator. Representatives of all
institutions form an institutional board, with its chair person.
The project is organized in work packages which are managed by lead institutions. Table 4.10
lists the work packages and the participating institutions. The schedule of the PXD production
and installation is shown in Fig. 4.42. The schedule is mainly driven by the production of the
DEPFET sensors. This happens in two stages: a prototype production (PXD6) in order to test
certain design and technology variants, and the final-design production. A production cycle ofa DEPFET takes approximately 16 months, due to the very complex processing (more than
80 process steps). Driven by the installation date (summer 2013), the DEPFET sensors need
to be ready for assembly mid 2012. In order to achieve this, sensor production needs to start
April 2011. By then, all technical developments explained in Sec. 4.2 (thin oxides, shorter gate
length) need to be finished and all geometrical parameters need to be finalized. The schedule
does not leave room for a ‘final’ prototype run (the PXD6 prototypes do not have final geometry
and thickness) but has enough contingency to cope with downtime of the production line. The
development and production of the control and readout electronics is done in parallel. Since
ASIC productions have a much faster turnaround, typically three months, these activities are
not on a critical path.

4.12.1

Upgrade Option with SOI Pixel Technology

The baseline design with the DEPFET technology is well studied and we are confident that the
DEPFET will work from the startup of the Belle II experiment. However, the readout rate of
the DEPFET is limited to 20 µs per frame, even with four-fold parallel readout. Depending on
the background conditions, this may lead to a high occupancy and make it difficult to find thevertex positions when the SuperKEKB luminosity is at its design value.
There is an advanced pixel detector development project, based at KEK, using the SiliconOn-Insulator (SOI) technology [33, 34]. With this technology, complex CMOS circuits can be
implemented in each pixel, so that intelligent data handling such as sparse data scan, pipelining,clustering etc. become possible. In addition, in the SOI pixel detector, all the peripheral
circuits can be integrated within the chip, so much finer segmentation becomes possible without
increasing materials. This will lead to a higher data acquisition bandwidth and a faster frame
rate.
The basic structure of the SOI pixel detector is shown in Fig. 4.43. It uses bonded SOI wafers:
the bottom wafer is high-resistivity Si and works as radiation sensor, and CMOS circuits are
implemented in the top wafer. The process is being developed based on the 0.2 µm CMOS
Fully-Depleted SOI process of OKI Semiconductor Co. Ltd. A major issue in the use of the SOI
material as a radiation sensor is the back gate effect. The potential applied to the sensor partwill affect the transistor characteristics since both are in close vicinity. This issue was recently
solved by introducing a Buried p-Well (BPW) process. Figure 4.44 shows the transistor draincurrent and gate voltage characteristics variation due to the back side voltage. By adding the
BPW layer under the transistors, the back gate effect is completely suppressed.
The SOI pixel detector development is conducted through Multi Project Wafer (MPW) submissions, which include many designs in a mask. Although a detailed readout scheme is not yet
determined, we designed a test chip (called SBPIX1) for the Belle II experiment. The block diagram of the chip and an image taken with laser light are shown in Fig. 4.45. We are pursuing a
possible upgrade with the SOI detector about 5 years after Belle II startup when the luminosity
will have reached its maximum.

133

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.43: The basic structure of the SOI pixel detector.

4.13

Summary

The Pixel Detector of Belle II will be optimized for precision vertex reconstruction of B-meson
decays. The DEPFET sensors used in the pixel detector are monolithic all-silicon sensors without
need of additional support and cooling material in the active region of the detector. The sensors
are thinned to 75 µm resulting in a radiation length of about 0.19% X0 . This is possible due thelow noise offered by the DEPFET technology allowing a high signal to noise ratio even with thina sensor, and the low power density of 0.1 W/cm2 of the matrix operated in a rolling shutter
readout mode. The location close to the beam, 14 mm, results in an extremely high backgroundrate and considerable radiation damage. The first is addressed by a fine granularity, with a pixel
size of 50 µm × 50 µm and a high readout rate of 50 kHz, which should limit the backgroundoccupancy to 1 − 2%. The DEPFET and the associated ASIC chips will be engineered towithstand up to 10 MRad without significant deterioration of the performance, which should
allow operation in Belle II for a minimum of five years. The high background occupancy results
in an extremely high data volume. The information of the outer tracking devices is used to filter
the PXD data in special processors, reducing the data volume to a manageable level without
loss of efficiency.
In summary, the Belle II PXD will be one of the most advanced pixel detectors ever developed
for a particle physics experiment.

134

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.44: The transistor drain current and gate voltage characteristics variation due to theback side voltage.

135

CHAPTER 4. PIXEL DETECTOR (PXD)

Figure 4.45: The block diagram of the chip and an image taken with laser light.

136

References[1] J. Kemmer and G. Lutz, Nucl. Instrum. Meth. A 253, 356 (1987).
[2] J. Treis et al, JINST 4 P03012 4, P03012 (2009).
[3] I. Peric et al., Nucl. Instrum. Meth. A 579, 685 (2007).
[4] E. Gatti and P. Rehak, Nucl. Instrum. Meth. A 225, 608 (1984).
[5] S. Rummel, Investigation of DEPFET as Vertex Detector at ILC, PhD thesis, Technische
Universität München, 2009.
[6] ISE TCAD Release 7.0 (V0l. 2b, DIOS, 2001).
[7] R. Richter et al., Nucl. Instrum. Meth. A 511, 250 (2003).
[8] K. Gärtner and R.H. Richter, Nucl. Instrum. Meth. A 568, 12 (2006).
[9] H. Gajewski et al, TeSCA Two Dimensional Semiconductor Analysis Package (Handbuch,
WIAS, Berlin, 1997).
[10] L. Andricek, G. Lutz, R. H. Richter, and M. Reiche, IEEE Trans. Nucl. Sci. 51, 1117
(2004), 10.1109/TNS.2004.829531.
[11] F. Faccio and G. Cervelli, IEEE Trans. Nucl. Sci. NS-52, 2413 (2005).
[12] V. Re et al., IEEE Trans. Nucl. Sci. NS-53, 1599 (2006).
[13] V. Re et al., Nucl. Inst Meth. A 596 Issue 1, 107 (2008).
[14] M. Karagounis et al., CERN-2008-008 , 70 (2008).
[15] M. Trimpl et al., Nucl. Instrum. Meth. A568, 201 (2006), 10.1016/j.nima.2006.05.278.
[16] TB-5V-LX50T/LX110T/SX50T/FX70T-PCIEXP,
http://ppg.teldevice.co.jp/m board/inrevium/b v5.htm#hibiki.
[17] L. Andricek et al., Nucl. Instrum. Meth. A604, 385 (2009), 10.1016/j.nima.2009.01.097.
[18] J. J. Velthuis et al., IEEE Trans. Nucl. Sci. 55, 662 (2008), 10.1109/TNS.2007.914031.
[19] R. Kohrs et al., Nucl. Instrum. Meth. A565, 172 (2006), 10.1016/j.nima.2006.05.073.
[20] M. Vos et al., write-up in progress .
[21] M. Trimpl et al., Nucl. Instrum. Meth. A511, 257 (2003), 10.1016/S0168-9002(03)01803-5.
137

REFERENCES[22] M. Trimpl and P. Fischer, Prepared for 11th Workshop on Electronics for LHC and Future
Experiments (LECC 2005), Heidelberg, Germany, 12-16 September 2005.
[23] H. Bichsel, Rev. Mod. Phys. 60, 663 (1988), 10.1103/RevModPhys.60.663.
[24] A. Ferrari, P. R. Sala, A. Fasso, and J. Ranft, CERN-2005-010.
[25] G. Battistoni et al., AIP Conf. Proc. 896, 31 (2007), 10.1063/1.2720455.
[26] GEANT4, S. Agostinelli et al., Nucl. Instrum. Meth. A506, 250 (2003), 10.1016/S01689002(03)01368-8.
[27] F. Berends, P. Daverfeldt, R. Kleiss, Comput. Phys. Commun. 14, 285 (1986).
[28] S. Jadach, W. Placzek, M. Skrzypek, B. F. L. Ward, and Z. Was, Comput. Phys. Commun.
119, 272 (1999), hep-ph/9906277, 10.1016/S0010-4655(99)00219-2.
[29] A. Denner, S. Dittmaier, M. Roth, and D. Wackeroth, Comput. Phys. Commun. 153, 462(2003), hep-ph/0209330, 10.1016/S0010-4655(03)00205-4.
[30] F. Gaede et al., physics/0306114.
[31] D. J. Lange, Nucl. Instrum. Meth. A462, 152 (2001), 10.1016/S0168-9002(01)00089-4.
[32] W. Waltenberger et al., J. Phys. Conf. Ser. 119 Volume 119 (2008), 032037 (2008),
10.1088/1742-6596/119/3/032037.
[33] Y. Arai et al., Nucl. Instrum. Meth. A In Press, Corrected Proof, (2010), DOI:
10.1016/j.nima.2010.02.190.
[34] SOI Pixel Detector R&D web page, http://rd.kek.jp/project/soi/, 2010.

138

Chapter 5

Silicon Vertex Detector (SVD)
5.1

Introduction

The main purpose of the Belle II SVD,1 together with the PXD (Ch. 4) and CDC (Ch. 6) is tomeasure the two B decay vertices for the measurement of mixing-induced CP asymmetry. In
addition, the SVD measures vertex information in other decay channels involving D-meson andτ -lepton decays.
The design of the Belle II SVD inherits the good characteristics of the Belle vertex detector:
low mass, high precision, immunity to background hits, radiation tolerance and long-term stability. It is designed with silicon strip sensors to avoid the huge channel count of pixels withoutcompromising the vertex-detection capability of Belle II.

5.1.1

Vertexing in the Belle II environment

As explained in Ch. 2, SuperKEKB uses a low-emittance collision scheme with electron andpositron beams colliding at 7 GeV and 4 GeV, respectively. The Lorentz boost factor of thecenter-of-mass system is βγ = 0.28, about two-thirds of that in Belle; this results in less separation between the B vertices in an event. However, the beam pipe at the interaction region has
a radius of 10 mm, two-thirds of that in KEKB, so Belle II’s vertex measurement performancewith the SVD and PXD is as good as or better than in Belle.
Due to the higher beam current and luminosity, the detectors are required to operate at up to
30 times larger beam background and up to 30 kHz trigger rate.

5.1.2

Requirements and Constraints

The main characteristics of the Belle II SVD are the following:• It covers the full Belle II angular acceptance of 17◦ < θ < 150◦ . The inner radius is 38 mm
and outer radius is 140 mm; these are determined by the radii of the PXD and CDC.
• It improves the quality of the reconstruction of charged tracks compared to Belle’s SVD2.
• It provides data to extrapolate the tracks reconstructed in the CDC to the PXD with highefficiency; this is the strategy we employ to determine a vertex.
1
This nomenclature is chosen to avoid confusion with the historic SVD1 and SVD2 as well as the SVD2.5 and
SVD3 projects of the Belle experiment.

139

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)• From the Belle experience, the hit occupancy2 should be less than 10% in order to assure
the association of correct hits in the vertex detector with tracks reconstructed in thedrift chamber. Therefore, a proper combination of sensor geometry and readout scheme isnecessary. In addition, information from the Belle II SVD will be very useful in eliminatingbackground hits in the PXD.
• In combination with the PXD, it is able to reconstruct low-pt tracks, down to a few tens of
MeV/c, that do not leave enough (or any) hits in the CDC. This is particularly important
for the efficient reconstruction of the D ∗ daughters that tag the flavor of the parent B
meson.
• It is able to reconstruct KS mesons that decay outside of the PXD volume. This isimportant for channels such as B → K ∗ γ or B → KS KS KS where the only charged tracks
are the KS daughter pions.
• It operates efficiently and with very low dead-time in the high beam-background andtrigger-rate environment of SuperKEKB and Belle II. The background rate may be 30
times higher that in KEKB, and the expected maximum average trigger rate is 30 kHz.
• It is mechanically stable, has low mass, and operates reliably.
• Its heat load is dissipated efficiently by its cooling system.
• Its associated software environment robustly maintains peak performance through ongoingand frequent calibrations, alignments, and monitoring.

5.1.3

Belle SVD2 Limitations

In the SuperKEKB environment, the estimated occupancy of the SVD2 is shown—with large
uncertainty—in Fig. 5.1 as a function of the sensor radius. Following the SVD2 design, a sensor
size of 2.5 × 7.5 cm2 and VA1TA [1] readout is assumed here, where the VA1TA is operated with
800 ns shaping time. It is obvious that the hit occupancy is too high by at least a factor of ten.
For this reason, the Belle II SVD’s innermost sensor layer is placed at a radius of 3.8 cm. The
background level at radii as large as ∼ 10 cm is estimated to be too high for a conventional drift
chamber, so the outermost sensor layer is at a radius of 14 cm.

5.1.4

Approach

To fulfill the above requirements, our design consists of four layers of double-sided silicon strip
detectors (DSSDs) fabricated from six-inch wafers. It would be prohibitive in cost and channel
count to instrument this volume with pixels.
To suppress the background hits, a readout chip with a fast shaping time of O(50 ns) is indispensable. In 2003, an assessment of readout ASICs was done [2], and the APV25 [3], which
was originally developed for the CMS silicon tracker, was chosen for the future vertex detector
readout. The APV25 chip (Fig. 5.2) consists of 128 identical channels of low-noise preamplifiers
followed by a shaper stage (50 ns nominal peaking time, tunable). Each channel has a 192-cell
deep analog pipeline (ring buffer) with an index FIFO that can label up to 32 cells pending for
subsequent readout, an analog pulse-shape processor (APSP) that will not be utilized here, andan analog multiplexer for the output.
2

The occupancy is defined as the average percentage of strips with a signal above threshold at any trigger.

140

Occupancy (%)

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

3

10

102

10
0

1

2

3

4

5
6
Sensor Radius (cm)Figure 5.1: Hit occupancy of the SVD2 expected with SuperKEKB.

MUX gain

128:1
Differential
MUX
current
output amp

inverterpipelinepreampAPSP

shaperS/H

Figure 5.2: Building blocks of one of the 128 channels of the APV25 front-end readout chip.

In addition to the short shaping time, the operation of the pipeline and the analog readout
scheme were found to be fully compatible with Belle trigger and data acquisition scheme. The
APV25 chip is radiation hard up to an integrated dose in excess of 30 MRad. Intensive evaluation
has been done and the results demonstrate that, even now, the APV25 is a perfectly suitablechip for the Belle II SVD.
Progress has been made regarding the DSSD sensor fabrication technology. In the LOI (2003)
design, the DSSDs were assumed to be produced from four-inch wafers. Now, the six-inch wafer
is standard and will be used here. This reduces the overall amount of structural elements andthus the material budget.
Due to the fast shaping and noise considerations, the input capacitance for the APV25 chips
must be minimized. To achieve this, APV25 hybrids will be mounted on the DSSDs. After the
optimization of hybrid and ladder structure, the material budget per DSSD ladder is 0.57% ofradiation length, where the DSSD sensor itself contributes 0.32%.

141

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.1.5

Detector Layout

The Belle II SVD is composed of four layers, with sensor radii listed in Table 5.1. The geometryis mainly driven by the achievable sensor size in six-inch wafer technology (Sec. 5.2) and how to
fit integer multiples thereof within the acceptance region.
Layer

Radius
(mm)
140
115
80
38

6
5
4
3
Sum

Ladders

Sensors/ladder
5
4
3
2

17
14
10
8
49

Sensors
85
56
30
16
187

RO chips/sensor
10
10
10
12

RO chips
850
560
300
192
1902

Table 5.1: Geometrical properties of the Belle II SVD. As the sensors are flat, the radii given
here are the minimum distances from the beam axis. “RO chips” stands for the number of
APV25 readout chips. For coherence with the PXD layer numbering scheme, the innermost
strip layer here is numbered 3.
The polar angular acceptance ranges from 17◦ to 150◦ , which is asymmetric to account for theforward boost of the center-of-mass frame. The radial coverage is almost double that of theBelle SVD2 and hence would require a significantly increased number of wafers in a traditional
cylindrical geometry. To avoid this, slanted sensors are used in the forward region, resulting ina lantern shape (Fig. 5.3).

r
160
140
120
100
80
60
40
20

-z

-200

0

-100

0

100

conf100210.dat
W -300 400 -20 180 1
B
0.0 0.0 15.0 16.5 -100.0 200.0 0 0 0
O 0.0 0.0 160.0 167.0 -400 800 0 0 0
C
17 150 0.0 2.0
200.0
C
45 135 0.0 2.0
200.0
X 0.3 110.0 16.0
18.0 -40.0 3 1 0.35 -2.0 8
X 0.3 140.0 22.0
22.0 -50.0 3 1 0.35 -5.0 8
R 0.3 122.8 38.4
38.0 -90.0 1 2 0.4 -5.0 8
R 0.3 122.8 57.6
80.0 -157.6 1 2 0.83 -8.0 10
R 0.3 122.8 57.6
115.0 -215.4 1 3 0.83 -8.0 14
R 0.3 122.8 57.6
140.0 -263.2 1 4 0.6 -8.0 17
S 0.3 122.8 57.6 38.4 140.0 232.0 -21.1
0.6 -8.0 17
S 0.3 122.8 57.6 38.4 115.0 156.0 -17.2
0.83 -8.0 14
S 0.3 122.8 57.6 38.4 80.0 90.0 -11.9
0.83 -8.0 10*** Total Sensor area=1.2366 / m2 ***

200

300

+z

160
140
120
100

+z

80
60
40
20
-150

-100

-50

0

0

50

100

150

Figure 5.3: Configuration of the four strip layers, with slanted sensors in the forward region,and the two PXD layers. All dimensions are in mm.
The overlap between adjacent sensors accounts for about 8 to 10% of the sensor area (depending142

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

on the layer). Due to the relatively low energy of the machine, most particle tracks originatingfrom collisions will be deflected by multiple scattering and thus cannot be used for high precisionalignment, which is only available from highly energetic cosmic muons. As their rate is limited,
we prefer to have a rather comfortable overlap to facilitate alignment, even though this slightly
increases the overall material budget.
The slanted forward region requires sensors of trapezoidal shape, and only one design is foreseen
to be used in all layers. The slant angle varies in such a way that the non-parallel strips of thosesensors all intersect with the beam pipe. In reality, this condition cannot exactly be met due tothe windmill structure (see below).
While this design is nearly final, there are a few minor issues to be optimized. In the outermost
layer, 17 ladders would be sufficient for full circular coverage and sufficient overlap, but an evennumber might be beneficial from the mechanics point of view; a similar consideration applies tothe innermost layer (Sec. 5.3). Furthermore, there is still a degree of freedom in how to rotate
the four layers with respect to each other. In Fig. 5.3, all layers are arranged in order to have acommon overlap at the 12 o’clock position. One may argue that this is less than optimal for thematerial budget; on the other hand, the overlap occurs only in very narrow azimuthal angularrange and, in fact, can help a great deal in the alignment with cosmic muons (hence the vertical
position).
All rectangular silicon sensors are double-sided with the long strips on the p-side, parallel toand facing the beam axis (z). The short n-side strips along r–φ are located on the sensor face
towards the outside. The slanted sensors are similar, except that the long strips are obviously notparallel to z anymore, but (almost) intersect at the beam axis. Figure 5.4 shows the dimensionsof the three different sensor types together with their pitches on the n-side (top) and p-side(bottom), respectively, and the number of readout chips needed for each sensor. All DSSDs will
be connected to APV25 front-end chips (Sec. 5.3), reading out 128 strips each.

20
[cm]

layers
4
6
6
4
5
6
4

10

4
6
4
6

3
0
-30

-20

-10

4
6

4
6

4
6

6
6

4
6

4
6
4
6

4
6

4
6

6
6

0

10

20

30

40
[cm]

Rectangular (122.8 x 38.4 mm2, 160 / 50 um pitch)
2z APVs (n-side)rphi APVs (p-side) Rectangular (122.8 x 57.6 mm , 240 / 75 um pitch)
2z APVs (n-side)rphi APVs (p-side) Wedge (122.8 x 57.6-38.4 mm , 240 / 75..50 um pitch)z APVs (n-side)rphi APVs (p-side)

Figure 5.4: Schematic configuration showing the three different sensor geometries and thenumber of APV25 readout chips for each detector.
~ coincides with the z axis. This leads to a Lorentz
The solenoid’s central magnetic field vector B
force on electrons and holes in the sensor, as shown in the left half of Fig. 5.5. Consequently,
the sensors should be tilted in such a way that the spread is minimized. According to Ramo’s
theorem [4], the motion of both carrier types (electrons and holes) induces the same currents
in both electrodes (p- and n-sides). Even though only holes spread out over the segmented
143

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

p-side strips, electrons moving towards the n-side induce image currents in the p-side strips.
Due to their higher mobility, the Hall angle and thus deflection of electrons is about three times
larger than that of holes. Consequently, the tilt of the sensor plane should reduce the electron
spread, at the cost of an increased hole spread (right half of Fig. 5.5). This conclusion has been
confirmed by a numerical simulation based on Ramo’s theorem.

e+hParticlefrom IPn-sideshort strips along r-phi
+HV

eh+

p-sidelong strips along z
-HV

B||z

Particlefrom IP

Figure 5.5: Sensor geometry and magnetic field. Left: In the presence of a magnetic field,
electrons and holes are deflected by the Lorentz force. Right: The overall charge spread can be
minimized by a tilt that reduces the electron deflection.
The Origami chip-on-sensor concept (Sec. 5.3.1.1), which will be applied to all sensors except
those located at the edge of the acceptance, uses pitch adapters bent around the sensor edge.
These bent fanout pieces can only be applied at the outer sides in a windmill structure, as shown
schematically in Fig. 5.6. Together with the readout direction, this unambiguously determines
the layout of each Origami hybrid (Sec. 5.4.2).

B||zFigure 5.6: Schematic cross-section of a windmill structure with Origami modules. The flex
pitch adapters, which are bent around the sensor edges, can only be placed on the outer edgeof each sensor.
Further details on the mechanical layout and the cooling pipes attached to the Origami modules
are provided in Sec. 5.3.

144

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.1.6

Readout Chain

The electronic readout chain of the Belle II SVD is based on previous developments for DSSD
readout with the APV25 chip: the APVDAQ system (2005) and its successor, the SVD3 prototype readout system (2007). The latter, described in Sec. 5.7.2, was intended for a partial
upgrade of the SVD2 that was never implemented. Our design builds on it, with a few changes
to accommodate the significantly larger number of channels and radiation issues.
Figure 5.7 symbolically shows the electronics chain. APV25 chips read out the silicon sensors
and their analog output is transmitted to junction boxes placed about 2 m away, at the outerwalls of the CDC, approximately where the DOCK boxes were located for the SVD2 [5]. The
main function of those junction boxes is to avoid having 10 m long cables directly attached to
the Belle II SVD assembly during installation and to detach the short cables that move with
the SVD from the long and permanently installed cables that lead to the outside.
Finesse Transmitter Board (FTB)
FADC+PROC~2m
coppercable

Junctionbox~10m
coppercable

Unified optical
data link (>20m)

COPPER

1902
APV25
chips

Front-end hybrids

Rad-hard
voltageregulators

Analog level translation,
data sparsification andhit time reconstruction

Unified FINESSE
receiverFigure 5.7: Schematic view of the Belle II SVD readout chain.
In early 2009, several dosimeters were installed around the forward DOCK boxes and an integrated dose rate of about 5 kRad/ab−1 was measured. Extrapolation to SuperKEKB and Belle II
is not trivial but, naively, we expect 250 kRad if we simply scale by luminosity to 50 ab−1 . Thisis a deadly dose for most commercial off-the-shelf components. Fortunately, the APV25 chipcan easily drive long cables: this was positively tested with 12 m and there was no indication
whatsoever that this was close to the limit. Consequently, we will push the repeater part farther
down the chain and integrate it into the FADC+PROC (Flash Analog-to-Digital Converter andProcessing) modules.
Apart from the cable patch panel, the junction box will also contain voltage regulators for thefront-end hybrids to protect them from transient overvoltages; these can appear on long cables
with remote sensing in case of a sudden load drop that would occur, for example, when the
APV25 chips are reset. We intend to use RHFL4913 regulators by ST, which were developed
for the ATLAS experiment and were successfully tested up to 100 MRad (Sec. 5.4.3).
The FADC+PROC units will be implemented as 9U VME boards and contain the analog leveltranslation part, flash ADCs and one or more FPGAs that handle the APV25 data processing,including data reordering, pedestal subtraction, a two-pass common mode correction, zero suppression (sparsification) and hit time finding. Apart from the last item, these data processing
functions are already implemented in the SVD3 readout system and were verified in the lab as
145

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

well as in beam tests. Further details are given in Sec. 5.4.4.
Finally, the processed data will be propagated to Finesse Transmitter Boards (FTB), which send
the information to the COPPER system using unified optical data links. In parallel, a replica
optical output will be implemented to make the data available for online data reduction of the
PXD system. The destination of that second link may either be the FPGA-based Giessen Box
or a computer system based on CPUs or GPUs (Ch. 4). More details on the data links are
discussed in Sec. 5.4.5.
Each FADC+PROC unit handles the input of 24 APV25 chips (which may either be six hybrids
with four chips each or vice versa) and thus we need 80 boards in total, which will completely fill
up four crates (leaving one slot each for the crate controller). Due to an imbalance in readout
channels on forward and backward sides, however, this is more likely to be 3 + 2 = 5 crates
in total. Clearly, the number of FADC+PROC boards also defines the number of FTBs andfurthermore the number of optical links and COPPER boards. Due to the data rate limitations,a single COPPER board might not digest more than one FADC+PROC output, in which case
80 COPPER boards will be needed (Ch. 13).

5.2

Sensors

The design of the silicon sensors is driven by the fact that multiple scattering is the mostimportant issue for the Belle II experiment. Thus, the largest available sensors have to be used
and the design has to be double-sided to achieve a low material budget. Nowadays, typical wafer
processing facilities are able to produce six-inch wafers, resulting in a maximum sensor size of
approximately 12 cm length and a width of 6 cm. The sensors will be made from n-type bulk
with high resistivity and will have a thickness of about 300 µm, which is a standard material
available from industry.
Hamamatsu Photonics (HPK), the Japanese company that provided the SVD2 DSSDs on fourinch wafers, had decided some time ago to abandon the production of doubled-sided sensors.
Therefore, a market survey was started to investigate alternative vendors. Discussions werestarted with the following companies:• Canberra (Belgium/US)• irst-Trento (Italy)• Micron Semiconductor (UK)
• SINTEF (Norway)
After short negotiations, irst-Trento and Canberra dropped out, because they were not able
to produce sensors with the requested specifications. More detailed discussions started with
Micron Semiconductor and SINTEF with the aim to proceed to a prototype batch and the fullproduction later on.
Meanwhile, HPK announced that it would restart the production of DSSDs. A test production
was launched with HPK for the Belle II SVD barrel sensors, while Micron Semiconductor willproduce some slanted (trapezoidal) sensors for the forward part.
It is commonly agreed that the sensors for both regions need to be AC-coupled with integrated
bias resistors. The designs of barrel and forward parts will be described in the next two sections.

146

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.2.1

Barrel Sensors

Two different rectangular sensors for the barrel part are produced by HPK on 320 µm thicksix-inch wafers. As can be seen in Fig. 5.4, the small sensors used in layer 3 differ from the large
ones used in layers 4 to 6 in both pitch and number of channels. Figure 5.8 shows the outerdimensions of the sensors (dark blue) and the dimensions of the active area (light blue, not toscale, approximated values). Note that the small rectangular sensors have not yet been ordered,
so the values of active and total areas are extrapolated, awaiting confirmation by the vendor.
The large sensor will be used with conventional readout hybrids as well as with special hybrids
for chip-on-sensor readout (Sec. 5.3.1.1). To this end, an additional row of readout pads (red)is foreseen on the p-side.
Table 5.2 states the main sensor parameters. The electrical parameters, given in Table 5.3, arevalid for both the small and the large sensors.

59,6 mm57,72 mm

0,94 mm122,9 mm

0,99 mm
25 mm
124,88 mm

Figure 5.8: Geometric dimensions (not to scale) of the rectangular sensor for layers 4 to 6.
Dark blue: outer dimensions. Light blue: active area. Red: additional pad row.
Quantity# strips p-side# strips n-side# intermediate strips p-side# intermediate strips n-side
Pitch p-side
Pitch n-side
Area (total)
Area (active)

Large sensor
768
512
767
511
75 µm
240 µm7442.85 mm27029.88 mm2 (94.5%)

Small sensor
768
768
767
767
50 µm
160 µm5048.90 mm24737.80 mm2 (93.8%)

Table 5.2: Basic parameters of the rectangular sensors.

147

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Quantity
Base material
Full depletion voltage FD
Breakdown voltage
Polysilicon resistor
Coupling capacitance
Breakdown voltage of AC coupling
Bias leak current at FDValue
Si n-type 8 kΩcm
< 120 V
≥ FD + 50 V
4 MΩ (min.), 10 MΩ (typ.)> 100 pF
> 20 V
1 µA (typ.), 10 µA (max.)

Table 5.3: Electrical parameters of the rectangular sensors.

5.2.2

Forward Sensors

To cover the forward acceptance region while minimizing the material, the sensors are slanted
to form a conical shape. Therefore, the individual sensors are trapezoidal.
Figure 5.9 shows the outer dimensions of the sensor (dark blue) and the dimensions of theactive area (light blue, not to scale, approximated values). Tables 5.4 and 5.5 give the sensor
parameters.
The strips of the p-side (junction side) feature a variable pitch, giving them a fan shape. The
strips of the n-side (Ohmic side) are parallel and perpendicular to the central strip of the p-side.
Electrical strip separation is achieved by p-stop blocking technique [6], where a combination
between the conventional method and the atoll method is used (Fig. 5.10).
The first batch of sensors is manufactured in Sussex, England, at Micron Semiconductor Limited,on 300 µm thick six-inch wafers. To comply with their design rules, the design features a 10-foldmulti-guard-ring structure on both p- and n-sides.

38.42 mm

57.59 mm60,63 mm41,02 mm122.76 mm

1.39 mm

125,58 mm

Figure 5.9: Geometric dimensions (not to scale) of the trapezoidal sensor. Dark blue: outerdimensions. Light blue: active area.

5.2.3

Radiation

Radiation damage on a silicon device by photons is dominated by surface effects rather thanbulk damage. This results in the localization of the radiation defects particularly in the Si−SiO2
interface. In contrast to irradiation with hadrons, no type inversion of the silicon bulk material
148

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Quantity# strips p-side# strips n-side# intermediate strips p-side# intermediate strips n-side
Pitch p-side
Pitch n-side
Area (total)
Area (active)
Slant angles

Value
768
512
767
511
75 . . . 50 µm
240µm
6382.6 mm25890 mm2 (92.3%)
Layer 6: 21.1◦
Layer 5: 17.2◦
Layer 4: 11.9◦

Table 5.4: Basic parameters of the trapezoidal sensor.

Figure 5.10: Combined p-stop structure for electrical strip separation on the n-side.

Quantity
Base material
Full depletion voltage FD
Operation voltage
Breakdown voltage
Polysilicon resistor
Interstrip resistance, p-side
Interstrip resistance, n-side

Value
Si n-type 8 kΩcm
40 V (typ.), 70 V (max.)
FD . . . 2 × FD
≥ 2.5 × FD
10 MΩ (min.), 15 ± 5 MΩ (max.)
100 MΩ (min.), 1 GΩ (typ.)
10 MΩ (min.), 100 MΩ (typ.)

Table 5.5: Electrical parameters of the trapezoidal sensor.

149

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

is expected. To avoid charge-up effects on bare sensors, the DSSDs need to be continuously
biased and read out during irradiation tests.
In the SVD2, the radiation dose of the silicon sensors can be estimated using RadFET radiation
monitors, which are positioned nearby [7]. From Fig. 5.11, one can extract a total dose of
approximately 55 krad for layers 2 and 3, which corresponds to the innermost DSSD layer ofthe Belle II SVD. Taking some uncertainties about the position of the RadFETs in respect
to the DSSDs into account, the dose is estimated to be approximately 90 krad per ab−1 ofintegrated luminosity. Therefore, one can extrapolate the radiation dose of the innermost DSSD
to approximately 4.5 MRad for the projected lifetime of Belle II (50 ab−1 integrated luminosity).
Adding a safety margin, the DSSDs should tolerate a total dose of 10 MRad.

Figure 5.11: Top: total measured dose in krad of layers 1, 2 and 3 of the SVD2. Bottom:
integrated luminosity.
Contact with a gamma irradiation facility has already be established in order to perform irradiation tests. This facility (SCK-CEN, Mol, Belgium) is equipped with a strong 60 Co source,
where the dose of 10 MRad can be accumulated in only four hours. This irradiation test will be
performed once prototype modules equipped with sensors from the prototype batches become
available.

5.2.4

Quality Assurance

The silicon sensors will be tested thoroughly before being mounted onto ladders. The vendors
must always test 100% of the sensors including strip scans. For our quality assurance, one has
to distinguish between tests on prototype sensors and full production. For the first sensors from150

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

the prototype batches, 100% will be tested. The testing effort can be reduced subsequently
during full production, depending on the number of defects and reliability of the vendor test
results. However, we will always test at least 10% of the sensors.
For the initial production lot, each sensor will be tested first by applying a voltage ramp whilemeasuring its dark current and total capacitance (IV and CV curves). This results in information
about breakthrough voltage and full depletion voltage. The amount of dark current at a certain
voltage is a measure of the quality of processing. Moreover, strip scans will be performed, where
the polysilicon resistors, the coupling capacitances, the currents through the dielectric of thecoupling capacitance and the dark current of every individual strip will be tested. This has tobe done on each strip of both, p-(junction) and n-(ohmic), sides of the sensors.
As a next step, long-term stability tests will be performed, during which the sensors will bebiased for a couple of weeks. This results in the evolution of the dark current, which should be
absolutely stable with time. In addition, similar measurements will be performed during andafter thermal cycle tests to simulate aging effects.
Apart from the tests of the silicon sensors itself, measurements on test structures will be performed.3 Destructive tests, such as on the coupling oxide, can be performed to determine its
breakthrough voltage.
Due to the uncertainty in radiation background, irradiation tests of the sensors have to be
performed with electron and photons. This will be done at a later stage, when the sensors are
already assembled into modules so that they can be read out during the irradiation.
During mass production of the main batches, the tests done by the vendors will provide thenumbers and positions of bad strips. Therefore, the collaboration can reduce its own strip
measurements and sample approximately 10% of all sensors; these tests are very time consuming
and not without risk of damage to the sensors—with scratches, for example. However, testsof IV and CV curves have to be carried out on every sensor to determine the dark current,
breakthrough voltage and full depletion voltage.

5.3

Mechanics

The mechanical structure is determined by the requirements of B physics. As the Belle II collider
operates at relatively low energies and requires a high precision track measurement, a very low
mass but stiff mechanical structure is necessary. This task is further complicated by the use ofslanted sensors in the forward region (Sec. 5.1.5). In this design, the angle between the slanted
and horizontal sensors has to be transferred to the supporting structure, which leads to a torqueon the structure due to the weight loads from the vertical sensors.
As mentioned in Sec. 5.1.5, there are two possible ladder counts in layer 6: 17 or 18. Eighteen ladders would allow the assembled barrel to split symmetrically in halves, thus it will likely ease theinstallation process. A larger overlap between the sensors (∆φ) offers some data redundancy—as
two sensors may be hit in the overlapping region—and also more data for position alignment
at the cost of material budget. On the other hand, seventeen ladders are sufficient for precise
track measurement and cosmic muon alignment, with lower cost and a reduced channel countand associated lower data rate. The benefits of either design are at hand and simulations will
have to be conducted in order to find the proper solution.
Similar considerations hold for layer 3, where the mechanical design showed that eight ladders
pose a space issue in the azimuthal view for a sensor width of 38.4 mm (active area). Again,
3

For Micron, we have placed a large set of standard test structures onto the wafer. This was not possible for
HPK and therefore these tests are limited to the test structures provided by them voluntarily.

151

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

simulations will have to determine whether the overlap is sufficient with only seven ladders.
The ladders for layers 4 and 5 will be similar in design to the ladder 6 (Fig. 5.12), but theangles and the numbers of mounted Origami hybrids are different. This allows us to use thesame construction and assembly methods for those three layers. The ladders of layer 3 will haveto fit in close proximity to the PXD. To have enough space for this layer a different support
structure is needed, because the “ribs underneath the sensors” design could interfere with the
PXD. Layers 3 and 4 are planned to share a common endring to save space or if possible a
structure can be implemented into the masks to embed the third layer.

5.3.1

Ladder Design

The ladders are designed with a restrictive material budget in mind. The averaged material
budget is close to 0.57% and the supporting structure accounts only for 0.08%, averaged over thewhole sensor width. The Origami concept offers few possibilities to attach a support structure,
which is why the sensor on rib design was chosen. In this concept, two composite sandwich
carbon fiber ribs (SCFR) are glued to the Origami sensor area in such a way that no structureinterferes with the bond wires on the sensor side and shorts are avoided. This is realized by
implementing a 2 mm gap between the top edge of the carbon fiber (CF) ply and the sensor.
Cutting rectangle silhouettes into the Rohacell core will create the sensor distancing structure(SDS). The rib thickness is 3.13 mm including the CF layers (65 µm each), and the height is
6.5 mm without the SDS. Other important dimensions are listed in Table 5.6 (length and height
being measured from one mounting point to the other). Table 5.1 give the ladder counts andradii.
Layer
6
5
4
3

Ladder length (mm)
645.3
515.6
390.4
262

Ladder height (mm)
50
37
25
0

Angle (◦ )
21.1
17.2
11.9
0

Table 5.6: Current ladder dimensions. Ladder 3 does not have a slant angle nor height due toits straight design.

At both ends, the ribs are reinforced with an additional layer of CF to have more stiffness inthe area that is being bolted to the endring mount structure (EMS). Shims are glued into holes
at the end of the rib to spread the clamping load of the bolts and also offer a high precision
structure to position the SCFR on the EMS. These shims allow the compensation of mechanicalimperfections the laminate surface naturally possesses, as they will be individually fitted withfiller glue to ensure parallel positioned ribs.
Bolts mechanically couple the ribs to the EMS so that the handling of the assembly becomeseasier. Attaching these SCFR to the EMS will be the first step in the assembly procedure. The
two components together form an integral unit that cannot be disassembled. The EMS offer all
the mechanical support the ribs need and will provide features for positioning the ladders andalso a location to stow the hybrid boards. These blocks will not be actively cooled due to theirsmall volume with little room for channels or tubes but they will offer some degree of coolinginfrastructure for the APV25 chips attached to the hybrid board.
In the SVD2, a CF bridge connects the two ribs to improve the stiffness. For the Belle II SVD,
no such structure is needed, thus reducing the material budget. Mechanical simulations have152

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.12: Composite sandwich rib of layer 6.

shown that the DSSD itself is stiff enough to distribute the loads between the ribs. Araldite
glue will be used to ensure a good and strong bond between the sensor and the SDS.
Figure 5.13 shows the current development status of a ladder from layer 6. The ladders fromlayers 4 and 5 will have the same EMS.

Figure 5.13: Ladder of layer 6 with Origami sensors, hybrid boards, and end ring mounts.
The mechanical stability was simulated and the results show a maximum gravitational sagof 108 µm when the ladder is loaded from above (horizontal position; 12 o’clock) and 48 µm
when loaded from the side (vertical position; 9 o’clock). Initially, the sag was designed to be
153CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

equal for each direction of load on the structure, resulting in a Rohacell core width of about
2 mm—however, such a thickness is not available in the market. As Rohacell is a very lightweight material and its contribution is negligible in the overall material budget, the standard
thickness of 3 mm was chosen, resulting in a stronger structure when side-loaded thanks to theproperties of sandwich composites. It would be possible to also reduce the gravitational sag incase of horizontal position, but this would require thicker CF and therefore increase the material
budget in a non-negligible way.
The results for the simulations of gravitational sag are shown in Fig. 5.14 and Fig. 5.15 forhorizontal and vertical positions, respectively. An ambient temperature of 25◦ C was assumed
for these static simulations. Further mechanical and thermal behavior will be studied on fullscale ladder mockups.
Deformation [µm]108.20
90.16
72.13
54.09
36.06
18.03
0.00

Figure 5.14: Ladder 6 with gravitational sag (sensors only) in horizontal position.

Deformation [µm]
48.46
40.38
32.31
24.23
16.15
8.77
0.00

Figure 5.15: Ladder 6 with gravitational sag (sensors only) in vertical position.
In general, CTE (coefficient of thermal expansion) mismatch between various materials canlead to thermally induced stress in composite objects. In our case, however, there is a layer ofRohacell foam between the CF ribs and the sensors; and another layer between the sensors andthe Kapton hybrids. Thus, we do not expect thermally induced mechanical stress in the ladders,as small variations in length will be absorbed by the Rohacell layers.
5.3.1.1

Origami Chip-on-Sensor Concept

The APV25 front-end chip will be used to read out the strip sensors of the Belle II SVD.
Unfortunately, its fast shaping is associated with higher susceptibility to noise, which mainly
results from the capacitive load of the amplifier inputs. Hence, the APV25 chips have to belocated as close to the sensor strips as possible. The SVD2 scheme, where up to three sensors
are ganged (concatenated) and read out together from the edge of the ladder, cannot be used
for the Belle II SVD. In order to achieve a reasonable signal-to-noise ratio, all sensors need to beread out individually. On the other hand, the material budget has to be kept as low as possible.
To fulfill both requirements, the so-called Origami chip-on-sensor concept is used to read out
the inner sensors, while conventional hybrids, located outside the acceptance, are foreseen at
the edge sensors.
In the Origami scheme, the APV25 chips of both r–φ and z sides are placed on a single flexible
circuit, mounted onto the n-side of the sensor. The flex-hybrid is made of two Kapton and154

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

three copper layers with thicknesses of 25 µm and 10 µm, respectively. The (short) strips on the
top side of the sensor (measuring the z coordinate) are connected by a pitch adapter, which
is either integrated into the hybrid itself or made as a separate two-layer piece, dependingon the capability of the manufacturer. The channels of the opposite side (long strips for r–φmeasurement) are attached by small flexible fanouts wrapped around the edge of the sensor,
hence the name Origami. All connections between flex pieces, sensor, and APV25 chips are
made by wire bonds.
a) Top view:
3-layer kapton hybrid

CF sandwich ribs
(mech. support)

APV25 chips(thinned to 100µm)

cooling pipeside view (below)

DSSD(integrated) fanout for n-side (z)double-layer flex
wrapped to p-side (r-phi)b) Side view (cross section):
wrappedflex fanout

cooling pipe
APV25
(thinned to 100µm)

KaptonRohacell
DSSD
CF sandwich ribs
(mech. support)

Figure 5.16: Top and side views of the Origami chip-on-sensor concept for a 6” DSSD. Eachview is to scale (but not the same scale). a) Top view: The six APV25 chips that read out
the strips on the opposite side are shown in green for clarity and the flex pieces to be wrappedaround the edges are unfolded. b) Side view: The wrapped flex, which connects the strips ofthe bottom side, is located at the left edge.
Figure 5.16 shows drawings of top and side views of an Origami chip-on-sensor module, where
only the fraction of the hybrid containing the readout chips is depicted. Depending on thelocation in the Belle II SVD, the flex circuit is extended either to the left or the right end of155

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

the ladder, where connectors are located outside the acceptance. Prototype flexes, designed fora four-inch wafer DSSD, are shown in Fig. 5.17.

Figure 5.17: Prototypes of an Origami hybrid and the two flex fanouts, designed for a four-inch
wafer DSSD, shown approximately in full size.
Thermal and electrical insulation between hybrid and sensor is given by a 1 mm thick sheetof low mass, but rigid foam (Rohacell). Nonetheless, the power dissipation of each chip isabout 350 mW and thus sufficient cooling of the APVs is required. Since all front-end chips arearranged in a row, cooling can be done by a single thin pipe. A detailed discussion of the coolingsystem is given in Sec. 5.3.3.
It is clear that using such a hybrid inevitably increases the material budget in the sensitive
volume, but there is no alternative solution, particularly in the outer layers, to ensure reasonable
signal-to-noise ratio (SNR) with fast shaping. To achieve the lowest possible material budget, theAPV25 chips will be thinned down to approximately 100 µm. The calculated average material
budget is 0.57% X0 , where the majority is contributed by the sensor itself (Sec. 5.8.1).
5.3.1.2

Materials and Properties

To have the lowest possible material budget, lightweight materials are used. For the sandwich
ribs, Rohacell HF 71 is used combined with plies of high modulus CF and aircraft grade epoxy
resin. The thermal properties of the materials used do not match: there is a significant coefficientof thermal expansion (CTE) mismatch between the Rohacell (≈ 30 × 10−6 K−1 ) and the siliconsensor (≈ 2.6 × 10−6 K−1 ). To reduce the negative effect of expansion, the contact areas are kept
relatively short (20 mm). The SCFR are less susceptible to CTE mismatch because the CF layer,with a CTE of −0.5 × 10−6 K−1 , expands by 9.8 × 10−6 m (at ∆T = −30◦ K, distributed over
650 mm) when cooled down, while Rohacell shrinks −5.8×10−4 m (at ∆T = −30◦ K, distributed
over 650 mm). This is a small mismatch that is expected to compensate itself and pose little
risk of misaligning the sensors.
A failure mode for sandwich composites is delamination. This can be caused by various factors
such as excessive transverse loads [8] or by a bad contact between the layers due to contamination.
First tests have shown that excessive bending quickly leads to the expected delamination, whichis due to buckling of the extremely thin CF layer. A delaminated rib does not offer the required
156

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

structural integrity and can lead to unwanted effects. It is rarely as easy as in Fig. 5.18 to spot
a delamination. Proper care and handling of the ribs is of the utmost importance in order toavoid this failure.

Figure 5.18: Delamination caused by applying excessive forces on both ends.

5.3.2

Endrings

The final endring design is still pending. The endrings will be joined and mounted on the
beam masks as symmetrical or asymmetrical halves, depending on the number of ladders in therespective layer. The main focus of the endring design will be to free up as much space forcable routing and cooling lines as possible while maintaining mechanical stability. The current
approach to achieve this is to cut out thin spokes that transfer the ladder loads onto the beammasks. The open areas between the spokes will be aligned with the underlying ladder in theazimuthal direction to ensure conflict-free cable routing. In Fig. 5.19, a possible solution isshown. The endring design on the slanted sensors side of the barrel is particularly challenging
as little space is available in this region to make cutouts big enough to route cables through.

5.3.3

Cooling

The SVD will be cooled with either a dual phase CO2 system or a glycol-water mixture as a
backup option. The decision on the system will depend on the outcome of our R&D efforts
using a CO2 blow system and will be made together in a common effort with the PXD group.
CO2 systems offer low temperature cooling down to −20◦ C and beyond, which improves thesignal-to-noise ratio significantly at a reasonable material budget (Sec. 5.8.1). Material in theactive area is kept minimal with a tube diameter of 1.4 mm and a wall thickness of 0.05 mm.
Those small tubes serve as the evaporator lines, where a relatively low mass flow and a pressureof 1.7 MPa are expected. Finite element method (FEM) simulations show that even at 8 MPa
the tubes withstand the pressure (Fig. 5.20). Under normal conditions, this pressure should
never be reached inside the evaporator. The pressure rating was chosen as it stands for thenominal pressure—including a safety factor—in the supply tubes where only fluid CO2 can befound. The simulation results will have to be verified by pressure tests and leak tests of theassembled cooling circuit.

157

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.19: Layer 6 forward endring design study, not split in halves and without alignment
tabs for the EMS.

The required wall thickness t (in mm) is related to the operating pressure P (in MPa) by:t=

D0
P · D0(1 +)2σa η + 0.8P
4R

(5.1)

where D0 is the outer diameter [mm], σa is the tensile strength [N/mm2 ], η is the welding
coefficient (typically between 0.8 and 1, depending on the weld quality) and R is the minimalbending radius [mm]. Putting the proper values and estimating a weld quality of 1 (seamlesstubes), the resulting thickness is t = 0.018 mm for an expected pressure of 1.98 MPa and a tube
diameter of 1.4 mm with a minimal bending radius of 5 mm. This implies that tubes with awall thickness of 0.05 mm will offer enough safety margin to operate the system under regularconditions.
From the mechanical point of view, it is important to reduce the number of inlets to save space.
This is done by cooling two ladders with one cooling loop. As many as four ladders could beconnected by one loop. Connecting two or more ladders requires a detachable cooling circuit toease up maintenance and reduce costs if ladders are to be replaced.
5.3.3.1

Cooling Materials

The Belle II SVD cooling circuit is part of a high pressure system that needs to withstandpressures up to 80 bar under regular operation. To withstand such pressure, the use of stainlesssteel is favored. Aluminum cooling pipes are not a good option as they would require thicker
tube walls to sustain the pressure and also would be susceptible to corrosion in copper-containing
environments [9]. The fact that the absence of copper cannot be guaranteed, combined with theincreased thickness, are sufficient reasons not to use aluminum.
One point of concern is the proper heat conduction from the APV25 chips to the cooling tube.
Thermal conductive paste tends to change its properties under radiation and therefore an ap158

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.20: Maximum stress from pressure on the tube end that connects two ladders in one
cooling loop at 8 MPa.

propriate alternative is needed. Thermal Pyrolytic Graphite (TPG) [10] and carbon foam are
two current options that have to be evaluated for their performance. As TPG is difficult tohandle, carbon foam is the preferred thermo-coupling material.

5.3.4

Assembly

To assemble the Belle II SVD, we will use the concept of cylindrically arranged DSSD ladders,which are mounted onto endrings. From the third to the sixth layer, one ladder consists of 2, 3,
4 or 5 sensors, respectively. In all but the innermost layer, the most forward detector is slanted.
Due to lack of space, we plan to attach a common cooling pipe onto two ladders, which meansthat either the smallest removable unit is a double-ladder or, preferably, the cooling pipe isdetachable and thus not glued onto the Origami hybrids.
5.3.4.1

Procedure

The following assembly procedure is in a very early stage and basically shows the steps required
to build a ladder. It strongly depends on the design of the mechanical support structure, which
is itself not finalized yet. The procedure is based on the experience gained from the constructionof the first Origami module prototype in summer 2009 [11]. Below, the steps required to build
a ladder of the outermost—and most complex—layer are described. We plan to make a more
precise definition of the procedure and build a prototype of such a ladder in late 2010 or early
2011, depending on the availability of components. The ladder of the outermost layer consistsof four rectangular (barrel) and one slanted trapezoidal DSSD. The rectangular and trapezoidal
edge sensors will be read out by conventional hybrids, whereas the Origami concept is foreseenwith the three inner barrel sensors.
The assembly steps are listed below:
159

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

plugged together
jig1

jig2
sensors with Origami readout
sensors with conventional readout
hybrids for edge sensors

holes for alignment pins

Figure 5.21: Sketch of assembly jigs 1 and 2 before they are plugged together.

1. The four rectangular (barrel) sensors are placed with the p-side (long strips) facing up onto
a jig (“jig1”) and aligned to each other using an optical position measurement system andan alignment tool that allows very precise movement. For each sensor, this jig provides a
separate inlay, made of porous stone, to lock it in position individually after alignment.
Furthermore, the pre-assembled hybrid for the edge sensor is placed on the jig and aligned
to the sensor.
2. The Origami fanouts and the pitch adapter for the edge DSSD is attached using a twocomponent epoxy glue, followed by wire bonding between sensors and flexes.
3. Since wire bonding is only possible on horizontal surfaces, it is necessary to assemble
the trapezoidal sensors with their flexes and hybrids separately, again by gluing and wirebonding. The resulting module is then placed onto a further jig (“jig2”), which can beplugged onto jig1 at the required angle between the straight and slanted sensors by using
precise alignment pins, as shown in Fig. 5.21.
4. The two support ribs are placed on another jig (“jig3”), which is used to precisely adjust
the distance between them. The endring mounts can then be attached to the ribs.
5. The support structure, still held by jig3, is turned around and glued onto the sensors. The
correct position is assured by alignment pins between jig3 and jigs 1 and 2.
6. After curing of the glue, all three jigs together are turned around and jigs 1 and 2 areremoved. The ladder is then presented on jig3 with the n-side (short strips) of the sensors
facing up.
7. The Rohacell foam sheet is glued onto the sensors.
8. Starting with the central sensor, the Origami hybrids, which have been populated with
AVP25 chips and the other electronic components in advance, are glued onto the top side.
9. This step is followed by wire bonding between the short sensor strips and the Origami
hybrids.
10. Finally, the flexible fanouts are bent around the sensors edges, glued onto the hybrids andconnected to the APV chips by wire bonding. A customized micro-positioner which was
already used for prototyping (see Fig. 5.38), is used to bend and align the flexes.
160

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

The above procedure contains several steps in which parts are glued together. To achieve thehighest possible mechanical precision, the glue must be applied by using a method that ensures
exact positioning of the glue as well as a well-defined uniform thickness of the resulting adhesive
film. Usually, this is done by a dispensing robot, but such machines are expensive and require
the complex and exhausting tuning of several parameters such as air pressure, motion speed,
and dispenser tip diameter to achieve the desired quality.
A much simpler, but equally precise, method is to apply the glue by using a stamp, whichmatches the form of the gluing area and has a grid of small bosses on its surface. To ensure an
exact adhesive amount, a small portion of glue is uniformly distributed on the floor of a basin byusing a mask with the required thickness. The stamp is then put into this glue bath and finallyplaced at the desired adhesive area. This concept was successfully applied at Paul Scherrer
Institute (PSI, in Villigen, Switzerland) to assemble the CMS pixel detector [12]. Thanks to its
simplicity and proven effectiveness, this method will be adopted for the assembly of the Belle II
SVD ladders.
5.3.4.2

Testing

To ensure high quality and reliability, each component of the Belle II SVD will be tested before
being mounted onto the ladder. This includes the sensors (Sec. 5.2), the thinned and diced
APV25 chips, the Origami hybrids, as well as all the other parts. As the ladder assembly is a very
complex task with many sophisticated steps, accompanying electrical testing is foreseen fromthe very beginning of the process. Therefore, we need a test setup, which can be built partiallyfrom already existing prototypes of the hardware and software. It will allow the identification oferrors such as shorted or open wire bonds. The results of these tests will be stored in a common
ladder-assembly database that can be consulted later, when each part is attached to the SVD
ladders.
Fully assembled ladders will be tested with a source and an xy-stage such that the functionalityof every strip can be verified. Such a test will take a couple of hours to allow for scanning andto accumulate a statistically representative signal distribution for each channel. An automatic
setup will be built to perform such tests in an unattended mode (e.g., overnight) and store theresults in a database.

5.3.5

Installation and Commissioning

The detector ladders will be mounted onto the endrings in a clean environment at KEK, preferably in the Tsukuba hall building. A rendering of the fully assembled Belle II SVD is shownin Fig. 5.22. Each ladder will be tested before and after assembly, and eventually the wholedetector will be powered as well as the cooling system. Four layers of silicon detectors are almost
impossible to penetrate using particles from radioactive sources—at best multiple scattering willcause zigzag paths rather than tracks. Thus, the only possibility for a full SVD test will be touse cosmics by triggering on the coincidence of scintillator paddles placed on top and beneaththe SVD assembly. The expected rate of cosmic events will be on the order of a couple perminute, but those will have perfectly straight tracks and thus can easily be used to check the
SVD-internal alignment. With long-term measurements, the rate should be sufficient to at least
verify the functionality of every channel.
Once the ex situ tests are finished and the PXD is mounted onto the beam pipe, the Belle II
SVD assembly will be inserted into and then bolted to the CDC. Even though Belle II SVD and
PXD are separate units, it will not be possible to insert or remove the PXD after the SVD isinstalled without first disassembling the SVD.
161

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.22: Belle II SVD barrel showing all four layers, cooling lines and hybrids (not connectedto Origami modules).
After installation and cabling, the Belle II SVD will again be tested. Once its functionality isverified in a standalone fashion, its controls and data outputs can be integrated into the Belle IIinfrastructure.

5.4

Electronics

This section describes the components of the electronic readout chain for the Belle II SVD.
Generally, its status is well advanced, as we reuse components developed for other experiments,
have put several years of R&D into the development of the system, and have successfully built
several prototypes.

5.4.1

APV25 Readout Chip

The APV25 [3] is a low-noise front-end amplifier chip in 0.25 µm CMOS technology originallydeveloped for the CMS Experiment at CERN. Its final version, APV25S1, was released in 2000
and thoroughly tested until the installation of about 70,000 devices in the CMS Tracker.
We already purchased approximately 5,000 chips for the Belle II SVD. All of them are wafer
tested. About half are already diced, and the remainder were delivered in a total of eight wafers(produced in 8” technology) with the aim of thinning them to minimize the material budgetof the Origami modules. As a test, one such wafer has been thinned down to a nominal valueof 100 µm and then diced. The actual thickness was measured to be 106.6 ± 3.2 µm and theprocedure had a mechanical yield of 98.4%. Up to now, about 20% of the thinned APV25 chips
have been electrically tested and all of them performed very well with no difference between themand unthinned APV25 chips. Hence, we will thin all the chips to be attached to the Origami
modules inside the polar-angle acceptance; the conventional hybrids at the edges, which resideoutside the sensitive volume, will use standard APV25s with a thickness of 325 ± 25 µm.
162

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.4.1.1

Features

The APV25 has a shaping time of 50 ns (adjustable), a 192-cell deep analog pipeline, and an
operating rate of 40 MHz; it is known to function over a wide range of clock frequencies. While
it is not surprising that the APV25 is fully functional at 31.8 MHz, a couple of chips were also
successfully tested up to 80 MHz.
The internal structure of the APV25 was already shown in Fig. 5.2. The usual preamp/shaperarchitecture can be seen on the left, where an optional inverter is placed between these blocks.
As the supply rails are limited to 2.5 V in the 0.25 µm technology, this switch is introduced to
optimize the dynamic range depending on the polarity of the signal, i.e., reading out positive(p-side, inverter on) or negative (n-side, inverter off) detector currents. Thus, a linear range ofapproximately −2 to +7 MIPs (referred to a standard 300 µm-thick sensor) can be achieved forboth polarities.
The shaper output is written to a pipeline of 192 cells at the clock frequency. In fact, the pipeline
is implemented as a ring buffer memory with an additional FIFO of 32 words to label memory
addresses that are requested for output by pending triggers. Until those data are read out, thetagged cells are skipped in the write cycle. Consequently, the available pipeline depth can vary
between 160 and 192 cells, depending on the amount of pending triggers. By multiplication withthe clock period, this translates to the maximum trigger latency time.
After the pipeline, the APV25 has an analog pulse shape processor (APSP). This is, in fact, aswitched capacitor filter that can perform a so-called deconvolution (see below) or, in a different
configuration, simply pass on the pipeline contents. Finally, the strip data are multiplexedthrough three hierarchical stages and sent to the differential-current-mode output.
Various bias voltages and currents as well as general parameters of the APV25 can be configured
through its I2 C interface. Clock and trigger signals are received by dedicated differential inputs.
The trigger line also accepts special 3-bit symbols, namely 100=trigger, 110=calibration request
and 101=soft reset. Consequently, two actual triggers must be at least 3 clock cycles apart;otherwise, they would be misinterpreted as a special symbol.
5.4.1.2

Operation Modes

In the CMS experiment, the APV25 is operated with a 40 MHz clock that is synchronous withthe bunch crossings of the LHC. Thus, the phase can be adjusted to always sample the peaksignal of the shaping curve if operating in the so-called peak mode.
Moreover, the APV25 can also use three consecutive samples around the peak to perform adeconvolution [13] with its internal APSP circuit. This operation essentially reverses the shaping
function, so that the train of output samples has just a single non-zero value and thus thecorresponding bunch crossing can be identified unambiguously at the cost of a moderate noise
increase. Operation in this deconvolution mode requires a clock frequency of 40 MHz and clocksynchronous particle signals to properly adjust the phase.
Unfortunately, the deconvolution mode cannot be in the Belle II SVD, because the SuperKEKB
bunch crossings occur almost continuously (precisely speaking, every second or third period of
the machine RF at about 508 MHz). Moreover, the APV25 clock frequency in the SVD is not
the same as in CMS: By default, it will operate at RF/16 (about 31.8 MHz) or, perhaps, RF/12(about 42.4 MHz).
Conveniently, the APV25 allows us to read out multiples of three consecutive samples without
applying the deconvolution. By taking six samples in this multi-peak mode, we can not only
take care of the non-constant phase shift between bunch crossings and APV clock, but also
process the data outside the APV25, thus identifying hits that belong to the triggered event
163

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

and discarding off-time background (Sec. 5.4.4.4). Nonetheless, the readout system will be built
in such a way that operation with between three samples and one will be possible simply byswitching some configuration bits.
The choice of the APV25 clock frequency has two immediate consequences for the system.
First, it defines the temporal length of the pipeline, which has a minimum effective lengthof 160 cells. This corresponds to either 5.04 µs (at 31.8 MHz) or 3.78 µs (at 42.4 MHz) anddefines the maximum trigger latency. To implement a 3D track trigger (Ch. 12), which takessome computation time, the earlier is preferred from the viewpoint of the Trigger Group. On
the other hand, a faster readout speed—and therefore a shorter overall trigger latency—makes
it less likely that the APV25 FIFO will fill (and therefore introduce dead-time into the dataacquisition system).
Assuming multi-peak mode operation with six samples read out per trigger, a simulation was
done to obtain the dead-time caused by a) the minimum distance of two triggers allowed by
the APV25 (six clocks) and b) the condition of a full FIFO with too many events pending
for readout. The average trigger rate was a tunable parameter, with triggers following an
exponential waiting-time distribution (i.e., Poisson distributed within fixed time intervals).

Figure 5.23: Dead-time caused by the APV25 at two different clock speeds and various averagetrigger rates.
The results of this simulation are shown in Fig. 5.23. Obviously, the dead-time caused by a)is essentially a linear function of APV25 clock and average trigger frequencies. The FIFO-fullcondition, however, reveals a strongly nonlinear dependence: at a trigger rate of 30 kHz, the deadtime fraction is only 0.87% at a clock frequency of 42.4 MHz, but rises to 3.43% at 31.8 MHz.
Clearly, the choice of APV25 clock speed is a trade-off between trigger latency and dead-timebudget: from the DAQ point of view, the faster readout is preferable. Table 5.7 summarizes the
behavior of the AVP25 depending on its readout clock.

164

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

fCLK
(MHz)
31.8
42.4

Min. trigger
distance (ns)189142Max. trigger
latency (µs)
5.04
3.78

Dead-time
a)
0.47%
0.36%

Dead-time
b)
2.96%
0.51%

Dead-timea) + b)
3.43%
0.87%

Table 5.7: Summary of APV25 properties as a function of the readout clock. Dead-times are
given for a Poisson-distributed average trigger rate of 30 kHz.

5.4.2

Hybrids

The APV25 chip needs a limited number of external connections: naturally, several bond pads
are needed for powering of the +2.5 V, +1.25 V and GND lines. These are not only needed on
the rear end of the chips, but also on the front-side, which holds the input pads for 128 strips.
Moreover, the rear side has differential inputs for clock and trigger, and a differential current
mode output. Single-ended lines are needed for the I2 C bus and the reset input. In addition,
there are a few pads to define the chip’s address within the I2 C bus.
Numerous PCB hybrids were produced in the past years for the readout of four APV25 chips
and used with prototype sensors. Fig. 5.24 shows such a test hybrid equipped with four APV25
chips. Apart from the chips and a connector (which is rather bulky in this case), there are a
few resistors needed for line termination and a special power line as well as some decoupling
capacitors. To the left of the connector, there are some parts related to the filtering of the biasline that supplies HV to the sensor. This (simple) hybrid concept has been well established andproven to work reliably in the lab as well as in several beam tests. So far, about 100 hybrids
were produced and tested using this design.

Figure 5.24: PCB hybrid used for APV25 and sensor tests.
In the Belle II SVD, there are two different implementations of hybrids. One is the Origami
concept (Sec. 5.3.1.1), which uses the same schematics and has already been verified on a prototype. The other type, which will also be derived from the existing prototypes, is intended forthe edge sensors. There, we will probably use a double-sided version of the hybrid with fouror six APVs, depending on layer and p- or n-side readout. As the electrical design is flexible,
165

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

the actual shape will be determined mostly by the mechanical layout. As each APV25 chipdissipates about 350 mW, this heat needs to be taken away by a thermal connection to cooling
blocks at the endrings, which is another mechanical constraint.
5.4.2.1

Connectors and Cables

Both for the Origami as well as for the PCB hybrids, small connectors will be used, which shouldhave the following properties:• Small feature size
• Mechanically locked• Gold plated contacts• Free of halogens• 50 (or more) pins
So far, only one connector type has been identified that fulfills all these requirements: this is
the Nanonics type STL051L2HN (part no. 2-1589483-6), already used in the SVD2.
For the cord, a halogen-free (Polyolefin) 0.05” pitch twisted-pair cable (3M type 79992-25P270A) will be used that has already been verified in prototype systems in both lab and beam
tests.
On the other end of the cable, the space constraints are not as stringent as on the detector side.
Consequently, a cheaper connector is used that fulfills all the above requirements except for thesmall feature size. The PCB part of this connector is also shown in Fig. 5.24; it is Samtec type
FTSH-125-01-L-DV-EJ-K-A.
5.4.2.2

Radiation

The hybrids—at least the Origami types—are subjected to the same radiation dose as thesensors, which is expected to be ≈ 4.5 MRad as extrapolated from the SVD2 (Sec. 5.2.3). The
APV25 is made from 0.25 µm CMOS technology and was tested to be radiation tolerant up toat least 30 MRad, which is far beyond what we can expect for the Belle II SVD.
Various types of SMD resistors and capacitors were tested for LHC applications to integrated
doses that far exceed the Belle II case and found to be compliant. Thus, we conclude that thoseparts are not critical for application in the SVD. The same is true for Kapton- and PCB-based
circuits.

5.4.3

Junction Box

The junction box will sit in a location that was previously taken by the so-called DOCK boxes
containing repeater boards. In Belle II, this location will only contain connectors, voltage
regulators, and passive components.
5.4.3.1

Functionality

The junction box joins the short cables attached to the Belle II SVD to the permanently installed
hybrid cables, which run from here to the FADC+PROC boards located between 8 and 10 m
away, outside of the Belle II detector. For the benefit of signal integrity, the disruption of166

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

impedance will be minimized, and thus the same cables will be used for the long leg of thatconnection. On the other hand, those cables present an ohmic impedance that is not critical forthe signal path but is harmful for power connections.
Thus, the power will be brought into the junction boxes using different cables with lower resistance and limited by voltage regulators in the junction box. In the absence of such local voltage
limiters, transient overvoltage can occur in case of load drop-off, e.g., when a reset signal is sentin common to a group of APV25 chips. As the 0.25 µm CMOS process specifies +2.7 V as the“absolute maximum” limit for the supply voltage, it is important to adhere to this boundary
even for short-term transients. This threshold will be observed by using voltage regulators in
the junction box as well as decoupling capacitors, which also damp voltage spikes.
A side benefit of using separate cables to bring in the supplies is that more leads of the hybrid
type cable become available for signal transmission. Thus, the plan is to merge two hybrid
cables into one single cable of the very same type for transmission to the FADC+PROC. This
concept still needs to be proven by prototypes.
5.4.3.2

Location, Mechanics and Cooling

The junction box is located at the outer wall of the CDC around the QCS magnets. This location
is outside the acceptance and cooling services are available there.
The mechanical layout of the junction boxes will follow the present concept of the DOCK boxes,and cooling will be needed for the voltage regulators. It is expected that the total cooling power
for both backward and forward parts will be less than 300 W and thus lower than the power
dissipation of the present DOCK boxes.
5.4.3.3

Radiation

To quantify the radiation to which the SVD2 DOCK boxes are exposed, dosimeters were placedat the forward side in early 2009. It was found that the total dose, extrapolated to Belle II, does
not allow us to use commercial off-the-shelf parts there (Sec. 5.1.6). In particular, a repeater,which would use such components, cannot be placed there.
Consequently, we decided to use only connectors and passive parts there, as well as radiationhard voltage regulators. Several such devices exists, and one candidate is the RHFL4913 type(previously called LHC4913) by ST that was developed for the ATLAS experiment. It has
now become a commercial device manufactured by ST, and is specified to withstand 300 krad.
Even though this is considered sufficient for our needs, tests performed by ATLAS found thatit tolerates an even higher dose of 100 MRad [14].

5.4.4

FADC+PROC

Each FADC+PROC board (9U VME) receives the outputs of 24 AVP25 chips in either 6 × 4
or 4 × 6 configuration, depending on the hybrid location. Consequently, about 80 such modules
will be needed, which are spread over several crates (Sec. 5.1.6).
In contrast to existing prototypes (Sec. 5.7.2) with a separate repeater box close to the front-end,
the FADC+PROC will incorporate that functionality, which is essentially the level translationof front-end signals from the bias voltage down to ground-bound low voltages. A sketch of the
FADC+PROC as a composite object of the existing repeater and FADC is given in Fig. 5.25.
As the APV25 chips have to drive their (differential) analog signal output all the way to the new
FADC+PROC without any intermediate buffer, this path has to be kept as short as possible.
Measurements have shown that a distance of 12 m is completely acceptable. More detailed
167

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.25: The combination of existing repeater (REBO) and FADC constitutes the future
FADC+PROC module (9U VME) with integrated voltage level translation.

studies were done earlier with an 8.7 m cable, resulting in no effect on the SNR within therepeat accuracy (±3%). Crosstalk was investigated with three (twisted-pair) cables stacked on
top of each other over a length of 1.8 m (including a total of 20 cm of flat regions). An internal
calibration signal of maximum amplitude (corresponding to about 10 MIPs) was injected in thecenter cable and the relative amplitude in the adjacent cables was found to be < 0.2% and thus
barely visible. As it is quite unlikely that cables will be precisely stacked over a long distance inthe future installation, we conclude that long hybrid cables are no problem for the signal quality.
We assume that an overall distance of about 10 m is sufficient to lead the cables out to the
FADC+PROC crates located on the top or at the side of the Belle II detector. These possible
locations, referring to the Belle detector, are shown in Fig. 5.26. The total space needed for the
FADC+PROC boards is one rack each in forward and backward sides, each containing two or
three crates, respectively. This does not include the space needed for front-end power supplies,
which should preferably (but not necessarily) be located nearby.
5.4.4.1

Analog Level Translation

Control signals sent to the front-end as well as analog data received from there need to undergo
a level shift from the bias voltages (±40 V in case of the SVD2, possibly higher in the Belle II
SVD) to ground-bound signals. This is done by using capacitive AC coupling for fast signals or
optocouplers for slow (quasi-static) signals.
The advantage of optocouplers is that they allow very high isolation voltages and static levels,
but they are limited in speed and linearity. Thus, they are used to transfer digital slow controls, namely the I2 C lines and the reset signal. Capacitive coupling, however, is used for fast,differential signals, namely, the clock and trigger (digital) and the signal output (analog). As
the capacitors need to charge with the DC bias voltage, the latter shall always be ramped up
and down slowly, which is also required by the silicon sensors. Nonetheless, a protection circuiton both HV and LV sides is foreseen in the translation schematics to absorb sudden voltage
excursions that could otherwise damage the integrated circuits. The existing repeater prototype
boards are designed for level shifts of up to ±100 V, which will also be sufficient for the Belle II
SVD.
168

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.26: Potential locations for the FADC racks (one each needed in forward and backwardsides).

150p
47

20
20

62
680

22n

360k

-5V

-2.5V
+2.5V

360k

47
150p

FADC+PROC

LV side

22n

680
62

+2.5V
-2.5V

APV25 Hybrid

HV sideFigure 5.27: Schematics of the analog voltage level translation (capacitive AC coupling) for the
APV25 signal output.

169

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.27 shows the circuit diagram for one APV25 channel as it is implemented in the repeaterboard. In the very center, there are 22 nF capacitors that block the DC bias level. They are
surrounded by clamping diodes and damping resistors that protect the amplifiers. On the HVside, the AD8132 in fact is an attenuator rather than an amplifier and thus may be omitted tosave space and power (to be tested). On the LV side, however, the EL5173 is essential, as it has
a high input impedance and thus primarily acts as a buffer.
The capacitive coupling is realized as a high-pass filter circuit with a time constant of approximately 450 µs. Figure 5.28 shows the unaltered output of the high-pass filter as recorded by
the FADC+PROC. In the idle state, the APV25 outputs are mostly at the digital baseline witha single tick mark (logic high) every 35 clocks. Thus, the DC level after the high-pass filter
will settle slightly above that baseline. When data frames are sent, the channel pedestal values
are significantly higher than the logic baseline and thus lead to an exponential discharge withthe time constant of the high-pass filter. However, as the duration of six frames is very short(only 26 µs at a clock frequency of 31.8 MHz) compared to the RC time constant, this decay isbarely visible. After the last frame, the baseline is slightly lower than before the data set andwill recover with the same time constant.

Figure 5.28: Scope snapshot of the output of six consecutive APV25 samples embedded in data
frames (abscissa: time in clock periods; ordinate: amplitude in ADC counts). One input channel
has a particle hit and clearly reveals the shaped signal waveform.

As the time constant is much larger than the duration of six frames, we can approximate theexponential decay by a straight line in that regime and thus the common-mode correction, whichis performed after digitization in the FADC+PROC, compensates the individual offsets for eachsample as long as the slope is (approximately) linear. In principle, the time constant of the highpass filter could be further increased by using larger capacitors, but this also implies that moreenergy would be stored in those devices and thus jeopardize the functionality of the protection
circuits. On the other hand, increasing the resistor value is also limited by the input impedanceof the EL5173 amplifier that is placed in parallel. The present device values were found to be a170

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

good trade-off between the different requirements and were demonstrated to work very well innumerous tests both in the lab as well as in beam.
5.4.4.2

Digitization

In the prototype system, dual flash ADCs (Analog Devices AD9218, rated for 65 MS/s) withparallel 10-bit output are used. As the number of channels per board will increase with the
Belle II SVD FADC+PROC, it is intended to use devices with higher density and serialized
output. One candidate for such an ADC is the AD9212, which accommodates eight independent
channels in a package that is only slightly larger (9 × 9 mm2 compared to 8 × 7 mm2 for theAD9218). In addition to the considerably higher device density, the space needed for lines on
the PCB is also significantly reduced. On the other hand, as signal transmission happens atmuch higher speed, signal integrity considerations become much more important.
5.4.4.3

Processing and Sparsification

Once digitized, the APV25 data streams are sent to one or more FPGAs, which will process
them as shown in Fig. 5.29. In the beginning, there is a frame detection circuit such that thelogic knows when a valid APV25 data block arrives. This is necessary as the APV25 data
output is locked to its internal APSP clock, which is 1/35 of the external clock (which is also thefrequency of tick marks appearing at the APV25 output in idle condition). Thus, the output
data not only arrive with some delay after sending a trigger, but also with a jitter of 35 clock
cycles. Once the header of a frame is detected, its contents and the subsequent channel data canbe extracted. Due to the construction of the APV25 output multiplexer, the natural strip order
becomes scrambled and needs to be disentangled. This is done by dual-port memories, whichhave a different address mapping for write and read operations so that the order is restored.
There are two identical such memories for each input channel on the FADC+PROC which aremutually operated such that subsequent data frames can be processed independently.

ADC
Frame Detection
Reordering
Pedestal Subtraction
CMC (2-pass)Time Finding

FPGA

Hit Finding

Figure 5.29: Signal processing chain in the FADC+PROC.

171

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

After reordering, several integer calculations happen. First, the pedestals of each strip, which are
stored in memory, are subtracted from each strip’s data value. Then, a common-mode correction
is performed in two passes. Essentially, all strip signals below a certain stored threshold aresummed and divided by their count. The resulting value is subtracted from each strip signal
in the next step, where the same procedure is applied once again. Finally, each resulting strip
value is compared to an individually predefined threshold and labeled as a hit if applicable inorder to discard empty strips later on (zero suppression).
5.4.4.4

Hit-Time Finding

By replacing the VA1TA readout chips of the SVD2 (800 ns shaping time) by the AVP25 for the
Belle II SVD (50 ns shaping time), the sensitive time window and thus the occupancy is alreadyconsiderably reduced. Depending on the actual shaper output waveforms and noise thresholds,
the gain might not necessarily be exactly be 16, the ratio of shaping times. In fact, the time overthreshold has to be considered in both cases, and was found to be 2000 ns vs. 160 ns, respectively,
yielding an improvement factor of 12.5.
Depending on the estimated background in the Belle II SVD, this improvement alone should
satisfy the requirement of having less than 10% occupancy even in the innermost layer. From
Fig. 5.1, we can extract an occupancy projection of approximately 50% for slow VA1TA shaping
at that radius using DSSDs from four-inch wafers. By scaling this figure to account for the
six-inch wafer size, the number of readout strips, and the faster shaping time in the Belle II
SVD, we estimate an occupancy of about 6.7%. This number includes a large uncertainty, as
the actual Belle II background conditions are unknown.
To cope with higher occupancy than expected, we reduce the sensitive time window by employing the “multi-peak mode” (Sec. 5.4.1.2) of the APV25. Multiple samples along the shaped
waveform allow for the off-detector reconstruction of the actual peaking time and, in conjunction
with precise trigger timing, enable us to discard off-time background hits [15]. Measurementswith prototype modules and readout electronics show that the RMS timing precision is of theorder of a few nanoseconds (Sec. 5.7.3); thus, the sensitive time window can be set to about
20 ns, provided that the SVD system receives a precise trigger time with an accuracy of a few
nanoseconds. This would allow an overall occupancy reduction of up to a factor of 100 comparedto the SVD2, as shown in Fig. 5.30, depending on the precision of the trigger timing and thesignal-to-noise ratio.
The hit time finding procedure has been verified in several beam tests using an offline numerical
waveform fit with two parameters, peak timing and amplitude. Figure 5.31 shows an example forthis waveform fit by two different methods. The exponential fit follows the theoretical output of
the CR-RC shaper, which is y ∝ τt exp(− τt ), and does not exactly represent the real waveform.
The shape determined from internal calibration of the APV25 obviously fits better, because it
has been obtained by measuring the shaper output when applying a well defined stimulus toeach input. Amplitude and timing of that test signal can be varied to sample the full waveformwith sufficient precision.
Using a numeric fit function gives high precision, but cannot be applied online because it would
require a large amount of computing power and/or time. To accomplish hit-time finding inreal-time, so that off-time background hits can be discarded immediately, the method has tobe fast and reliable. FPGA logic and memory can be used to obtain the required information
within a short and constant period of time.
The FPGA implementation of hit-time finding will first extract the three highest samples(triplet) of each measured set of six consecutive samples (sixlet). It has been shown that such a172

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.30: Occupancy reduction potential with the APV25 and hit time finding.

Figure 5.31: Hit time finding by a numerical fit using two different functions. Apparently, theIntCal fit delivers a better result.

173

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

triplet around the peak contains the essential timing information and thus delivers almost thesame precision with numeric fitting as the full sixlet. A predefined lookup table is used to findthe peak timing and quality information (similar to the χ2 of numerical fitting) of the triplet
data set. Different implementations of such a lookup table were evaluated by software and foundto give similar results close to the output of a numeric fit applied to all samples. We assume
that clustering before hit finding will improve the results, especially with tilted hits where thecluster signal scales with the number of strips while the noise only increases with the squareroot, leading to a higher overall cluster signal-to-noise compared to individual strips. (Thisneeds to be confirmed by actual measurements.) In any case, the FADC+PROC output willcontain individual strip signals, as those will later be needed to calculate the exact hit position
by means of center-of-gravity or other methods.
The contents of the lookup table for hit-time finding can, in principle, be generated by software. However, it is important to include noise fluctuations, since the measured sixlets will becontaminated by random excursions. The best method to obtain the data is to use the internal
calibration of the APV25, where particle signals are emulated by artificial stimuli, as mentioned
above. With high statistics of triplets recorded in this mode, it is possible to construct a lookup
table with intrinsic noise variations as these appear during calibration in the same way as they
happen with particle signals. If needed, extra noise can be added by software to further broaden
the distributions and thus ensure that all possible triplets are covered by the lookup table.
5.4.4.5

Data Rates

The output data rate depends on various conditions, but the system must be designed to handle
the worst case. We assume an instantaneous luminosity of 8 × 1035 cm−2 s−1 and an averagetrigger rate of 30 kHz for the following considerations.
Referring to Fig. 5.1, we extract an occupancy of 6.7% in the innermost layer. (See Sec. 5.4.4.4
for additional information.) For outer layers, we extrapolate this number using an 1/r 2 law
and adjust to the larger sensor size and number of APV25 chips for readout. Following thesecalculations, Table 5.8 shows the number of struck strips for each layer.
Layer
6
5
4
3
Average / Sum

Radius (mm)
140
115
80
38

Occupancy
0.9%
1.3%
2.7%
6.7%
1.9%

RO chips
850
560
300
192
1902

RO strips
108800
71680
38400
24576
243456Hit strips
967
944
1045
1647
4602

Table 5.8: Expected worst case occupancy for the Belle II SVD. “RO chips” stands for the
APV25 and “RO strips” is the previous number multiplied by 128 strips per APV25.
We consider four levels of data processing related to hit time finding:
1. no hit time finding, 6 samples per hit
2. no hit time finding, 1 sample per hit
3. online reduction by hit time finding, 6 samples per hit
4. online reduction by hit time finding, 1 sample per hit
174CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

In the first and third cases, sixlets of all found hits are transferred to the output. Otherwise,
only the peak sample of each hit is propagated, which should normally be sufficient for further
analysis. The latter two options include the possibility that off-time hits are immediately discarded in the FADC+PROC and thus are not propagated. Consequently, the last case provides
the smallest data set.
Even though the data format is not yet defined, we can assume that 12 bytes are needed
to transmit a full sixlet, while 4 bytes are sufficient for a single sample. The data are zerosuppressed in both cases, such that the position information is included in these data sizes. The
size of the overhead (such as header and trailer) can be neglected for the given conditions.
Table 5.9 summarizes the resulting data rates for each of the four cases mentioned above. When
online data reduction is performed by hit-time finding, we assume that the average occupancyof 1.9% is reduced by a factor of five. This includes a safety margin compared to the gain of (upto) eight, described in Sec. 5.4.4.4. For these calculations, we recall that the Belle II SVD has 80
FADC+PROC boards in total, each with its own data link to COPPER/FINESSE (Sec. 5.4.5).
Case
1
2
3
4

Averageoccupancy
1.9%
1.9%
0.4%
0.4%

Data size/
channel (B)
12
4
12
4

Event size
(B)
53.9k
18.0k
10.8k
3.6k

Total data
rate (B/s)
1.54G
527M
316M
105M

Data rate/link (B/s)
19.7M
6.6M
3.9M
1.3M

Table 5.9: Expected worst case data rates for Belle II SVD, depending on the level of online
data processing.
Assuming that the full sixlet information is not needed in the further data analysis, we canspecify case 2 as the baseline design with the improvement potential of online hit time finding,leading to a reduced data rate as stated for case 4.

5.4.5

COPPER/FINESSE Data Transfer

The main view of the data stream propagation from the FADC+PROC to the central DAQ isshown in Fig. 5.32.

Figure 5.32: SVD main data stream.
The dedicated FTB (Finesse Transmitter Board) module is the main device for data streaming.
175

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Its functionality is shown in Fig. 5.35. A general description of the two data streams—the mainstream to the DAQ and the additional one to the Pixel DRU (Data Reduction Unit, a.k.a.
“Giessen box”)—is provided below. A description of the other signals from/to the FTB can befound in Sec. 5.4.6.
5.4.5.1

Link to DAQ

Figure 5.33: Link to DAQ.
The main data stream contains the Belle II SVD detector readout data sent from the FADC+PROC
to the DAQ (Fig. 5.33). Data are prepared in the FADC+PROC as a parallel, four-byte-widebus, clocked at 31.8 MHz (or 42.4 MHz) and sent to the FPGA on the FTB. This Xilinx device
performs CRC input data checking and adds additional information such as CRC for the output
data. Then, the prepared data are written to a FIFO buffer at 42.4 MHz. A Rocket I/O module(implemented inside the FPGA) reads out data, serializes and sends them via a fast optical linkto the FINESSE Receiver Board (FRB) in the COPPER module. Another Rocket I/O FPGA
module on the FRB converts back the data to a parallel four-byte bus, which is then written
to a FIFO on the COPPER board. A processor on COPPER reads the data and transfers it to
the central DAQ via Ethernet link.
The High Speed Data (HSD) link connects the FPGA Rocket I/O on the FTB to the Rocket
I/O on the FRB in the COPPER board. It is a universal part common for the majority of
Belle II subdetectors. Eighty sets of FTB boards, one for each FADC+PROC module, areused to transfer the information of the whole Belle II SVD. At the other end of the HSD, one
COPPER board can hold up to four FRBs, so that at least 20 modules are needed. However,the bandwidth of COPPER is limited by its PCI bus, so each HSD link might terminate into
its own COPPER board; thus, up to 80 COPPER boards might be needed.
5.4.5.2

Link to Pixel Data Reduction Unit

A large amount of data is read out by the pixel detector (PXD), because it has a long integration
time. The PXD group plans to use the SVD data (which, in contrast to the PXD, have a veryfine time granularity but less position sensitivity) to discard the majority of off-time hits in the
PXD. A dedicated Data Reduction Unit (DRU) is intended to fulfill this purpose, and the SVD
data are sent not only to the DAQ, but also to the DRU in parallel (Fig. 5.34). Based on tracks
found in the SVD data, this device will identify regions of interest in the pixel detector andpropagate only the relevant data to the DAQ, discarding other hits.
176

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.34: Link to pixel data reduction unit.

The data stream from the FTB to the pixel DRU is unidirectional without any possibility for(partial) re-sending in case of bad transmission. The only possibility of data quality checking is
the CRC code appended to each data block. For transmission, a fast optical link (also Rocket
I/O in FPGA) will be used.

5.4.6

Clock, Trigger and Control

There are basically two options for the distribution scheme of clock, trigger and controls. Either
these signals are propagated to each FTB and sent to all FADC+PROC boards from there, orthey are passed on to the central FADC Controller module and distributed from there. The
latter option appears preferable in the sense that not only the global clock, trigger, and controls
need to be propagated to each FADC+PROC board, but so do SVD-internal control signals(such as I2 C slow controls). Moreover, only that scheme allows consistent timing throughout
the system and also allows a central trigger throttling logic to be included in the controller. On
the other hand, a low jitter clock will be needed by the FTB boards to be used for serializationof the data stream, which calls for an immediate clock distribution to each FTB. Thus, the final
system will be a mixture of both options, which also provides some freedom in choosing one or
the other path.
The global control signals are RCLK (127 MHz), Trigger, TAG[7:0] (trigger number) and GRST
(global reset). In addition, a ready signal and the status of FADC+PROC and FTB modules
are sent to the Trigger Timing Distribution (TTD) system. Differential LVDS levels will be used
for transmission.
Inside the FTB, signals from the TTD are divided into two streams. One stream is connected
directly to the differential inputs of the FPGA. The other goes through buffers to each FADC
module (shown on Fig. 5.35) or to the FADC Controller. The same FTB board will be used forconnection to both FADC and Controller modules, but the DAQ part firmware of the latter will
be disabled and no optical transceivers need to be equipped there.
5.4.6.1

FADC Controller

A total of 80 FADC+PROC boards are used for the Belle II SVD, spread over five crates. In
order to control all those distributed boards, a unique controller module is used that connects toa custom backplane in each crate, thus reaching every FADC+PROC module. The task of thecontroller is to distribute configuration signals as well as clock and trigger signals. The latter
177

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.35: Generic FTB module with full DAQ and TTD paths. Depending on whether the
FTB is used with an FADC or the FADC Controller, only one of those paths will be used.

is not the same as received from the TTD system, but needs to be refined before sending itto the APV25 chips at the front-end. Moreover, local (SVD-internal) triggers may be sent, forexample, to perform pedestal and noise evaluation or internal calibration. The APV25 clock caneither be 31.8 MHz or 42.4 MHz, but the latter is needed in either case by the FTB boards. Bothclocks are distributed by the controller to all FADC+PROC modules, and the APV25 clock is
selected there according to a configuration register.
The controller unit is also the natural location for throttling the trigger to prevent a buffer
overflow of the APV25 when there are too many triggers pending for readout. Such a solution
was also adopted in CMS, where a special module called the “APV Emulator” has an FPGA
implementation of the APV25 internal state machine and thus provides real-time information
about the current APV25 condition. As all APV25 chips operate synchronously, it is sufficientto have one single emulator that can throttle further triggers in a busy condition.
Moreover, such an “APV Emulator” can be used to predict the header of each APV25 data
frame, depending on the history of reset (synchronization), clock and trigger signals. Everyheader contains an encoded 8-bit pipeline address that denotes the APV-internal storage cellnumber from which the data were taken. As this is the only time-dependent piece of the data
frame, it should be verified in order to check that a certain data frame belongs to a particulartrigger. Otherwise, it would be almost impossible to detect missing or excessive frames in thecontinuous (dead-time-free) DAQ scheme and those would obviously spoil all subsequent data.
The controller also sends configuration information to each FADC+PROC board and, throughthose, to the front-end chips. It also distributes fast controls such as enable signals for digitization
or requests for copying data blocks to spy memories. Finally, it measures the precise trigger
timing (probably obtained by a direct link from the global decision logic, GDL) and propagatesthat information to each FADC+PROC to (optionally) perform online data reduction.
The design of the FADC Controller module is based on the “NECO” (New Controller) and“SVD3 Buffer” boards as well as the backplane of the existing prototype readout system (Sec. 5.7.2),
which essentially cover the same tasks.

5.5

Environmental Monitoring

The environment monitor for the SVD consists of temperature, humidity and instantaneousradiation sensors. The monitors for low- and high-voltage supplies are built into the power
supply units. The leakage current monitor for each DSSD sensor resides inside the readout
electronics.
178

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.5.1

Temperature and Humidity

The APV25 chips in the Belle II SVD will consume about 700 W in total at full operation. The
stable operation of the cooling system is essential to maintain high performance of the detector
system.
As the readout chips are mounted on the DSSD sensors with Kapton flex circuits, a temperature
sensor should be included on each hybrid and read out by the front-end readout system.
To prevent failure of the cooling operation, a redundant interlock on hardware level will be
prepared and installed at a very early stage of the SVD commissioning.
Moreover, it is important to ensure a dry atmosphere, as the ambient temperature in the SVD
volume will be lower than the dew point in the experimental hall (up to 13◦ C in the past). This
will be done by several humidity sensors placed in suitable locations to be determined once themechanical design of the SVD is frozen. As humidity sensors are bulkier than the temperatureprobes, it is not useful to mount them on each hybrid, but rather place a few of them in theendring regions.

5.5.2

Instantaneous Radiation

The instantaneous radiation monitor protects the SVD and PXD from dangerous radiation
damage and diagnoses the background sources under normal operation. Silicon PIN diodes with
4 × 6 × 0.3 mm3 volume, which were used in the Belle IR region, are capable of measuring doselevels above 0.1 mRad/s. The characteristics of PIN diodes are, however, sensitive to the total
dose. To perform a reliable measurement of dose level over several years of operation, we use
diamond sensors, which are very robust against radiation effects.
The primary purpose of the instantaneous dose measurement is accomplished by generating a
beam-abort request to the accelerator control when the dose rate exceeds a threshold level in avery short time. As the revolution period of SuperKEKB is 10 µs, an extremely fast response is
not necessary.

5.5.3

Integrated DoseIn the harsh radiation environment of SuperKEKB, the integrated dose monitor is necessary to
predict the lifetime of the detector system. In the SVD2, RADFETs [16, 17] are used for thispurpose. It is known, however, that the effect of integrated dose depends on the radiation doserate, the particle type (electron, photon, proton, or neutron), and energy. This is true even forthe sensors of the radiation monitor. Therefore, it is best if the integrated radiation effect canbe monitored by the sensor itself. In the Belle II SVD, the leakage current of each sensor ismonitored and used to calculate the total radiation dose.

5.5.4

Detector Leakage Current

The detector leakage current and the full depletion voltage are important properties in the
lifetime of a DSSD sensor. As each DSSD sensor is read out by a hybrid, the individual detector
currents can be monitored. The full depletion voltage can be estimated by the bias voltage
dependence of the leakage current and the noise level of the APV25 output.
The individual detector current of each DSSD is permanently measured by a dedicated circuit oneach FADC+PROC module. As the high voltages are split into positive and negative supplies,
two readings are available for each sensor on different FADC+PROC boards. Occasionally, highvoltage sweeps are performed to obtain the depletion voltage by measuring the noise level of the179CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

APV25 chips. Alternatively, the full depletion can also be obtained by the amplitude of particle(or cosmic) signals as a function of the bias voltage.

5.6

Power Supplies

The low voltage power supply (LVPS) levels for the readout chips are put on top of the detector
bias voltages, so that the AC coupling in the DSSD do not have to withstand the full bias voltage.
In exchange for the complex power supply design, the probability of pin-holes is kept low and,if pin-holes appear, the risk of malfunctioning of the APV25 chip is reduced significantly.
Achieving this goal requires several independent LVPS units with relatively small current. Table 5.10 shows the properties of the power supply crate that was used for the SVD2, which
consists of 11 independent LVPS units and two bias voltage channels. Each unit has individual
voltage/current setting, interlock control and monitors. As we have 10 such crates, we have 110
independent LVPS available.
Voltage
(V)
10
10
100

Current
(A)
10
5
0.001

Units
/crate2
92

Total
current (A)
20
45
0.002

Table 5.10: Properties of the SVD2 power supply system.
As mentioned already in Sec. 5.4.4, the Belle II SVD power supplies should ideally be locatednext to the FADC+PROC crates (see Fig. 5.26 for potential locations). This eases the threefold connectivity between power supplies, FADC+PROC boards and front-end and reduces thepossibility of ground loops.

5.6.1

Low Voltage Power Supply (LVPS)

The APV25 chip is operated with 2.5 V and 1.25 V supplies. According to [18], the typicalsupply currents for 2.5 V and 1.25 V are 0.116 A and 0.052 A, respectively. The total supply
currents are summarized in Table 5.11. From this table, we find that a LVPS system similar tothat used in the SVD2 can satisfy the requirements.
Layer

# of
ladders
3
8
4
10
5
14
6
17
Total
Total current @ 2.5 V
Total current @ 1.25 V

p-sideChips/ladder
12
18
24
30

total
96
180
336
510
1122
131 A
59 A

n-sideChips/ladder
12
12
16
20

total
96
120
224
340
780
91 A
41 A

Table 5.11: Number of APV25 chips and necessary supply currents.

180

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

The digital clock transmitters and analog signal receivers on the FADC+PROC are also suppplied by floating low voltages, which can be supplied from the same LVPS system or be provided
by DC-DC converters placed on the FADC+PROC boards in order to avoid ground loops andreduce the potential power loss in long supply cables.

5.6.2

High Voltage Power Supply (HVPS)

The main component of the radiation background in the Belle II SVD from SuperKEKB arises
from electromagnetic showers. As a result, the DSSD sensors suffer from surface damage: thedetector leakage current increases but saturates at less than 1 µA/cm2 , while the full depletion
voltage does not change significantly. Thus, the HVPS system for the SVD can be designed
to deliver power to the sensors corresponding to at most 10 mA at ±100 V. However, to copewith variation of damage and characteristics of DSSDs, the HVPS system is divided into several
independently controllable units. Such products are available on the market.
In order to control the SVD performance, a reliable HVPS and monitoring of bias voltages andleakage currents are necessary.

5.7

Prototyping

Several years ago, an intermediate upgrade of the SVD2 was planned for Belle, to cope with the
expected boost in luminosity and SVD2 strip occupancy associated with the installation of the
crab-crossing scheme in KEKB. Consequently, a replacement of the innermost layer by modules
with APV25 readout was envisaged and initially called SVD2.5. Later, this plan was extended
to the second layer and named SVD3. In the end, the luminosity increase with crab cavities wasless than expected and, thus, the intermediate vertex-detector upgrade was suspended.
Nonetheless, significant R&D effort was put into the planned upgrade and this is now proving
useful for the design of the Belle II SVD. In fact, many building blocks devised for SVD2.5 and
SVD3 will be reused for Belle II. These developments include several double-sided sensors andreadout modules of both conventional as well as chip-on-sensor type. Some of those modules arepresented in Sec. 5.7.1. Moreover, two readout systems were constructed: a compact one for lab
and beam tests and a larger, modular one that was intended for the SVD3. The Belle II SVD
readout system resembles the latter.

5.7.1

Sensors and Modules

In the course of our R&D effort during the past six years, we built several sensor modules withdifferent configuration and evaluated them at various beam tests. Below, the design of the threemost interesting modules, the JP Module, the Flex Module, and the recently finished Origami
module prototype, are described. The performance of those modules is discussed in Sec. 5.7.3.
For all three modules, APV25 readout and the same type of DSSDs were used. The sensor ismade from a four-inch wafer, has a size of 79.6 × 28.4 mm2 , and was originally designed for theintermediate SVD2.5 upgrade. The readout pitch of p-side (long) strips is 50 µm, while thatof n-side (short) strips is 152 µm. On each sides, a sensor has 512 readout strips plus 511
intermediate strips.
The so-called JP Module (Fig. 5.36) is based on the design used for SVD2, where up to three
sensors are ganged (concatenated) and read out from the edges of the ladders. The “JP” inthe name stands for Japanese design. This module consists of two sensors, whose strips areconcatenated by wire bonds on the p-side and single layer Kapton flexes on the n-side. Aiming

181

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

to compare the signal-to-noise ratio between a single and two ganged sensors, we only ganged
384 of the 512 strips on each side, which means that one APV25 chip is attached only to a single
sensor, while the other three have both detectors attached to their inputs.

Figure 5.36: JP Module made of two ganged double-sided four-inch sensors.
We introduced the chip-on-sensor concept with the Flex Module (Fig. 5.37), where the readoutchips are placed onto a thin double-layer flexible circuit placed on top of the sensor. As describedin Sec. 5.3.1.1, this method is required to achieve a reasonable signal-to-noise ratio when fast
front-end amplifiers are used for readout. In the case of the Flex Module, the chip-on-sensor
concept is only implemented on the n-side, while the p-side is read out by a conventional hybrid
attached to the edge of the sensor. Moreover, we used a relatively thick carbon fiber tube forcooling, which has more material budget than desirable. Nonetheless, the main goal of thismodule was to demonstrate the feasibility of the chip-on-sensor concept with APV25 readout.
Encouraged by the excellent performance of the Flex Module (Sec. 5.7.3) and keeping the material budget in mind, we wanted to extend the chip-on-sensor idea to both sides of a DSSD
without doubling everything. This resulted in the Origami chip-on-sensor concept (Sec. 5.3.1.1),
where both sides can be read out by a single three-layer hybrid placed on the sensor face withthe short strips. The connection to the long strips of bottom side is done by Kapton fanouts
that are wrapped around the edge of the sensor. By building the Origami module in 2009, we
have shown that the concept [19] is feasible, even though its assembly is a complex task. Thanks
to the use of micro-positioners equipped with a custom vacuum nozzle as shown in Fig. 5.38,
wrapping the flexes around the sensors edge turned out to be surprisingly easy. A detailed description of the assembly procedure can be found in Ref. [11]. The final four-inch wafer Origami
module prototype is depicted in Fig. 5.39. A simple, 5 mm high rib made of G10 was used as
the support structure. In contrast to the Flex Module, a thin aluminum pipe with a diameterof 2 mm and a wall thickness of 0.2 mm was used for cooling, which is much closer to the final
design.
In spring 2010, a first batch of six-inch wafer DSSDs, designed for the outer barrel layers (seeSec. 5.2.1) of the Belle II SVD, were delivered by HPK. In parallel, a final-size prototype of the182CHAPTER 5. SILICON VERTEX DETECTOR (SVD)n-side(short strips)

p-side(long strips)

Figure 5.37: Top and bottom views of the Flex Module prototype. The n-side (top) is built
according to the chip-on-sensor concept, while the p-side (bottom) is conventionally read out
from the edge.

183

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Figure 5.38: Origami module: Bending and positioning of the flex fanouts.

Figure 5.39: Top and bottom views of the prototype Origami module (using a four-inch wafer
DSSD), built into a frame for beam tests.

184

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

central Origami hybrid of the outermost layer (i.e., the longest of all variants), was producedby the Japanese Taiyo Industrial Co., along with pitch adapters to be bent around the edge ofthe sensor. In Fig. 5.40, these parts are arranged in the way they will be put together. The
assembly of such a single-sensor module is underway.

Figure 5.40: Six-inch wafer DSSD (≈ 125×60 mm2 ), Origami hybrid (≈ 445×57 mm2 ; only abouta third is shown here) and pitch adapters arranged in the Origami style, but not folded. The
objects are shown approximately in full size. Except for the 1 Euro coin (≈ 23 mm diameter),all pieces were manufactured in Japan.

5.7.2

Electronics

5.7.2.1

APVDAQIn 2005, we developed a compact test system for readout of single- or double-sided silicondetectors. It consists of one or more 6U VME modules, each connected to one hybrid with up
to four APV25 chips, and one repeater board for each hybrid between front-end and back-end,
which performs the voltage level translation as described in Sec. 5.4.4. Further information
about the APVDAQ system can be found in Refs. [20] and [21].

185CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.7.2.2

SVD3 Prototype Readout System

The SVD3 system was designed to read out 384 APV25 chips in the inner two layers of thedetector. Each FADC module has inputs for 16 chips, and thus 24 boards were needed in total,
spanning over two 9U VME crates.
Figure 5.41 shows a block diagram of the system, which is very similar to what will be implemented for the Belle II SVD. A master controller (“NECO” for new controller) is located in
one of the crates and connected to a “SVD3 Buffer” board located in each of the crates. The
latter board drives the control signals onto a custom-made backplane bus that runs along the P3
connectors in the VME crate. Each FADC module had a PCI-Link plug-on board transmitting
data to the unified COPPER/FINESSE DAQ system. Clock, trigger, and controls were transmitted to the controller through a dedicated link. Precise trigger timing information (for online
data reduction in conjunction with hit time finding) was intended to be provided directly fromthe global decision logic (GDL). On the front-end side, repeater boxes (“DOCK”) containing“MAMBO” and “REBO” boards are responsible for buffering and voltage level translation.

Figure 5.41: Readout concept for the SVD3 system.
A “REBO” (repeater board) and an FADC board are shown in Fig. 5.25. Further informationand photos of the SVD3 system can be found in Ref. [22].
The Belle II SVD readout system closely resembles the SVD3 design, but differs in some details
like the granularity of the FADC+PROC boards (24 instead of 16 inputs) and the integration of186CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

the voltage level translation. Nonetheless, many of the building blocks of the SVD3 prototype
system will also be used in Belle II.

5.7.3

Beam Tests

Aiming to evaluate prototypes of the readout electronics, the sensor modules, and the hit-time
finding procedure (Sec. 5.4.4), we performed several beam tests at PSI, CERN, and KEK. Since
2007, the prototype readout system was used in four beam tests and continuously operated forapproximately 1,000 hours. During this period of operation it has shown excellent performanceand reliability.
The setup of the most recent test (August 2009) in an SPS beamline at CERN is depicted in
Figure 5.42. The modules described above, in particular the Origami prototype, were exposed
to a 120 GeV proton/pion beam and tested with the full readout chain.

Figure 5.42: Setup of the beam test at CERN in August 2009, from left to right: Micron
module (equipped with a sensor by Micron Semiconductor), Flex Module, Origami module, andJP Module.
Figure 5.43 shows the signal distribution measured on the p-side of the Origami module. It canbe well fitted by a Landau distribution convoluted with a Gaussian component to account forelectronic noise and intrinsic detector fluctuations, shown in red.
The performance of the sensor modules is shown in Table 5.12, where the measured most probable (MP) cluster SNR is compared for both p- and n-sides, respectively. It is obvious that theachieved SNR of the JP Module for two ganged sensors is unacceptably low (even though theseare only four-inch sensors), while the values of the single sensor readout are satisfactory. Also,
the other modules, which read out a single sensor, demonstrated good results.
Compared to the JP Module, both Flex Module and Origami prototype revealed similar SNR
results for the p-sides. On the n-side, however, the latter two perform much better thanks tothe short connection through the integrated pitch adapters.
These measurements clearly show that it is not possible to operate the APV25 chip with morethan one sensor (like on the JP Module/ganged) due to SNR degradation, especially when they187

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

siC7entries []Origami_p_side (Origami) - Signal
EntriesMean
RMS
c 2 / ndf
Width
MP
Area
GSigma

5000

4000

60220
2.726e+04
1.115e+04
281.8 / 72
1775 ± 17.1
2.118e+04 ± 226.104e+07 ± 251742
2241 ± 33.0

3000

Peak = 22050.6
FWHM = 43.3%

2000

1000

0

0

10000

20000

30000

40000

50000

60000

70000

80000

90000
signal [e]Figure 5.43: Signal distribution of the Origami module (p-side) and a Landau*Gauss fit (redline).
ModuleSensor side
Cluster SNR:

JP ganged
p
n
9.4
10.1

JP singlepn13.1 13.9

Flexpn
13.8 18.4

Origamipn12.8 18.5

Table 5.12: Cluster SNR of the Belle II SVD prototype modules, measured at beam tests at
CERN in 2008 and 2009.
are made from six-inch wafers. Consequently, individual readout of all sensors using the chipon-sensor concept, as it was demonstrated with Flex Module and the Origami prototype, ismandatory for Belle II SVD.
Another interesting outcome of the beam tests is the efficiency and precision of the hit-time
finding procedure, which is used in the Belle II SVD to discard off-time background hits. A
description of this method is given in Sec. 5.4.4.4. For the beam tests, the hit-time reconstruction was done offline by a numeric fit using the pulse shape previously determined by internal
calibration of the APV25 chips. As time reference, the distance between the incoming trigger
signal and the following clock edge was measured by a time to digital converter (TDC), whichis integrated in the controller board (NECO). In Fig. 5.44, the results of several beam tests
and different prototype modules are plotted. Clearly, there is a double-logarithmic correlation
between the RMS time resolution and the cluster SNR. A time resolution of between 2 and 4 ns
can be expected for a cluster SNR range of 18 to 12.

5.7.4

Lab Tests

Before and after the beam tests, all prototypes of the electronics as well as all sensor modules
were extensively tested in the laboratory. In one of these tests, the effect of cooling on the SNRof the Origami module was measured. To achieve this, the cooling pipe of the Origami module
was connected to a chiller, which was used to cool the liquid.
The temperature of the coolant was observed by three thermal sensors attached to the coolingpipe of the module at three different spots. Figure 5.45 shows these locations. One is mounted
on the left side at the entry of the coolant, one is placed in the center of the module, and the188CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Time Resolution vs. Cluster SNR

6Previous beam tests
SPS 09 beam test
Log-Log Fit

5

Origami moduletrms [ns]

7

4
3
2
1
0
5

10

15

20

25

30

Cluster SNR [1]Figure 5.44: Measured time resolution vs. cluster signal-to-noise ratio of various Belle II SVD
prototype modules, measured in several beam tests.
APV25 Surface
Temperature(◦ C)(uncooled) 67.7:
8.7:
-8.5:

Cluster SNR
p-side
11.0
12.2
13.3

n-side
14.6
17.2
17.7

Improvement over the
uncooled conditionp-siden-side
11%
20%

18%
21%

Table 5.13: Cluster SNR of the Origami module with and without cooling, respectively, measured with a 90 Sr source at two different temperatures of the coolant.
last one at the exhaust to the right end of the hybrid. The air temperature inside the frame wasmeasured by an additional thermal sensor. A mixture of water and ethylene-glycol was used as
coolant. During this test, the module was slightly flushed with dehumidified air through a holeof the frame to avoid condensation. With this (simple) setup, a moderate liquid flow of about
1 mℓ/s could be achieved.
In Table 5.13, the results for the uncooled case and with coolant temperatures of 8.7◦ C and−8.5◦ C, respectively, are compared. Even though sufficient SNR can be achieved by liquid
cooling at a moderate temperature, it is obvious that an improvement of about 20% is possible
with sub-zero temperatures. This result is a good motivation to use a CO2 cooling system as
described in Sec. 5.3.3, even though it is more complex than single-phase liquid cooling. A
dual-phase system would allow us to achieve even lower temperatures, e.g., −20◦ C, by using
very thin tubes, and thus maintaining a small material budget.

5.8

Expected Performance

The design goals of the Belle II SVD and the properties of its components are described in detailin the earlier sections of this chapter. The overall system feasibility was demonstrated by the189CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

coolant flow direction

air temperature sensor

thermal sensors
attached to cooling pipe

Figure 5.45: Origami module with thermal sensors attached to the cooling pipe at three spots.
The fourth probe was used to measure the air temperature inside the module frame.

successful operation of the SVD3 readout system in conjunction with several prototype modules
both in the lab and in beam tests (Sec. 5.7.3). Performance details of key aspects of the future
SVD will be described in the following sections.

5.8.1

Material Budget

To reduce multiple scattering especially for low energy particles, the detector mass needs to be
as low as possible. There is a high component density on the Origami modules, so it is nottrivial to minimize the material budget. Steps to reduce it are to thin out the APVs as wellas the sensors as much as possible. Another factor is the mechanical structure and the cooling
circuit. Both have a large impact and need to be carefully dimensioned in order to keep thematerial budget as low as possible. The sandwich carbon-fiber ribs (SCFR) are a good approachto reduce the budget as well as the use of stainless steel tubes and CO2 as the primary choiceof cooling fluid.
The total average material budget is calculated to be 0.568% X0 over the width of the Origami
module, as listed in Table 5.14. In this calculation, the sensor is the largest component with
0.32% X0 , followed by the copper signal lines (0.068% X0 ), the mechanical structure (0.022% X0 )and cooling.
The averaged material budget was calculated using the formula:
X tm · wm
X0rel =
X0m · wtotalm190

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Layer

Material

SensorIsolation
HybridSiliconRohacell HF 71 (Degussa)
Polyimide (3 layers of 50um each)
Copper (3 layers of 5um each)
Nickel (top: 1.3um)
Flash Gold (top: 0.4um)
Polyimide (1 layer of 25um)
Copper (1 layer of 5um)
Nickel (top: 1.3um)
Flash Gold (top: 0.4um)
Silicon
SMD
Sil-Pad 800 (Bergquist)
Aluminum (D=2.0mm, wall=0.2mm)
Carbon Fibre (0.065mm)
Rohacell HF 71 (Degussa)
Araldite 2011
H2 O

Flexes

10 × APV25
SMDs
Sil-Pad
Pipe
Sandwich
Filling
Glue
Cooling

X0
(mm)
93.7
5450.0
300.0
14.0
14.3
3.4
300.0
14.0
14.3
3.4
93.7
50.0
200.0
89.0
280.0
5450.0335.0
360.5

Thickness
(mm)
0.3
1
0.15
0.015
0.00130.00040.025
0.005
0.00130.0004
0.1
0.4
0.127
0.56
6.5
6.5
0.2
1.26
Total

Averaged
X/X0
0.320%
0.018%
0.022%
0.068%
0.006%
0.007%
0.005%
0.010%
0.002%
0.003%
0.008%
0.002%
0.003%
0.021%
0.010%
0.012%
0.030%
0.021%
0.568%

Table 5.14: Averaged material budget of a single Origami cross section using an aluminum tube
with water cooling. The overall figure becomes 0.548% in case of CO2 cooling.
In this equation, tm (in mm) stands for the thickness of material mm, X0m (in mm) denotes its
radiation length, wm represents its component width, and wtotal is the overall width (59.6 mm).
Table 5.14 uses water as coolant with an aluminum tube. Stainless steel, as used for the CO2
option, has a 5 times smaller X0 (17.55 mm for ANSI 304) compared to aluminum (89 mm); on
the other hand, the steel tubes have a 4 times thinner wall thickness and a 40% smaller diameter.
Taking this into account, the overall material budget for both pipes is about the same, as shownin Tab. 5.15.
Material
Aluminum
Stainless Steel

Dimensions
2 × 0.2 mm2
1.5 × 0.05 mm2Avg. X/X0
0.021%
0.018%

Table 5.15: Material budget comparison for the cooling pipes: aluminum versus stainless steel.
The situation for H2 O and CO2 is slightly different, as CO2 is in a dual-phase state, and thus
the radiation length depends on the location in the tube: at the entrance of a cooling pipe,
the medium is (mostly) liquid and gradually evaporates toward the end of the line, where thecomposition is a mixture of liquid and gas. Assuming a (constant) CO2 temperature of −20◦ C
and an entrance vapor saturation of 8% (corresponding to a density of 400 kg/m3 ), we obtain aradiation length of 905 mm, which is almost three times higher than that of water. At the exit,
we can assume a vapor fraction of 75% (or 75 kg/m3 ), leading to a radiation length of 4827 mm.
In average, the CO2 radiation length is 2464 mm and thus about a factor of seven better thanwater. In addition, the CO2 pipe diameter is a bit smaller, so the contribution of CO2 becomes191

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

negligible compared to water, as shown in Tab. 5.16.
Material
Water
CO2

Cross-Section
2.01 mm2
1.54 mm2

Avg. X/X0
0.021%
0.003%

Table 5.16: Material budget comparison for the coolant: water versus CO2 .
Another issue not considered so far is that pure water cannot be used at sub-zero temperatures,
but needs to be mixed with an anti-freeze agent such as glycol, which has a slightly lower
radiation length than pure water and thus would add a bit to the overall material budget. The
same is true for another commonly used cooling agent, C3 F8 , and that would also require thicker
tubes to achieve higher flow rates in order to achieve the same cooling effect as CO2 .
To summarize the cooling medium discussion, we conclude that CO2 offers the best performance
to material budget ratio, even though the overall material contribution of the cooling is not verysignificant. Future R&D will show whether mixed-phase cooling is worth the effort.
A low level material budget distribution has been prepared for reference, assuming that a particle
traverses the sensors perpendicularly. The result, shown in Fig. 5.46, is calculated taking thedimensional parameters of the main components into account. The distribution of the material
budget appears quite inhomogeneous at perpendicular view, which in reality will be far lesssevere. Due to the curved particle trajectories and the small carbon-fiber layer width, it is very
unlikely for a particle to completely traverse the thin 3% X0 peaks. This leads to the conclusionthat further homogenization of the cross section—such as distributing the support structure overthe sensor width instead of having SCFR—will not be necessary to obtain good physics results.

Figure 5.46: Detailed material budget distribution along the cross-section of the module.
The integration of the Belle II SVD mechanics in the simulations for the material budget X/X0
vs. pseudorapidity η = − ln[tan(θ/2)] is currently under way. Preliminary results in Fig. 5.47
show the full integration of the beam pipe and the PXD as well as the active area (silicon sensors
only) of the SVD. “Blind” material such as the structure and readout electronics have yet to be
192

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

added to the simulation, thus it is likely the SVD contribution will nearly double.
0.10

Material budget studies - TrkBelleII_PXD075um1600_R14

0.09

X/X 0

0.08

Beam pipe

0.07

Beam pipe + PXD

0.06

Beam pipe + PXD + SVD

0.05
0.04
0.03
0.02
0.01
0.00
-1.0

-0.8

-0.6

-0.4

-0.2

0.0
cos(J)

0.2

0.4

0.6

0.8

1.0

Figure 5.47: Material budget (SVD: sensors only) vs. cos(θ) = tanh(η). The forward region
extends to cos(17◦ ) = 0.96, while the backward acceptance is limited to cos(150◦ ) = −0.87.

5.8.2

Intrinsic Resolution

The intrinsic resolution as well as occupancy of the future vertex detector—PXD and SVD—hasa natural impact on tracking and vertexing efficiency, and thus on the overall physics performance. In particular, high resolution in z is very important. On the other hand, too precise
a geometrical resolution, which is correlated with the number of read-out channels, may automatically lead to big cluster sizes and thus to high occupancy. This would lead to more SVD
ghost-hits (mismatched 2D spatial information combined from r–φ and z channels in doublesided strip detectors).
To determine the expected Belle II SVD resolution, cluster sizes, impact parameter resolution,and vertex resolution, several full simulation studies have been performed. The full simulation
chain consists not only of detailed implementation of the PXD and SVD geometries in the
Geant4 toolkit (as well as the SVD2 geometry for comparison), but also of the simulation of
all in-detector physics processes (i.e., signal processing and digitization) that typically occur insuch detector devices. As the design is still ongoing, not all the parameters are known; thus,
typical values have been used instead. For more details, see the simulation section in Ch. 14.
The expected intrinsic SVD resolutions in both r–φ and z directions are shown in Fig. 5.48 andthe cluster sizes in Fig. 5.49 as a function of the particle incident angle in the forward region.
All results are symmetric around 90 degrees (which denotes the radial direction), except for theslanted sensors in the forward region which have no such counterpart in the backward side. The
increase of spatial resolution in z towards 90 degrees is due to the fact that there is a probabilityof single-strip clusters with such perpendicular hits and thus the exact hit position cannot be
193

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

determined due to the absence of charge sharing among neighboring strips. The detailed studiesof impact parameter resolution as well as vertex resolution for the Belle tracker (SVD2 andCDC) and the Belle II tracker (PXD, SVD, and CDC) are presented in Sec. 4.11.
SVD Resolution (RMS90) in R- Φ

SVD Resolution (RMS90) in Z

20

50
Belle II - Baseline
1st layer
2nd layer
3rd layer
4th layer

Spatial Resolution [ µm]

16
14

40

12
10
8
6

35
30
25
20
15

4

10

2

5

0
10

20

30

40

50 60
ϑ [deg]70

80

Belle II - Baseline
1st layer
2nd layer
3rd layer
4th layer

45
Spatial Resolution [ µm]

18

0
10

90

20

30

40

50 60
ϑ [deg]

70

80

90

Figure 5.48: Expected intrinsic resolution in r–φ and z direction for 0.5 GeV single muons.

SVD Cluster size in R-Φ

SVD Cluster size in Z

10

10
Belle II - Baseline
1st layer
2nd layer
3rd layer
4th layer

9887Cluster size

Cluster size

7
6
5
4

6
5
4

3

3

2

2

1

1

0
10

20

30

40

50 60
ϑ [deg]70

80

Belle II - Baseline
1st layer
2nd layer
3rd layer
4th layer

9

0
10

90

20

30

40

50 60
ϑ [deg]

70

80

90

Figure 5.49: Expected cluster sizes in r–φ and z directions for 0.5 GeV single muons.

5.9

Software

5.9.1

OnlineThe Belle II SVD online software duties consist of online control systems, data acquisition andmonitoring. Online alignment and track finding is managed by the tracking group since it is an
issue common for all three tracking detectors.
194

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

Cooling system
Temperature &flow monitor

Hard-wired
interlock signal
Control

CDAQ (central
data
acquisition)

Monitor

SVD SCS (slowcontrol system)

SVD power
supplyBuilt-in over-voltage andover-current protection

Humidity sensor

FADC+PROC &FTB control

I2C line

APV25
HybridtemperaturemonitorFigure 5.50: Block diagram of the slow control system of the Belle II SVD.

5.9.1.1

Control

The online control system of the Belle II SVD will be based on the SVD2 online control scheme.
It includes the DAQ control (start, stop and pause of the local SVD DAQ), SVD low and highvoltage control and a restart procedure of the SVD subsystem. These functions have to be
integrated with the central data acquisition system (CDAQ) of Belle II.
The function of the SVD slow control system (SCS; Fig. 5.50) is to run the SVD according tothe operation mode of the Belle II CDAQ. SCS has software links to CDAQ, FADC+PROC,FTB, COPPER, FINESSE, SVD power supplies, the monitor system of the cooling system aswell as front-end temperature and humidity sensors. A typical data acquisition is initiated asfollows. CDAQ sends the “run start” signal to each detector subsystem. SCS first turns on
the low voltage power supply (LVPS) for the APV25 chips and the initialization of APV25
is done using the I2 C link via the FADC+PROC boards. Once the APV25 chips are active,
SCS ramps up the the bias voltage for the DSSD sensors. In parallel, the initialization of DAQ
system (FADC+PROC, FTB and Finesse boards) will be done. The SVD then becomes ready toaccept the trigger signal from the global trigger decision logic (GDL). Once the data acquisition
is started, SCS samples monitor data from FADC+PROC and FTB in order to confirm thehealthy operation of the Belle II SVD. In addition to the CDAQ, the SVD stand-alone dataacquisition for debugging and calibration of SVD is done under the control of SCS.
Another function of the SCS is to protect the Belle II SVD from hardware problems. In particular, a failure of the cooling system can potentially destroy the SVD system in a short time.
Therefore, the SVD power supplies should be shut down immediately if such a problem occurs.
For this purpose, the SCS continuously monitors the temperature and flow rate of the coolant.
In addition, the humidity in the detector region is measured in order to protect the SVD fromdew or moisture following a failure of the dry air system. The temperature of the hybrid will bemonitored in order to detect blocking of coolant flow in the front-end circuit. If any anomalous
behavior is detected, the SCS will shutdown the SVD power supplies and inform CDAQ thatthe data acquisition has to be stopped due to a SVD problem.
195

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

A hard-wired interlock will also provided in order to protect the Belle II SVD even if the SCS
software is not working properly. The relay output of the cooling system failure should bedirectly connected to the shutdown input of the SVD power supplies. These supplies must also
have internal over-voltage and over-current protection to prevent damage to the front-end incase of anomalous function.
5.9.1.2

Data Acquisition

The data acquisition scheme is presented in Sec. 5.4.4. After processing and sparsification, thedata will be sent via optical links to the common Belle II data acquisition system. In addition,
we should be able to provide the SVD information for PXD online data reduction. Several
possibilities are under investigation: dedicated FPGA based boards (a.k.a. the Giessen box),
CPU-based boards in which Belle II SVD-only hits will be used to find a track and then be
extrapolated to the PXD detector, or eventually at the online farm level where dedicated GPU
boards can find and extrapolate tracks based on Belle II SVD and CDC information. The
tracking group is studying the track finding algorithm schemes.
5.9.1.3

Monitoring

Belle II SVD monitoring tasks include the observation of radiation levels, temperatures, humidity
values and detector leakage currents. These issues are introduced in Sec. 5.5. In addition,
we monitor average occupancy as well as noise and pedestal levels for every readout channel.
The necessary procedures will be implemented to measure and monitor those properties. The
occupancy level can be obtained directly from the data during a normal run. Pedestals andnoise levels will be obtained for each channel during startup of a run (as this is necessary toprogram the threshold memories in the FADC+PROC boards), but they could also be extracted
regularly in a special procedure when we will be able to read data without zero suppression.
This should be done automatically as often as possible without interfering with normal datataking and would allow to monitor changes in running conditions and the eventual appearanceof problematic channels to be masked from further analysis. The task of online software will beto store necessary information in the Belle II database.

5.9.2

OfflineThe Belle II SVD offline software tasks include internal alignment of the detector, local patternrecognition and track reconstruction, and the implementation of the SVD into the Belle IIdetector simulation software.
5.9.2.1

Alignment

SVD alignment corrects the detector geometry for small misplacements of the sensitive elementsin the detector. The actual sensor positions can be determined in the lab by a mechanical survey
but the ultimate precision of the device can only be achieved with track-based alignment.
An alignment procedure for the Belle II SVD is now under development. First studies haveused the Millipede/Millipede II algorithm [23] and cosmic muons. Possible worries are therequired frequency of the realignment procedure which depends on the mechanical stability ofthe mounting. Another issue are the so-called weak modes, i.e., parameters that are only weakly
constrained by the alignment procedure but that might bias the physics output. Ultimately, it
would be desirable to have several alignment methods for debugging and cross-validation.

196

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.9.2.2

Local reconstruction

This task involves decoding of the raw data, clustering, and calculation of the hits in each Belle II
SVD layer. These hits are associated into track candidates for global track finding.
For the latter, an “inwards/outwards” strategy is currently under study: track candidates in the
CDC are extrapolated inwards to the SVD and hits which can be associated to a track candidate
are removed. The remaining hits are searched for low momentum track candidates.
5.9.2.3

Simulation

The simulation task includes the implementation of the Belle II SVD geometry into the Geant4based detector simulation software. The task of the SVD-specific software is also to simulate thein-detector physics processes and the detector electronics, taking into account the magnetic field(i.e., charge collection, signal processing, and digitization). This simulation includes the drift ofthe electron-hole pairs in the silicon, the collected charge at each strip, and random noise.

5.10

Organization

5.10.1

Institutes and Responsibilities

The design of the Belle II SVD has been established by discussion among the following institutions (in alphabetic order):• HEPHY (Vienna, Austria)• Jozef Stefan Institute (Ljubljana, Slovenia)• Karlsruhe Institute of Technology (Germany)• KEK (Tsukuba, Japan)• Kyungpook National University (Daegu, South Korea)• Max-Planck-Institut für Physik (Munich, Germany)• University of Melbourne (Australia)• Henryk Niewodniczanski Institute of Nuclear Physics (Krakow, Poland)• Niigata University (Japan)• University of Nova Gorica (Slovenia)• University of Sydney (Australia)• Tata Institute of Fundamental Research (Mumbai, India)• Tohoku University (Sendai, Japan)• University of Tokyo (Japan)
As shown in Sec. 5.10.2, the critical path of this project is the ladder assembly, which requires
skillful handling of fragile sensors with high precision. The ladder assembly will be shared byseveral institutes. The final ladder mounting to the support system and system test will bedone at KEK and thus we need to concentrate the human resources at the last stage of theconstruction in KEK.
197

CHAPTER 5. SILICON VERTEX DETECTOR (SVD)

5.10.2

Schedule

The schedule of the Belle II SVD construction is shown in Fig. 5.51. We assume that the
production of DSSD sensors starts from the second half of 2010. The critical path in the present
schedule is whether enough parts can be prepared for the ladder assembly in 2011. Anothercritical path is the preparation of the support system, also scheduled in 2011. Once laddermounting is finished, the next important step is the system test, where the whole Belle II
SVD system (ladder, data acquisition and cooling system) will be integrated and the overall
performance is examined before the system is installed to the Belle II structure.
Depending on the readiness of the pixel detector, an integration test will be also necessary.
Once the SVD system is installed, further tests with other subdetectors and the trigger and
DAQ systems will be done before the beam operation starts.
The Belle II SVD will be installed within the CDC in November 2013. The information fromthe SVD will be helpful for the accelerator commissioning, scheduled for April 2014.

5.10.3

Summary

The Belle II Silicon Vertex Detector will consist of four layers of double-sided silicon detectors
made from six-inch wafers. The SVD layers are located at radii of 38, 80, 115 and 140 mm fromthe beam pipe, between the PXD and the CDC.
In order to cope with the 40-fold increase in luminosity, the Belle II SVD will use the APV25
readout chip with a shaping time of 50 ns, which will, together with online hit time reconstruction
at a precision of 2 . . . 4 ns, give an occupancy of a few percent at most. Eighty “FADC+PROC”
9U VME modules, distributed over five crates, will be connected to the front-end, providing
both controller and readout functionality.
The front-end modules will be cooled either by CO2 or by a conventional single-phase liquid
system. Much effort is put into the design of the mechanical structure as well as the routing ofcables and pipes in a very compact space.
The “Origami” chip-on-sensor concept has been proposed for the construction of modules toensure low-mass readout, achieving an averaged material budget of only 0.57% X0 (or 0.55% X0
in case of CO2 cooling), while maintaining a good cluster signal-to-noise ratio in the range of
12 . . . 18 despite of using large sensors. As each sensor will be read out individually, the total
number of readout chips will be 1902, more than double the number in the Belle SVD2.
Fully functional prototypes of detector and electronics components have been built and tested,
including a four-inch wafer Origami module that performed well in the lab and in a beam test.

198

Name

2010

Work
Q2

Overall design

35d

DSSD

750d

DSSD test production

170d

DSSD evaluation with Origami

60d

DSSD order

10d

DSSD delivery

510dPhase 1120d

Phase 2120d

phase 3120d

phase 4 (spare)

150dHybrid20d

Test with existing dssd

150d

Origami design

70d

PCB Production and test assembly

40d

Origami Long Prod.

100d

Origami Middle Prod.

100d

Origami Short Prod.

100d

Normal Narrow Prod.

100d

Normal Wide Prod.

100d

Ladder assembly

1030d

Assembly Jigs

300d

Parts production

300d

Test Assembly

60d

Evaluation

50d

Ladder Production

320d

Layer 1 Ladder

50d

Layer 2 Ladder

60d

Layer 3 Ladder

90d

Layer 4 Ladder

120d

200d

Test

50d

Production

250d

Power supply

350d

Design100d

Production

250d

250d

Test with prototype ladders

50d

Production

250d

test

30d

Cooling

500d

Scheme R&D

150d

Design50d

Production

250d

Test

50d

Monitors

750d

Design200d

Production (Sensor)

200d

Production (DAQ)

200d

Monitor test

50d

Installation to Support system

50d

Installation to IP chamber

50d

Ladder mount

270d

Preparation

20d

Layer1 mount and test

50d

Layer 2 mount and test

50d

Layer 3 mount and test

60d

Layer 4 mount and test

60dCompletion and test

30d

IP chamber preparation

760d

design360d

Production

400d

Q3

Q4

Q1

2012
Q2

Q3

Q4

Q1

2013
Q2

Q3

Q4

Q1

130d

Assemble IPC+PXD+SVD

40d

Connect cables and tubes

30dLong term operation

60d

Operation in Belle

77d

Install to Belle

10d

Connecting tubes and cables

20d

Turn on power

7d

Cosmic ray test

40d

Belle Roll IN

2011
Q2

580d

Prototyping

System test

Q1

500d

Test production

FADC DAQ

Q4780d

APV25 purchase

Support system

Q3

10d

Figure 5.51: The schedule of the Belle II SVD construction.

2014
Q2

Q3

Q4

Q1

References[1] Ideas ASA, VA1TA Manual Version 0.9, 2001.
[2] K. Abe et al., KEK Report 2004-4 (2004).
[3] M. French et al., Nucl. Instrum. Meth. A 466, 359 (2001).
[4] S. Ramo, Proceedings of the I.R.E. 27, 584 (1939).
[5] BELLE SVD Group, Technical Design Report of BELLE SVD, 1998.
[6] Y. Iwata et al., IEEE Transactions on Nuclear Science 45, 303 (1998).
[7] S. Stanic et al., Nucl. Instrum. Meth. A 545, 252 (2005).
[8] S. R. Finn, Y.-F. He, and G. S. Springer, Composite Structures 23, 191 (1993), DOI:
10.1016/0263-8223(93)90222-C.
[9] I. Bakos and S. Szab, Corrosion Science 50, 200 (2008), DOI: 10.1016/j.corsci.2007.06.002.
[10] Momentive Performance Materials Inc.,TPG Thermal Management Material,
http://www.advceramics.com/downloads/documents/85505.pdf, 2007.
[11] C. Irmler, M. Friedl, and M. Pernicka, TWEPP-09 CERN-2009-006, 211 (2009).
[12] S. König et al., Nucl. Instrum. Meth. A 582, 776 (2007), VERTEX 2006 - Proceedings ofthe 15th International Workshop on Vertex Detectors, DOI: 10.1016/j.nima.2007.07.090.
[13] S. Gadomski et al., Nucl. Instrum. Meth. A 320, 217 (1992).
[14] N. Boetti, P. Jarron, B. Kisielewski, and F. Faccio, IEEE Radiation Effects Data Workshop
2002 IEEE, 115 (2002).
[15] M. Friedl, C. Irmler, and M. Pernicka, Nucl. Instrum. Meth. A 569, 92 (2006).
[16] A. Holmes-Siedle, Nucl. Instrum. Meth. 121, 169 (1974).
[17] J. Kaneko et al., IEEE Transactions on Nuclear Science 49, 1593 (2002).

[18] M. Raymond, APV25 Power Consumption, http://www.hep.ph.ic.ac.uk/~dmray/pdffiles/Detailed%2006.
[19] M. Friedl, C. Irmler, and M. Pernicka, TWEPP-08 CERN-2008-008, 277 (2008).
[20] M. Friedl, APVDAQ Reference Manual, http://apvdaq.hephy.at, 2009.

200

REFERENCES[21] C. Irmler, Upgrade Studies for the Belle Silicon Vertex Detector, Master’s thesis, Vienna
University of Technology, 2008.
[22] M. Friedl, C. Irmler, and M. Pernicka, TWEPP-09 CERN-2009-006, 417 (2009).
[23] V. Blobel and C. Kleinwort, (2002), hep-ex/0208021.

201

Chapter 6

Central Drift Chamber (CDC)
6.1

Overview

In the Belle II detector, the central drift chamber (CDC) plays three important roles. First,
it reconstructs charged tracks and measures their momenta precisely. Second, it provides particle identification information using measurements of energy loss within its gas volume. Lowmomentum tracks, which do not reach the particle identification device, can be identified using
the CDC alone. Finally, it provides efficient and reliable trigger signals for charged particles.
As described in the LOI [1], the Belle CDC has worked well for more than ten years without any
serious problems. Therefore, the Belle II CDC follows the global structure of its predecessor forthe material of the major parts, the superlayer wire configuration, the cell structure, the wirematerial, and the gas mixture. The main parameters are listed in Table 6.1, together with thoseof the Belle CDC for comparison. The main differences between the two designs are describedin the following paragraphs.
Table 6.1: Main parameters of the Belle CDC and the CDC upgrade for Belle II.
Radius of inner cylinder (mm)Radius of outer cylinder (mm)Radius of innermost sense wire (mm)Radius of outermost sense wire (mm)Number of layers
Number of sense wires
Gas
Diameter of sense wire (µm)

Belle
77
880
88
863
50
8,400
He–C2 H630

Belle II
160
1130
168
1111.456
14,336
He–C2 H630First, the new readout electronics system must handle higher trigger rates with less deadtime.
The front-end electronics are located near the backward endplate and send digital signals to theelectronics hut through optical fibers. The front end uses a new ASIC chip that incorporates anamplifier, shaper, and discriminator. The drift time is measured with a TDC that is implemented
in an FPGA. A slow FADC (around 30 MHz) measures the signal charge, and is controlled by
the same FPGA. The ASIC chips, the FADC, and the FPGA are mounted on a single board,which is described in Sec. 6.4.
Second, to avoid the high-radiation and high-background region near the interaction point and202

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

to provide more space for the SuperSVD, the CDC inner radius is 160 mm. Since the Belle IIbarrel particle identification device is more compact than in Belle, the CDC outer radius is1130 mm (tentative value). A new wire configuration fills the modified volume.
Third, the CDC generates three-dimensional trigger information. A z trigger for charged particles is essential to reduce background without sacrificing physics events. In the original Belle
CDC, there was a cathode chamber with three strip layers in the innermost region [2]. Thischamber reduced the charged trigger rate by a factor of three. When the SVD2 was installedin Belle, the cathode chamber was removed to make space. In principle, the SVD2 would havebeen able to provide the z-trigger information. Fortunately, the charged-track trigger rate waslow enough that this was not needed for background suppression. However, we expect that theavailability of a z trigger will be important for Belle II, particularly during the early stages when
the beam backgrounds are expected to be high. The z trigger will be based on a 3D tracking
method implemented in an FPGA using axial and stereo wires. (Charge division between thetwo ends of a sense wire is a possible alternative to provide the z information.) This approachis robust against high beam background and does not require additional material. The 2D and3D charged-track triggers are described in Ch. 12.

6.2

Structure

6.2.1

Wire configuration

We retain the square cell and the superlayer wire configuration of the Belle CDC. There are
six layers in each superlayer to make track segment finding easier; this is particularly valuablefor the stereo superlayers. (There are only 3 or 4 layers in a Belle stereo superlayer.) The
innermost superlayer has two additional layers that contain active guard wires. Even though theperformance of these two layers is compromised by the high occupancy from beam backgrounds
and the wall effect, the remaining six layers ensure that the innermost superlayer performs
as well as the others. The innermost and outermost superlayers contain axial (“A”) layers, tomatch the shape of the inner and outer cylinders. The intervening superlayers alternate between
stereo (“U” or “V”) and axial layers. In total, there are 9 superlayers (AUAVAUAVA) and 56
layers. The radial cell size is 10 mm for the innermost superlayer and ∼ 18.2 mm for the othersuperlayers.
From the trigger group’s simulation studies of the 3D trigger, they find a better z resolution using
an alternate wire configuration (AUVAUVAUVA) in which the stereo superlayers are adjacent.
If this result is confirmed and is essential for the z-trigger performance, we will re-consider theoverall wire configuration. In addition, the barrel PID group will soon decide the final PID
configuration, which will allow the outer radius of the CDC to be fixed. It is likely that the final
wire configuration will be slightly modified as a result.
The number of cells in each layer is chosen according to the following considerations. We
require multiples of 32 to match the number of electronics channels and trigger segments. For
the innermost superlayer, a smaller azimuthal cell size is required to reduce the occupancy inthe face of the large beam background. The lower limit is determined by the size of the feedthroughs. The optimal configuration has 160 cells are selected with the minimum azimuthal cellsize of only 7 mm. To realize such a small cell size, the innermost superlayer is implemented
separately as a so-called small-cell chamber that is then attached to the rest of the CDC. The
overall wire configuration is shown in Table 6.2 and Fig. 6.1.
The stereo angles are listed in Table 6.2. A larger stereo angle provides better z resolution,
but a large variation in the radial cell size along the z direction occurs in the boundary region
203

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Table 6.2: Configuration of the CDC sense wires.
superlayer
type and No.
Axial 1
Stereo U 2
Axial 3
Stereo V 4
Axial 5
Stereo U 6
Axial 7
Stereo V 8
Axial 9No. oflayers
8
6
6
6
6
6
6
6
6

Signal cells
per layer
160
160
192
224
256
288
320
352
384

radius(mm)
168.0 – 238.0
257.0 – 348.0
365.2 – 455.7
476.9 – 566.9
584.1 – 674.1
695.3 – 785.3
802.5 – 892.5
913.7 – 1003.7
1020.9 – 1111.4

Stereo angle(mrad)
0.
45.4 – 45.8
0.
-55.3 – -64.3
0.
63.1 – 70.00.
-68.5 – -74.0
0.

Figure 6.1: Wire configuration of the Belle and Belle II drift chambers.
between axial and stereo superlayers. To obtain a 60 mrad stereo angle, a special technique isadopted without adding insensitive regions: we string field wires in the transitions with half ofthe stereo angle and we adjust the radial positions at both endplates around the transitions.
The same method is used in the Belle CDC [3]. The sense wire is only ∼ 1 mm closer to thefield wire in this case, so that a large gain variation is avoided.
The sense and field wire properties and counts are shown in Table 6.3. The properties are
inherited from the Belle CDC, where there were no serious problems during more than ten yearsof operation. The counts are about a factor of 1.7 greater than in the Belle CDC. The 30 µmdiameter sense wires will operate at a slightly higher operating voltage so that the stronger
electric field in the drift region reduces the maximum drift time. The aluminum field wires are
unplated to avoid unnecessary material and to lower the cost.

204

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Table 6.3: Wire parameters in the CDC.
Material
Plating
Diameter (µm)
Tension (g)Number of wires

6.2.2

Sense
TungstenGold
30
50
14,336

Field
AluminumNo
12680
42,240Mechanical design

There are three main structural components of the CDC (Fig. 6.2): a thin carbon-fiber reinforced
plastic (CFRP) inner cylinder, two aluminum endplates, and a CFRP outer cylinder similar tothe one in the Belle CDC.

Figure 6.2: Main structure of the CDC.
The outer cylinder, with a thickness of 5 mm, supports most of the wire tension of about 4 tonnes.
The inner cylinder should be thin (0.5 mm thickness) to minimize material, but it should also
support the wire tension for the small-cell chamber (i.e., the innermost superlayer), which has
its wires strung independently before installation into the main chamber. Tapered aluminum
endplates are used for the outer region to reduce the deformation caused by wire tension, while
conical aluminum endplates are used for the inner region to match the detector’s polar angular
acceptance of 17◦ –150◦ . (The endplates of the small-cell chamber are conical as well.) The
tapered shape in the outer region reduces the deformation by a factor of two compared to the205CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Belle CDC.
As shown in Fig. 6.3, a step structure is machined in all three endplate sections to allow easierand more precise drilling of the many holes for the wire feedthroughs. This avoids the difficulty
encountered in the Belle CDC, where it was quite hard and time-consuming to drill the holes
through the long depth in its conical endplate. The step structure here gives a drilling depth of
10 mm for every endplate section; this is shown in Figs. 6.3 and 6.4.
The endplates for the main and conical parts are machined and drilled separately. Just before
the wire stringing, the two parts bolted together, as shown in Figs. 6.3 and 6.5. The forwardand backward-connected endplates are attached on the outer CFRP cylinder (Fig. 6.3), at whichtime these endplates are precisely aligned.

Figure 6.3: Close-up view in the connection region between the outer cylinder and the main
endplate.

Figure 6.4: Close-up view around the small cell chamber.
The tension for the sense wires is the same (50 g) as in the Belle CDC. However, the tension
206

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Figure 6.5: Close-up view around the connection region between the main and conical endplates.
of the field wires is reduced to 80 g from 120 g to reduce the deformation of the endplates. The
gravitational sags for the sense and field wires differ by 85 µm. We estimated the maximum
distortion in the x–t relation function using a Garfield simulation, and found a difference of at
most 20 µm at the cell edge. The total wire tension is 4.1 tonnes (vs 3.4 tonnes for the Belle CDC).
Using this wire tension and the described structure, a Finite Element Method calculation showsthat the maximum stress of 31 MPa at outer edge of the endplate is smaller than the allowed
limit of 107 MPa. In addition, the maximum deformation is 3 mm (vs 4 mm for the Belle CDC)
at the inner edge of the endplate. We take account of this deformation in the design of the small
cell chamber. Pre-stressing of the endplates is necessary when stringing the wires for the mainand conical parts. The thin CFRP inner cylinder supports 370 kg of wire tension, which is afactor of six lower than the buckling load of 2300 kg.
The wire stringing is performed separately for the main chamber (including its conical part)and the small-cell chamber. The small-cell chamber has no outer cylinder and is small, so it
is easy to string its wires horizontally from the inside on a table without any special jigs. The
wire stringing for the main chamber is more challenging. The outer cylinder, already in place
during the stringing operation, is constructed in one piece to be strong enough to support thelarge wire tension and to maintain the operating gas pressure absolutely constant. However, weneed to observe directly each wire as it is being strung. We will string the wires vertically fromthe outside, while a person stands inside the chamber to observe each wire as it placed and to
make any needed adjustments.
The feedthrough is used to fix the wires and to ensure insulation between the wire’s high voltage
and the endplate’s ground. The shape of the feedthrough is the same as in the Belle CDC.
However, the feedthrough material is changed from Delrin to Noryl due to the latter’s morereliable insulation performance at high voltage. Noryl is used successfully in the Belle small-cellchamber, installed in 2003. For our small-cell chamber, we do not have enough space to use
feedthroughs for the field wires: only aluminum pins are used to hold the wire tension. The pin
is attached directly on the endplate, as was done in the Belle small-cell chamber.
There is space between each endplate and its thin aluminum cover to contain the feedthroughs,
high voltage cables, signal cables, and readout electronics. All front-end electronics are locatedon the backward side to reduce the material in the forward side. The forward side is used only207

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

for the connection of high voltage cables. If we adopt the charge-division method for the z
trigger, a small amount of additional electronics will be located on the forward side, but justoutside the detector acceptance.
The CDC is supported by the outer detector. We are considering a huge cylinder, like the Belle
inner detector support (IDS), for the forward side. It connects the CDC forward endplate to theforward inner-detector support flange, which is located inside the barrel ECL’s inner cylinder.
For the backward side, the support of the CDC is slightly more complicated. A similar backward
support cylinder is connected to the CDC backward endplate prior to installation. The outerradius of this support cylinder is smaller than inner radius of the barrel PID. This support
cylinder is attached to the backward inner-detector flange though several separate jigs just after
the CDC has been installed. The details will be fixed after the barrel PID option is selected.

6.3

Gas system

We would have preferred to use a new gas mixture with faster drift velocity to reduce themaximum drift time in each cell. Several candidates have been studied, but none has beenfound that is better than the Belle gas mixture of 50% helium – 50% ethane, so we will use this.
Its performance has been established in the Belle CDC: low radiation length, good position
resolution, good energy loss resolution, low cross section for synchrotron radiation X-rays, andlittle radiation damage.
The gas distribution system will be similar to that used in Belle. Separated pure-gas bottles
are located in a gas stock room. Gas mixing is performed using two mass flow controllers in aroom on the ground level. The mixed gas is fed into the detector through a gas system thatis located on the roof of the electronics hut. The gas system consists of a circulation pump,flow controller, pressure controller, and oxygen filter (Fig. 6.6). A relatively modest flow rate
(2 ℓ/min, which corresponds to one volume every two days) is necessary to remove oxygen fromthe CDC gas volume. Fresh gas is fed in at only 1/10 of the circulation flow rate to reduce cost.
An oil free metal bellow pump maintains the gas circulation; the existing pump has been used
for more than ten years without any problem. A small amount of hydrogen gas is mixed into
the oxygen filter as a platinum catalyst.

Figure 6.6: Gas system for the CDC.
208

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

6.4

Readout electronics

6.4.1

Overview

The CDC front-end readout system is comprised of front-end digitizer boards on the CDC
endplate and signal/power distributors. Requirements for the system are listed in Table 6.4.
The system transfers digitized analog signals and associated timing signals to the DAQ systemin the electronics hut via the Rocket IO link. Synchronization signals (i.e., trigger, system
clock, event tag, etc.) from/to the DAQ system are fanned out on signal/power distributors andtransferred to each front-end-digitizer board via Rocket IO. The front-end-digitizer boards aremounted near the CDC endplate to reduce channel-to-channel cross-talk, cross-talk from othersubdetector systems, and the number of cables to the electronics hut.
Table 6.4: Requirements for the CDC front-end readout system.
Number of channels
Total channel
Board size
Trigger latency
Single channel hit rate
Dynamic range
Timing resolution
Voltage resolution
IO interface

6.4.2

48 ch/board
15k
15 × 30 cm2
5 µs max< 1 MHz (average)
2 pC max
1 ns
10 bits for 2 pC
Rocket IO

Front-end digitizer board

The block diagram of the digitizer board is shown in Fig. 6.7. The board consists of front-end
ASICs (DC-FEAT), ADC, DAC, FPGA and Rocket IO links. Six DC-FEAT (Drift Chamber
FrontEnd for Analog and Timing measurements) ASICs process the current signal from thedrift chamber to optimize several requirements: signal-to-noise ratio, dynamic range, timing
resolution, and power consumption. After the analog output is digitized by a 10 bit 30 MHz
ADC, the digital data are fed into a ring buffer in the FPGA. In parallel, after the timing signal
from the DC-FEAT is fed into a TDC with 1 ns resolution in the FPGA, the digitized timing
data is stored in the ring buffer. A trigger from DAQ system asserts data transfer from the ringbuffer to a local readout buffer. In the local buffer, data suppression and formatting are done tominimize deadtime during the Rocket IO data transfer to the electronics hut. In the alternate
data acquisition mode, all data in the ring buffer is transferred directly to the electronics hut
for detector calibration and debugging. In both cases, the DAQ system can control the buffer
depth to keep data during the trigger decision and an acquisition window for ADC data via
Rocket IO.

6.4.3

ASIC design

Figure 6.8 shows a block diagram of the CDC front-end electronics. The output of the preamplifier (operating in current mode) is split into two signals. One is for a shaper to measure dE/dx
and the other is for a comparator to measure the timing. The gain for the analog measurement

209

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Figure 6.7: Block diagram of the CDC readout system.
is designed to maintain a dynamic range of 2 pC, while the gain for the comparator is set to
optimize overdrive characteristics and reduce power consumption as shown in Fig. 6.9.

Figure 6.8: Block diagram of the CDC front-end electronics.
The overdrive characteristics of the comparator in the simulation are shown in Fig. 6.10. The
simulation shows that the time walk is less than 500 ps, which is sufficient for our application.
The specification of the DC-FEAT is summarized in Table 6.5. The DC-FEAT was developed byusing the NJR 0.8 µm BiCMOS process. The transition frequency of the NPN (PNP) is 8 GHz(5.5 GHz). The layout of the chip and its package are shown in Figs. 6.11 and 6.12.

6.4.4

System and FPGA design

A prototype board was developed to test the functionality of the CDC front-end readout systemand to confirm operation of the whole system with a CDC prototype chamber. Figure 6.13 shows210

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Figure 6.9: Expected pulse shape with electronics circuit simulation.

Figure 6.10: Overdrive characteristics for the comparator.
the prototype board. ASB (Amplifier Shaper Buffer) chips are used instead of DC-FEATs in the
prototype. Although there are some differences between the specification of the ASB and therequirements for DC-FEAT (i.e., the number of channels in a chip, absence of a discriminator,etc.), we developed a daughter board to meet our requirements. Figure 6.14 shows the analog
output from the daughter board. We furthermore use SiTCP (an Ethernet processor) instead ofRocket IO for the data transfer, since there was no specification for the data transfer interface
at the time of the production of our prototype board. We tested the entire functionality—
including the digital data transfer for the trigger system—with the drift chamber except for thedata transfer link. The data acquisition sequences are shown in Fig. 6.15. As already mentioned,
two acquisition modes are implemented in the FPGA and were tested using a 100 Mbps Ethernet
interface.

211

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Table 6.5: Specification of the CDC front-end ASIC.
Signal processing
Gain for analog measurement
Analog output
Dynamic range
Gain for timing measurement
Overdrive voltage for ≥ 10 mV
Digital output
No. of channels
Chip size
Process

1/t cancellation
1.1 V/pC
Single ended (8 mA max)
2 pC
15 V/pC≤ 400 ps
CMOS (single/differential)
8
4 × 4 mm2
NJR 0.8 µm BiCMOS

Figure 6.11: Layout of the ASIC chip.

6.4.5

Schedule

The first production prototype will be tested with the CDC prototype by the middle of 2010.
At that time, we will determine where modifications of the DC-FEAT specification (i.e., gain
and shaping time) are necessary. The production of the DC-FEAT will be finished by theend of FY 2010. In parallel, we will determine the number of links for trigger data transfer
and the specification of DAQ interface in detail by the end of FY2010. We will be ready formass-production at the beginning of FY2011.

212

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Figure 6.12: Photo of the prototype ASIC chip.

Figure 6.13: Prototype for the CDC readout electronics board.

6.5

Beam Test for a Prototype readout board

A test was carried out at the Fuji test beam line of KEK, using a 2 GeV/c electron beam to
study the performance of the prototype board. The readout board was connected to the test
chamber, which is about 30 cm long and has five layers. The cell size is 15 × 15 mm and thewires are the same as those in the Belle CDC. A 50% helium – 50% ethane gas mixture is used.
The sense wire high voltage of 2.3 kV was adjusted to obtain the same gain as is typical in the
Belle CDC. The chamber and board were operated without any magnetic field. Figure 6.16 is aschematic view of the setup on the beam line.

213

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Figure 6.14: Pulse shape for the prototype CDC ASIC chip.

Figure 6.15: Data acquisition time sequence.

6.5.1

Specification

The board has an analog pre-amplifier and signal shaper, a 30 MHz sampling FADC, and a
1 ns-resolution TDC, which is implemented in an FPGA. Fast Ethernet is used for the datatransfer.
6.5.1.1

Readout mode

The board has two readout modes, raw data mode and suppressed data mode. The raw data
mode was used for debugging and an initial test: all ADC and TDC data are transferred. The
suppressed data mode is the normal mode of operation. Summed ADC and TDC data aretransferred if a requirement is satisfied. The sparsified data size is small, typically several tensof bytes.

214

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Readout Board

Beam

Trigger Counter 2
Test Chamber
Trigger Counter 1
Figure 6.16: Beam test setup at Fuji test beam line, with a 2 GeV/c electron beam. Trigger
counter 1 is a plastic scintillator and a PMT; Trigger counter 2 is lead glass and a PMT.

Performance

6.5.2.1

Efficiency

Efficiency

6.5.2• Layer 2
N Layer 3
 Layer 4

HV[kV]

Figure 6.17: Efficiencies for layers 2, 3 and 4 as a function of high voltage.
Figure 6.5.2.1 shows the efficiency curves for layers 2, 3 and 4 as a function of the high voltage.
Two outer-layer hits are required in the calculation of the efficiency. The efficiency is adequate
in the region above 2.2 kV.
6.5.2.2

Drift time measurement

The x–t (time-to-distance) relation is extracted as polynomial function or linear function, depending on the drift time region. Figure 6.5.2.2 shows this relation (left) and the residual
distribution (right). The measured spatial resolution is about 100 µm.

215

Drift time [nsec]

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

300

150

10

0

10

[mm]

[mm]

Figure 6.18: Left: the measured x–t relation. Right: the difference between the measured andparameterized relation.

6.5.2.3

dE/dx measurement

The specific ionization, dE/dx , is measured by summing a 30 MHz sampling FADC bin by bin.
We sum FADC values that are larger than a fixed threshold. The threshold corresponds to the
TDC threshold (Vth ) in this analysis. To obtain the dE/dx resolution, we take the truncatedmean to minimize the contribution of the Landau tail. In this analysis, 80% truncated means
are used. The dE/dx resolution was found to be 11.9% for nine layers at an incident angle of90◦ . Figure 6.5.2.3 shows the distribution of the FADC sum at an incident angle of 90◦ . In theanalysis, three events are associated and treated as one event. We reject the outer two layers,which have open cells.
The incident-angle dependence of dE/dx resolution was measured. Figure 6.5.2.3 shows thedE/dx resolution for nine layers with an incident angle of 90◦ , 60◦ or 30◦ . The results agreewith the expectation.
6.5.2.4

Event Buffer

The board has an event buffer that allows storage of at most four events in the suppressed data
mode. In the raw data mode, there is no buffering, so about 30 in 104 (0.3%) events were lost at
an event rate of ∼ 20 Hz. Under the same conditions, all events were received on the suppresseddata mode.
6.5.2.5

Suppressed data mode

We compared the raw data mode with the suppressed data mode under the same conditions.
Figure 6.5.2.5 shows the typical distribution of the FADC sum and the TDC for both modes.
The value of the TDC is calculated as the difference between the time at which the trigger wasreceived and the time when the signal exceeded threshold. The trigger is delayed by ∼ 2 µs
relative to the signal.
216

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

Figure 6.19: The distribution of the FADC sum at an incident angle of 90◦ .

Figure 6.20: dE/dx resolution as a function of 1/sinθ at incident angles of 90◦ , 60◦ and 30◦ .

6.6

Expected performance

We achieved good performance throughout the beam test using the test chamber and the prototype readout electronics board. The obtained position resolution and energy loss resolution
for each cell are similar to or better than those achieved in the Belle CDC. Therefore, similar or
better performance is expected without beam background.
The larger beam background in Belle II might degrade the CDC tracking performance. We
assume 20 times higher beam background than in Belle and estimate the effect using a GEANT
simulation. Only a 10% loss is expected for B → J/ψKS events. For B → D ∗ D ∗ events, asignificant efficiency loss is expected without any corrective measures. However, new softwareand standalone tracking in the PXD and SVD will improve the overall efficiency dramaticallyso that even better performance can be obtained [4].
217

CHAPTER 6. CENTRAL DRIFT CHAMBER (CDC)

(a)

(b)

(c)

(d)

ns

ns

Figure 6.21: The typical distributions of the FADC sum and the TDC. (a) FADC sum in theraw data mode, (b) FADC sum in the suppressed data mode, (c) TDC in the raw data mode,and (d) TDC in the suppressed data mode.

218

References[1] K. Abe et al., KEK Report 2004-4 (2004).
[2] M. Akatsu et al., Nucl. Instrum. Meth. A454, 322 (2000).
[3] H. Hirano, Doctor thesis in Tokyo Univ. of Agriculture and Technology (2000).
[4] sBelle Design Group, I. Adachi et al., (2008), 0810.4084.

219

Chapter 7

Particle Identification - Barrel
7.1

Introduction

To extend our physics reach, we would like to improve the K/π separation capability of thespectrometer by upgrading the particle identification (PID) system. An upgrade of the system
is also compulsory to cope with the higher background environment. Finally, to improve thecalorimeter response to electromagnetic particles, we would like to to reduce the amount of PID
material and make it more uniform.
In the barrel region of the spectrometer, the present time-of-flight and aerogel Cherenkov counters are replaced with a Time-Of-Propagation (TOP) counter [1], whose conceptual overview isshown in Fig. 7.1. In this counter, the time of propagation of the Cherenkov photons internallyreflected inside a quartz radiator is measured (Fig. 7.2). The Cherenkov image is reconstructedfrom the 3-dimensional information provided by two coordinates (x, y) and precise timing, which
is determined by micro-channel plate (MCP) PMTs at the end surfaces of the quartz bar. The
array of quartz bars surrounds the outer wall of the CDC; they are divided into 16 modules in
φ in the baseline geometry.
The PID power is limited by the broadening of the time resolution due to the chromaticity of
Cherenkov photons. To minimize the chromatic effect, we introduce a focusing system [2], which
divides the ring image according to the wavelength of Cherenkov photons.

Figure 7.1: Conceptual overview of TOP counter.

quartz radiator

Cherenkov angle θc

K
tons

pho

π
photon detectors
charged particle

Figure 7.2: Schematic side-view of TOP counter and internal reflecting Cherenkov photons.
220CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Virtual readout screen
22x5mm matrix

Focusing mirror
charged particle

1850mmFigure 7.3: The principle of the focusing scheme in the TOP counter. The virtual extension of
the focal surface and of the photon detector plane are shown by the dashed curves and lines.
Focus mirror(sphere, r=7000)

MCP-PMT

Backward

Forward

MCP-PMT

Focus mirror(sphere, r=5000) MCP-PMT

Backward

ForwardFigure 7.4: Conceptual sketches of the 1-bar and 2-bar TOP baseline designs.
Figure 7.3 shows the schematic set-up. A focusing mirror is introduced at the end of the quartz
bar. The PMT is aligned to measure the position of the photon impact in x and y. The
cross section of the quartz bar is a rectangle. We can therefore expand the light trajectory
into the mirror-image region and create a virtual readout screen. The Cherenkov photons withdifferent θc will focus onto the different PMT channels; we thereby obtain λ information fromthe y detection position through θc . The focusing TOP reconstructs the partial ring image from
3-dimensional information: time, x and y.

7.2

Detector configuration

We studied two options for the detector configuration as shown in Fig. 7.4. For the 1-bar
option, we employ an expansion prism on the bar end and expand the partial ring image onto
the readout plane. It clarifies the ring image and improves the discrimination of wavelength.
It also increases the number of effective photons slightly. For the 2-bar option, in order toreduce temporal degradation due to chromatic dispersion, each radiator bar is subdivided into
two pieces at z ∼1070 mm, where the “short” bar with ∼750 mm length is used in the forward
direction, and the “long” bar of ∼1850 mm length is used in the backward direction. The shortbar is instrumented by PMTs at the forward edge and the long bar has PMTs at the backwardedge. In both options, a wavelength filter (λ & 400 nm) is introduced in front of the PMTs tofurther reduce the chromaticity.
As discussed in Section 7.5, the performance estimates for the 1-bar and 2-bar options are similar
for the physics cases considered, though the 2-bar option shows slightly better performance than
the 1-bar option in general. The performance is affected by non-ideal measurements. The 1-bar
configuration is less sensitive to the event timing degradation, while the 2-bar is less sensitive todegradation of incident angle determination in the tracking. Practically, the 1-bar case has an
221CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

advantage, since it shows larger forward acceptance and requires readout only in the backward
direction, so that we can avoid the crowded forward cable routing. Therefore, we chose the 1-bar
configuration as a baseline, with the 2-bar as a backup option.

7.3

Components

7.3.1

Quartz radiator

The quality of the synthetic fused silica (quartz) optical components is important for the proper
performance of the TOP detector. The radiator has three components: a long bar for radiating
Cherenkov light and propagating this light via total internal reflection to the bar end, where the
MCP-PMTs are mounted; a spherical mirror mounted on the forward end of the bar for focusing
the light; and, for the 1-bar design, a prism that attaches to the backward end of the bar andallows the Cherenkov ring image to expand before the photons are recorded by the PMTs.
7.3.1.1

Quartz bar

To propagate Cherenkov photons inside the radiator and preserve the Cherenkov ring image, thesides must be flat and parallel to a very tight tolerance. Our baseline specification for flatness isless than 10λ over the entire bar length (∼ 1.2m). The roughness must be less than 5 Å r.m.s.
to minimize photon loss. According to the G Kirchhoff equation, the reflectivity depends on
the surface roughness. In the case of 100 bounces on the surface, the total reflectivity is 0.97
and 0.87 for the roughness of 5 and 15 Å, respectively. The chamfer size should be as small
as possible, to reduce photon loss at the bar edges. Table 7.1 lists our current baseline bar
specifications. With these specifications, the number of photons reaching the phototubes after
total internal reflection is ∼ 100.
We have received two prototype bars of dimensions 400 × 915 × 20 mm3 fabricated by Okamoto
Optics, Inc. in Japan, and we have ordered another (longer and wider) bar from Zygo Corporation in the US. The Okamoto bar is shown in Fig. 7.5. Using this bar, we have measured thetiming resolution and the number of photons detected for internally reflected laser light and theperformance obtained was satisfactory.
Table 7.1: Baseline quartz bar specifications.
Size
Material
Index tolerance
Flatness
Roughness (r.m.s.)Angle between planes
Chamfer size

7.3.1.2(440 ± 0.15) × (1200 ± 0.5) × (20 ± 0.10) mm3
Synthetic fused silica (e.g., Corning 7980, Shin-etsu Suprasil)±0.001
10λ over full aperture
5 Å
(90 ± 1/60) degree< 0.20 mm

Focusing mirror and other optical components

The focusing mirror is spherical with a focal length of (coshθi)−1 × (bar length), where hθi is themean angle of incidence of tracks on the mirror surface for decays of interest. For a bar of length
2.5 m, this focal length corresponds to a radius of curvature of about 7 m. At present, we have222

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Figure 7.5: Photograph of the Okamoto prototype quartz radiator bar.

22 (effective area)
27.5 mmFigure 7.6: SL-10 prototype MCP-PMT photograph (left) and anode structure diagram (right).
received a 40-cm width prototype mirror with a 5-m radius of curvature from Okamoto Optics
and a 44-cm wide prototype mirror with a 7-m radius of curvature from Optical Solutions, Inc.
(OSI) in the US. We have tested the mirror from Okamoto in the laboratory and determined
the peak position of the image to be within 1 mm of expectation. We have recently received themirror from OSI are starting to evaluate it.
To attach the MCP-PMTs to the expansion prism and that to the radiator bar, we plan touse one or more of the following methods: a UV-cured optical adhesive such as Norland NOA61, 63; a two-component optical epoxy such as Epotek 301-2; or a high-grade silicone opticalgrease such as Bicron BC-630. The last option allows for the possibility of easily separating thecomponents if desired, e.g., for replacing PMTs in-situ. We used NOA 63 for the prototype,which works well as shown in the beam test result (Sec. 7.4).

7.3.2

Photon detector

A TOP counter requires the precise timing measurement of single photons at the end of its quartz
bar radiator. MCP-PMTs have excellent timing and gain performance. We have investigated
the single-photon detection performance of several MCP-PMTs [3]. Transit time spreads (TTS)of ∼ 30 ps at the gain of 106 for single photo-electrons, even in the presence of a 1.5 T magnetic
field, have been observed.
We have developed square-shape MCP-PMTs [4], denoted SL-10, to improve the packing efficiency when the MCP-PMTs are abutted on the end of the quartz bar. The basic SL-10
specifications are summarized in Table 7.2, and a photograph and diagram of the anode structure is shown in Figure 7.6. The SL-10 has a 4 × 4 anode array, a multi-alkali photocathode,two MCP plates with 10 µm pore size, and an aluminum layer on the second MCP to protect
against ion feedback.

223

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Table 7.2: Hamamatsu SL-10 MCP-PMT specifications.
27.5 × 27.5 × 15.6 mm3
22 × 22 mm2Multi-alkali
2
10 µm
∼60%
13◦
on second MCP
4×4
5.3 mm
0.3 mm
3.5 kVPMT size
Effective area
PhotocathodeNumber of MCP layers
MCP pore diameter
MCP aperture
MCP bias angle
Al protection layer
Anode pattern
Anode width
Anode gap
Maximum supplied HV

300
1000

(a)

(b)
750

200

500
100
250

0

0

50

100
150
ADC (count/0.25pC)

0

-20

0

20
40
TDC (count/25ps)

Figure 7.7: (a) ADC and (b) TDC distributions for SL-10 single photon detection. The dashedhistogram is a pedestal distribution. The TDC distribution is corrected for amplitude (ADC)
discriminator threshold timing dependence.
Figure 7.7 shows ADC and TDC distributions for the SL-10 MCP-PMT response to single
photons as generated by a fast, pulsed laser (Advanced Laser Diode Systems; PiL040). From
the ADC distribution, the gain is evaluated to be 1.2 × 106 . After ADC amplitude correction,a single photon timing resolution of 31 ps is seen in the TDC data. The tail of the TDC
distribution is due to the bounce of secondary electrons on the MCP surface, and is taken into
account in the simulation programs.
Figure 7.8 shows the quantum efficiency (QE) distribution as a function of wavelength. The
baseline MCP-PMT has a multi-alkali photo-cathode with the QE of 18% at 400 nm.
Long term MCP-PMT stability is also evaluated under high background rates. The main sourceof background is expected to be due to spent electrons from the beam. The number of the background photons is estimated using a Belle spent-electron simulation. The consistency between
this generator and the data is evaluated using the trigger hit rate of the existing Belle TOF
counter. At a luminosity of 1034 cm−2 s−1 , the trigger hit rate is measured to be 187 kHz, while
the simulator indicates a 400–500 kHz rate. For such background estimates, agreement withina factor of 2–3 is respectable, and our simulation estimate is on the conservative side. Using
this generator, the Cherenkov photon rate is estimated. Optical photons are produced in the224

Q.E.(%)

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

40

Super Bi-alkali
Multi-alkali
30

20

10

0
200

400

600

800

λ(nm)

Figure 7.8: Quantum efficiency distributions as a function of wavelength.
radiator due to the Cherenkov radiation generated by relativistic electrons from spent electron
shower gammas. The detected photon rate is estimated to be 300 kHz/(TOP module). Scaling
this estimate up by a factor of 20 to account for the increased background at Belle II, a photon
hit rate of 68 kHz/cm2 on the photon detector window is predicted, corresponding to an output
charge from anodes of 120 mC/cm2 /year, assuming a gain of 106 .
Stability is determined by LED light pulse illumination. Test results for a round-shape MCPPMT are summarized in Refs. [4] and [5], which indicate that stable gain and TTS can beobtained by changing the supplied HV. The quantum efficiency, however, is the critical item.
With an aluminum protection layer, the round-shape MCP-PMT demonstrated sufficient lifetime
for ten Belle II years of operation. We have also checked these parameters for the SL-10 MCPPMT. Figure 7.9 shows the relative efficiency as a function of integrated anode charge output.
Adequate lifetime (over at least three Belle II years) is also seen for the SL-10 MCP-PMT after
improvement through the modification of the inner MCP structure and a cleaning method thatavoids neutral gas and ion feedback from the second MCP to photocathode.
The baseline MCP-PMT described above has shown adequate performance. To provide additional operating margin, it is desired to improve the number of detected photons. Therefore,
we are developing an MCP-PMT with a super bi-alkali (SBA) photo-cathode in collaboration
with Hamamatsu Photonics. Figure 7.8 compares the quantum efficiency (QE) distribution as afunction of wavelength for multi-alkali and SBA. The multi-alkali QE is measured using a prototype MCP-PMT, while the SBA QE curve is from a Hamamatsu data sheet. Before starting
mass production, we will check the long term stability of the photo-cathode.
We also maintain the option of using a Photonis MCP-PMT. The status of a tube capable ofoperating in a 1.5T magnetic field is described further in Ch. 8.

225

Relative Q.E.

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

1

0.75

0.5

0.25

0
0

100

200
300
400
2
Integrated Charge (mC/cm )Figure 7.9: Relative QE as a function of integrated output charge for round-shape MCP-PMT(◦) and SL-10 MCP-PMT ( and △ before improvements; •, N, H, and  after improvements).

7.3.3

Electronics

7.3.3.1

Fast Timing with Waveform Sampling

Upgrade of the barrel PID device for the Belle II detector relies heavily on precision time
recording of individual Cherenkov photon signals. This places severe demands on the transit
time performance of photodetectors that need to operate in a 1.5T magnetic field, as well as
precision single photo-electron signal recording. Key to this latter challenge, in a compact
and cost-effective method, has been the development of low-power GHz analog bandwidth,
high-performance waveform recording [6, 7, 8] Application Specific Integrated Circuits (ASICs).
In contrast with previous GHz rate sampling devices such as the ATWD [9], having higher
analog input bandwidth exploits the full benefit of GHz sampling. Such waveform sampling has
been successfully flown twice on the ANITA long duration balloon payload [10, 11], where theexcellent timing thus obtained (≤ 30 ps) was able to provide sub-degree pointing resolution to
an in-ice transmitter located more than 100 km away. Subsequently this “oscilloscope on a chip”
technology (Fig. 7.10) has been explored for use in several Belle II subdetectors.
This development is well aligned with recent developments in high-density, high precision timing
photodetectors. Direct integration of the sampling and digitization ASICs with both traditional
vacuum-based (Micro-Channel Plate, Hybrid Photo-Diode) and solid state (Geiger-mode APD)
photodetectors have demonstrated that lower cost, higher quantum efficiency, and improved
transit-time-spread (TTS) photon detection modules are possible. Fig. 7.11 illustrates thatwithout these improvements, the performance of large-scale Time-Of-Flight (TOF) systems for
precision spectrometers has stalled at a resolution of about 100 ps.
While electronics have been available for decades that can readily measure signal times to 25 psor less, cost and lack of direct integration with the detector sensor elements has limited system performance as illustrated. This is also true for the Time-of-Flight system of the Belle
detector [13, 14]. In recent years, studies have explored mating of the photodetectors with theelectronics [15]. Depending upon the timing and amplitude resolution required, a number of
options for signal triggering, time encoding, and digitization have been explored [16, 17, 18].
The results are reference designs for high speed waveform sampling for iTOP precision timing,
slower speed (1–2 GSa/s) sampling for drift chamber and KLM endcap scintillator readout, anddirect FPGA conversion for the KLM barrel RPC readout.
226

CHAPTER 7. PARTICLE IDENTIFICATION - BARRELPMT pulse comparison
0.2

Amplitude [V]0-0.2
scope [2GSa/s]
STUD [2.56GSa/s]

-0.4
-0.6
-0.8
-1
0

20

40

60

80

Time [ns]Figure 7.10: Recording of a fast Belle fine-mesh Photo-Multiplier Tube (PMT) signal with ahigh-speed digital oscilloscope and a prototype sampling ASIC (SalSA Transient UHF Digitizer[STUD]).

Summary of TOF System Timing Resolution

Resolution [ps]1000

Pi2e [3]KL2g [4]CTC [5]MARKIII [6]
BES-I [7]BES-II [8]CLEO-II [9]s2H [10]
Belle [11]NA49 [12]CDF-II [13]STAR [14]

100

10
1950

1960

1970

1980

1990

2000

2010

Year

Figure 7.11: A historical comparison of large Time-Of-Flight system timing performance, where
progress has largely stagnated. The reference numbers in the legend are found in Ref. [12]. To
do significantly better, improved techniques, photodetectors, and electronics are needed.

227

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Based on these studies, it was determined that waveform sampling—if the sample buffer depth
can be extended—is the most attractive approach for readout of a Cherenkov timing device.
Therefore, a deeper sampling ASIC, designated the Buffered LABRADOR (or BLAB), wasfabricated and evaluated [19], a die photograph of which is seen in Fig. 7.12.

1.4mV

Figure 7.12: Upper left, a die photograph of the BLAB1 ASIC (3 mm × 3 mm), a single-channel
demonstrator with 65,536 storage cells fabricated in the TSMC 0.25 µm process [19]. At rightand below are the measured noise and adjustable sampling speed, respectively.
This compact ASIC demonstrated excellent performance during testing. Sampling rates of over
5 GSa/s were measured, while single samples could be recorded with over 1.4 V dynamic range
and 1.4 mV of noise, or 10 real bits per sample. A 16-channel prototype was subsequently
assembled and tested with the fast, focusing DIRC (fDIRC) prototype [20] at SLAC. Excellent
beam test results were obtained [21], and a complete readout system has been constructed basedon the next generation of this ASIC.
Further testing of this ASIC indicated that through careful calibration and attention to reference
timing distribution, sub-10 ps timing can be obtained [12] between two BLAB1 ASICs recording
single photon signals. This measured time difference is plotted in Fig. 7.13. If the errors√ wereuncorrelated, the actual timing would be better per single measurement by a factor of 2.
Research continues toward the goal of obtaining something like a few ps of timing resolution,
where recent studies [22] are encouraging if a sufficient signal-to-noise ratio can be realized,
and systematic errors are kept under control. However, such exquisite resolution is not strictly
necessary for the TOP application, as systematic errors in determination of the collision time [23]are expected to limit timing resolution at the 25 ps level, as discussed later. Maintaining suchtiming resolution under operating conditions is a significant challenge, as we have learned fromover a decade of continual calibration of the Belle TOF. As in the latter case, there is no needto maintain tens of ps timing over the 5 µs L1 trigger latency: all hits are recorded with respect
to the collision time, minimizing timing errors.
228

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

6.4 psRMS

Figure 7.13: Example timing resolution that has been obtained with low-power CMOS waveform
sampling [12].

A third generation Buffered LABRADOR ASIC (BLAB3) is the baseline for readout of either
barrel PID configuration. The specifications for this device are listed in Table 7.3.
Table 7.3: Specifications for the baseline BLAB3 readout ASIC.
Parameter
Value
Comment
Channels/BLAB3
8
die size constraint
Sampling speed4Giga-samples/second (GSa/s)
Samples/channel
32768
allows ≥5 µs L1 trig latency
Amplifier gain
60
voltage (3 kΩ TIA)
Trigger channels
8for hit matching/zero suppression
Effective resolution≈9
bits (12/10 bit logging)
Sample convert window
64
samples (≈16 ns)
Readout granularity
1
sample, random access
Readout time
1 + n · 0.02 µs to read n samples (same window)
Sustained L1 rate30
kHz (multi-buffer)

7.3.3.2

Integrated High-Speed Readout

To build a viable, large-scale system, it is necessary to process, sparsify and collect the data
generated by the devices mentioned above. Recently, the fDIRC prototype was moved into a
cosmic test stand at SLAC and outfitted with 450 channels of BLAB ASIC-based waveform
digitization electronics, as shown in Fig. 7.14.
Commissioning of this readout system [24] was performed in 2009 and the results of one yearof operation will be reported at a later date. A similar system, consisting of a few hundred
channels of cosmic test stand of an imaging Time Of Propagation (iTOP) prototype, has also229

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Figure 7.14: An example of highly integrated photodetector readout, where each of the 64channel PMTs is instrumented with its own readout module, consisting of a group of four
BLAB2 ASICs, and the data is collected via fiber-optic link.

been commissioned [25]. An advantage of this compact readout system is that it is easily andcost-effectively scaled up to several hundred thousand channels.
In terms of the Belle II DAQ infrastructure, Hawaii has been collaborating with colleagues inJapan and China on the fiber-optic based upgrade of data acquisition platform, named COPPER [26]. As part of this effort, a set of custom FINESSE cards [27] have been developed at
Hawaii that digitize, store and match (to event or track) hits in the data stream within the
COPPER context. This new architecture is presented in Fig. 7.15, where prototypes of each of
the components have been fabricated and large scale system performance tests have begun.

Figure 7.15: Block diagram of the Belle II Trigger and DAQ system. Optical fiber links are used
to convey trigger and front-end digitized data, significantly reducing the cable infrastructure, as
well as improving signal recording fidelity.

230

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Both of the baseline detector configurations (1-bar and 2-bar) presented in Sec. 7.2 utilize thesame number of 16-channel SL-10 PMTs (512). Therefore, apart from differences in mechanicallayout, both configurations have 8k channels of readout electronics. Table 7.4 summarizes thereadout system requirements. Details of the trigger processing are provided in Ch. 12.
Table 7.4: Specifications for the barrel PID readout electronics.
Parameter
Value Comment
Total electronics channels
8k
either 1-bar or 2-bar
Number of BLAB3 ASICs
1k
8 channels/ASIC
Number of channels/SRM
64
8 BLAB3 ASICs
Number of SRM
128
Subdetector Readout Modules
Bi-directional fiber links/SRM 1+1 DAQ/Trigger (see relevant Chapters)
Total DAQ/Trigger links
128
10% bandwidth at full luminosity
Number FINESSE
64
2 fiber links (COPPER limited)
Number COPPER
16
COPPER bus limited
Average size/event
4
kByte (2.5% occupancy)

Qualified radiation tolerant components are prohibitively expensive, difficult to access due toexport restrictions, and often many generations behind the technology forefront. Therefore,
the Belle II DAQ group has undertaken a program to qualify all needed components in theenvironment in which they will be used. These include Gigabit fiber transceivers, programmable
logic devices, and front-end ASICs. Initial tests have been carried out at particularly highradiation areas of the existing KEKB tunnel, near the Belle detector. Operation to O(100 kRad)
dose has been successfully demonstrated for both fiber optic transceiver links, as well as a least
one target programmable logic device. Testing in the KEKB environment is preferred over large
radioactive source or reactor tests, as the particle species and energy are representative of thosethat will be seen in the Belle II detector. At this point, these initial tests indicate that, fordetectors located at a radius larger than the silicon tracking layers, the radiation tolerance ofthe components tested thus far is adequate. However, the qualification of every part to be placed
inside the detector—considering a reasonable operational safety margin—will be undertaken.

7.3.4

Structure

7.3.4.1

Design strategy

The TOP counter will be installed between the ECL support structure inner surface and the
CDC outer cover. A 3D conceptual drawing of the integrated TOP detector and CDC is shown in
Fig. 7.16. For compelling financial reasons, the existing Belle barrel ECL structure will be reusedin the Belle II detector. Therefore, the outer envelope on the radial position and the z-length of
the TOP counter is fixed by the existing barrel ECL support structure and its integral support
fixtures. However, with the construction of a new CDC (Ch. 6), an optimization of the TOP–
CDC boundary region can be considered. Under these boundary conditions, a series of studies
of how best to integrate the TOP detector array into the available space, while maximizing the
expected performance, has been performed.
Upon closer scrutiny, a number of severe design constraints impact the detector integration.
One of the most important issues is to have access to the PMTs after their installation. At
this point, it is not evident that the MCP PMTs can survive the expected integrated charge
231

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

antipated for ∼10 years of operation. It is therefore desirable to have a mechanism to access the
PMTs. Openings in the support structure, referred to as “PMT access windows,” can be used
for maintenance and PMT replacement. Due to various geometrical constraints in the integrated
Belle II detector system, provision for such access is not trivial.
Another important issue is to minimize the material budget of the entire structure. To perform
well, the TOP counter needs a precise determination of the incident angle and the impact
position of a candidate particle on the detector. Multiple Coulomb scattering in excess structural
material degrades knowledge of these track extrapolated parameters and has a correspondingly
deleterious impact on particle identification.

Figure 7.16: A 3D conceptual rendering of the TOP detector integrated together with the CDC.
f-ECL/b-ECL flange shows the structure of ECL conical part. f-CDC/b-CDC flange is the
support of CDC from ECL flanges.

7.3.4.2

Requirements on the structure

Due to emission angle differences, a longer Cherenkov light propagation path should provide alarger time-of-propagation difference between different particle species of the same momentum.
However, chromatic dispersion of the emitted spectrum of Cherenkov light increases as the
propagation length increases. Studies indicate that the optimal z-length of a TOP module is∼1850 mm [28]. For comparison, the z-distance for spanning the polar angle range of 32.2–128.7
degrees between the forward and the backward ECL endcaps, at the nominal TOP radius, is2980 mm. Given this long z-distance to be covered, compared with the ideal TOP bar length,
there is no obvious constraint on the detector z-length in terms of performance. However, astrong geometrical constraint comes from the flanges attached to the BECL container, whichcannot be removed without completely disassembling the barrel ECL, an operation that will not
be performed.
The inner radius of the BECL container is 1250 mm and represents the absolute maximum outer
TOP radius. Existing fixtures attached to the container and a need for installation clearance
will reduce the final TOP counter radius slightly. The CDC outer radius (and corresponding
TOP inner radius) is flexible since it will already be much larger than the 880 mm of the current
232

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

detection efficiency

Belle detector [29]. The mechanical width and thickness of a single TOP module is dictated bya trade-off between technical constraints on the quartz bar production, distance from the ECL,
sufficient light yield, and quartz radiator thickness. As there is no strong optimum in theseparameters, a quartz bar width of 400–500 mm and thickness ∼20 mm has been considered.
Given the quartz bar dimensions and the available radial space, 12–18 modules can be arranged
to surround the CDC volume. The number of TOP modules was chosen to be 18 in the LoI [30],but subsequently changed to 16 to better match the azimuthal symmetry of the existing BECL
flange. The resulting azimuthal segmentation is 22.5 degrees per module.
Two considerations constrain the TOP geometrical envelope. First, a larger TOP outer radius
makes the gap between the ECL and the TOP (∆ECL ) smaller. A 20-mm-thick quartz radiatorcorresponds to 16% of a radiation length and causes γ-conversions ∼6% of the time for normal
incidence energetic photons. These e± pairs will curl in the 1.5 T magnetic field; depending on
their polar angle and ∆ECL , some of these e± may miss the ECL or may be detected in distinct
CsI clusters. This effect has been studied in GEANT simulation, one specific result of which isshown in Fig. 7.17 for 100 MeV photons (the typical minimum energy for “good gammas” inthe barrel ECL). As clearly indicated, a larger outer radius (i.e., a smaller ∆ECL ) increases theefficiency of detection of these low energy photons, which are vital to many physics analyses.

TOP radius

100 MeV•1240 mm
•1210 mm
•1180 mm•1120 mmPolar angle (degrees)
Figure 7.17: A GEANT study of the impact of TOP outer radius for 100 MeV photons as afunction of polar angle.
Second, Belle’s forward-endcap PID device (the Aerogel Cherenkov Counter) may need to beretained due to budget and resource limitations; the new endcap PID device would then be
installed at a later stage. To accommodate this scenario, a generous clearance between theforward inner-detector support cylinder and the EACC (∆ACC ) is needed to assure mechanicalcompatibility with the existing EACC structure.
7.3.4.3

Module container

A TOP module consists of a quartz radiator for the generation and propagation of the Cherenkov
light and a readout block for photon detection and signal readout. These components are housed233

CHAPTER 7. PARTICLE IDENTIFICATION - BARRELin the quartz bar box (QBB) and the readout enclosure, respectively.
The QBB, together with the TOP structure, is required to have sufficient rigidity so that thequartz bar can be properly supported. Specifically, the quartz should be subjected to at most atolerable deflection. Referring to a past study for the BaBar DIRC [31], the maximum deflection
allowed is set to 100 µm. A quartz bar with dimensions 400–500 mm (wide) × 20 mm (thick) ×
2870 mm (long) weighs 51–63 kg. To satisfy the maximum deflection requirement without theneed for an excessive material budget, the QBB design uses honeycomb panels for the inner andthe outer faces and solid aluminum sides. The honeycomb panel sandwiches a honeycomb core
between aluminum skins.
TOP performance simulation studies (Sec. 7.5) indicate that a resolution of ≤ 0.5 mrad isdesirable and ≤ 1.5 mrad is essential. The 5-mm-thick CFRP used for the CDC outer coveralready contributes a multiple scattering mean deflection angle of ∼0.7 mrad for a normally
incident π ± at 4 GeV/c. Therefore, minimizing the structural support material is important.
The stiffness of the QBB is dominated by the thickness of the honeycomb panel, whereas thealuminum skins are the dominant contribution to the multiple scattering. Thus, a thicker
honeycomb core with thinner aluminum skins is preferable for a fixed honeycomb panel thickness.
Based on deflection calculations and considerations for practical handling of the QBB, the thickness of the honeycomb panel is chosen to be 10 mm, including two 0.3-mm-thick aluminum skins,
and that of the aluminum side is chosen to be 2 mm. Although this aluminum side thickness
does not contribute significantly to either the stiffness of the QBB or the multiple scattering for
the TOP measurement, it does affect azimuthal hermeticity. On the other hand, the stiffnessof these walls is dictated by the need to support many threaded plungers, used for positioning
and supporting the quartz bar in the QBB. These sides must withstand the spring load, while
maintaining an air gap of 2 mm to the quartz radiator. It is necessary to verify the aluminumside thickness using simulation (FEM) or a mechanical prototype. The current design of the
QBB for the 2-bar configuration is shown in Fig. 7.18, where the readout enclosures are included
but not detailed. The dimensions of the QBB are summarized in Table 7.5.

Component
QuartzQBB
Honeycomb panel
Al sideTable 7.5: Module dimensions
Width [mm]Thickness [mm]
443
20
451
44
451
10 (core: 9.4, skin: 0.3×2)
2
44Length [mm]
∼2750
2870
2870
2870

The readout enclosure houses the readout block and includes an array of readout units. The
readout unit consists of a group of PMTs and their readout printed circuit boards (PCBs). The
readout enclosure is mounted on the end of the QBB and provides a flush optical connection
between the quartz bar end and the readout array. Figure 7.19 illustrates conceptual 3D drawingsof the readout arrays; the double-row and the single-row arrays will be used for the 1-bar andthe 2-bar schemes, respectively. A 3D drawing of the readout block mounted at the quartz bar
end is also shown in Fig. 7.19. The readout enclosure has the PMT access window at its innersurface. Its rear end must accommodate the cabling for the PCBs and piping for the cooling. It
also has to maintain the optical connection between the readout array and the quartz bar end
as well as the light shield. All of these are strongly correlated with the PCB dimensions derived
from the electronics design, which is in progress.

234

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

2

3

4

5

6

7

!"#$%&'()*+,-./0123-./0456712895:;

9

10

11

12

:#Z=[\]^_`abcQdY_e^f*gh_`abcQdY_e^f

A

B:=N3XY;A8

qrs7<tuv^w-./xJKK0QyzG{{0|}~hwe^f b0CD0v./z

:NN

1

B

M

:#<=3 !"#$%&'()0>?@ABCDEF;

6M

GHMNO !"#$%&'()0PQ0RSTUVWC

GH=6IJKKL

C

M
M
=

::

:

i
i

­.uabcQzdY*¢,
HN

ÔÕ¬ÖG

¬

:#Z=[\]^_`abcQdY_e^f*gh_`abcQdY_e^f

HN

D

Dijj)kklmn'opm­.uabcQzdY*¢,®_`abcQ¯°0±²z¢,³U+,´µ¶b£*·,±²¸¹º07_`abcQ¸ !"#$%&'()*
dY¢,»0_e^fz¼*½¾¿7JKK®[\]^Àh5Á¿µeÂcÃ,·*¢,´ÄÅÆ¸ !"#$%&'()PQ0RSGHMN0
7dY_e^fzÇÈ5ÁÉÊËÌGH=*¿Í*,´ÎÏhÐÁÑ­.uabcQ
zdY7ÒÑ*_`abcQzdY¢,´ÄÅÓ«Æ¸¬{{µeÂc¢,´EEijj)kklmn'opm
i#iÚÅÛÜÄO OÔÕ¬ÖG<twe^f b3µwv^Ý;(456 ~ 460)

FJ¦&¨©Þ

<twe^f b3dY;<tuv^w-./_`abcQ?@× !"#$%&'()®JKK0Øh
ÔÕ¬ÖG
Ù

Ù

Radial support(456 ~ 460)

we^f b¸JKK0âãä*,ªzdY7Æ*,ªzµwv^ÝXijj)kklmn'opm0_bc0dY
<3bc;0ub05r
JKK ¡zdY¢,£¤b/I¥&on&%lk¦§§p¨©L0
O JKK0dYª«

G_`abcQdY_e^f
:#<=

H
IDS

IDS

QBB

QBB

:#Z=

::N

=

DESIGNED

3

4

5

6

7

8

M

Takashi Kohriki
20100205

1/5,1/2

TITLE

9

10

G

CHECKED

SIZE

SHEET

A1

of

REV.

R0

H

DRAWING NO.

TPO 2-bar QBB@nagoya

Parameters are not Þxed yet
2

DRAWN

ORIGINAL SCALE

CLEAN & DEGREASEREMOVE ALL BURRS

6M

:NN

Takashi Kohriki
20100205

FINISH

::
:

IDS
H

1

F

¥ßIK%&jàLáb}

Radial support
ECL-ßange

KEK

MECHANICAL ENGINEERING GROUPINSTITUTE FOR PARTICLE AND NUCLEAR STUDIESHIGH ENERGY ACCELERATOR RESEARCH ORGANIZATIONOHO 1-1, TSUKUBA, IBARAKI 305-0801, JAPAN11

TOP-QBB
20100205.vwx
PROJECTPROJECTION

Belle II

12

Figure 7.18: A drawing of the QBB design.

7.3.4.4

Baseline design

The rz-views of the baseline structure designs are shown in Figs. 7.20 and 7.21 for the 2-bar andthe 1-bar schemes, respectively. The corresponding rφ-views are shown in Fig. 7.22. The 2-bar
scheme has a single row of readout at both the forward and the backward ends of the QBB,
each row consisting of 16 PMTs. The 1-bar scheme has an expansion volume instrumented
by a double-row readout array at the backward end of the QBB, consisting of 32 PMTs. The
difference between the two schemes is the application of an expansion volume in the 1-bar case;this has an impact on the mechanics around the boundary between the TOP and the CDC.
The radial geometries are summarized in Table 7.6, where the entries are the maximum radiusavailable to the TOP counter (R0 ), providing for a minimum ECL (∆ECL ) and the maximum
EACC (∆EACC ) clearance, as indicated. Values reported in this table take into account themeasured deformation of the BECL container and the fixtures attached to its inner surface. In
the 2-bar scheme, the CDC clearance (∆CDC ) is derived from the thickness of the CDC Support
Cylinder [CDC-SC] (4 mm), an installation clearance (5 mm) and a 3-mm buffer space. In the
1-bar scheme (values shown in parentheses), the values are derived from the backward end of the
QBB, where the expansion volume and the double-row readout array are equipped. The CDC
outer radius (RCDC ) cannot be larger than the inner radius of the CDC-SC, due to the existenceof wire feedthroughs and preamplifier boards. The resulting CDC radial clearance (∆CDC ) is
49 mm in the 1-bar scheme. Although this ∆CDC value seems somewhat large, even a few
mrad scattering in the CDC outer cyclinder will lead to a sub-mm error in the projected TOP
impact position—much smaller than typical helix-fit projection errors. The radial configurationin the forward end is almost identical for the two configurations. The only difference is theexistence of the readout block, which requires having cut-outs for the PMT access windows
on the forward CDC-SC. These cut-outs will be covered by 4-mm-thick aluminum covers to235

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Figure 7.19: Readout array illustrations. Top: two arrays of readout units corresponding to the
1-bar and 2-bar cases. Bottom: detailed three-dimensional rendering of the readout units inside
electro-mechanical enclosures.

236

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

reinforce the stiffness of the CDC-SC, leading to the 4-mm difference in the EACC clearance(∆EACC ) between the two schemes. This ∆EACC annular region is reserved for the cabling andpiping of the inner sub-detectors.
Table 7.6: Geometrical parameters of the current mechanical designs. Tabulated values refer tothe 2-bar (1-bar, if different) detector configuration.
Parameter
Maximum TOP counter radius
ECL inner radius
TOP-ECL clearance
Azimuthal acceptance loss
CDC outer radius
TOP-CDC clearance
Fwd inner-detector-support radius
EACC outer radius
TOP-EACC clearance

Symbol
R0
RECL
∆ECL
ηφ
RCDC
∆CDC
RIDS
REACC
∆EACC

Value
1243 mm
1250 mm
40 mm
7%1166 (1120) mm
12 (24/58) mm
1166 (1162) mm
1145 mm
17 (21) mm

In both designs, the fraction of the insensitive azimuthal coverage (ηφ ) is not small and approximately 7% at the center radius of the QBB in the 2-bar scheme. To increase the azimuthal
coverage, a staggered module arrangement was considered in the LoI [30]. Unfortunately, thisstaggered arrangement doubles the material budget in the overlap region, makes the structuraldesign more complex, and increases the azimuthally-dependent worst-case spacing to both the
ECL and CDC.
An approach applicable to the current module arrangement is to maximize the quartz bar width,with a starting point of 451 mm in Table 7.5. If the need for middle support can be mitigated,
a quartz bar width of 460 mm would be possible, reducing ηφ to ∼3%. Since the width of the
PMT array is rigidly quantized, some area of the quartz bar end is typically not fully covered by
the PMTs. The covered fraction is estimated to be 96% in the latter bar width case. The typicalnumber of Cherenkov photons detected is ∼20 and a 4% loss does not significantly affect detector
performance, while the azimuthal track coverage can be increased by 4%. Such a configuration,
though with different module dimensions, has already been evaluated in a beam test [32] and it
performed as expected, as reported in the next section.

7.4

Prototype test

We have produced a prototype TOP counter to check the effects of chromatic dispersion and todemonstrate overall timing performance [32]. This prototype is comprised of a quartz radiatorwith a spherical focusing mirror (5-m radius) and 12 square-shape MCP-PMTs with a multialkali photo-cathode (Hamamatsu R10754X-00-L4). Two quartz bar pieces and the mirror wereglued together for a total radiator size of 1850 × 400 × 20 mm3 . To reduce chromatic dispersion
effects, a wavelength high-pass filter of λ > 400 nm was inserted between the radiator and the
MCP-PMTs. Operation of the MCP-PMTs demonstrated stable gain (∼ 106 ) and good time
resolution (< 40 ps) for all channels. The average QE observed was 17% at 400 nm. We also
developed constant-fraction-discriminator (CFD) modules as the high-speed readout for thistest; these use a fast amplifier (µPC2710 MMIC, 1 GHz, ×20 gain) and a comparator (180-ps
237

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

2

3

4

5

6

2980
2870

80

7

8

9

11

12

30

940

A

10

ECL
1930

1.6

1

A

17

IDS
Barrel PID
CDC support cylinder
TOP QBB(Quartz bar box)
1590

60

1650

R1166 CDC@nagoya

Pre-ampC

280

IDS(Inner detector support) and CDC-SC(Support cylinder):t=4
Endcap PID
EACC

Preamp board

B

(20)

CDC

PMT access window cover:Max. t=4"#"$%&'()*+$,-./0012345'6789:*8$;<=$,->?@/0A
BCDEB"F>GH4IJ23KLMN3A?@OPQRSTAUVW1IJXY3Z[

1200 Bar box
R1250 BECL inner R???min. / 800max.
1000

R1166 IDSTOF support bracket
50

(20)

R1145 EACC

150
B

R1162(Current R of IDS)

PMT access window coverC"#".9:7\)]23^$_`.abbOP1234cdFF1
e-fghi>j<=$klXmnncopXbOnnA

D

D

30º

17º

E

E

Backward IDS detail : Scale 1/2
8075(PMT+PCB)
4

IDS"#".9:7\)]234Y
1KLWhiAPnnJqrAu]\x&\4WrT1.3

M6 Nuts(IDS)

F

6

20
8

4

ø10

4

DESIGNED

2

3

4

5

6

7

DRAWN

Takashi Kohriki
20100207

FINISH

89CHECKED

Takashi Kohriki
20100207

SIZE

ORIGINAL SCALE

CLEAN & DEGREASEREMOVE ALL BURRSTITLEParameters are not Þxed yet
1

G

4

R1166 IDS

IDS and CDC-SC
PMT access window cover

26

R1162(Current IDS)R1145 EACC

P/
R1166 CDC@nagoya

R1175 CDC envelope

R1170 CDC-SC

H

1200 from center

PMT access window cover

R1250 BECL inner Radi.

4
50

R1166 CDC@nagoya

80
150

CDC-SCø16

3
Pm~c"#".9:7\)]1

G

s#t.u]\vw23gw$x&\Myz-f{r3AdF
FX|T}~$x&\>JKLNAdFF$:*)\1>s#t x&\1WrT1.3A
M6x15 Bolts(IDS)!!

F

Forward IDS detail : Scale 1/2

of

REV.

R0

H

DRAWING NO.

ConÞgration of
IDS and TPO@Nagoya

IDS-TOP
20100207.vwx
PROJECTKEKMECHANICAL ENGINEERING GROUPINSTITUTE FOR PARTICLE AND NUCLEAR STUDIESHIGH ENERGY ACCELERATOR RESEARCH ORGANIZATIONOHO 1-1, TSUKUBA, IBARAKI 305-0801, JAPAN

10

SHEET

A1

1/5,1/2

PROJECTION

Belle II

11

12

Figure 7.20: rz-view drawing of the current 2-bar scheme baseline design.
4

5

6

2980
2870

7

8

9

1930

A

Barrel PID

CDC support cylinder

TOF support bracket
150

50

TOP QBB(Quartz bar box)???min. / 800max.

1590

1000

Pre-amp

C

B

(20)

CDC

280

IDS(Inner detector support) and CDC-SC(Support cylinder):t=4
Endcap PID
EACC

Preamp board

60

1650

R1120 CDC@hawaii(20)

R1145 EACC

PMT access window cover

12

21

IDS

B

11

30

940

A

10

ECL

1200 Bar box
R1250 BECL inner Radius

3

80

R1166 Forward IDS

2

1.6

1

C

D

D

30º

17º

E

E

Forward IDS detail : Scale 1/2

Backward IDS detail : Scale 1/2
8075(PMT+PCB)
4!"#!$%&'()*+,-.*+/0(1/234
This clearance need for CDC installation!"#!$%&'()*+,-.*+/0(1/234

M6 Nuts(IDS)

M6x15 Bolts(IDS)

F

F

6

20

2

3

4

5

ø10

M6

DESIGNED

Takashi Kohriki
20100214FINISHDRAWN

Takashi Kohriki
20100214ORIGINAL SCALE

CLEAN & DEGREASEREMOVE ALL BURRS

1/5,1/2

TITLE

7

8

9

10

CHECKED

SIZE

SHEET

A1

REV.

KEK

MECHANICAL ENGINEERING GROUPINSTITUTE FOR PARTICLE AND NUCLEAR STUDIESHIGH ENERGY ACCELERATOR RESEARCH ORGANIZATIONOHO 1-1, TSUKUBA, IBARAKI 305-0801, JAPAN

R0

11

IDS-TOPhawaii
20100207.vwx
PROJECT

Belle II

12

Figure 7.21: rz-view drawing of the current 1-bar scheme baseline design.

238

of

DRAWING NO.

IDS and TPO@Hawaii

6

G

4

Parameters are not Þxed yet
1

ø16

8

4
R1145 EACC

IDS and CDC-SC

R1166 IDS(Forward)

!5

46

26

R1120 CDC@hawaii

R1129 TOP envelope

PMT access window coverH

1200 from center50

CDC-SC

R1250 BECL inner Radi.

150

R1120 CDC@hawaii
R1124 CDC-SC

80

4

G

R1129 TOP envelope

5

71

5

IDS

!!

3

PROJECTION

HCHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Figure 7.22: rφ-view drawings of the current baseline designs for the 2-bar (upper) and the
1-bar (lower) concepts.

propagation delay). The CFD time resolution is ∼ 5 ps for test pulses.
Using a prototype counter, we performed beam tests with 2 GeV/c electrons at the KEK Fuji
test beam line in June and December 2008. The TOP counter was located between trigger
scintillation counters and tracking chambers. To determine the beam timing precisely, we put atiming counter [33] along the beam line; this consisted of a small quartz radiator (10 mmφ ×10mmL ) and a round MCP-PMT (Hamamatsu R3809-50-11X). The time resolution obtained forthese start counters was determined to be 14.8 ps during the beam test.
Figure 7.23(a) shows a partial ring image obtained during the beam test. The beam was normally
incident at the center of the radiator. The distance between this incident position and the nearest
MCP-PMT was 358 mm. A clear partial ring image was obtained, as predicted by simulation.
Figure 7.23(b) shows the number of detected photons for the normal-incidence case and thematch to our simulation prediction. Figure 7.23(c) is the TDC distribution for an anode at thecenter of the readout plane. The distance between the incident position and this MCP-PMT was
875 mm. A comparison was made of the time resolutions obtained during the beam test with theresolution expected from simulation, which included PMT resolution and the effect of chromatic
dispersion. The time resolution of the first peak was (76.0 ± 2.0) ps and (77.7 ± 2.3) ps for dataand simulation, respectively, indicating consistent results between data and simulation. The

239

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

TDC [/25ps]

background tail under the peak is due to Cherenkov photons generated by δ-rays and electron
showers from upstream. These effects are included in the simulation.
500

450

450
400
400
350
350
300
300
250
250
200

200
150

150

100

100

50

50

0

(a)

5

10

15

20

25

30

35

40

45

0

50

channel

0.12

(b)

(c)

250

0.1
200
0.08
150
0.06
100

0.04

50

0.02

0

5

10

15

20

25

30

35

40

45

50

Number of hits/event

0
200

220

240

260

280

300

320

340

TDC (/25ps)

Figure 7.23: Beam test results. (a) Partial ring image from about 350,000 events, (b) numberof detected photons, and (c) TDC distribution of an anode at the center of the quartz end.
The colored scale in (a) corresponds to the number of events in the bins. The solid and shaded
histograms in (b) correspond to data and simulation, respectively. In (c), the histogram is thedata, and the curves show the fitted Gaussian and background functions.

7.5

Expected performance

7.5.1

Simulation methods

To study expected TOP performance in various configurations, three independent Monte Carlosimulation studies have been undertaken:• Nagoya simulations utilize the Belle Geant3-based Monte Carlo, GSIM, to determine
the trajectory of primary charged particles, as well as any secondary charged tracks produced by electromagnetic and hadronic interactions as the primaries traverse the quartz.
The threshold energy for propagation of electrons is 0.2 MeV; this is smaller than the
Cherenkov radiation threshold. Portions of charged tracks that pass through the TOP
radiator bars are then passed to a stand-alone code to simulate all optical processes occuring in the counters (Cherenkov emission, photon propagation with the velocity variation240

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

on the wavelength, total internal reflection, optical attenuation, photon detection at the
MCP-PMTs, etc).
• Ljubljana simulations utilize a stand-alone simulation that tracks a charged primarythrough the detector volume and handles optical processes in the counters. No attempt ismade to handle secondary tracks.
• Hawaii simulations utilize a stand-alone Geant4-based program to fire primary tracks,
produce secondary particles resulting from electromagnetic interactions in the bar, andcarry out all optical processes for all charged particles. The threshold energy for propagation of electrons is about 0.5 MeV, which is determined by the minimum step length.
All programs model the multiple scattering effect inside quartz. Simulation inputs for the TTS
and QE distributions are taken from MCP-PMT prototype measurement data, as described inSec. 7.4. Consistency between simulation output and measurement is confirmed by checking the
GSIM program against beam test data.

7.5.2

Reconstruction

x (cm)

Existing studies have thus far focused primarily on K/π separation. To determine expected
efficiencies and fake rates, the detected photons for each track are tested against probability
distribution functions (PDFs) for each particle hypothesis (P K (x, t) and P π (x, t)).
The source of the PDFs differs by simulation group. In the methods employed by Nagoya and
Hawaii, the PDFs are based upon a large number of events using single tracks at a particular
momentum, impact position, and angle on the quartz bar. The Ljubljana reconstruction utilizes
the known properties and distributions of Cherenkov radiation to form analytically calculated
PDFs [34]. Typical distributions used to construct the PDF are shown in the left of Fig. 7.24.

20
700
15
600
10
500

5
0

400

-5

300

-10

200

-15

100

-20
10

20

30

40

0

50
time (ns)

-60

-40

-20

0

20

40

60

80
∆ log(L)

Figure 7.24: (Left) Sample distributions for an ensemble of 500 tracks of detected photon positions, x, and times, t, for a 2-bar counter with 3 GeV/c pions (red) and kaons (blue) at normal
incidence on the quartz bar. (Right) Distributions of ∆ log L for pions (red) and kaons (blue),corresponding to the distributions on the left.
From the PDFs, a likelihood is determined for a simulated primary charged particle:
LK,π =Yi

PiK,π (x, t)

241

(7.1)

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

where the index i runs over each detected photon in the event. Typically the log of the likelihood
is used as it is more computationally stable. The difference between the likelihood under eachhypothesis is calculated.
∆ log L = log Lπ − log LK(7.2)

If this log-likelihood difference is positive, the particle is classified as a pion, and if negative, akaon. Example distributions of log likelihood can be found in Fig. 7.24. These likelihood-basedclassifications can be compared with the known species of particle simulated to determine thefractions of correctly identified kaons and incorrectly identified pions.
Because the Nagoya and Hawaii methods utilize PDFs determined from Monte Carlo, generatinga PDF for a single combination of track momentum, impact angle, impact position, and particle
species takes a significant amount of time and computational resources. As such, the expected
efficiencies and fake rates can be calculated only for a limited number of track parameters.
In contrast, the reconstruction procedure utilized in the studies by Ljubljana makes use ofanalytically calculated PDFs, thus drastically reducing the computation required to make aperformance estimate and allowing much finer sampling of performance across the parameter
space for potential charged tracks. The potential drawback to this method is that these PDFs
may lack some of the details seen under realistic operating conditions (e.g., secondaries producedby the initial charged track).
As the method utilizing Monte Carlo based PDFs is unrealistic to apply in the final detector
configuration, there is an ongoing effort to determine suitable reconstruction methods for the
final system, for example by adapting the analytical reconstruction method to the Geant-basedMonte Carlo data.

7.5.3

Simulated configurations

Performance of the 1-bar and 2-bar configurations have been studied. These studies use thedetector dimensions described previously. For each configuration, both multi-alkali and superbialkali photocathodes have been studied.

7.5.4

Included uncertainties

Various non-idealities in reconstruction, detector geometry, and actual detector performance(both within the TOP and other Belle II measurements) will degrade ideal TOP performance.
We describe here the primary uncertainties that have been studied and their baseline values forthe performance estimates.
7.5.4.1

Tracking uncertainty

The performance estimates include event-by-event variations in each track’s impact angle andposition, relative to their nominally generated values. These variations are due to the tracking
resolution and multiple scattering in the CDC outer wall and inner wall of the quartz bar support
structure. These estimates reflect the resolution expected from the Belle II tracking systems
and algorithms.
At the inner surface of the TOP counter, each track can be defined by four parameters: incident
position (z, x) and incident angle (θ, φ). Track uncertainties can thus be defined as the uncertainties of these four respective parameters; σz , σx , σθ and σφ . Estimates of these uncertainties
have been obtained using the Belle Geant3 framework, with the existing Belle ACC removed.

242

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

These results are shown in Table 7.7. As a cross check, results obtained in this way are roughly
consistent with an analytic calculation of multiple scattering, which includes the material of the
CDC outer cylinder and the TOP honeycomb frame.
The nominal values used for the performance estimates are:• σz = 1.4 mm• σx = 1.0 mm• σθ = 1.5 mrad
• σφ = 1.5 mrad
Table 7.7: Tracking resolution estimates using Belle GSIM MC, with the ACC removed.
p [GeV/c] particle σdz [mm] σdx [mm] σθ [mrad] σφ [mrad]
2
π
2.0
0.57
2.6
3.6
2
K
1.8
0.49
2.6
3.3
3
π
1.4
0.45
1.8
2.5
3
K
1.3
0.39
1.8
2.3
4
π
1.3
0.42
1.5
2.0
4
K
1.2
0.33
1.4
2.0

7.5.4.2

Event start time (t0 ) jitterAs the TOP requires high performance timing resolution, it is particularly sensitive to timing
uncertainties. One such uncertainty is in the event start time, t0 , which determines the timeof the e+ e− collision. This quantity can be estimated based upon numerous studies with the
Belle TOF system. Reported results of one such study [23], as well as estimates of performance
improvements for Belle II, have been used to estimate the start time uncertainty, σt0 .
For the purposes of TOP reconstruction, the target value for the final t0 resolution is σt0 = 25 ps,
and this is the baseline value used in simulations to estimate detector performance. Fromexperience, to achieve this level of precision will require significant and concerted calibration
efforts. Within the uncertainties of the studies performed, a more pessimistic event timing
outcome is also possible and thus σt0 = 50 ps has also been studied. This will be summarized ina more detailed note on TOP simulations and is an important consideration in the final detector
configuration choice.
7.5.4.3

PMT efficiency degradation

As evident in Fig. 7.9, MCP-PMT efficiency degrades over their lifetime due to aging effects.
Furthermore, variations in the production process may cause some PMTs to exhibit lower efficiencies. To account for these effects, the performance estimates can be made using the nominal
efficiencies, and repeated with efficiencies at 80% of their nominal values.

243CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

7.5.4.4

Beam background rate

The detected photon rate due to beam background is estimated to be 300 kHz/(TOP module)at the luminosity of 1034 cm−2 s−1 , as described in Sec. 7.3.2. Scaling by a factor of 20 andassuming a time window of ∼100 ns for each TOP reconstruction, the number of backgroundphotons is estimated as 4.8 [(photons detected)/(TOP module)/(event)].
Baseline estimates of TOP performance use estimates of 0–1 detected background photons per
TOP module per event. However, backgrounds as high as about 7 detected photons per module
per event have been studied, and show only minor (≤ 1%) degradation to efficiencies and fakerates, as seen in Figures 7.25 and 7.26.

Figure 7.25: Kaon efficiencies estimated using GSIM for the TOP detector at 3 (left) and 4(right) GeV/c momentum with varying numbers of background photons from spent electrons.

Figure 7.26: Kaon fake rate estimated using GSIM for the TOP detector at 3 (left) and 4 (right)
GeV/c momentum with varying numbers of background photons from spent electrons.

7.5.4.5

Mirror misalignment

Estimates of misalignment parameters from prototype testing in Nagoya indicate that, due tomanufacturing limits, the mirror’s center of curvature may be displaced from its nominal position
by approximately 0.3 mm. During the process of gluing the mirror to the quartz bar, rotationsof order 0.2 mrad may be introduced. These imperfections were added into the simulations, and244

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

there was little noticeable impact on the overall performance. As such, we report here only the
results assuming perfect mirrors, and leave the results of simulated misalignment studies for a
detailed TOP simulation document.
7.5.4.6

ECL Backsplash

The contribution of albedo from the calorimeter (“backsplash”) is suppressed by the 1.5T
solenoidal magnetic field. Nevertheless, preliminary studies indicate that the effect could besignificant and further study is needed.

7.5.5

Performance estimates

7.5.5.1

Estimated performance by momentum, polar angle

Kaon efficencies and pion fake rates are tabulated for various track momenta and polar angles. The results of the three independent simulations and reconstruction methods are shownin Figs. 7.25–7.28. The three methods show reasonable agreement, particularly in terms ofreproducing similar features as a function of track impact angle.
Kaon efficiency, 1−bar

1

∈K

∈K

Kaon efficiency, 2−bar

1

0.98

0.98

0.96

0.96

0.94

0.94

0.92

0.92

0.9

0.9

0.88

0.88

0.86

0.86

0.84

0.84

0.82

0.82

0.8
−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8
−0.6

0.8
cosθ

0.18

0.16

0.16

0.14

0.14

0.12

0.12

0.1

0.1

0.08

0.08

0.06

0.06

0.04

0.04

0.02

0.02
−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8
cos θ

0

0.2

0.4

0.6

0.8
cos θ

0.2

0.18

0

−0.2

Pion fake rate, 1−bar

0.2

fπ

fπ

Pion fake rate, 2−bar

−0.4

0

0.2

0.4

0.6

0

0.8
cosθ

−0.6

−0.4

−0.2

Figure 7.27: Kaon efficiencies (top row) and pion fake rates (bottom row) for the 2-bar (leftcolumn) and 1-bar (right column) configurations, estimated from a Geant4-based simulation andreconstruction. Results are plotted for 1.5 GeV/c (•), 2.5 GeV/c (), and 3.5 GeV/c (N).

245

efficiency, fake rate

efficiency, fake rate

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Kaons (efficiency)

1

0.8

0.6

0.4

Kaons (efficiency)

1

0.8

0.6

0.4

0.2

0.2

Pions (fake rate)
0

-0.4

-0.2

-0

0.2

0.4

Pions (fake rate)
0.6

0

0.8

-0.4

cos θ

-0.2

-0

0.2

0.4

0.6

0.8

cos θ

Figure 7.28: Kaon efficiency and pion fake rates for the 2-bar (left) and 1-bar (right) configurations, based on a stand-alone simulation and reconstruction. Results are plotted for 3 GeV/c.
7.5.5.2

Estimated performance in B → ππ and B → ργ

Two B decay modes that are expected to significantly benefit from an improved PID system are
B → ππ and B → ργ, distinguished from the background modes of B → Kπ and B → K ∗ γ,
respectively. Estimates of the efficiencies and fake rates in these modes are computed in oneof two ways. For the Geant-based simulations, the efficiencies and fake rates as a function of
momentum and track polar angle are coarsely sampled, as in Figs. 7.26 and 7.27. The phasespace of charged tracks from each decay mode is then used to perform a weighted average ofefficiencies and fake rates. For the analytical reconstruction method, charged tracks from theappropriate decay mode are produced using a Monte Carlo generator, and the overall efficiencies
and fake rates are determined for these tracks. In both cases, the overall efficiency and fake rate
values are reported only over the acceptance of the TOP counters. A summary table of theresults for each simulation group can be seen in Tables 7.8 and 7.9.

246

CHAPTER 7. PARTICLE IDENTIFICATION - BARREL

Table 7.8: Efficiencies and fake rates obtained from simulation for B → ππ, under the set ofassumptions described in the text. “MA” and “SBA” indicate the multi-alkali and super-bialkali
photocathode, respectively. The GSIM simulations include secondaries from both electromagnetic and hadronic interactions, the Geant4 simulations include secondaries from electromagnetic
interactions, and the stand-alone simulations do not include secondaries.
π efficiency (%)
K fake rate (%)
Geometry Condition GSIM Geant4 stand-alone GSIM Geant4 stand-alone
1-bar
MA
92.8
96.1
92.6
7.2
4.5
4.0
2-bar
MA
96.2
97.6
96.5
3.8
2.7
3.8
1-bar
SBA
95.6
98.1
94.8
4.4
2.8
2.5
2-bar
SBA
97.7
98.5
97.2
2.3
1.9
2.7
1-bar
MA 50ps
91.3
94.7
90.6
8.7
5.8
6.0
1-bar
MA 2mrad
92.2
–
91.4
7.9
–
4.8
1-bar
MA 80%
91.3
95.0
90.7
8.7
5.6
5.3
1-bar
SBA 80%
94.6
97.5
93.6
5.4
3.5
3.3
2-bar
MA 50ps
93.2
93.9
91.6
6.8
6.9
8.9
2-bar
MA 2mrad
95.7
–
95.9
4.3
–
4.2
2-bar
MA 80%
95.2
96.9
95.3
4.8
3.4
4.8
2-bar
SBA 80%
97.1
98.2
96.8
2.9
2.2
3.4

Table 7.9: Efficiencies and fake rates obtained from simulation for B → ργ, under the set ofassumptions described in the text. “MA” and “SBA” indicate the multi-alkali and super-bialkali
photocathode, respectively. The GSIM simulations include secondaries from both electromagnetic and hadronic interactions, the Geant4 simulations include secondaries from electromagnetic
interactions, and the stand-alone simulations do not include secondaries.
π efficiency (%)
K fake rate (%)
Geometry Condition GSIM Geant4 stand-alone GSIM Geant4 stand-alone
1-bar
MA
97.6
99.5
98.5
1.3
0.9
0.8
2-bar
MA
98.4
99.7
99.4
1.1
0.5
0.6
1-bar
SBA
98.6
99.9
99.1
0.9
0.4
0.4
2-bar
SBA
98.9
99.9
99.6
1.0
0.2
0.4
1-bar
MA 50ps
97.3
99.1
98.1
1.5
1.0
1.1
1-bar
MA 2mrad
97.5
–
98.3
1.3
–
1.0
1-bar
MA 80%
97.0
99.1
97.9
1.8
1.3
1.1
1-bar
SBA 80%
98.3
99.7
99.0
1.0
0.6
0.6
2-bar
MA 50ps
97.6
98.9
98.3
1.5
1.3
1.9
2-bar
MA 2mrad
98.4
–
99.3
1.2
–
0.7
2-bar
MA 80%
98.1
99.5
99.2
1.3
0.8
0.9
2-bar
SBA 80%
98.7
99.9
99.6
1.0
0.3
0.6

247

References[1] K. Inami, Nucl. Instrum. Meth. A595, 96 (2008), 10.1016/j.nima.2008.07.045.
[2] B. N. Ratcliff, Nucl. Instrum. Meth. A502, 211 (2003), 10.1016/S0168-9002(03)00276-6.
[3] M. Akatsu et al., Nucl. Instrum. Meth. A528, 763 (2004), 10.1016/j.nima.2004.04.207.
[4] K. Inami et al., Nucl. Instrum. Meth. A592, 247 (2008), 10.1016/j.nima.2008.04.014.
[5] N. Kishimoto, M. Nagamine, K. Inami, Y. Enari, and T. Ohshima, Nucl. Instrum. Meth.
A564, 204 (2006), 10.1016/j.nima.2006.04.089.
[6] G. S. Varner et al., Nucl. Instrum. Meth. A583, 447 (2007), 10.1016/j.nima.2007.09.013.
[7] G. S. Varner, L. Murakami, D. Ridley, C. Zhu, and P. Gorham, Nucl. Instrum. Meth.
A554, 437 (2005), 10.1016/j.nima.2005.08.069.
[8] G. Varner et al., Proc. SPIE Int. Soc. Opt. Eng. 4858-31 (2003).
[9] S. Kleinfelder et al., IEEE Trans. Nucl. Sci. 50 955 (2003).
[10] G. Varner and et al. [ANITA collaboration], SLAC-PUB-11872, SNIC-2006-0046, Proceedings of International Symposium on Detector Development for Particle, Astroparticle andSynchrotron Radiation Experiments (SNIC 2006), Menlo Park, California, 3-6 Apr 2006,
pp 0046 (2006).
[11] P. Gorham and et al. [ANITA collaboration],
10.1016/j.astropartphys.2009.05.003.
[12] L. L. Ruckman and G. S. Varner,
10.1016/j.nima.2009.01.217.

Astropart. Phys. 32, 10 (2009),

Nucl. Instrum. Meth. A602, 438 (2009),[13] H. Kichimi et al., Nucl. Instrum. Meth. A453, 315 (2000), 10.1016/S0168-9002(00)00651-3.
[14] J. W. Nam et al., Nucl. Instrum. Meth. A491, 54 (2002), 10.1016/S0168-9002(02)01231-7.
[15] G. Varner, L. Ruckman, J. Schwiening, and J. Va’vra, International Workshop on New
Photon-detectors PD07, June 2007 Kobe, Japan, Proceedings of Science, PoS (PD07) 026(2007).
[16] G. Varner, Journal Instr. 1 P07001 (2006).
[17] G. Varner and L. Ruckman, Journal Instr. 2 P04006 (2007).
[18] L. Ruckman and G. Varner, Journal Instr. 3 P12003 (2008).
248

REFERENCES[19] L. L. Ruckman, G. S. Varner, and A. Wong, Nucl. Instrum. Meth. A591, 534 (2008),
10.1016/j.nima.2008.03.095.
[20] J. Benitez et al., Prepared for 2006 IEEE Nuclear Science Symposium, SLAC-PUB-12236 .
[21] J. Benitez et al., Nucl. Instrum. Meth. A595, 104 (2008), 10.1016/j.nima.2008.07.042.
[22] J.-F. Genat, G. Varner, F. Tang, and H. J. Frisch, Nucl. Instrum. Meth. A607, 387 (2009),
10.1016/j.nima.2009.05.193.
[23] H. Kichimi et al., Journal Instr. 5 P03011 , Collision timing “start” (t=0) systematic
error is dominated by the beam bunch overlap interval (≈ 16ps), with additional terms due
to integral path length differences and RF clock distribution system. A detailed study ofcollision timing stability has been performed with the existing Belle TOF system.
[24] L. Ruckman et al., Technology In Particle Physics conference, March 2009, Tsukuba Japan.
Accepted for publication in Nucl. Instr. Meth. A .
[25] K. Nishimura, L. Ruckman, and G. Varner, Technology In Particle Physics conference,
March 2009, Tsukuba Japan. Accepted for publication in Nucl. Instr. Meth. A .
[26] T. Higuchi et al., (2003), hep-ex/0305088.
[27] Y. Igarashi et al., (2003), physics/0305137.
[28] K. Aoki, http://www.hepl.phys.nagoya-u.ac.jp/public/www/Intro/top/aoki-m_th.pdf(master thesis in Japanese) (2006).
[29] Belle, A. Abashian et al.,9002(01)02013-7.

Nucl. Instrum. Meth. A479, 117 (2002),

10.1016/S0168-[30] S. Hashimoto, M. Hazumi, J. Haba, J. Flanagan, and Y. Ohnishi, editors, Letter of Intent
for KEK Super B Factory (KEK Report 2004-04, 2004), http://belle2.kek.jp/.
[31] I. Adam and et al. [BABAR-DIRC],
10.1016/j.nima.2004.08.129.

Nucl. Instrum. Meth. A538, 281 (2005),[32] K. Inami, Journal Instr. 5 P03006 (2010).
[33] K. Inami, N. Kishimoto, Y. Enari, M. Nagamine, and T. Ohshima, Nucl. Instrum. Meth.
A560, 303 (2006), 10.1016/j.nima.2006.01.027.
[34] M. Staric, K. Inami, P. Krizan, and T. Iijima, Nucl. Instrum. Meth. A595, 252 (2008),
10.1016/j.nima.2008.07.018.

249

Chapter 8

Particle Identification: End-cap
8.1

Introduction

Identification of charged particles over the full kinematic range is one of the basic requirements
for Belle II. In the forward endcap, the proximity-focusing Aerogel Ring-Imaging Cherenkov
detector (ARICH) has been designed to separate kaons from pions over most of their momentum
spectrum (Fig. 1.9) and to provide discrimination between pions, muons and electrons below
1 GeV/c.
The ARICH elements (Fig. 8.1) are:aerogelphoton detector

Cherenkov photons

charged particle

2 cm

20 cm

Figure 8.1: Proximity focusing ARICH - principle• an aerogel radiator where Cherenkov photons are produced by charged particles,• an expansion volume to allow Cherenkov photons to form rings on the photon detector
surface,• an array of position sensitive photon detectors, that is capable of detecting single photons
in a high magnetic field with high efficiency and with good resolution in two dimensions,and• a read-out system for the photon detector.
250

1095.

/ 116
7289.
0.30740.1428E-01
74.49
884.4

8000

n1 n2

N

N

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

P1
P2
P3
P4
P5

n1<n2
6000

2467.

/ 116
5495.
0.29650.2072E-01
85.32
796.0

P1
P2
P3
P4
P5

6000

4000

4000

nf= 10.27

nf= 10.64
2000

nb= 1.05

2000

nb= 1.36

0

0
0

0.1

0.2

0.3

0.4

0.5

θc(rad)

0

0.1

0.2

0.3

0.4

Figure 8.2: Left: Proximity focusing RICH with an inhomogeneous aerogel radiator in the focusing configuration. Center: the distribution of Cherenkov photon hits vs. Cherenkov angle fora focusing configuration with n1 = 1.046 and n2 = 1.056. Right: the corresponding distribution
for a 4-cm homogeneous radiator.
The design choices are governed by the following criteria:• To achieve the necessary performance, enough photons (about 10) have to be detected foreach ring image for at least one of the particle species. This requirement fixes the lengthof the aerogel radiator to several centimeters.
• The required resolution in the measurement of the Cherenkov angle is achievable only foran expansion gap of about 20 cm and a radiator thickness that does not exceed a few
centimeters, with a photon detector granularity of a few millimeters.
As already discussed in the LoI [1], a prototype of the counter showed excellent performanceboth in on-the-bench and in beam tests. However, two major issues remained: the need toincrease the number of detected Cherenkov photons and the development of a detector for single
photons that would reliably work in the high magnetic field of Belle II. Both problems weresolved in a satisfactory manner.
The key parameter in the performanceof a RICH counter is the Cherenkov angle resolution√
per charged particle σtrack = σθ / N . With a longer radiator, the number of detected photons
increases, but in a proximity focusing RICH the single photon resolution degrades because of
the emission point uncertainty. For Belle II, the optimal thickness is around 20 mm [1, 2, 3].
However, in the R&D phase following the LoI, we have found a solution to this limitation. The
problem is solved if a proximity focusing RICH with a non-homogeneous radiator is employed [3,4, 5, 6]. By appropriately choosing the refractive indices of consecutive aerogel radiator layers,
one may achieve overlapping of the corresponding Cherenkov rings on the photon detector(Fig. 8.2) [6]. This is equivalent to focusing of the photons within the radiator, and eliminates
or at least considerably reduces the spread due to emission point uncertainty. Note that sucha tuning of refractive indices for individual layers is only possible with aerogel, which may be
produced with any desired refractive index in the range 1.01-1.2 [7].
In Fig. 8.2, we compare the data for two 4-cm thick radiators: one with aerogel tiles of equal
refractive index (n = 1.046), the other with the focusing arrangement (n1 = 1.046, n2 = 1.056).
The improvement is clearly visible. The single photon resolution σθ = 14.3 mrad for the dual radiator is considerably better than the corresponding value for the single refractive index radiator(σθ = 20.7 mrad), while the number of detected photons is the same in both cases.
251

0.5

θc (rad)CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

photocathode-8 kV~20 mmphotone-

Pixelated APD
Figure 8.3: Schematic drawing (left) and a photograph (right) of the HAPD, hybrid avalanche
photon detector.
The second open issue—development of a reliable sensor of single photons—has also been solvedin a satisfactory manner, as reported in Secs. 8.2.2 and 8.5.2. As the baseline detector, a hybridavalanche photo-detector (HAPD by Hamamatsu Photonics) of the proximity focusing type wasselected, while the Photonis MCP-PMT is kept as a backup option.

8.2

Basic Detector Elements

8.2.1

Aerogel Radiator

The silica aerogel Cherenkov radiator should be highly transparent in order not to lose photons
inside the medium via Rayleigh scattering or absorption. To obtain well separated patterns
from kaons and pions at 4 GeV/c, a refractive index near the range 1.04–1.06 is required. In
our design, two 20-mm thick layers of silica aerogel with refractive indices of 1.055 and 1.065 areemployed as Cherenkov radiators. As discussed above, the indices are chosen so that the rings
from the two aerogel layers overlap on the photon detector plane.
The optical quality of the aerogel can be characterized as T = T0 exp(−d/Λ(λ)), where T0 and
T are light intensities before and after passing through the aerogel tile of thickness d, and Λ isthe transmission length at wavelength λ. The value of Λ at λ = 400 nm is required to exceed
40 mm for both layers to guarantee high transparency.
The shape of one piece of the radiator is hexagonal in the baseline design. Thanks to thehydrophobic property of our aerogel material, we can cut them from square tiles using a water-jet
device without degrading the optical characteristics. At present, the tile dimension is assumed
to be 160 × 160 × 20 mm3 . In this case, about 300 square-shaped tiles are needed for eachrefractive index, (600 tiles for two layers) to cover the entire radiator area.
Further R&D to increase the photoelectron yield as well as to establish technical procedures tomaintain uniform quality during large-scale production is still ongoing.

8.2.2

Photon Detector

The square-shaped HAPD produced by Hamamatsu Photonics (HPK) is the baseline photon
detector. This device consists of a vacuum tube with enclosed solid state sensor of the avalanche
photo-diode (APD) type (Fig. 8.3 (right)). Figure 8.3 (left) shows a schematic view of the HAPD
operation, while typical specifications are summarized in Table 8.1.
Cherenkov photons enter through the entrance window and generate photoelectrons from abialkali photocathode. Photoelectrons are accelerated along the electric field, where a typical252

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP
72×72 mm2
12×12 (6×6/APD chip)
4.9×4.9 mm2
67 %
25 %
∼ 105
220 g

package size
# of pixels
pixel size
effective area
typical QE
gainweightTable 8.1: HAPD specifications.
1000

a-22
b-22
c-22
d-22

1400

1.0E-05
avalanche gain (chipA-ch22)
leakage current (chipA-ch22)
leakage current (chipA-All)

100

1200

Avalanche Gain

Electron Bombarded Gain

1600

1000
800
600
400

1.0E-0610

1.0E-071

1.0E-080.1

1.0E-09

AD Leakage Current [A]

1800

200
0

0.01

0

1

2

3

4

5

6

7

8

9

Photocathode Applied Voltage [-kV]

0

50

100

150

200

250

300

350

1.0E-10400

AD Reverse Bias Voltage [V]Figure 8.4: Electron bombardment gain (left) as a function of photocathode voltage and APD
gain and leakage current as a function of APD reverse bias voltage (right). Both are taken from
HPK data sheets.
voltage is 7–10 kV, and are directed onto the avalanche photodiode. In the APD, an additional
gain of ∼40 is obtained when a bias voltage is provided. The photon detector consists of four
APD chips, each of which is pixelated into 6×6 pads for a position measurement, and each pad
has a size of 4.9×4.9 mm2 .
Fig. 8.4 (left) shows the electron bombardment gain as a function of HV. Typically, the gain is
about 1500 at −8 kV. The avalanche gain and leakage current in a typical APD are given in
Fig. 8.4 (right). The leakage current is around a few µA for 36 channels, and an avalanche gainof 50 is obtained at 330 V [8].

8.2.3

Read-Out System

Because of the large number of photon detector read-out channels, ∼ 80k in total, a dedicatedfront-end read-out system based on an ASIC (Application Specific Integrated Circuit) chip is
employed. In the ASIC chip, the input signal is processed in three successive steps: a preamplifier, a shaper and a comparator. The output signal is fed to an external FPGA. The gain andthe shaping time are variable, and can be externally set. The threshold to the comparator iscommon to all the channels in a chip, but the offset of the signal is adjustable for each channel. A schematic of the ASIC and its layout are shown in Fig. 8.5. Table 8.2 summarizes the
specifications of the present ASIC chip.
After the comparator, only the on/off information is registered in the FPGA to conform to
the overall Belle II DAQ scheme. In our design, one FPGA manipulates all signals of the 144
channels from one HAPD. The clock signal inside the FPGA runs at 64 MHz and the latency
and the time window are programmable.
The ASIC and the FPGA chips are encapsulated in a printed circuit board directly attached to253

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

PreampShaperComparator

Figure 8.5: Schematic and layout of the ASIC (SA02).
process
chip size
noise level
amplification
peaking timeoffset adjustment

TSMC CMOS 0.35 µm
3.0 × 6.5 mm21200 e− at 80 pF
4 steps: 18–70 mV/fC
4 steps: 250–1000 ns
coarse: 60 mV/ch; fine: 5 mV/ch

Table 8.2: Specifications of the present ASIC (SA02).
the HAPD output pins. The data merger may be situated inside the ARICH container to makefull use of the bandwidth in optical fibers as well as to reduce the number of fibers, dependingon the available space.

8.3

Mechanical Design

A schematic view of the mechanical structure is shown in Fig. 8.6. The RICH container consistsof two cylinders with tentative inner and outer radii of 410 mm and 1140 mm, respectively.
The two cylinders are connected by reinforcement bars in the radial direction at the back plane.
The front surface, which is mounted on both inner and outer cylinders, is a thin Al plate. The
back-end plane is machined so that HAPDs with readout electronics modules are mounted on it.
The photon detector support plane is further reinforced by few-cm high radially oriented septum
walls of 0.5-mm thick Al. The septums define six identical azimuthal sectors, each organized
as a honeycomb-like structure. The container housing the ARICH counter is supported by the
inner cylinder of the E-CsI container in the same way as the present end-cap aerogel Cherenkov
counter. The HAPDs are arranged in 9 concentric rings in the radial direction; in total, 540
sensors of this type are required. The breakdown of sensors per ring is listed in Table 8.3. The
Layer #
# of HAPDs

1
36

2
42

3
48

4
54

5
60

6
66

7
72

8
78

9
84

Table 8.3: Number of HAPDs for the nine concentric rings.
minimum distance between HAPDs as well as between HAPD and aluminum walls is assumed
to be ∼ 2 mm.
We are considering mounting a segmented flat mirror on the inner side of the outer cylinder to254

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

Figure 8.6: Schematic drawing of the RICH mechanical structure.
255

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

100transmittance (%)

80

60

40

20

0
200

300

400

500

600

700

800

wavelength (nm)Figure 8.7: Transmittance of 20-mm thick aerogel with n = 1.065 as a function of wavelength(nm). The solid curve is fit used to determine the clarity.
reflect Cherenkov photons, which would otherwise be absorbed at the cylinder walls, to the area
covered by photo-sensors. As discussed in Sec. 8.6, such a mirror would allow for a continuoustransition in PID coverage from the barrel to the end-cap boundary region.
The aerogel radiators are tiled as shown in Fig. 8.6. They are assumed to be tiled on a thinaluminum plate and black paper will be inserted into the gaps between the tiles to absorb
photons hitting the radiator boundary.

8.4

Cabling and Other Services

One HV cable per HAPD is assumed at the moment, although the final decision might dependon the cost. For the bias voltage, each APD needs a separate cable since the avalanche gainin the HAPD is highly sensitive to the bias voltage. On the other hand, several guard voltage
channels may be combined. In the readout system, three fiber cables will be used: two forreadout and one for triggering.
In addition to these cables, two cooling pipes (in/out) and one nitrogen pipe per sector are
required. Monitoring cables for temperature and humidity are also necessary.
The joint station has to be located at the back plane of the E-CsI container. In this station, allcables and pipes have to be pluggable to permit retraction of the end-cap apparatus.

8.5

R&D Results

8.5.1

Aerogel Radiator

Since 2008, we have worked to improve the optical quality of the aerogel radiators, particularly
those with refractive index greater than 1.055 [7, 9]. Recently, a new production technique,the so called “pin-hole drying” method, was invented and successfully tested [10]. This method
allows us to reach a transmission length of more than 45 mm λ = 400 nm for n > 1.055 samples.
Such a performance was not achieved with the previous method. Figure 8.7 shows the measured
transmittance of an n = 1.065 aerogel sample with 20 mm thickness. These data were fitted with256

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

Figure 8.8: A large-size (180× 260× 20 mm3 ) aerogel tile.
the Hunt formula T = A exp(−d C/λ4 ), where C is the clarity of the aerogel with thickness d, λis the photon wavelength, and A is the absorption (assumed to be independent of wavelength).
We obtained C = 0.00048 µm4 /mm and A = 0.9934. The corresponding transmission length
was calculated to be Λ = 55.2 mm at λ = 400 nm.
In parallel, an effort to produce large aerogel tiles was also made. Larger radiator tiles areimportant to reduce the loss of the Cherenkov photons at the radiator boundaries. Figure 8.8
shows a photograph of a 180 × 260 × 20 mm3 aerogel tile with transmission length of about
40 mm at 400 nm. Further optimization of the supercritical drying process to suppress cracks
inside the samples is underway.

8.5.2

Photon Sensor

8.5.2.1

Hybrid Avalanche Photo-Detector (HAPD)• Noise level and gain As a first check, we measured the noise level of the signal channel byapplying a bias voltage. The noise level was estimated as the r.m.s. value, σpedestal , obtained byfitting a gaussian function to the pedestal distribution. We tested one channel for each diodechip in the HAPD; the obtained values are plotted in Fig. 8.9. As can be seen in the figure,the noise level quickly decreases at a bias voltage of 50 V, where individual channels become
electrically disconnected. Minimum noise is obtained around 300 V, and then gradually increases
due to leakage current. We confirmed that the diode behavior for all four chips, with the bias
voltage turned on, was consistent with expectations.
Gains and S/N for HAPDs were then checked using a blue LED light source. A typical pulse
height distribution is plotted in Fig. 8.10. In this figure, a clear single photon peak can beobserved, where the typical gain is G ≃ 5×104 . The S/N ratio was then calculated as the ratio
G/σpedestal ; We obtained S/N ∼ 15 from these data.
The responses from all HAPD channels were studied using the ASIC readout electronics system.
In this system, the digitized hit information is stored if the signal from individual pixels exceeds
the threshold value (for a detailed description see Sec. 8.5.3).

257

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

Figure 8.9: Noise level as a function of bias voltage (V).

250

3ph.
200

0ph.

150

4ph.

100

...
50

0

0

500

1000

1500

2112. / 1543
-4.6750.1110-0.6739E-04
135.0
98.03
17.47
239.7
373.6
20.54
232.4
648.8
24.59
149.0
927.0
26.29
69.90
1208.
27.82
30.05
1497.
42.97

P1
P2
P3
P4
P5
P6
P7
P8
P9
P10
P11
P12
P13
P14
P15
P16
P17
P18
P19
P20
P21

1ph. 2ph.

300

2000

2500

3000

3500

4000

Figure 8.10: HAPD pulse height distribution.
The noise level from each pad was first checked by varying the threshold value applied to the
ASIC chips. The standard deviation of the noise value was then calculated. The threshold level
was set to 4σ of the noise distribution, which roughly corresponds to 0.5 photoelectrons. After
this procedure, a light source was placed on a two dimensional displacement stage controlled by apersonal computer. The detector was illuminated at different positions and the hit informationfrom all HAPD pixels was recorded; the light intensity was adjusted so that on average ∼0.4 photoelectrons per pulse were detected [11]. Figure 8.11 shows the result of such a twodimensional scan. In this figure, all the hit counts are accumulated, where x and y positions aretaken from the incident light beam position. Several pads are missing because of dead channels
either on the APD or the ASIC chip. A high detection efficiency was observed over entire
active area. Image is distorted at the edges due to the nonuniform electric field. Distortion will
disappear when HAPD is operated in the magnetic field.
• Quantum efficiency (QE) A high QE is always beneficial to photon detection. In recent
years, Hamamatsu has provided photomultiplier tubes with very high peak QE, greater than 30%(“Super Bialkali”) and 40% (“Ultra Bialkali”) [12]. On the other hand, fabrication of the HAPD
258

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

1400

100

1200

90

1000
80

800
70
600
60
400
50
200
40
40

50

60

70

80

90

100

XY

Figure 8.11: Hit responses in 144 channels by scanning a light beam across the HAPD surface.

QE(%)

is different from conventional PMT production since the transfer method has to be employed.
This could be one of the barriers for a direct application of the high QE technology. Last
year, the producers tried to adapt the “Super Bialkali” technique to the HAPD photocathodeproduction process and a high QE sample was successfully fabricated for the first time. This
sample was tested using a Xenon lamp in the laboratory, and a QE exceeding 30% at 400 nm wasconfirmed, as shown in Fig. 8.12, where a comparison to a conventional bialkali photocathode is40
35Super Bialkali
Conventional Bialkali

30
25
20
15
10
5
0
300

350

400

450

500

550
600
650
Wave length(nm)Figure 8.12: QE of the “Super Bialkali” photocathode in the HAPD as a function of wave
length measured with a Xenon lamp. Measurement of the QE values for a conventional bialkali
photocathode is also shown for comparison.
shown. From this measurement, 32% peak quantum efficiency at 360 nm was obtained.
We expect that a higher QE HAPD can be produced in a stable way as the technology improves
and that 30% QE on average will be achieved in mass production.

259

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

Count

Count

• Magnetic field immunity The behavior in a magnetic field was studied using the “Ushiwaka” magnet at the KEK PS (Proton Synchrotron). The scanning stage in two directions was
attached to the magnet so that the HAPD performance in the presence of a magnetic field could
be examined. The experimental setup including the readout system is identical to what wasused in the bench tests. After adjusting the threshold value for all pads, the hit informationfrom the HAPD was measured by varying the incident light position. The hit distributions for
12 channels of one HAPD row, with and without a magnetic field, are plotted in Fig. 8.13.

10 3

10 3

10 2

10 2

10

10

1

1
40

50

60

70

80

90

100

40

Light incident position (mm)

50

60

70

80

90

100

Light incident position(mm)Figure 8.13: One dimensional scan across the HAPD surface with 0 T (left) and 1.5 T (right)
magnetic fields.
Two improvements in this distribution are apparent when the magnetic field is on. One is anelimination of the strange hit behavior close to the side of the detector, which can be seen in
Fig. 8.13 (left) without the magnetic field. This was eliminated in the right figure; it is caused
by a distortion in electric field near the detector side wall, illustrated in Fig. 8.14. There is a

Figure 8.14: Schematic view of the electric field in the HAPD.
4-mm wide metal tape on the side wall, covering the connection between the entrance window
and the detector housing made of ceramic, with the HV to the window supplied through thismetal component. Since the electric potential of the window and of the metal tape are the same,the electric field is distorted in this area. However, once the magnetic field is turned on, thephotoelectrons propagate along the magnetic field lines, on a helix with a Larmor radius of theorder of 1 µm.
260CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

The other effect is a considerable reduction of the tails observed in the hit distribution. Thiseffect is thought to be due to photoelectrons scattered on the APD surface, which bounce intoneighboring APD pads (back-scattering).
To study this effect in detail, the hit correlation between two pads is investigated. Two hits
are required, with one detected in a particular pad and the other in any other pad. We thenplotted the location of the second hit relative to the first (Fig. 8.15). From this plot it is evident

100

100

10 3
90

10 3

90

80

80
10 2

10 2

70

70

60

60
10

10

50

50

40
20

30

40

50

60

70

80

40

1

20

xy ch. 57

30

40

50

60

70

80

1

xy ch. 57

Figure 8.15: Back-scattering electron effect observed with 0 T (left) and 1.5 T (right) magnetic
fields.
that backscattered photoelectrons can generate signals on other pads within 40 mm, in good
agreement with expectations. Note, however, that this effect is considerably reduced in a 1.5 T
magnetic field (Fig. 8.15 right). The remaining spread is thought to be due to incident-lightreflections.
Based on these studies, we conclude that the single photon sensitivity in the HAPD is notdegraded and that a 1.5-T magnetic field is actually beneficial for sensor performance [13].
• Aging test Effects of aging of a HAPD have been studied in order to evaluate and possibly
predict its performance under conditions of elevated irradiation by light inside the Belle II
spectrometer.
The test apparatus (Fig. 8.16) consists of an HAPD and a reference photomultiplier tube (HPK
R1463), both mounted on a computer-controlled, mobile XY stage. In standard operation, theentire HAPD surface is illuminated by 470-nm light from a light emitting diode (LED).
Measurements of the photon detection efficiency (PDE) and quantum efficiency (QE) have been
performed at the beginning and the end of the aging process (Fig. 8.17). An additional PDE
measurement was performed during aging after an irradiation corresponding to about nine yearsof operation in Belle II (corresponding to 3×1012 detected photoelectrons per cm2 ). For the PDE
and QE measurements, we used tungsten and deuterium lamps, both with a monochromator(SP-2155 PI Acton) and a reference PMT. Measurements of QE and PDE show no significant
degradation of performance after an accumulated irradiation corresponding to about 27 yearsof operation in Belle II (≈ 1013 detected photoelectrons per cm2 ).
• Radiation damage From a study of leakage current increase in the photodiodes used in
the Belle ECL [14], severe neutron damage is expected in the Belle II environment. We estimate
261

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

30
25

PDE [%]

QE [%]

Figure 8.16: Schematic drawing of the aging test setup.

before aging
after aging

20
17.5

before aging
during aging
after aging

15

20

12.5
15

10
7.5

10

5
5

2.5
0

300

400

500

600

0

700

λ [nm]

300

400

500

600

700

λ [nm]

Figure 8.17: QE and PDE of the HAPD measured before, during and after the aging test.

262

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

QE(%)

that the neutron fluence will be 1011 neutrons/cm2 /year after the accelerator upgrade. To study
the impact of neutrons on the photo-sensor performance, several HAPDs were irradiated with up
to 5 × 1011 neutrons/cm2 in the “Yayoi” nuclear reactor facility at the University of Tokyo [15].
This dose corresponds to 5 years of operation in Belle II. Note that the average energy of theneutron flux in the Yayoi is 370 keV. To convert to a 1-MeV equivalent flux, an ELMA diode [16]was also irradiated in the same way for calibration. The fluence of 5 × 1011 neutrons/cm2 in
the Yayoi facility was found to be equivalent to a fluence of 2 × 1011 1-MeV neutrons/cm2 . In
this section, the neutron fluence with the Yayoi energy spectrum is employed unless explicitly
stated otherwise.
The first comparison in QE before and after the neutron irradiation of 5 × 1011 neutrons/cm2
30

25

Before irradiation
After irradiation

20

15

10

5

0
300

350

400

450

500

550
600
650
Wave length(nm)Figure 8.18: Comparison in QE before and after exposure of 5×1011 neutrons/cm2 .
was made, and the results are plotted in Fig. 8.18. As can be seen in this figure, no degradation
was observed. On the other hand, a significant increase in APD leakage current was measured(Fig. 8.19). As can been seen in this figure, the leakage current increases linearly as a function

Figure 8.19: Leakage current increase in one APD as a function of neutron dose.
of neutron exposure, reaching more than 10 µA in one APD chip. Noise measurements showed263

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

a large width of the pedestal peak. In addition, the increase in leakage current caused a dropin actual bias voltage, resulting in an avalanche gain reduction. Because of these phenomena,
the post-irradiation single-photon signal is barely separated from noise, as shown in Fig. 8.20
(left). The p
width of the noise level, σnoise , is related to the readout electronics parameters
as σnoise ∝ Ileak × Tshaping , where Ileak and Tshaping represent the leakage current and signal
shaping time in the readout electronics system, respectively. Therefore, a shorter shaping timein signal processing allows us to compensate for the degradation due to noise.
The pulse height distribution plotted in Fig. 8.20 (left) shows a S/N ratio of ∼ 3 after exposure to
5×1011 neutrons/cm2 . However, with a considerably shorter shaping time of 20 ns in the readout

h1_adc_1

adc (ch1)

EntriesMean
RMS
χ2 / ndf
p0
p1
p2
p3
p4
p5
p6
p7
p8

1400
1200
1000
800
600

h1_adc_1

adc (ch1)

500000579.6
373.3
2736 / 1591
813.8 ± 2.2
358.7 ± 0.7
154 ± 1.0
312.9 ± 2.3
831.5 ± 1.9
181.3 ± 2.3
41.18 ± 0.421540 ± 10.3
388.4 ± 28.4

EntriesMean
RMS
χ2 / ndf
p0
p1
p2
p3
p4
p5
p6
p7
p8
p9
p10

9000
8000
7000
6000
5000
4000

499939140.4
66.18
1747 / 319
8009 ± 18.3
102.2 ± 0.0
16.36 ± 0.03
2279 ± 9.6
218.6 ± 0.1
17.57 ± 0.07
322.9 ± 3.8
340.1 ± 0.2
17.72 ± 0.24
375.5 ± 5.2−0.9501± 0.0158

3000
400
2000
200
0

1000
200

400

600

800

0

1000 1200 1400 1600 1800 2000

100

150

200

250

300

350

400

Figure 8.20: Pulse height distributions of the HAPD after exposure to 5×1011 neutrons/cm2
using a 1 µs shaping time with HV of −7 kV (left) and a 20 ns shaping time with −8.5 kV(right).
system we could suppress the deterioration due to higher noise. Furthermore, by applying an
increased HV of −8.5 kV, a S/N ratio of ∼ 7 was achieved, and detection of a clear single photon
signal was possible (Fig. 8.20 right).
In conclusion, by optimization of the shaping time parameter in the electronics readout, radiation
damage up to 5 × 1011 neutrons/cm2 is manageable [13].
In the present ASIC readout, the shaping time is one of the adjustable parameters, and it canbe varied in the range from 250 ns to 1 µs. A 1 µs shaping time has been used as the default
set up, for instance in the beam test described later. It should be noted that excessively shortshaping times may emphasize the intrinsic APD noise rather than reduce noise from radiation
damage. From this viewpoint, further studies to optimize the shaping time should be done.
As an alternative approach, the possibility of suppressing the increase of leakage current after
neutron irradiation is also investigated. The leakage current is proportional to the APD volume,
so it can be reduced if a thinner APD layer can be produced. The first APD samples with athinner layer structure were recently delivered and were irradiated at Yayoi in January 2010.
Detailed tests are now in progress.
8.5.2.2

Micro-channel plate photomultiplier tube (MCP-PMT)As an alternative photo sensor, a micro-channel plate photomultiplier tube (MCP-PMT) has
been studied. The characteristics of the sensor, Photonis/Burle 85112, are listed in Table 8.4.
The tube has two micro-channel plates with 10-µm pores, and 64 (=8× 8) anode pads at 6.5 mm
264

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

package size
# of pixels
pixel size
effective area
typical peak QE
gainweight59 × 59 mm2
64 (8 × 8 array)
5.9 × 5.9 mm2 @ 6.5 mm pitch80%≈25%≈ 0.6 × 106
130 g

Table 8.4: MCP-PMT specifications.
pitch [17]. It has a bialkali photocathode on the inside of a 2-mm thick quartz window, separated
by 6 mm from the microchannel plates.

Figure 8.21: Schematic drawing and photograph of the MCP-PMT.
Single photon detection
Extensive tests have been performed on the bench to test the position and timing resolution
for single photons [18]. A picosecond laser (a fast laser with picosecond timing resolution) wasused as a light source. Light from the laser was focused onto the surface of the MCP-PMT toform a spot of ≈ 10 µm diameter. The light spot could be positioned at a desired location by
a 3D moving stage to investigate the uniformity of response. A timing resolution better than
40 ps RMS can be obtained for prompt signals, as shown in Fig. 8.22. Effects of charge sharing(Fig. 8.22) and photoelectron backscattering, which can affect the position resolution for single
photon detection, were also observed. Due to charge sharing, double counting appears in a
≈2 mm wide region at the pad boundaries. Photoelectron backscattering has a longer range ofabout 1 cm. Both effects are expected to be strongly reduced when the MCP-PMT is operated
in a magnetic field.
• Operation in magnetic field An advantage of the MCP-PMT over conventional PMTs is
its ability to operate in a high magnetic field. Operation up to 1.5 T is possible if the diameter ofpores is 10 µm or less [19]. Tests of a sample with 10-µm pores were performed in the magnetic
field using the same setup as for the tests of the HAPD. The variation of the gain as a functionof the magnetic field up to 1.5 T is shown in Fig. 8.23.
To achieve the same gain and the same single photon detection efficiency at 1.5 T as with nomagnetic field, the high voltage needs to be increased by about 200 V (Fig. 8.23). A position
sensitivity scan was also performed at 1.5 T to assess the effect of magnetic field on charge
sharing and photoelectron backscattering. From the result of the scan (Fig. 8.24), we conclude
265632.8
P1
P2
P3
P4
P5
P6

5000

4000

ADC1/(ADC1+ADC2)

countsCHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

/ 65
4890.
-1.525
37.17
553.4
233.8
144.9

3000

1
10 3
0.8

0.6

10 2

0.4

2000
10

0.2

1000
0

0
0

2000

4000

49

50

51

52

53

54

55

TDC [ps]1

56

x [mm]

Figure 8.22: Left: timing distribution measured for single photons. Right: position dependenceof the signal fraction appearing on the left of two pads, with the boundary between the pads
located at x = 52 mm.
10 6
10

5

10 4
10 3
10 2
10
1
0

250

500

750

1000

ADC ch. 2

count

count

Figure 8.23: Left: variation of the single-photoelectron pulse height as a function of the magnetic
field. Right: pulse height distribution for single photons at 1.5 T and HV of 2500 V.
10 4

10 4

10 3

10 3

10 2
10

2

10
10
1
10

20

30

40

50

60

10
x (mm)

20

30

40

50

60
x (mm)

Figure 8.24: Total count rate of one row of channels measured without magnetic field (left) andwith a magnetic field of 1.5 T (right).
266

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

that the range of both effects is strongly limited and that the position resolution in a magnetic
field will improve.
• Aging test To check the stability of the photon detection efficiency during the lifetime ofthe experiment, an aging test was performed in a similar way as with the HAPD. The total
accumulated anode charge during the aging test was ≈400 mC/cm2 , after which we observeda drop in PDE of the order of 10%. Since such a value of accumulated charge corresponds toten years of operation of Belle II, the observed drop in photon detection efficiency is acceptable.

PDE

ch28

Zbran naboj / cm^2
0 mC/cm^2
200 mC/cm^2
400 mC/cm^2
400 mC/cm^2 [laser]

14
12
10
8
6
4
2
0
200

250

300

350

400

450
500
valovna dolzina [nm]Figure 8.25:
Measured PDE before the MCP-PMT aging and after 200 mC/cm2 and2
400 mC/cm , respectively.

Beam test
In a series of beam tests between 2004 and November 2009 [20], we measured the performanceof the Photonis multichannel-plate PMTs. The experimental arrangement was similar to theone used for the HAPD, as described in section 8.5.4, except that a single MCP PMT was usedin the tests.
From the distribution of hits and clusters with respect to the corresponding Cherenkov angle,
we obtain the resolution (σ of the fitted Gaussian) as well as the average number of hits (pads)
or clusters per incident charged particle (Fig.8.26). The number of detected Cherenkov photons
is obtained by normalising a Poissonian distribution at zero hits and, as expected, is found to
be in between the number of clusters and the number of hits. For the present MCP PMT,with a geometrical acceptance of 14% (for a single MCP PMT), we detected 1.4 clusters/track,corresponding to 3.1 Cherenkov photons/track. For full coverage of the photon detector planewith MCP PMTs, the acceptance would be 80% and one extrapolates to 8 clusters/ring, or toabout 17 detected Cherenkov photons per ring. The angular resolution for single Cherenkov
photons as obtained from the measurement is 14.8 mrad.
As Cherenkov photons are emitted promptly with respect to the charged particle traversing theradiator, they may be used for timing purposes. The time distribution of Cherenkov photons
emitted in the MCP-PMT window was measured relative to a start signal provided by another
MCP-PMT with a quartz radiator [21]. The standard deviation of the distribution for single
photons from the aerogel is found to be 50 ps. For about 10 detected photons, one may therefore
expect σ ∼ 20 ps. Since a large number of Cherenkov photons (≈ 20) are emitted in the267

ty(rad)N

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

131.5

/ 76
762.6
0.30570.1483E-01
62.34-83.90

P1
P2
P3
P4
P5

800

600

0.4

0.2

0
400
-0.2
200
-0.4
0
0

0.1

0.2

0.3

0.4

theta Cherenkov

0.5

θc(rad)

-0.5

-0.25

0

0.25

0.5

tx(rad)ring in Cherenkov spacestart counter
MCP PMTHPK R3890

countsFigure 8.26: Beam test of the MCP PMT as a detector of Cherenkov photons. Left: thedistribution of Cherenkov angles corresponding to center of gravity of hits in clusters as recorded
for 4 GeV/c pions. Right: accumulated hits in Cherenkov space.

MCP PMT
BURLE 85011

117.0

200

P1
P2
P3
P4
P5
P6

175

window

150

/ 62
165.3
40.18
1.505
52.33
48.19
1.848

125

M
W
P
C

M
W
P
C

beam

quartzCherenkov photons
from PMT window
Trigger counters100

σ ∼ 38ps

75
50
25
0

20

30

π

p

40

50

60

70

time [1bin=25ps]

Figure 8.27: Beam test of the TOF capabilities of a RICH counter with MCP-PMTs as photosensor. Left: The experimental set-up; Cherenkov photons emitted in the window of the MCPPMT are used for measuring the time of arrival. The start signal is provided by another MCPPMT. Right: the distribution of the time of flight as measured for the Cherenkov photons from
the MCP-PMT window, shown for 2 GeV/c pions and protons.

268

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

MCP-PMT entry window (Fig.8.27), a TOF measurement is possible even for particles below
Cherenkov threshold in aerogel. The timing capability of the apparatus is illustrated by themeasured time distribution of Cherenkov light generated by beam particles in the glass windowof the MCP PMT. One clearly separates pions from protons at 2 GeV/c, even for the very shortflight path (65 cm) of the present measurement.

8.5.3

Read-out Development

We first produced several versions of ASICs for prototyping at the VLSI Design and Education
Center (VDEC) of the University of Tokyo using the ROHM CMOS 0.35 µm process [22]. The
ASIC consists of a charge-sensitive preamplifier, a shaper and a variable gain amplifier (VGA),
followed by a comparator for the digitization of analog signals to on/off hit information, and adigital shift register for pipelined readout. Each chip has 18 channels, so we need eight chips toread out one HAPD. The threshold voltage for the comparator is common to all channels, but
the offset voltage can be adjusted channel-by-channel. Therefore, we can effectively vary thethreshold voltage for each channel.
The target noise level is 1200 e− at 80 pF, which corresponds to a signal-to-noise ratio of 10,
assuming an HAPD gain of 12000. After four iterations of test production since 2003, the noiselevel of the final evaluation ASIC is measured to be around 1900e− , which is higher than thetarget value of 1200e− but is still small enough for the detection of single photons with an
HAPD. We have confirmed that noise in all HAPD channels can be suppressed by adjusting theoffset values. We then performed a beam test of a prototype aerogel RICH in 2008. Here, weread out six HAPDs using 48 prototype ASICs, and succeeded in observing a clear Cherenkov
ring, as mentioned in Sec. 8.5.4.
The remaining issues revolve around compatibility with the Belle II central DAQ scheme and the
management of all the readout channels. To meet these requirements, we have started developing
a new second-generation ASIC, which consists of a preamplifier, shaper and comparator, in which
the digital readout elements are excluded from the ASIC; instead, the hit information is passed
through output pins, and is subsequently manipulated by an external FPGA. The amplification
factor and the shaping time are variable, and the offset voltage for each channel is adjustable
as well. They can be controlled by setting external parameters. The first version ASIC of thistype, called SA01, was produced at MOSIS with the TSMC CMOS 0.35 µm process. This SA01
chip handles only 12 channels since the primary purpose for this iteration is just to check basic
performance.
Figure 8.28 shows the dependence of the measured noise level in the SA01 on input capacitance.
The noise level at 80 pF is around 1200e− , which is better than the ASICs in the previous
generation.
Figure 8.29 shows the signal pulse height measured before the comparator as a function of input
charge with four different gain settings. We find good linearity when the input charge is small,but saturation is observed when the input charge exceeds 60,000 electrons, even when runningat the lowest gain. This is because the HAPD gain is assumed to be 12000 at the design stage,
while recent HAPD samples exhibit excellent performance with a gain of more than 40000.
This mismatch, related to the input signal saturation, is fixed in the SA02 by reducing thepreamplifier gain to one-fourth. In the beam test in 2009, we succeeded in reading out HAPD
signal with SA01. Details of the beam test are discussed in Sec. 8.5.4.
Based on feedback from the SA01 results, a second iteration—the SA02—was made with thesame process at TSMC. Aimed at higher density, the SA02 chip is capable of 36 channels, andan appropriate gain is designed. The SA02 is packaged in a 160-pin QFP for the first time.

269

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

Output (mV)

1000

Noise (electron)

2500
2000
1500

800
600
400

1000

200

500

0
0

50

100

Input Charge (103 e-)
0
0

100

200

Capacitance (pF)

Figure 8.29: Measured linearity of SA01. The
horizontal axis is the input charge from the
Figure 8.28: The dependence of the SA01
test pulse, while the vertical axis indicatesnoise level on detector capacitance, where thethe pulse height before the comparator. MeaHAPD corresponds to 80 pF capacitance.
surements with four different gain settings areshown.

However, the size of this package, around 30 mm × 30 mm, is too large for our application:
we need a smaller package to make the front-end electronics compact. One of the candidate
technologies is Low-Temperature Co-fired multi-layer Ceramic (LTCC) substrates. The sizeof an LTCC substrates that we produced with SA02 is 1.3 mm × 1.3 mm (Fig. 8.30). The
performance of this LTCC substrate will be tested.

Figure 8.30: SA02 chip with LTCC substrates (left: front view, right: rear view).
We then need to design readout electronics that would fit in the small space behind the HAPD.
ASICs and the FPGA will be placed on a readout board attached to the rear of the HAPD. We
may put another patch board, connected to several readout boards, to collect the data and send
it to the electronics hut via an optical fiber.

8.5.4

Test Beam Experiment8.5.4.1

Experimental Setup

The first beam tests of a prototype RICH counter with HAPDs, equipped with the ASIC readout
system, were performed in March and June 2008. We used the Fuji test beam line at KEK,
where a 2.0 GeV/c electron beam was available. In these beam tests, we successfully observed a270

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

Cherenkov ring image for the first time with HAPDs and ASICs. In November 2009, we carriedout another more realistic test beam experiment with an improved prototype RICH counter thatincorporated the aerogel radiators produced with the “pin-hole drying” method, new HAPDs
with the “Super Bialkali” photocathode, and SA01 ASICs. The setup of the prototype RICH
counter is shown in Fig. 8.31.

Figure 8.31: Prototype RICH counter used in the test beam experiment in November 2009.
Six HAPDs were arranged in a 2 × 3 array, as illustrated in Fig. 8.32. The HAPD geometry
was taken from the innermost two layers of one sector of the final photon detector sextant.
Table 8.5 summarizes the HAPD QE used in this beam test. The average QE taking into
account the geometrical acceptance and the distribution of tracks on the photon detector is 24%
at λ = 400 nm.
The front-end electronics system, equipped with the ASIC chips, was directly attached to theback plane of the HAPD. The upper three HAPDs are read out by 36 chips of the ASIC SA01,
and the bottom three are read out by the ASIC chips of the old version used in the 2008 beam
test for the purpose of comparison. The aerogel radiator was located 200 mm from the surfaceof the HAPD, which is the same configuration as in the final detector.
The track parameters were determined by two multi-wire proportional chambers (MWPCs)
placed upstream and downstream of the prototype counter. The size of the sensitive area of the

Figure 8.32: HAPDs of the prototype RICH counter.

271

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

serial #SHP120
SHP077
SHP070
SHP113
SHP117
SHP118

QE (%) at λ = 400 nm
20.5
22.0
25.0
21.1
30.1
27.4

Table 8.5: Summary of HAPD QE (at 400 nm) used in the beam test.
MWPC is about 5 × 5 cm. Figure 8.33 shows the distribution of the measured track position on
the radiator plane with the HAPD positions overlayed.

y (mm)

Track position
100
100
80
60
80
40
20

60

0
-20

40

-40
-60

20

-80
-100

-100

-50

0

50

100
x (mm)

0

Figure 8.33: Track position on the radiator plane. Boxes indicate the HAPD positions.

8.5.4.2

Photoelectron yield and Cherenkov angle resolution

In this beam test, two aerogel radiator layers of n = 1.054 and 1.065, each 20 mm thick, were used
to produce a Cherenkov ring image on the HAPD window plane. Their transmission lengths
at λ = 400 nm are 47.8 mm (n = 1.054) and 55.2 mm (n = 1.065). Figure 8.34 shows theaccumulated hit image and the Cherenkov angle distribution for the tracks passing through thecenter of the prototype RICH counter (−10 < x < 10 mm and −10 < y < 5 mm) perpendicular
to the radiator and to the photon detector plane. By fitting this distribution with a gaussian,
the single photon resolution was measured to be 13.5 mrad. The photoelectron yield (Npe ) was
calculated by integrating the fitted function over a 3σ area; a one dimensional polynomial was
assumed for the background contribution. We obtained Npe = 15.3 with this configuration, anda simple calculation indicates that a 6.7σ π/K separation can be achieved at a momentum of
4 GeV/c . The background contribution was found to be about two photoelectrons, which is
sufficiently small. Only a few HAPDs used in the experiment were equipped with a “Super
Bialkali” photocathode. In HAPD mass production, the QE of “Super Bialkali” HAPDs is
expected to be improved further to an average peak value of 30%, with a resulting ∼ 30%
increase in photoelectron yield.
The expected number of photoelectrons can be calculated from the radiator properties, the272

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

rich_2d_1

RICH Hit Map, w.r.t. track

Entries 412449
Mean x -0.09929
Mean y -0.4329

6000

100

RMS x

43.24

RMS y

42

5000
50
4000
0

3000
2000

-50

1000

-100
-100

-50

0

50

0

100

ahistmiki

ahist

6000

Entries

64801

Mean

0.3092RMS

0.07419

χ 2 / ndf

143.5 / 28
6129 ± 39.4

constant

5000
4000

mean

0.3067 ± 0.0001

sigma

0.01349 ± 0.00007

BG const-192.6 ± 20.5

BG slope

1715 ± 69.4

# of tracks : 2700

3000

# Photons : 41339.7 +- 227.3
Photon/track: 15.31 +- 0.08
BG / track : 2.00 +- 0.03

2000

run0481000
00

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

Figure 8.34: Cherenkov image and Cherenkov angle distribution.
HAPD QE, and the acceptance of the prototype RICH counter as
Nphot = N1 + N2 ,

(8.1)




d2
N1 = 2πα sin2 θc1 ǫa exp −Λ2 (λ) cos θc1



d1
×Λ1 (λ) cos θc1 1 − exp −ǫq (λ) λ−2 dλ,(8.2)
Λ1 (λ) cos θc 1



Z
d2
2
N2 = 2πα sin θc2 ǫa Λ2 (λ) cos θc1 1 − exp −ǫq (λ) λ−2 dλ, (8.3)Λ2 (λ) cos θc2
Z

where the indices 1 and 2 indicate the upstream and the downstream aerogel, respectively, λ is
the wavelength of the Cherenkov photon, α is the fine structure constant, θc is the Cherenkov
angle, Λ(λ) is the transmission length of the aerogel, ǫq is the QE of HAPDs, and ǫa is theacceptance of the setup including the geometrical acceptance and other effects. The acceptanceof the setup is estimated to be 40%, taking into account the APD sensitive region for the ring
image (61%), the fraction of events without electron backscattering on the APD surface (80%),273

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

the counting loss of photoelectrons hitting the same channel (90%), and the fraction of active
channels (96%). The expected numbers of photoelectrons as a function of the incident photon
wavelength are shown in Fig. 8.35 for the case of 100% acceptance. They are N1 = 5, N2 = 12,
so that Nphot = 17, which is within 10% of the measured result.
 &'( )*
 




  
&'()*&'( )* +,-. /0 1234  



 



 


 

 


















  !" #$%Figure 8.35: Expected number of photoelectrons depending on the incident photon wavelength
for the case of 100% acceptance. The upstream aerogel is PDR20-3a (n = 1.054) and thedownstream aerogel is PDR11-4a (n = 1.065).

8.5.4.3

Performance for inclined tracks

In the Belle II environment, the charged tracks from the interaction region hitting the ARICH
are inclined with polar angles between 15 and 30 degrees. Hence, we measured the RICH performance for tracks inclined by 15 and 30 degrees in the test beam experiment. Figures 8.36 and8.37 show the Cherenkov ring image and Cherenkov angle distribution. In these measurements,
the tracks detected in the full acceptance of the MWPCs are used. For tracks inclined at anangle of 15 degrees, we obtained Npe = 14.5 and a single photon resolution of 14.9 mrad, whichcorresponds to 5.8σ π/K separation at 4 GeV/c. For 30-degree inclination, the fit to the test
beam result gives Npe = 13.4 and a single photon resolution of 16.7 mrad, corresponding to 5.0σ
π/K separation. The detected number of photoelectrons is smaller than that for 15 degrees
because about 15% of the ring image is outside of the acceptance of the 2 × 3 HAPD array.
Corrected for the acceptance loss, the result for 30 degrees corresponds to Npe = 15.8 and 5.5σ
π/K separation at 4 GeV/c. We have therefore confirmed that the prototype RICH counterachieves more than 5σ π/K separation.

8.6

Expected Performance

8.6.1

Number of Photons

The expected number of Cherenkov photons was calculated by combining the measured values
for quantum efficiency ǫq (λ) (Fig. 8.12) and for aerogel transmission T (λ) (Fig. 8.7),
Nphot ≈ 370cm−1 d ǫe ǫa ǫt sin 2 θcZǫq (λ) T (λ) λ−2 dλ,(8.4)

where d is the radiator thickness (2 cm for single aerogel layer), ǫe is the single photoelectron
detection efficiency (estimated to be 0.80 for the HAPD), and ǫa is the active surface fraction of
the photon detector (0.67 in the case of HAPD); ǫt = 0.9 is the fraction of the surface covered274

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

rich_2d_1

RICH Hit Map, w.r.t. track100

rich_2d_1

RICH Hit Map, w.r.t. track

Entries 795145

Entries 728303

Mean x

6.137

Mean x

2.622

Mean y12000-3.287

Mean y16000-4.219

RMS x

45.92

RMS x

47.94

RMS y

42.47

RMS y

42.72
14000

100

10000
50

12000

50
8000

10000

0

6000

0

-50

4000

-50

8000
6000
4000

2000

-100
-100

-50

0

0

50

100

Cherenkov Angle, accumulated

ahist2

Entries

60000

0.2626RMS

0.1201χ 2 / ndf

50000
40000
30000

-100

100

Cherenkov Angle, accumulated

ahist2611.9 / 31

constant

5.503e+04 ± 116

mean

0.3111± 0.0000

sigma

0.01494 ± 0.00002

BG const

2312 ± 60.4

BG slope

3475 ± 193.5

45000# Photons : 411097.2 +- 726.2

40000

10000

BG / track : 2.14 +- 0.01

728303Mean

0.22830.13

χ 2 / ndf

1328 / 35

constant

4.01e+04 ± 93

mean0.3158 ± 0.0000

sigma

0.01664 ± 0.00003

30000

BG const

4768 ± 47.1

BG slope-7573 ± 138.0

20000# of tracks : 24891# Photons : 333676.6 +- 651.8
Photon/track: 13.41 +- 0.03

15000
10000

run077

Entries

35000

Photon/track: 14.46 +- 0.03

20000

0

RMS

25000

# of tracks : 28422

-50

0

50

795145

Mean

2000

-100

BG / track : 1.91 +- 0.01

run0845000
00

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

001

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

Figure 8.36: Cherenkov image and Cherenkov Figure 8.37: Cherenkov image and Cherenkov
angle distribution for tracks inclined at 15 de- angle distribution for tracks inclined at 30 degrees.
grees.

275

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

with photon detector modules in a particular tiling scheme (Fig. 8.6). The resulting expected
average number of detected Cherenkov photons from both layers is 20.

8.6.2

Resolution of Cherenkov angle

From the photon hit coordinate as measured by the photon detector and from the particle
trajectory as given by the tracking chamber, the photon direction is reconstructed to obtain
the Cherenkov angle and thus the velocity βc of the particle. Sources of error in the measurement with a single photon√ are as follows. The finite radiator effective thickness, d = 2 cm,
contributes σθemp = d/(ℓ 12) sin θc cos θc = 9.8 mrad. The second contribution comes from the√finite coordinate resolution of the photon detector σθpix = a/(ℓ 12) cos2 θc = 6.6 mrad, witha pad size of a = 4.9 mm and the radiator to photon detector distance of ℓ = 19 cm. The
chromatic error, i.e., the variation of the refractive index over the energy range of Cherenkov
photons that are detected by the photon detector, is determined from the measured variation ofrefractive index with wavelength, the transmission of aerogel and the photo-detector quantum
efficiency. The resulting r.m.s. spread σn of the refractive index can be determined, from whichσθdis = σn /(n tan θc ) = 2 mrad is obtained. From the experience with the HERMES RICH [23],we conclude that the contribution due to the imperfections and inhomogeneity of the radiator are about 2 mrad. Finally, the contribution arising from the error in track parameters as
determined by
p the tracking system and extrapolated to the radiator is expected to amount toσθtr = 6 mrad 1 + (1.75GeV/c/p)2 .
Finally, the combined single-photon error is obtained by summing the above errors in quadrature.
For 4 GeV/c momentum tracks this gives σθ = 14 mrad. Assuming 20 detected photons for aβ = 1 particle, the measurement precision isσθσθ (N ) = √ = 3.1 mrad.
N

(8.5)

In the absence of backgrounds, the proposed counter would thus enable better than 5σ pion-kaon
separation at the kinematic limit of 4 GeV/c. Pions would be separated by 4σ from electrons
up to about 1 GeV/c.

8.6.3

Background

Since the number of photons per ring can be rather low, backgrounds could degrade the performance as discussed above. The following sources of background expected in the RICH photon
detector were considered:
1. Rayleigh-scattered Cherenkov photons from the same charged particle.
2. Cherenkov photons emitted by the same charged particle in the photon detector window.
3. Cherenkov photons emitted by other charged charged particles in the event.
4. Cherenkov photons emitted by products of a primary photon conversion in the material infront of the RICH radiator and in the radiator itself.
5. Beam related background hits.
6. Electronic noise.

276

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

The levels of backgrounds (1) and (2) were estimated from the test beam data (Fig. 8.34) andturned out to be the dominant source. The levels of backgrounds (3) and (4) were studied
by computer simulation. Because of the rather small diameter of Cherenkov rings (12 cm)
as compared to the typical distance between charged particle impact points on the aerogel
radiator, background (3) does not contribute significantly. The level of source (5) was estimatedfrom the background rate in the Belle EACC, and scaled by a factor of 20 as expected from thebackground calculations. This rough estimate yields values on the order of 100 Hz/cm2 . Finally,
the electronic noise was estimated by assuming a conservative value of 10−3 for the probabilityof a noise hit. In total, we expect ≈0.7 smoothly distributed background hits within a ±3σθannulus of the 4 GeV/c pion ring.

8.6.4

Particle Identification Capabilities

Kaon identification efficiency

The particle identification capabilities of the counter were evaluated by using simulated data.
The backgrounds that are not included in the simulation (Rayleigh-scattered Cherenkov photons
from the same charged particle, Cherenkov photons emitted by the same charged particle in
the photon detector window, beam related background hits, and electronic noise) were added
according to observed or expected rates. In the analysis of simulated events, the likelihood for

1

0.8

0.6

0.4
Detector configuration
focusing

0.2

single layer

00.5

1

1.5

2

2.5

3

3.5

4
4.5
5
momentum (GeV/c)

Figure 8.38: Particle identification capability of the aerogel RICH counter: kaon efficiency for
1% pion misidentification probability. The focusing radiator configuration (N) is compared tothe homogenous radiator (◦).
the observed hit pattern is calculated for each hypothesis, and momentum-dependent selection
criteria are chosen for a given misidentification probability [24]. The resulting identification
efficiency for kaons is shown in Fig. 8.38; as expected, we observe a clear advantage of using a
focusing radiator compared to a homogenous one.
We have also investigated the performance of the counter in the region close to the boundary of
the barrel PID device. As can be seen from Fig. 8.39, a sizable fraction of Cherenkov photons
emitted by charged particles close to this boundary do not hit the photon detector. This problem
could in principle be overcome by a planar mirror as illustrated in Fig. 8.40.

277

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

1

ε

ε

Figure 8.39: Propagation of Cherenkov photons of a charged particle hitting the aerogel radiatorin the vicinity of the boundary to the barrel part, for the case with an additional planar mirror.

1

0.9

0.9

0.8

0.8

0.7

0.7

0.6

0.6

0.5

Kaon identification ε

0.5

Kaon identification ε

0.4

Pion misidentification prob.

0.4

Pion misidentification prob.

0.3

Geometrical acceptance

0.3

Geometrical acceptance

0.2

0.2

0.1

0.1

0
-50

0

50

100

150

200

0
-50

250
300
track position (mm)

0

50

100

150

200

250
300
track position (mm)Figure 8.40: Particle identification capability in the vicinity of the boundary to the barrel PID:
kaon efficiency for 1% pion misidentification probability. Cases with an additional planar mirror(right) and without it (left) are shown as function of the distance from the boundary.

278

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

8.6.5

Physics Impact Study in B → ργ Analysis

The physics impact of the ARICH is estimated by the analysis of B → ργ for two forward-endcap
configurations:(F1) the Belle PID (EACC and dE/dx). This corresponds to the scenario where the EACC isused in Belle II; this is the reference configuration.
(F2) the ARICH detector.
The simulation for the (F1) case is done using Belle’s gsim with the Belle geometry, whereas the(F2) case is simulated with fsim [25].
In addition to the end-cap configuration, the following barrel-PID cases are evaluated:(B1) the present Belle PID (BACC, TOF and dE/dx); this is the reference, corresponding to(F1) in the end-cap.
(B2) the focusing TOP detector.
The (B1) and (B2) simulations are performed using gsim and fsim, respectively.
We reconstruct B 0 → ρ0 γ and B + → ρ+ γ events from a B → ργ signal Monte Carlo (MC)sample. The B → K ∗ γ process is also simulated as the physics background channel, with theevents subjected to the same analysis program. The selection criteria are similar to those in the
recent Belle analysis [26]. For simplicity, the contribution from the q q̄ background is assumed to
be independent of the PID configuration and is fixed to 2000 events for 7.5 ab−1 . We estimate
the figure of merit (FOM) from the number of signal (B → ργ) events NS and background(B → K ∗ γ and q q̄ background) events NB in the signal region. The signal region is definedby Mbc > 5.27 GeV/c2 and ∆Emin < ∆E < 0.08 GeV, where ∆Emin is chosen for each PID
configuration to maximize the FOM.
BarrelB1
B1
B2
B2

Forward
F1
F2
F1
F2

NS
987
1032
982
1027

NB
5242
5026
2865
2651

FOM
12.5
13.3
15.8
16.9

∆Emin [ GeV]
−0.25
−0.25
−0.30
−0.30

Table 8.6: Number of signal (NS ) and background (NB ) events, figure of merit (FOM), andthe ∆E lower limit ∆Emin chosen for each barrel and forward PID configuration for B 0 → ρ0 γ
analysis at 7.5 ab−1 . See the text for an explanation of the configuration label.
BarrelB1
B1
B2
B2

Forward
F1
F2
F1
F2

NS
1152
1194
1141
1183

NB
3006
2981
2490
2465

FOM
17.9
18.5
18.9
19.6

∆Emin [ GeV]
−0.30
−0.30
−0.30
−0.30

Table 8.7: Number of signal (NS ) and background (NB ) events, figure of merit (FOM), and the∆E lower limit ∆Emin chosen for each barrel and forward PID configuration for B + → ρ+ γ
analysis at 7.5 ab−1 . See the text for an explanation of the configuration label.

279

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP(b)
EventsEvents

(a)
ργ
*0
K γ
0

400

300

ργ
*0
K γ
0

200
200

0

100

-0.4

-0.2

0

0.2

0

0.4
∆E

-0.2

0

0.2

0.4
∆E

(d)
EventsEvents

(c)

-0.4

ρ +γ
K*γ

150

150

100

100

50

50

0

-0.4

-0.2

0

0.2

0

0.4
∆E

ρ +γ
K*γ

-0.4

-0.2

0

0.2

0.4
∆E

Figure 8.41: Expected ∆E distribution at 7.5 ab−1 for (a) B 0 → ρ0 γ with Belle PID configuration (B1+F1), (b) B 0 → ρ0 γ with TOP and ARICH (B2+F2), (c) B + → ρ+ γ with Belle PID
configuration (B1+F1), (d) B + → ρ+ γ with TOP and ARICH (B2+F2).
Tables 8.6 and 8.7 tabulate the FOM for four detector configurations. The ∆E distributions for
two PID configurations—F1+B1 with the Belle devices and F2+B2 with the ARICH and TOP—
are shown for ργ signals together with K ∗ γ backgrounds in Fig. 8.41. Comparing the histogramsfor B 0 → ρ0 γ in this figure, the suppression of the K ∗ γ background is quite significant with
the TOP and ARICH. The K ∗ γ component below −0.2 GeV contains events that arise frommisreconstruction rather than a simple misidentification between K and π. In Fig. 8.41(b), where
the misidentification is highly suppressed by the good PID devices, such misreconstructed eventsare more apparent. For the B + → ρ+ γ case in the same figure, we also observe a significant
improvement in the analysis, although the effect is smaller if compared to the ρ0 γ channel:
misreconstructed events already represent a significant fraction of the background in the Belleconfiguration. Tables 8.8 and 8.9 show the “luminosity gain” of the B2+F2 configuration relative
to the B1+F1 configuration, defined as the square of the ratio of the FOM; it is the luminosity
ratio that would be necessary to obtain the same sensitivity with the Belle PID configuration.
From Table 8.8, the TOP detector gives us a significant luminosity gain in the B 0 → ρ0 γ mode,and the ARICH detector further improves the physics sensitivity: up to ∼ 80% gain. In the
B + → ρ+ γ mode, we obtain 20% higher sensitivity with the new PID system.
280

CHAPTER 8. PARTICLE IDENTIFICATION: END-CAP

B1
B2

F1
1.00
1.60

F2
1.12
1.83

B1
B2

F2
1.07
1.20

Table 8.9: Luminosity gains for B + →ρ+ γ for four PID configurations.

Table 8.8: Luminosity gains for B 0 →ρ0 γ for four PID configurations.

8.7

F1
1.00
1.12

Schedule

Figure 8.42 shows the ARICH construction schedule. After the photon detector technology

Figure 8.42: ARICH construction schedule by calendar year.
choice made in December 2009, we continue R&D on HAPD improvement and will finalize its
specification for bidding. According to the producer, the HAPD production will take 2.5 years;
this could be on a critical path in the ARICH overall schedule. In parallel, readout electronics
production will be planned in 2012 after a further two years of R&D to arrive at the final version.
The aerogel radiator is not a critical component for the timeline. After some further work on
optical improvements, the producer for mass-production will be selected in the coming years.
For the mechanical structure, the baseline design has to proceed in detail after the outer radiusof the end-cap is decided. In 2010-2011, a 1/6-size mock-up will be produced to verify manytechnical issues such as radiator tile alignment, HAPD arrangement cabling space, and so on.
After this, the mechanical container will be ordered.
Modules consisting of an HAPD and the front-end readout system will be produced in 20122013, and they will be installed into the container in the 3rd to 4th quarter of 2013. The
attachment of the ARICH to the E-CsI container will be done at the beginning of 2014; theend-cap apparatus will be installed in the spring of 2014. The cosmic ray test in situ as well as
ARICH commissioning is expected in the summer of 2014.

281

References[1] S. Hashimoto, (ed. ) et al., KEK-REPORT-2004-4.
[2] T. Matsumoto et al.,10.1016/j.nima.2003.11.384.

Nucl. Instrum. Meth. A 521,

367 (2004),

DOI:[3] T. Iijima et al., Nucl. Instrum. Meth. A 548, 383 (2005), DOI: 10.1016/j.nima.2005.05.030.
[4] P. Križan et al., Aerogel rich, 2004, presented at the Super B Factory Workshop, Honolulu,
Hawaii, http://www.phys.hawaii.edu/superb04.
[5] A. Barnyakov et al., Nucl. Instrum. Meth. A 553, 70 (2005), Proceedings of the fifthInternational Workshop on Ring Imaging Detectors, DOI: 10.1016/j.nima.2005.08.073.
[6] P. Krizan, S. Korpar, and T. Iijima, Nucl. Instrum. Meth. A 565, 457 (2006), DOI:
10.1016/j.nima.2006.05.233.
[7] I. Adachi et al., Nucl. Instrum. Meth. A 553, 146 (2005), Proceedings of the fifth International Workshop on Ring Imaging Detectors, DOI: 10.1016/j.nima.2005.08.022.
[8] Hamamatsu Photonics K.K., HAPD data sheet, private communication.
[9] I. Adachi, Y. Ishii, H. Kawai, A. Kuratani, and M. Tabata, Nucl. Instrum. Meth. A595,
180 (2008), 10.1016/j.nima.2008.07.056.
[10] M. Tabata et al., Status of Aerogel Radiator with High Refractive Indices, 2010, presented
at VCI2010, Vienna, Austria.
[11] S. Nishida et al., Nucl. Instrum. Meth. A610, 65 (2009), 10.1016/j.nima.2009.05.051.
[12] Hamamatsu Photonics K.K.,UBA and SBA Photomultiplier Tube Series, HPK Catalogue.
[13] S. Shiizuka et al., Study of 144-channel Hybrid Avalanche Photo-Detector for Belle II RICHCounter, 2010, presented at VCI2010, Vienna, Austria.
[14] I. Nakamura, J. Phys. Conf. Ser. 160, 012003 (2009), 10.1088/1742-6596/160/1/012003.
[15] The reactor Yayoi, Univ. of Tokyo, http://www.nuclear.jp/index-e.html.
[16] CERN-ROSE/RD48, M. Moll, E. Fretwurst, and G. Lindstrom, Nucl. Instrum. Meth.
A426, 87 (1999), 10.1016/S0168-9002(98)01475-2.
[17] Photonis Planacon, XP85112 data sheet, private communication.
[18] S. Korpar, P. Krizan, and R. Pestotnik, PoS PD07, 021 (2006), 10.1016/j.nima.2008.07.022.
282

REFERENCES[19] M. Akatsu et al.,Nucl.
10.1016/j.nima.2004.04.207.

Instrum.

Meth.

A

528,

763

(2004),

DOI:[20] P. Krizan et al., Nucl. Instrum. Meth. A567, 124 (2006), 10.1016/j.nima.2006.05.217.
[21] S. Korpar et al., Nucl. Instrum. Meth. A572, 432 (2007), 10.1016/j.nima.2006.10.398.
[22] S. Nishida et al., Development of the readout ASIC for the 144ch HAPD for Aerogel RICH,
2009, presented at TIPP09, Tsukuba, Japan.
[23] N. Akopov et al.,9002(01)00932-9.

Nucl. Instrum. Meth. A 479, 511 (2002),

DOI: 10.1016/S0168-[24] R. Pestotnik, P. Krizan, S. Korpar, and T. Iijima, Nucl. Instrum. Meth. A 595, 256 (2008),
RICH 2007 - Proceedings of the Sixth International Workshop on Ring Imaging Cherenkov
Detectors, DOI: 10.1016/j.nima.2008.07.019.
[25] sBelle Design Group, I. Adachi et al., (2008), 0810.4084.
[26] Y. Ushiroda et al., Phys. Rev. Lett. 100, 021602 (2008), 10.1103/PhysRevLett.100.021602.

283

Chapter 9

Calorimeter (ECL)
9.1

Introduction

Since one third of B-decay products are π 0 ’s or other neutral particles that provide photons ina wide energy range from 20 MeV to 4 GeV, a high resolution electromagnetic calorimeter isa very important part of the Belle II detector. CsI(Tl) was chosen as the scintillation crystal
material for the Belle calorimeter due to its high light output, relatively short radiation length,
good mechanical properties and moderate price. The main tasks of the calorimeter are:• detection of photons with high efficiency,• precise determination of the photon energy and angular coordinates,• electron identification,• generation of the proper signal for trigger,• on-line and off-line luminosity measurement.
• KL0 detection together with the KLM (Ch. 10).

9.2

The Belle electromagnetic calorimeter

The Belle electromagnetic calorimeter (ECL) consists of a 3 m long barrel section with an inner
radius of 1.25 m and annular endcaps at z = 1.96 m (forward) and z = −1.02 m (backward)
from the interaction point. The calorimeter covers the polar angle region of 12.4◦ < θ < 155.1◦ ,except for two gaps ∼ 1◦ wide between the barrel and endcaps.
The barrel part has a tower structure that projects to a region near the vicinity of the interaction
point. It contains 6624 CsI(Tl) crystals of 29 distinct shapes. Each crystal is a truncated pyramidof an average size about 6 × 6 cm2 in cross section and 30 cm (16.1X0 ) in length. The endcaps
consists of 2112 CsI crystals of 69 shapes. The total number of crystals is 8736, with a total
mass of about 43 tons.
Each crystal is wrapped with a layer of 200-µm thick Gore-Tex porous teflon and covered by alaminated sheet of 25-µm thick aluminum and 25-µm thick mylar. For scintillation light readout,
two 10 × 20 mm2 Hamamatsu Photonics S2744-08 photodiodes are glued to the rear surface ofthe crystal via an intervening 1-mm thick acrylite plate. An LED attached to the plate can inject
light pulses into the crystal volume to monitor the optical stability. A preamplifier is attachedto each photodiode, which provides two independent output signals from each crystal. These284

CHAPTER 9. CALORIMETER (ECL)

two pulses are summed at an external shaper board. To monitor the stability of the electronics,
the test pulses can be injected into the inputs of the preamplifiers.
The barrel crystals are installed in a multi-cell structure formed by 0.5 mm thick aluminum
septum walls stretched between the inner and outer cylinders. Eight crystals, four rows in θ andtwo columns in ϕ, are inserted in each cell and fixed in position from behind support jigs. The
overall support structure is gas tight and flushed with dry air to provide a low humidity (5%)
environment for the crystals. The heat generated by the preamplifiers (about 3 kW in total) is
extracted by a water cooling system. The endcap support structure is similar to the barrel one.
The calorimeter is described in detail in reference [1].
The preamplifier attached to the crystal is followed with a shaper board placed in the crates
around the detector, as well as a digitizing and trigger module in the electronics hut. The shaperboard contains CR − (RC)4 active filters with shaping time τ = 1 µs and MQT300A chips,
which convert the input charge integrated over certain gate time to three time intervals that aremeasured by a multi-hit TDC (LeCroy 1877S). The corresponding ranges are: 0.06 MeV/bin,
0.5 MeV/bin and 4 MeV/bin. An auto-range selection option provides readout of only one range
with optimal sensitivity. In addition to the main channel, the shaper board contains fast shaper
amplifiers (τ = 200 ns), which generate signals used for triggering and timing [2].
The average output signal of the crystals, as measured by using calibration with cosmic raymuons, is about 5000 photoelectrons per MeV, while the noise level was about 200 keV prior toirradiation.
The intrisic energy resolution of the calorimeter, as measured in a prototype [3], can be approximated as:s
0.81% 2
0.066% 2
σE√+=+ (1.34%)2 ,
(9.1)
4
E
E
E
where E is in GeV and the first term represents the electronics noise contribution.

9.3

Performance with increasing luminosity

The Belle detector has been operating since 1999 and, throughout this period, the calorimeterhas demonstrated high resolution and good performance [4]. The photon energy resolution
measured for the e+ e− → γγ process, averaged over the entire calorimeter, is σE /E=1.7%. The
photon energy range for this process is 3.5 GeV < Eγ < 8 GeV, depending on the photon angle.
The azimuthal angular resolution for these photons is 0.23◦ . The γγ invariant mass for π 0 andη mesons is determined with a resolution of 4.8 MeV/c2 and 12 MeV/c2 , respectively. These
results are in good agreement with Monte Carlo simulation.
However, the Belle II experiment, operating with a SuperKEKB luminosity of up to 8 × 1035
cm−2 s−1 , puts new, severe requirements on the calorimeter. An obvious concern is the anticipated degradation of the thallium-doped CsI crystal performance parameters due to the highradiation dose.
The absorbed dose collected by the crystals in the course of the Belle exeriment is shown in
Fig. 9.1. By summer 2009, the measured integrated dose (i.e., for an integrated luminosity of
900 fb−1 ) is about 100 rad for the barrel crystals and about 400 rad for the highest-dose endcap
crystals. This has caused the light-output deterioration shown in Fig. 9.2. The light output loss
is around 7% in the barrel and up to 13% in the endcap region closest to the beam pipe.
These results are in good agreement with previous measurements of the crystal radiation hardness [5, 6]. Since these studies show the loss of the light output to be less than or about 30% at

285

CHAPTER 9. CALORIMETER (ECL)

Integrated Dose, radBarrel

120
100
80
60
40
20
0

0

1000 2000 3000
Time, Days

500
450
400
350
300
250
200
150
100
50
0

Inner Forward

01000 2000 3000
Time, Days

Figure 9.1: Absorbed dose recieved by the CsI(Tl) crystals during the Belle experiment.

A(2009)/A(1999)

Integrated Dose, rad

140

FWD

1

Barrel

BWD

0.9

0.8
0

20

40

60

Θid

Figure 9.2: Decrease in crystal light output after ten years of Belle operation.

286

CHAPTER 9. CALORIMETER (ECL)

3.6 krad, an increase of the absorbed dose by one order of magnitude in Belle II will not pose aserious problem.
Another effect of the radiation background is the increase of the photodiode dark current due toneutron bombardment. At present, the dark current increase in the barrel is not substantial—
less than 10 nA—while it is rather large in the endcap calorimeter—up to 200 nA. Thus, at
higher luminosity, the elevated dark current may be a problem.
An important issue requiring careful treatment is the so-called pile up noise, caused by softbackground photons with an average energy less than 1 MeV. Fluctuation in the number ofthese photons arriving during the integration time prior to readout contributes to the totalnoise level. The measured noise level, σ, is near the 1 MeV level in the endcaps at a luminosityof L = 1034 cm−2 s−1 .
High-energy photon backgrounds produce random cluster candidates in the calorimeter. At
present, each triggered event contains an average of 6 background clusters (3 in the barrel and3 in the endcaps) with an energy exceeding 20 MeV. By simple extrapolation, assuming thatthe current ECL hardware and software is unchanged, we will have several tens of backgroundclusters at ten times higher luminosity. This results in a substantial combinatorial backgroundfor the event reconstruction. Our approaches to address this problem are described in thefollowing sections.

9.4

General electronics upgrade

Modification of the calorimeter electronics follows the strategy in the other Belle II subsystems.
The main idea is to shorten the shaping time and to use pipelined readout with waveform
processing. In the barrel region, the shaping time is changed to 0.5 µs and each crystal counter
output signal is digitized continuously at 2 MSa/s. (Further reduction of the shaping time is
not effective, since the CsI(Tl) scintillation decay time is 1 µs.) Upon receipt of a trigger, 16
sample points within the event window are fit to a signal function F (t) = A0 × f (t − t0 ), where
the pulse height A0 and the event time t0 are free parameters. The shape of the signal response
function, f (t), is evaluated using separate measurements. The on-line fit determines A0 and t0
by minimizing
X
−1
χ2 =
(Ai − F (ti ))Sij(Aj − F (tj )),
(9.2)
i,j

where Ai is the sampled amplitude at time ti and Sij is the predetermined covariance matrix.
To realize the scheme described above, the existing shaper-QT modules will be replaced with
newly developed shaper-digitizer modules. Expected improvements from this modification were
estimated by calculation, as well as the prototype tests.

9.4.1

Signal reconstruction

To estimate the effects of beam background for the current calorimeter and to test its performance with the improved readout, a MC simulation was performed, taking into account thesignal shape and the background measured under the highest-luminosity conditions in Belle.
To simulate the pipelined readout, we use the obtained signal amplitudes (Ai ) that are recorded
in 16 sample points around the maximum of the signal and with a sample time interval ∆t =0.5 µs. For each set of generated data {Ai }, the magnitude A0 and time t0 are determined by
the fit procedure described above. Figure 9.3(left) shows the distribution of the reconstructedtiming (t0 ) with respect to the trigger timing (ttrig ) for both signal and fake clusters. In BelleII, the trigger timing is determined by one of several detector subsystems, including the ECL.
287

efficiency

CHAPTER 9. CALORIMETER (ECL)

150

1

0.98
0.96

signal E=25 MeV

100

0.94
50
0.92

background

0
-0.5

0

0.9

0.5
1
t0-ttrig (µs)

0250

500 750 1000
barrel , E(MeV)

Figure 9.3: Left: distribution of the event times determined by pulse shape fit for signals andfake clusters. Right: efficiency vs. photon energy (above 20 MeV) for true photons in the ECL
barrel after the in-time cut on |t0 − ttrig |, where the dotted blue line corresponds to 5 additional
background clusters, the dashed red line to 10 clusters, and the solid black line to 20 clusters.
Applying an energy-dependent in-time cut of |t0 − ttrig | < 5000 ns/(E/MeV), we suppress thenumber of fake photons by a factor of 7 while keeping the efficiency for true photons at morethan 93% for photons above 20 MeV. However, with the factor of 20 larger background expectedin Belle II, the pile-up noise will be a factor of 3 higher. In this case, we will need to increase thephoton energy threshold to 30 MeV to maintain the same level of combinatorial background.

9.4.2

Electronics for CsI(Tl) crystal with PIN-PD readout

A block diagram of the ECL electronics is presented in Fig. 9.4. At the beginning of the BelleII experiment, the existing CsI(Tl) crystals, PIN-Photo-diodes, preamplifiers and the cables toreach the shaper will be reused. However, the Shaper-QT modules used in Belle are replacedwith new Shaper-DSP modules.
Each signal channel contains a shaper circuit and an 18-bit flash ADC (Analog Devices AD7641)
that digitizes the signal at a 2-MHz clock frequency. The ADC data are processed by the digital
filtering algorithm implemented in a XILINX FPGA. The data processing is initiated by arrivalof a trigger signal and yields three parameters: amplitude, time, and data quality, which arecalculated according to the algorithm described above.
This data from the Shaper-DSP modules are sent to a Collector module that combines the datafrom 8-12 Shaper-DSP modules and sends this via high-speed serial link utilizing the XILINXROCKET-I/O resources to a COPPER FINESSE module, wich is the back end (common)
interface to the data acquisition system (Ch. 13). Each collector module also contains a circuit
for test pulse generation, to calibrate the response of each channel.
Each Shaper-DSP module channel also includes fast shaping (τd = 0.2 µs) and gain adjustment
circuits for calorimeter-trigger purposes. A fast analog sum signal, which is a combination of
16 gain-corrected fast shaping channels, is delivered to the FAM (Flash-ADC trigger Module),
where a trigger cell signal is generated when a threshold (∼ 100 MeV) is exceeded. These trigger
288

CHAPTER 9. CALORIMETER (ECL)

FAM

TMM
To Global trigger

Fast sum

Collector

FPGA

RocketI/O

To Finesse
Triggerclock

Decoder distributor

PA
ShaperADC

Ethernet
Calibration

Shaper DSP

Collector module

Figure 9.4: Block diagram of the electronics used to read out the CsI(Tl) crystals in Belle II.
cell signals are collected and processed by the TMM (Trigger and Monitoring Module), where
ECL subtrigger decisions are made and sent to the Global Decision Logic.
A schematic of the shaper circuit is shown in Fig. 9.5. Signals from the two preamplifiers are
summed at the stage U1 and the sum pulse is processed by the differential part at differentiating
amplifier U2 (τd ≈ 0.5 µs). Component U3 provides subtraction of the certain fraction of theintegrated signal to suppress the tail caused by long CsI(Tl) scintillation decay components.
The signal is formed by two second-order active integration stages, U4 and U5, with a shaping
time of τ ≈ 0.5 µs. Figure 9.6 shows the output signal with and without the long component
suppression.
A simplified block diagram of the pulse feature extraction logic is shown in Fig. 9.7. The digital
signal processing is performed with a XILINX XC3S1500-FG456 FPGA, which has enoughresources to realize the required waveform analysis in real time. SDRAM chips are used to store
precomputed coefficients for the digital signal processing.
The waveform analysis algorithm proceeds as follows. First, we tabulate the signal function f (t)and its deriviative f ′ (t) to obtain the tables of values fki = f (tki ) = f (kδt + i∆t), where ∆t
is the digitizing interval, and δt is the timing bin width of tabulation that is 100 times smaller
than ∆t, i and k are the corresponding bin indexes. Linearizing A0 f (t) in Eq. 9.2,′,
Af (tki − t0 ) = A0 f (tki ) − t0 A0 f ′ (tki ) = A0 fki + Bfki

289

1K

10pF

U1

PA1_OUT
4.7uF

1K

4.7uF

1K

+
4
-

560pF

3

910

3.3K

1200pF1

1200pF

U2
1uF

10K

51K

PA2_OUT

510

+
4
3

U4

510

+
4
-

1

680pF

10K

1uF

13K

3.9K

3K

51K

+
4
-

SH_OUT

680pF

1

560
7.5K
F_OUT

2K

U3
10K

+
4
3

0.1uF

2200pF

1uF

U5

510

1

560
0.1uF

560pF 910

510

3

3

1

10K

Figure 9.5: Circuit schematic of the shaping amplifier chain.

CHAPTER 9. CALORIMETER (ECL)

1

1

0.75

0.75

0.5

0.5

0.25

0.25

0

0

5

10

0

15
t (µs)

0

5

10

15
t (µs)

Figure 9.6: Shape of the CsI(Tl) scintillation signal without (left) and with (right) tail suppression.

Figure 9.7: Block diagram of digital signal processing logic implemented in XILINX FPGAs
for the energy and time feature extraction.
we can rewrite Eq. 9.2, incorporating the pedestal p as well:X′′− p) .
− p)(S −1 )ij (Aj − A0 fkj − Bfkj
χ2 =(Ai − A0 fki − Bfki
i

291

(9.3)

CHAPTER 9. CALORIMETER (ECL)

The minimization of this expression is equivalent to the linear-system solutions:X
P k−1
fki Sij(S −1 )ij (Aj − A0 fkj − Bf ′ kj − p) = 0
A0 =
αi Ai
i

i,j

X
i,j

′ −1
fki
Sij (S −1 )ij (Aj − A0 fkj − Bf ′ kj − p) = 0 ⇒ B =

X
i,j

−1
Sij
(S −1 )ij (Aj − A0 fkj − Bf ′ kj − p) = 0

Pi

βik Ai , t0 = −B/A0

p=

P
i

γik Ai(9.4)′ and a covariance matrix S −1 .
where αki , βik , γik are expressed via tabulated values fki , fki
Three parameters are obtained from these solutions: the amplitude A0 , the peak time t0 , andthe pedestal p. The extracted event time t0 allows the calculation of a new k-index for the
next iteration. Three iterations are enough for the convergence of the solution. For the first
iteration, the trigger time is used as the initial pulse time. As one can see from Eq. 9.4, one
division and one multiply-and-accumulate (MAC) operation are needed in each iteration. Fixedpoint arithmetic and a precomputed array of coefficients (αki , βik , γik ) are sufficient to realize thereal time implementation of this algorithm in the chosen FPGA.
The FPGA is capable of processing up to 8 events in parallel. ADC data are stored in an input
cyclic buffer inside the FPGA. Its capacity is 8192 18-bit words (512 samples × 16 channels),enough to delay event processing by up to 290 µs. The input buffer must not be overwritten
while the digital signal processor is busy with the previous events.
The DSP is highly parallelized, as shown in Fig. 9.8 (left), where the two independent cores are
depicted. Each core has its own computing resources: MAC, division unit, and interface to one

Figure 9.8: Left: DSP cores. Right: DSP core details.
SDRAM chip, and up to 8 channels are processed in parallel by each core, which utilizes its
resources with priority given to earlier events. In this way, a MAC operation can be performed
for one channel, while division and the fetching of coefficients are performed for the others.
There are two amplitude thresholds, THR LOW and THR HIGH (0 < THR LOW < THR HIGH).
The former is used for zero-suppression. If the pulse amplitude is smaller than THR HIGH
(which is typically around 5 MeV), the parameter t0 is fixed in the pulse shape fit at the trigger
time value. This constraint improves the energy resolution for low amplitude pulses. The processed data are packed in the specified event data format and sent to a FIFO. For debug andcalibration purposes, the ADC samples can be attached to reconstructed data for the chosen
fraction of events.

292

CHAPTER 9. CALORIMETER (ECL)

The shaper-DSP modules and FAM modules are designed for a 9U VME module and the collector
for a double-width 6U VME module. The modules are located in the same racks that are used
for Belle’s TKO crates (containing shaper-QT modules [1]). One VME crate contains 8-12
Shaper-DSP modules, one FAM and one collector module. In total, there are 52 VME crates.
9.4.2.1

Performance

The preamplifier and shaper have nonlinearity less than 0.3% for output signals from preamplifiers up to 4 V, corresponding to a 10-GeV energy deposition.
If an energy deposition in the crystal exceeds 19 GeV—which can happen at the beam injection—
the preamplifier becomes overloaded and does not respond to the input signals during a deadtime of tdead [µs] ≈ (E[GeV] − 19) × 2.7. Even for a 100-GeV energy deposition, this injectionoverload dead time is only about 220 µs, which corresponds to about 2% at a 100-Hz injectionrate.
For the most severe background conditions, we expect 30% occupancy. In this case, the FPGA
algorithm can continue to process data for a trigger rate of up to 30 kHz.

9.4.3

Electronics Test

The performance of the Wave Form Analysis (WFA) circuitry and algorithm have been tested
with the existing CsI(Tl) crystals [7]. Eight prototype modules of the new electronics were
produced and installed into the ECL DAQ temporarily. The shaper and digitizer circuitry were
mounted on a TKO-standard module to match the current detector electronics infrastructure.
Digitized signals from the modules were sent to FINESSE cards on a COPPER [8] module.
This module contained the FPGAs that implemented the signal signal processing algorithm ofSec. 9.4.2. The shape of the reference signal and noise correlation information were stored in anarray uploaded to the FPGA memory. The results of the pulse fit to the amplitude, time andfit quality information were calculated and recorded as a 32 bit word (18 bits for amplitude,
12 bits for time and 2 bits for quality). To test the reliability of the FPGA algorithm, raw
information was recorded together with fitted information for a portion of the events and thefitting algorithm was performed again offline. No online-offline difference was found in morethan 50 million events.
During October 16-23, 2008, the ECL was operated in a configuration with 120 channels being
readout by the new shaper-digitizer boards. About 965 pb−1 of integrated luminosity werecollected at the energy of the Υ(4S) resonance. Measured time distributions for low (5 MeV)
and high (100 MeV) energy depositions in the crystals are presented in Fig. 9.9.
Incoherent and coherent noise is measured with and without beam. The incoherent noise without
beam was 330–410 keV, depending on polar angle. With beam, the incoherent noise increases
due to pile-up noise to about 500–600 keV, as shown in Fig. 9.10. The impact of the pile-up noisewith the new electronics is reduced compared with the case of the Belle electronics. Closest to
the beampipe, the pile-up noise suppression is about a factor of 1.5. The coherent noise within
one module was about 70 keV.
The dependence of time resolution on a crystal’s energy deposition is shown in Fig. 9.10 (right).
It is about 100 ns for a 5 MeV energy deposition and only 3 ns at 1 GeV. The beam backgroundhas a uniform time distribution; applying energy-dependent cuts on the time can be used tosuppress fake clusters. For example, a roughly 3 σ cut can suppress the rate of fake clusters bya factor of 7, while maintaining an efficiency of about 97%. These values are in good agreementwith estimates of the expected perfomance improvement.

293

CHAPTER 9. CALORIMETER (ECL)

600
600

E=100 MeV
σt=9.1 ns

E=5 MeV

400
400
200

200

0
-2000 -1000

0

0
-100

1000 2000∆t (ns)

-50

0

50
100
tecl-toff (ns)1.5

σt (ns)σnoise (MeV)

Figure 9.9: Measured time distributions for 5 MeV (left) and 100 MeV (right) cluster energy
depositions.

old

10 2

1
10
new

0.5

1
0
130

140

150
160
Θ (degrees)

1

10

10

2

3

10
Ehit (MeV)

Figure 9.10: Left: pile-up noise dependence on polar angle for new and old electronics. Right:
measured time resolution as a function of single-crystal hit energy.

294

CHAPTER 9. CALORIMETER (ECL)

9.4.4

Dead time during injection

tin circ (µs)

SuperKEKB will operate with continuous injection (Ch. 2). For a brief interval after each
injection pulse, the beam is excited and produces more background in the detector. Belle’s
DAQ copes with this by blocking triggers for about 4 ms after an injection pulse. However, at
a 100-Hz injection in SuperKEKB, such a veto time would correspond to 40% dead time. To
reduce this, the following veto scheme is proposed. The DAQ is blocked for 4 ms ± 0.5 µs for the
injected bunch only, as it is the most copious source of background. For the other bunches, theDAQ is blocked for a much shorter time of about 150 µs.
We have studied the feasibility of this scheme in Belle using a special run without the injectionveto. A signal from the backward end-cap calorimeter was used to study the energy deposition
during injection.

a)

10

5

b)
10 3

10 3

10 2

10 2

10

10

c)

0
1

1
0

1

2

3

4
tafter inj (ms)

0

1

2

3

4
tafter inj (ms)

0

2.5

5

7.5
10
tin circ (µs)

tin circ (µs)

Figure 9.11: Trigger time distributions for LER injection. a) Scatter plot of time within arevolution period vs. time after injection. b) Time-after-injection distribution (red: all events;
blue: excluding the two horizontal bands in (a)). c) Time-in-revolution distribution for tafter inj <150 µs.

a)

10

5

b)

10 4

10 4

10 3

10 3

10 2

10 2

10

c)

10

0
1
0

1

2

3

4
tafter inj (ms)

0

1

2

3
4
tafter inj (ms)

0

2.5

5

7.5
10
tin circ (µs)

Figure 9.12: Trigger time distributions for HER injection. a) Scatter plot of time within arevolution period vs. time after injection. b) Time-after-injection distribution (red: all events;
blue: excluding the two horizontal bands in (a)). c) Time-in-revolution distribution for tafter inj <150 µs.
Figures 9.11 and 9.12 show the distributions of the trigger time within one revolution period(tin circ ) and the trigger time after injection (tafter inj ). Most of the triggers come within 150
295

CHAPTER 9. CALORIMETER (ECL)µs after injection. Later triggers are clustered around the time when the injected bunch passes
through the interaction point. A less prominent cluster of late triggers appears at a tin circ timeof 3.45 µs beyond the IP-crossing time. If we veto any post-injection trigger with tafter inj <150 µs or within the boundaries of these two clusters in Figs. 9.11(a) and 9.12(a), the dead timecorresponds to an acceptable 5%.
The energy distributions for the time regions of Figs. 9.11(a) and 9.12(a) are shown in Figs. 9.13
and 9.14, respectively. More than 97% of the energy is deposited during first 150 µs. The energy
deposited by the injected bunch is less than 2.7%, which would not cause preamplifier saturation.
So if the injection-background conditions are similar in Belle and Belle II, we can accept thisnew veto scheme. As one improvement, we will develop a more sophisticated algorithm for theenergy reconstruction in the possible presence of a tail from the injected bunch. The trigger
channel should also be designed with efficient tail suppression after a fast signal to avoid energy
shift during injection.

10

3

10

2

Entries
Mean
RMS

7551
14.27
20.30

a)

10

3

10

2

6806
0.40430.6086

Entries
Mean
RMS

456
0.3316
0.9722

Entries
Mean
RMS

b)

c)

10 2

10
10

10

1

1
0

250

500

750
1000
E1/8 (GeV)

1
0

2

4

6

8
10
E1/8 (GeV)

0

2

4

6

8
10
E1/8 (GeV)

Figure 9.13: Energy distribution in 1/8 backward end-cap for LER injection. a) for events inthe vertical band of Fig. 9.11(a). (∼97% of lost energy); b) for events in either horizontal bandof Fig. 9.11(a) extended leftward to tafter inj > 0 (∼ 2.7% of lost energy); c) for events outside
the vertical and horizontal bands of Fig. 9.11(a) (∼0.2% of lost energy).

10 3

Entries
Mean
RMS

30763
189.0
224.4

a)

10 2

10 3

11310
3.585
2.178

Entries
Mean
RMS

b)

10 3

1140
0.33600.8981

Entries
Mean
RMS

c)

10 2

10 2

10

10
10

1

1
0

250

500

750
1000
E1/8 (GeV)

0

2

4

6

8
10
E1/8 (GeV)

0

2

4

6

8
10
E1/8 (GeV)

Figure 9.14: Energy distribution in 1/8 backward end cap for HER injection. a) for events inthe vertical band of Fig. 9.12(a). (∼99% of lost energy); b) for events in either horizontal bandof Fig. 9.12(a) extended leftward to tafter inj > 0 (∼ 0.7% of lost energy); c) for events outside
the vertical and horizontal bands of Fig. 9.12(a) (∼0.01% of lost energy).

296

CHAPTER 9. CALORIMETER (ECL)

9.4.5

Electronics Schedule

Design and production prototype evaluation of the shaper-DSP module will have to be finalized
in 2010. During 2011-2013, the mass production and tests of the required 600 modules will be
done.
The collector module will be designed and tested during 2010-2012, following the developmentof the readout DAQ modules. The production of 55 modules is expected in 2013. Module
installation will be finished by the end of 2013. The DAQ tests will start in the beginning of2014.
To cope with the PIN-PD leakage current increase, the bias voltage resistors, which are 100 MΩ
combined, will be replaced by lower-resistance ones in the endcap region.

9.5

Options for the endcap upgrade

A drastic way to improve the performance of the ECL is the replacement of the slow CsI(Tl)crystals with faster ones, at least in the endcaps. Three options of such an endcap upgrade
are presently under consideration. All options were examined by a special Review Committee
assigned by the Executive Board of the Belle II collaboration. The following conclusions of thisCommittee were provided for each of these options.
1. Pure CsI crystals are used instead of Tl doped crystals [7]. Scintillation light readout ismade with vacuum photopentodes. The existing endcap mechanical structure is kept. This
option has been explored for the last five years and now it is well prepared for construction.
Reducing the number of photosensors per crystal to one from the existing two for PIN-PD
readout represents a weakness of this proposal, since there is zero redundancy. Furthermore, the long-term stability of the photopentode has yet to be confirmed. Pure CsI plus
multiple APDs can provide redundancy, though further signal-to-noise ratio improvement
is needed.
2. PWO2 (improved lead tungstate) plus Avalanche Photodiodes (APD): this is being actively
studied by the PANDA experiment [9] and could be promising. Production costs and theneed for cooling to achieve good performance is a concern and requires further study.
These much denser crystals could provide better forward/backward π 0 detection at highmomentum and would be an improvement in basic ECL performance.
3. Bi4 Si3 O12 (BSO) scintillating crystal plus APD: a potentially interesting option, thoughrather immature in terms of detailed studies. Cooling is not required, though costs andreadiness for large-scale production are unclear. Again, it would represent an improved
gamma isolation and is worth considering, if a strong improved physics performance casecan be made.
In the latter two cases, in addition to the need for a compelling physics case, further and detailed
mechanical support studies and engineering are needed.
Based upon these conditions, the Review Committee formulated the following recommendations.
Considering this state of development, and the physics and economic situation,
our recommendation is therefore the scenario to defer upgrade of the ECL endcaps
until a solid physics reach case has been made and the degradation due to backgrounds
mandates an upgrade. During this time innovation can continue. At such a later
point in time any mature technology, with solid costing and delivery schedule, that297

CHAPTER 9. CALORIMETER (ECL)

justifies physics return on investment, should be earnestly evaluated. We note insummary that this timescale could be accelerated if the backgrounds observed end up
being significantly higher than those considered in the studies presented.

9.5.1

Pure CsI for the endcap

9.5.1.1

Primary motivation

A mature option to use pure CsI crystals of the same shape and size as the presently-used CsI(Tl)counters is proposed for the endcap. An advantage of this crystal choice is a short scintillation
decay time and moderate cost as compared to other scintillation crystals. Since the physicalproperties of pure CsI are the same as CsI(Tl), the present sizes of the calorimeter elements aswell as the mechanical structure may be kept.
However, the light output of pure CsI crystals is approximately one tenth that of the doped
crystals. Thus, to keep the energy noise equivalent value at the same level, one needs to use
photodetectors with internal gain. A suitable solution is to use vacuum photopentodes (PP),i.e., photomultiplier tubes with three dynodes. Since the emission wavelength of pure CsI is
about 300 nm, the photosensor should be UV sensitive. Such a 2-inch diameter device, with alow output capacitance of C ≈ 10 pF, has been developed recently by Hamamatsu Photonics.
The low output capacitance is attractive because the electric noise depends on that value. These
newly developed PPs have a quantum efficiency of about 20–25% at 300 nm and an internal
gain factor of 120–200 in zero magnetic field. We tested several pure CsI crystals of the same
size as those presently used in the Belle endcap calorimeter.
The obtained preamplifier’s equivalent noise charge (ENC) is about 980 electrons, while the PP
output anode signal varies from 20000 to 30000 electrons per MeV at the PP anode. The ENC
corresponds to an equivalent noise energy (ENE) of 40-60 keV. Taking into account the decreaseof the PP gain due to the magnetic field, we can expect an ENE of about 120-200 keV in the
Belle II 1.5 T magnetic field.
Shorter scintillation decay times and matched, shorter shaping times of the electronics suppresses
the pile-up noise by a factor of about 5.5 in comparison to the present endcap calorimeter.
Estimated pile-up noise behavior as a function of background for the current and upgradedelectronics is shown in Fig. 9.15. The fake photon rate is suppressed by a factor of more than
100 due to improved timing provided by the new electronics. Thus, even in the case of 20 times
larger background, the resulting fake rate is expected to be lower than in the current barrel
calorimeter.
The advantages of this option follow.
• Low pile-up noise and good energy and spatial resolution can be obtained while maintaining
efficient fake cluster suppression.
• The physical characteristics and the radiation length of the crystals are the same as forpresent CsI(Tl) so that the same granularity of the calorimeter can be kept and the same
container can be used for the endcaps.
• Pure CsI crystals of acceptable quality can be produced by three manufacturers: Kharkov(Ukraine), Saint Gobain (France), and Beijing (China). The required number of thecrystals can be produced within two years following mass production preparation.
• A large amount of R&D work on pure CsI counters with PP readout has already been
performed.
298

4

σ (MeV)σ (MeV)CHAPTER 9. CALORIMETER (ECL)

3

4
3

2

2

1

1

0

0

0

5
10
15
20
25
FWD background (rel. units)

0
5
10
15
20
25
BWD background (rel. units)

Figure 9.15: Dependence of the pile-up noise per crystal for the current (red) and modified(blue) endcap calorimeters. The background at Belle (for a luminosity of 1034 cm−2 s−1 ) is taken
for unity.
There are disadvantages:• Usage of a single photodetector per counter represents a single-point failure and therefore
less robustness in comparison with the present scheme, employing two PIN photodiodes
per counter.
• The PP gain factor depends on the magnetic field and calibration is needed more often.
This gain factor can also vary slightly with background conditions.
• The PP depth of 58 mm requires rebuilding of the supporting structure inside container.
Each CsI crystal is wrapped by one layer of a white porous 200-µm Teflon sheet and placed in a
40-µm aluminized mylar envelope. The light of each crystal is read by a 2-inch photopenthode(PP) that is fixed to the large-end face of the crystal with optical grease.
The counters are installed in the existing endcap containers. Due to the increased thickness of the
new PP sensor, with respect to the low-profile of the existing PIN photodiodes, the assembled
counters are longer (360 mm) compared to the present counters (319 mm). Therefore, thesupport structure of the containers must be modified. The final design of the counter and locationof the electronics (connection board and HV feed) are coupled to the supporting structure design
and will be done together.
A first version of the preamplifier has been developed. The input transistor is the same as in
the existing Belle calorimeter. The modification includes a change of the output cascade to thedifferential transmitter. The signal from the preamplifier is sent to the intermediate electronics
via the existing twisted pair cable. The power consumption of the new preamplifier and voltage
divider is about 190 mW/channel, similar to the present 140 mW/channel.
The downstream electronics will be built using the same basic architecture as for the barrel(Sec. 9.4). The shaping and digitization part is proposed to be implemented on VME boards.
Each VME board contains 16 channels. Each channel includes a differential receiver, CR-(RC)4299

CHAPTER 9. CALORIMETER (ECL)

shaper with shaping time τ = 30 ns, and two 14-bits fast flash ADCs. The use of two ADCs
provides an effective 18-bit digitization for the full dynamical range. Digitization of the shaper
output signals will be performed using a common 43-MHz reference clock. The digitized data areprocessing in FPGAs to obtain the amplitude, time and quality bits for each cluster candidate.
The feature-extracted information from 8 (10) boards are aggregated by the collector module andsent to the COPPER with ROCKET-IO. In total, the endcap electronics includes 144 (80+64)
VME boards located in 16 (8+8) crates.
9.5.1.2

Study of the radiation hardness

ampl(ref. units)

We performed radiation hardness studies of pure CsI crystals from the Kharkov, Saint Gobain
and SIC companies. Most of the crystals show no essential degradation up to 10 krad of gamma
irradiation and reactor-neutron irradiation with the flux of up to 1012 cm−2 . The results for γ
irradiation are presented in Fig. 9.16. Since one of the crystals showed significant degradation,an additional test of the radiation hardness should be performed.

1
0.8

cr.8
cr.1

0.6
0.4
0.2
0
1

10

10

2

10

3

10

4

5

6

10 10
dose, radFigure 9.16: Radiation hardness measurement results of Kharkov crystals [10].

9.5.1.3

Tests with prototype and other R&D on pure CsI

An accelerator measurement of 20 pure CsI crystals coupled to PPs and readout electronics
providing waveform analysis was carried out at the BINP photon beam. The obtained energy
resolution (Fig. 9.17) is consistent with both present calorimeter energy resolution and MC
prediction. A time resolution better than 1 ns for deposited energies greater than 20 MeV has
been obtained [11].

300

5

στ (ns)σE/E %

CHAPTER 9. CALORIMETER (ECL)

4 CsI(Tl) TB results
Pure CsI TB results

3

2

3
MC

2

1

1
0

0

50

100

0

150
200
E (MeV)050

100
E (MeV)

Figure 9.17: Energy and time resolution for photons obtained in the test beam measurements
at the BINP photon beam line.

σpure CsI (MeV)

We have also carried out a direct comparison of the pile-up noise for the counter based on pure
CsI and one of the CsI(Tl) counter from the Belle detector. The pile-up noise was emulatedusing gamma rays from a 60 Co radioactive source. The background intensity varied by changing
the distance between the cobalt source and the crystals. The pile-up noise was calculated fromthe width of the test pulse signal. Figure 9.18 shows the effective noise of the pure CsI counteras a function of that for the CsI(Tl) counter.
2
1.5
1
0.5
0

0

2

4

6
8
10
σCsI(Tl) (MeV)

Figure 9.18: The pile-up of pure CsI and new electronics counter and that for the standard BelleCsI(Tl) counter readout using the present MQT-TDC electronics.
The gain factor reduction of photopentodes in a magnetic field have been measured. The results
are shown in Fig. 9.19. When subjected to a magnetic field, the gain factor of the photopentode
decreases but remains reasonably high.
An aging test of the PPs is being carried out. We have studied PP sensitivity depending on the

301

1

K(θ)/K(0)K(B)/K(0)CHAPTER 9. CALORIMETER (ECL)

ZG01
ZG02
ZG03

0.75

ZG06

1.5

ZG01
ZG02
ZG03
ZG06
ZG10

1

ZG10

0.5
0.5
0.25
0

0

5

10

0

15
20
B (kGs)

0

20

40
60
80
Angle (degrees)

Figure 9.19: Left: gain factor dependence on the magnetic field along the photopentode axis.
Right: gain factor dependence on the angle between the 1.5-T magnetic field direction and thephotopentode axis.
integrated anode charge. The signal from a pure CsI crystal was used as a reference light source.
For calibration we measure the maximum of the cosmic particle spectrum as a function of time.
The result of this study is shown in Fig. 9.20. A blue LED was used to provide the illumination
to a rate about 100 times larger than we expect at Belle II. This intensity corresponds to anodecurrent of 35 µA without magnetic field and about 9 µA with magnetic field. We saw a sensitivity
increase of 10% after 15 C of integrated anode charge (with 3 C corresponding to one year of
Belle II operation with magnetic field). With further integrated charge, the increase appears tosaturate. There is about a 2% increase of PP gain during intense illumination that should bestudied more carefully. In a 1.5-T magnetic field, the same sensitivity increase of about 10%
and absence of the degradation was observed.
9.5.1.4

Simulation study

Use of faster-scintillator crystals in the endcaps allows us to suppress the background clusters
more efficiently and reduce the pile-up noise smearing. To estimate the calorimeter performancefor different options, we chose to study B − → τ − ν̄ decay since this mode is very sensitive to themissing energy accuracy.
For the background simulation, we used the Belle GEANT3 program package with the overlaidbackground component (“addbg”) scaled for different options and a modified pile-up noise contribution.
Simulations of the signal MC and generic MC were performed for the cases shown in Table 9.1.
The tagged B was reconstructed in the D̄ 0 π + mode with D̄ 0 → K + π − . The requirements
Mbc > 5.27 GeV/c2 , |∆E| < 50 MeV, and |MD0 − 1.865| < 15 MeV/c2 were applied for tagged
B selection. The τ − lepton was reconstructed in the π 0 π − ν mode. To select signal events, themissing energy plot was analyzed. The missing energy includes a sum of the ECL cluster energythat excludes the clusters matched to the reconstructed tracks and the photons matched to π 0 .
Figure 9.21 shows the missing energy distribution for the signal and generic MC in case of a 20
302

PP signal (rel.units.)

CHAPTER 9. CALORIMETER (ECL)

1.2
Q=140 C
Q=15 C

1.1

1

0.9

0

20

40

60
t, (days)

Figure 9.20: The PP sensitivity dependence on time during the illumination of the light. Threedays correspond to about 1 year Belle II operation.

1
2
3
4

Present calorimeter ×1
Present calorimeter ×10
New electronics ×10
Pure CsI ×10

addbg
1
10
2
2

barrelσpile
σpile (θ)√σpile (θ) × √10
σpile (θ) × √5
σpile (θ) × 5

end cap
addbg
σpile
1
σpile (θ)√
10
σpile (θ) × √10
2
σpile (θ) ×√ 5
0
σpile (θ)/ 3

Table 9.1: Simulated overlaid-background and pileup noise options; σpile (θ) is the pileup noise
measured at a luminosity of 2 × 1034 cm−2 s−1 .
MeV cluster energy threshold. As expected, the pure-CsI case has the narrowest signal peak(i.e., best resolution) for the missing energy.
To estimate the sensitivity of the method, we fit the generic MC distribution with the sum of
background B(E) and signal S(E) functions: F = NS S(E) + NB B(E). We then studied thedependence of the NS statistical error on the cluster energy threshold. An example of such fit
and the dependence of the sensitivity on the threshold energy are shown in Fig. 9.22. The resultsof the study show that the replacement of the end-caps with pure CsI crystals will allow us to
improve the sensitivity for B → τ ν decay by ∼25%, assuming ten times larger background thanin Belle. This difference in sensitivity is magnified with larger background levels.

303

CHAPTER 9. CALORIMETER (ECL)

2000

a)

b)

60
1500
40
1000
20

500
0

0

0.25

0.5

0

0.75
1
Emiss (GeV)

0

0.5

1

1.5

2
Emiss (GeV)

Figure 9.21: Missing energy distributions: a) for the signal MC; b) for the generic MC. Black:case 1; blue: case 3; red: case 4.

Sensitivity

40
a)

30

80
b)

60

20

40

10

20
F(E)=Ns*S(E)+Nbg*B(E)

0

0

0.5

1

1.5

2
Emiss (GeV)

0

0

50

100
150
Ethresh (MeV)

Figure 9.22: a) Fit of the missing energy distribution for case 4 (Ethresh = 20 M eV ). b)
Dependence of the sensitivity on the threshold energy.

304

CHAPTER 9. CALORIMETER (ECL)

9.5.2

The APD readout option

9.5.2.1

Motivation

Thanks to the recent semiconductor photon sensor development, large area (1 cm2 ) APDs havebecome available. Such semiconductor photosensors are naturally insensitive to the magnetic
field. The Hamamatsu S8664-series APD is widely used, for example, in the PWO calorimeters
for CMS experiment and the PANDA experiment. In the catalog for this series, the Hamamatsu
S-8664-1010 device has the largest sensitive area of 1×1 cm2 . Since it is a compact device,
we can put a few pieces on the scintillator crystal readout surface to realize a redundancy forrobustness in the practical operation of the calorimeter.
9.5.2.2

Performance

The electromagnetic shower development depends only on the choice of the scintillating crystal.
Therefore, the energy and position resolutions for high energy photons and neighboring-shower
separation are independent of the photosensor selection. In the Υ energy region, the photon
energy is typically a few hundred MeV. The corresponding energy resolution is predominantly
affected by the equivalent noise energy of each channel. Attaching one S8664-1010 sensor onan actual-size pure CsI crystal, a cosmic ray test has been performed. The resultant equivalentnoise energy is described in Sec. 9.5.2.2.2.
9.5.2.2.1 Advantages Since the Hamamatsu S-8664-1010 APD is a compact device, one
scintillator crystal can be equipped by 2–4 APDs on its readout surface. This redundancy gives
us the operational robustness in order to avoid an entirely dead channel due to APD or signalline failure. Its compactness enables us to use the same (or quite similar) preamplifier casing andcounter-fixing mechanical structure inside the endcap calorimeter container as in Belle. This
minimizes the needed change of the mechanical structure and other infrastructure, especiallywhen combined with pure CsI crystal.
9.5.2.2.2 Concerns The device capacitance of the APD, 270 pF, is larger than that for thephotopentode (10 pF) or PIN-photodiode (80 pF), so that the noise due to the device capacitanceis larger than for these alternatives. To estimate the equivalent noise energy of the APD option
with pure CsI, we constructed a prototype counter by attaching one APD on a real-size crystal
and performed a cosmic ray test. The prototype counter was placed inside a thermostatic box
to maintain its temperature at 25◦ C and the applied high voltage was 455 V (15 V below its
breakdown). The preamplifier was based on the existing one for Belle’s PIN-photodiode. The
preamplifier output signal was fed to the CAMAC module equipped with a τ =30 ns shaper
circuit and 43 MHz 12 bit FADC. The obtained pulse height spectrum is shown in Fig. 9.23.
The cosmic particles transversely penetrating the crystal are triggered, so the energy deposit isapproximately 30 MeV for passage through 5.5 cm thick CsI. The corresponding average pulse
height is 120 FADC counts. The noise level is 8 FADC counts, based on the width of a Gaussian
fitted to the pulse height spectrum for random triggers. Hence, the estimated equivalent noise
energy is 2 MeV. This is significantly higher than the requirement of ∼0.6 MeV. The possible
test to improve it is mentioned in Sec. 9.5.2.3. Note that the S8664 APD has a lower quantum
efficiency (QE) of ∼35% at the wavelength of pure CsI (330 nm), compared to its QE of 80% at
500 nm.

305

CHAPTER 9. CALORIMETER (ECL)
Number of events

Pulse height [FADC counts]

Figure 9.23: Pulse height spectrum obtained by the cosmic run of the prototype conter of the
APD readout option. The average pulse height is 120 FADC counts.
9.5.2.3

Remaining research and development items

In the first test of the APD readout with pure CsI crystal, the existing preamplifier for theCsI(Tℓ) crystal was used by adding the driver circuit for differential signal transfer to the τ =30 ns
shaper input. In addition, another preamplifier developed for the KEDR experiment has beentested. The KEDR-type preamplifier, with a 5-pF feedback capacitor, is found to have a factorof 1.7 higher signal charge collection efficiency. This means that the existent preamplifier’s openloop-gain is not high enough at the τ =30 ns signal shaping. Therefore, using a preamplifier withhigher open-loop-gain for the corresponding frequency as well as smaller feedback capacitor to
obtain a higher absolute gain, will result in a significantly larger APD signal. This will allow us
to decrease the APD operating voltage, which will lower the leakage current—whose fluctuation
contributes to the noise. (A lower operating voltage is also strongly preferred from the viewpointof long term stability.)
When the applied voltage is kept constant, the gain of the APD strongly depends on the temperature. Nowadays, in many APD applications in high energy physics, nuclear physics, astrophysics
and medical instruments, the temperature is sensed by an appropriate device and is used in a
feedback circuit to manipulate the applied voltage to maintain constant APD gain. For example,
the Matsusada HAPD-T series compact power supply unit has the voltage temperature correction functionality as well as the proper electrode pin to be connected to the temperature sensing
diode. CAEN also provides the high voltage power supply modules equipping temperature correction functionality. Those might be designed, tested, produced and implemented commonlywith the Particle identification detector system (PID) if the Hybrid Avalanche Photo-diode(HAPD) is selected as the photon detector for PID.
Finally, we would like to determine if the Hamamatsu S-8664-1010 APD can achieve our needed
18-bit-equivalent linearity.
9.5.2.4

Cost

According to the estimate by Hamamatsu, mass production of 8000 S8664-1010 APDs can bedone within two years. The price quotes from Hamamatsu are 28 kyen/piece for 4000 APDs and306

CHAPTER 9. CALORIMETER (ECL)

24 kyen/piece for 8000 APDs. Since the PP price is 76 kyen/piece for 2000 pieces, attaching a
few pieces of S8664-1010 APD results in similar or even a little smaller cost with respect to thebaseline PP option.

9.5.3

BSO crystals with APD readout

9.5.3.1

Motivation

Bi4 Si3 O12 (BSO) scintillating crystal has been recently developed. It has comparable light
output with pure CsI and a relatively short scintillation decay time of 100 ns. The 480-nm
wavelength of the scintillation light is well-matched to many photon sensors. The radiation
length (X0 ) and Molière radius (RM ) are 1.2 cm and 2.4 cm, respectively, both significantly
shorter than for CsI. Thus, BSO provides better two-shower separation for high momentum
π 0 → γγ decays. Large-size crystal ingots, up to 70 mm diameter and 200 mm length, havebeen produced. In 2009, the Oxide Corp. [12] succeeded in the test production of four pieces of
2 × 2 × 20 cm3 blocks (Fig. 9.24).

Figure 9.24: The Bi4 Si3 O12 (BSO) crystals with 2 × 2 × 20 cm3 dimensions produced by Oxide.
9.5.3.2

Expected performance

The BSO scintillator’s Molière radius of 2.4 cm is about two thirds that of CsI. This contributes toimprove high momentum π 0 reconstruction, for example from B 0 → π 0 π 0 . To get a quantitative
estimation, a simulation study is necessary. For lower energy photons, the equivalent noise
energy of each channel is important. Since the amount of scintillation light is almost the same
as for pure CsI, the photopentode (PP) can be used for the photosensor. The light output has
been measured and compared with pure CsI by PMT readout using a 1×1×2 cm3 crystal sample,
as shown in Fig. 9.25. Using two APDs on a single BSO crystal, we expect an equivalent noise
energy of 0.7 MeV. This would be adequate to have reasonable energy resolution. To verify thisexpectation, we are performing a cosmic ray test by attaching one Hamamatsu S-8664-1010 APD
on the 2.2×2.2×18 cm3 BSO scintillator borrowed from Prof. H. Shimizu of Tohoku University.
307

CHAPTER 9. CALORIMETER (ECL)

Figure 9.25: Light output measurement for Pure CsI (left) and BSO (right) using 662 keV γ-ray
emitted by a 137 Cs source. The readout is done by Hamamatsu H3167 PMT and LeCroy 2249W
charge sensitive ADC. The scintillator dimensions are 1 × 1 × 2 cm3 . The full-energy peak by
photoelectric absorption shows that both scintillators provide similar light output.
Radiation hardness of BSO seems to be adequate. After gamma irradiation of several Gy, no
significant light output degradation was observed. Neutron radioactivation was found to besmall: less than 0.1 µSv/h even after 1011 n/cm2 irradiation. The light output degradation is∼20% for 1012 n/cm2 dose.
9.5.3.3

Remaining research and development items

As mentioned in Sec. 9.5.3.2, the simulation study to quantitatively check the improvement inhigh energy photon and π 0 detection is necessary. Since BSO crystal is harder than CsI, it isdifficult to tap holes in the crystal. Therefore, the mechanical counter construction—including
crystal wrapping and attaching APDs and preamplifiers—must be newly designed. Also, crystal
containers and crystal-fixing structures must be newly designed with very careful finite element
analysis calculation to ensure their strength. These structural issue would be the limiting factor
to make this option ready in time for the inauguration of Belle II.
9.5.3.4

Cost

Corresponding to smaller Molière radius and radiation length of BSO, a suitable crystal dimension would be ∼ 4.5 × 4.5 × 20 cm3 . To cover the existing endcap area, ∼3000 BSO crystals areneeded to fill both endcaps. According to the test-production experience of ∼0.75 Myen per
2 × 2 × 20 cm3 crystal, it is thought to be feasible to make one ∼ 4.5 × 4.5 × 20 cm3 crystal for∼0.35 Myen in mass production, taking into account the fact that the test production includes
extra initial costs such as pots and rejects to find the optimum crystal growth. Photosensor andreadout electronics costs scale with the number of crystals. In addition, because of the different
crystal density, the endcap crystal containers need to be newly built. This is estimated to cost
100 Myen = 1 Oku-yen. The expected costs are summarized in Table 9.2.

308

CHAPTER 9. CALORIMETER (ECL)

Item
CrystalAPD
Preamp.
Electronics
Mechanical structure
Test bench
Assemble
Total

Cost/unit
0.35 Myen
56 kyen∼10 kyennumber
∼3000
∼3000
∼3000

Oku-Yen
10
1.7
0.3
1.3
1.0
0.1
0.3
14.7

Table 9.2: Summary of expected cost for BSO option.

9.5.4

PWO-II option for the endcap upgrade

9.5.4.1

Motivations

R&D on a PWO-II option was initiated in response to issues with the present pure CsI option
for the Belle II endcap calorimeter upgrade. Existing crystal technologies were comprehensively
surveyed to determine which technology is the best option from purely scientific and technicalviewpoints. The technical details were presented in a separate document and the results andconcerns raised in the response to the internal committee’s review are summarized here.
9.5.4.2

Expected Performance• Strengths

We expect the energy resolution of 1 GeV photons to be in the range of 1–2% for 2 × 2 ×
20 cm3 PWO-II crystals when using the waveform readout of the signal. Unfortunately, theproponents had no time to demonstrate this directly; it is based on the results achieved inrecent studies by the PANDA collaboration. The radiation hardness of PWO-II crystals(106 –107 rad) is excellent and more than adequate. Since the peaking time of PWO-II
is also short (30 ns) and the transverse size of the shower in PWO is smaller than inCsI (the Molière radii being RM (PWO) = 2 cm and RM (CsI) = 3.6 cm, for a gain of(RM (CsI)/RM (PWO))2 = 3.2), the pile-up is also significantly smaller than for pure CsI.
The smaller transverse area also helps in π 0 separation for pion momenta up to 4 GeV/c.
The PWO-II crystal length can be 20 cm (rather than 30 cm for CsI) because of thedifference in radiation length. Their finer segmentation should also improve the gammaand π 0 efficiency.

• Weaknesses of alternatives

The main weakness of the PWO-II option is the lack of experience with the large scale
operation of a cooling system operating at −25◦ C. A full study has been carried out by
PANDA, but our Belle II proponents have no direct experience. Even if it is claimed
that lower temperature operation has no technical show-stoppers, based on PANDA’s
experience, an alternative to this issue is to run the endcap detectors at some higher
temperature, such as 0 ∼ 10◦ C, to avoid the complication of sub-zero cooling system. To
compensate for the lower light yields due to this, we plan to study the case of the two-APD
readout configuration.

309

CHAPTER 9. CALORIMETER (ECL)

Ongoing R&D suggests that the crystals from SICAS can have even higher (∼double)
light yields though, at the moment, there is an issue of light uniformity and stability ofthe production of SICAS crystals that needs to be understood. If this can be resolved,
there is a chance to operate these crystals even at room temperature.
9.5.4.3

Increased Robustness/Reduced background sensitivity

The mechanical properties PWO crystals have been studied by CMS and PANDA, who showedno significant differences compared with other standard crystals. Therefore, the mechanicalrobustness of the crystal modules themselves is not a major issue. The only concern is thedesign of a new container to house the denser material. This design effort has not yet been
started.
9.5.4.4

Cost and proposed cost sharing

Note: this cost estimation is for the forward endcap option only. The extrapolation to thebackward endcap is straightforward.
• Crystal

For the forward endcap, we expect to have approximately 8,000 PWO-II crystals. Basedupon a small production volume quotation 480 Euro/crystal, we estimate the amortizedcost for the crystal production to be 3,840,000 Euro (or 516,000,000 Yen).

• Photosensors

For the APD photosensors, based upon a small-volume quote of 56,000 Yen/sensor for theS8664-1010 from Hamamatsu, a total photosensor cost of 224,000,000 Yen is estimated.

• Electronics and Infrastructure

For the readout electronics and infrastructure, including the new container, there is nocost estimate for the PWO-II option. Using quoted numbers from other options, we
expect 150,000,000 Yen for electronics and 130,000,000 Yen for the mechanical structure.

• Total Cost

Summing all these, the total cost is in the range of 10 Oku-Yen. The proponents will apply
for a grant of up to 0.8 Oku-yen equivalent for this forward-endcap upgrade from Korean
Agency for National Research Foundation. We hope that the main funding source will be
the Japanese Belle II budget.

9.5.4.5

Remaining R&D items• Beam tests with full size crystals in realistic Belle II environment• Two APDs/crystal option• Radiation tolerance tests for crystals and photosensors• Electronics and readout• Light improvement with SICAS crystal production for room temperature operation

310

CHAPTER 9. CALORIMETER (ECL)

9.5.4.6

Schedule

In the near term, we plan to perform• a full beam test with an array of 5×5 PWO-II crystals, and• SICAS crystal characterization.
These are urgent R&D steps planned for the first half of 2010. We would like to note that theusual crystal production rate at the Bogoroditsk Plant of Technochemical Products (BTCP) for
the PANDA experiment was 800/month.

311

References[1] A. Abashian et al.,9002(01)02013-7.

Nucl. Instrum. Meth. A 479, 117 (2002),

DOI: 10.1016/S0168-[2] B. G. Cheon et al.,9002(02)01547-4.

Nucl. Instrum. Meth. A 494, 548 (2002),

DOI: 10.1016/S0168-[3] H. Ikeda et al.,9002(99)00992-4.

Nucl. Instrum. Meth. A 441, 401 (2000),

DOI: 10.1016/S0168-[4] K. Miyabayashi,
9002(02)01483-3.

Nucl. Instrum. Meth. A 494, 298 (2002),

DOI: 10.1016/S0168-[5] K. Kazui et al., Nucl. Instrum. Meth. A 394, 46 (1997), DOI: 10.1016/S0168-9002(97)006438.
[6] D. Beylin et al., Nucl. Instrum. Meth. A 541, 501 (2005), DOI: 10.1016/j.nima.2004.11.023.
[7] A. Kuzmin, Nucl. Instrum. Meth. A In Press, Corrected Proof, (2010),
10.1016/j.nima.2010.02.212.
[8] M. Nakao and M. Tanaka,
10.1109/TNS.2005.852705.

IEEE

Trans.

Nucl.

Sci.

52,

1196

DOI:
(2005),[9] PANDA EMC Technical Design Report, (2008).
[10] I. Bedny et al., Nucl. Instrum. Meth. A 598, 273 (2009), DOI: 10.1016/j.nima.2008.08.106.
[11] B. Shwartz, Nucl. Instrum. Meth. A 598, 220 (2009), DOI: 10.1016/j.nima.2008.08.024.
[12] Oxide Corporation, http://www.opt-oxide.com.

312Chapter 10

KL0 and µ detection (KLM)
10.1

Overview

The KL and muon detector (KLM), shown in side view in Fig. 10.1, consists of an alternating
sandwich of 4.7-cm thick iron plates and active detector elements located outside the superconducting solenoid. The iron plates serve as the magnetic flux return for the solenoid. They also
provide 3.9 interaction lengths or more of material, beyond the 0.8 interaction lengths of thecalorimeter, in which KL mesons can shower hadronically.
The octagonal barrel covers the polar angle range from 45◦ to 125◦ , while the endcaps extend
this coverage from 20◦ to 155◦ . There are 15 detector layers and 14 iron plates in the barrel and
14 detector layers and 14 iron plates in each endcap.
Muons and non-showering charged hadrons (that decay in flight or do not interact hadronically)
with a momentum above ∼ 0.6 GeV/c traverse the KLM until they escape (if their momentum
exceeds ∼ 1.5 GeV/c, depending on the polar angle) or range out due to electromagnetic energy
deposition. They travel along nearly straight lines through the KLM. KL mesons that interact
in the ECL or the iron plates create a hadronic shower that can be detected in either the ECL
alone, the KLM alone, or both.
The Belle KLM, based on glass-electrode resistive plate chambers (RPC) [1, 2], has demonstrated
good performance during the entire data taking period of the Belle experiment. The principleof operation of RPCs is described in Sec. 10.2.
The long dead time of the RPCs during the recovery of the electric field after a discharge
significantly reduces the detection efficiency under high background fluxes. At the present
KEKB luminosity, the background occupancy in the barrel KLM is estimated to be consistent
with the cosmic ray flux. Thus, even with the much higher beam background expected forSuperKEKB, the barrel RPCs can be operated successfully.
In the endcaps, the background is worse because of the limited shielding of neutrons and otherparticles that are generated externally along the beam lines. At the background rate in the
Belle KLM endcaps of about 0.1–0.3 Hz/cm2 , the RPC efficiency has already sagged to between
90% and 95% [3] and the two outermost layers (in each endcap) have been turned off since
2002. In SuperKEKB, the background rate in the endcaps is expected to be a factor of 20 to 40
higher, resulting in an RPC efficiency of below 50%. In addition, the proportion of backgroundto true KL clusters seen by the endcap RPCs would rise in SuperKEKB. (Our backgroundstudies are described in Sec. 10.4.) Therefore, the endcap RPCs will be retired and replacedwith scintillators in Belle II (Sec. 10.5).
313

CHAPTER 10. KL0 AND µ DETECTION (KLM)

0

3m

2

1

Magnet Yoke

Nikko
Side

Barrel KLM

Backward
Endcap
KLM

ForwardEndcap
KLM

Oho
Side

Solenoid
Barrel ECL
Pole Tip

ForwardECL

Backward
ECL

Pole Tip

Figure 10.1: Side view of the KLM, located outside the ECL and solenoid. The gray lines markthe nominal polar angular acceptance of Belle II.

314

CHAPTER 10. KL0 AND µ DETECTION (KLM)

10.2

Resistive Plate Chambers

In the Belle KLM, charged particles are detected by glass electrode RPCs. The glass electrodes,
although technically insulating, do conduct electricity but with a very high bulk resistivity of∼ 5 × 1012 Ω · cm. The electrodes are two parallel sheets of float glass (73% silicon dioxide, 14%
sodium oxide, 9% calcium oxide, and 4% uncategorized compounds for the 2.4-mm thick barrel
glass; 70–74% silicon dioxide, 12–16% sodium oxide, 6–12% calcium oxide, 0–2% aluminumoxide, and 0–4% magnesium oxide for the 2.0-mm thick endcap glass) separated by 1.9-mm thicknoryl spacers, epoxied in place. High voltage is distributed to the electrodes via a thin layerof carbon-doped paint (conducting carbon-loaded tape in the endcaps) on the outer surfaces ofeach electrode; this layer has a surface resistance of 106−8 Ω/ and is transparent to fast pulses.
The energized electrodes maintain a quiescent uniform electric field of up to 4.3 kV/mm in thegas-filled gap. The current drawn from the high voltage supply corresponds to roughly 1 µA/m2
of electrode area, and most of this flows through the noryl spacers. We use a gas mixture of
62% HFC-134a, 30% argon, and 8% butane-silver (the latter being a mixture of 70% n-butane
and 30% isobutane).
A throughgoing charged particle ionizes the gas molecules along its path. The electric field thenaccelerates the electrons toward the anode and the ions toward the cathode. In the strong electricfield, the electrons initiate more ionizations, leading to a streamer between the electrodes. The
electrode charge in the ∼ 2 mm2 spot nearest the streamer then flows across the gap, momentarily
reducing the electric field there. The gas enhances the initial streamer formation and suppresses
afterpulsing in the surrounding area from ultraviolet photons ejected from the electrode atoms.
With a weaker electric field, streamer formation is inhibited and the electrodes do not discharge
nor deaden. Nevertheless, a small signal from the primary ionization is seen in this “proportionalmode.”The streamer (or proportional-mode pulse) is imaged on a plane of external pickup strips,
each about 5 cm in width. These strips, separated from an outer conducting ground planeby dielectric foam, behave like a transmission line with a characteristic impedance of about
50 Ω. Orthogonal pickup strip planes are mounted on either side of a pair of RPCs to form asuperlayer. Figure 10.2 shows an exploded view of the superlayer geometry. Because the RPC
materials are electrically transparent to fast signals, a pulse that forms in either RPC is imaged
on both readout planes and then travels along the transmission line and twisted-pair cables todiscriminators and serializers mounted on the periphery of the iron yoke. The redundancy inthis design results in a superlayer detection efficiency of up to 99% at the low ambient rates seenin Belle (Fig. 10.3).
During the normal high-electric-field operation, the amplitude of a streamer’s image pulse(∼ 100 mV into a 50 Ω termination) is large enough that it can be discriminated without amplification. (A proportional-mode pulse would need a preamplifier with a gain of 10 at the RPC andbefore the discriminator.) The pulse width is under 50 ns FWHM; the intrinsic time resolution
is a few ns. The discriminator threshold is typically set to near 40 mV (70 mV) for the barrel(endcap) RPCs due to the presence (absence) of an impedance-matching resistor at the junction
between the transmission line and the 100 Ω twisted-pair signal cable.
Each of the two RPCs in one module has independent high voltage and gas connections so that,in the event that a problem develops in one RPC, the other continues to function (but with asingle-RPC muon detection efficiency of between 90% and 95%).
The layout of one barrel RPC and of one octant of a barrel superlayer is shown in Fig. 10.4.
The corresponding geometries for the endcap are shown in Fig. 10.5.
The area of each barrel module ranges from 2.2×1.5 m2 to 2.2×2.7 m2 , except near the solenoid’s
315

CHAPTER 10. KL0 AND µ DETECTION (KLM)

Ground plane

0.25 mm Mylar
0.035 mm Copper

Dielectric foam

7 mm

+HV

0.035 mm Copper
0.25 mm Mylar
3.00 mm

Gas gap

2.00 mm-HV

3.00 mm

Insulator

0.5 mm Mylar+HV3.00 mm

Gas gap

2.00 mm-HV

3.00 mm

Cathode plane

0.25 mm Mylar
0.035 mm Copper

Dielectric foam

7 mm

Ground plane

0.035 mm Copper
0.25 mm Mylar

Cathode plane

31.6 mm total

Figure 10.2: Exploded cross-section of an RPC superlayer.

M021
M021( NewCS( NewCS) )Top
Top

EciencyEciencyMap
Map, cut, cut= =0.80
0.80

Bottom
BottomFigure 10.3: Two-dimensional
efficiency
EciencyEciencyMap
Map
, cut
, cut= =0.00
0.00map in an endcap superlayer module, with efficiency
proportional
to the size of a box, for (a) only Bottom
thefive top-layer RPCs, (b) only the five bottomTop
Top
Bottomlayer RPCs, and (c) all ten RPCs.

316

CHAPTER 10. KL0 AND µ DETECTION (KLM)

Internal spacers

Gas input
+HV

RPCs

Conducting Ink

440 cm-HV
Gas output

Iron

167-275 cm

220 cmFigure 10.4: Left: top view of a barrel RPC, showing the internal spacers and service ports.
Right: isometric view of one octant of a barrel superlayer, with two side-by-side modules above
an iron flux-return plate.

Figure 10.5: Left: top and side view of an endcap RPC, showing the internal spacers and service
ports. Right: cutaway isometric view of an endcap superlayer module.

helium chimney (Fig. 10.1), where the modules are shorter by 0.63 m. Each full-size module
weighs an average of 110 kg. The two RPCs in a module are placed so that the gas-gap spacers
do not overlap geometrically. In each module, there are 48 pickup strips to measure z (or,equivalently, θ) and 36 (48) pickup strips in layers 0–6 (7–14) to measure φ. Each strip isroughly 5 cm wide; this matches the scale of multiple scattering of a muon passing through theiron.
The area of a wedge-shaped endcap RPC is about 1.26 m2 , with a slightly smaller area for twoout of ten RPCs placed in a module to avoid geometric overlap of the RPC borders in the twoplanes. In each module, there are 48 coaxial-arc cathode strips of width 3.6 cm to measure θ
and 96 radial-trapezoid cathode strips of average width 3.3 cm to measure φ. There are no
termination resistors on these strips. Gas, high voltage and signal lines penetrate the module
frame at one of its outer corners. There are dead regions of a few centimeters’ width at theradial borders of each module (Fig. 10.3).
The spatial resolution of a superlayer is 1.1 cm (one standard deviation) when either one or two
adjacent cathode strips fire, and rises to 1.7 cm for the infrequent case where three strips fire317

CHAPTER 10. KL0 AND µ DETECTION (KLM)(due to UV-photon-induced afterpulsing of the neighboring electrode area).

10.3

Muon and KL identification

10.3.1

Muon identification

Muon identification [4] begins with the reconstruction of a charged track in the CDC. Each track
is extrapolated outward beyond the outermost CDC hit as if it were a pion; the extrapolation
uses the simulation geometry but only considers mean energy loss in determining the range ofthe track; fluctuations in energy loss as well as the average amount of multiple scattering are
accumulated in the track parameters’ evolving covariance matrix during this extrapolation. The
track is considered to be within the KLM acceptance if it crosses at least one RPC layer; thisrequires a momentum of at least 0.6 GeV/c. (The pion hypothesis is used initially because thisbenefits the initial extrapolation into the particle-identification detector and calorimeter.)If a KLM hit is found near the crossing of the extrapolated track with a detector layer, that
hit is associated with the track. The outermost layer crossed by the extrapolated track defines
the predicted range of the track; the actual range is determined by the outermost layer with anassociated hit.
If the predicted and actual ranges disagree substantially, the track is classified as a hadron andnot treated further (“pre-rejection”). Otherwise, the extrapolation is restarted at the entry point
into the KLM, but now using a muon hypothesis. In this re-extrapolation, we use the associatedhits with a Kalman filtering/fitting technique to steer the track as it is swum through the KLM.
The difference between the predicted and measured ranges as well as the goodness of fit of
the transverse deviations of the associated hits from the re-extrapolated track provide the twovariables used in a likelihood ratio to test the hypothesis that the track resembles a muon rather
than a charged hadron.
Typically, a physics analysis requires a value of 0.9 or greater for this normalized likelihood ratio
to classify a track as a muon. The muon detection efficiency plateaus at 89% above 1 GeV/c,
while the hadron fake rate is about 1.3% (but rises with lower momentum to as high as 3.8% at
0.7 GeV/c). The fake muons are pions that have neither decayed in flight (to a softer muon) nor
suffered an inelastic hadronic interaction. (Kaons that might have this behavior are positively
identified by the PID subsystem and are therefore much less likely to contribute to the hadron
fake rate.)

10.3.2

KL identification

Hits in the KLM that are within a 5◦ opening angle of each other (measured from the interaction
point), whether in the same layer or not, are grouped together into a cluster. After all clusters
have been formed, the charged track veto is applied. Each track is extrapolated to its entrance
into the KLM (as described earlier), then a straight line is drawn between this entrance point
and the interaction point. If this line is within 15◦ of the line between the cluster centroid
and the interaction point, the cluster is discarded. If the cluster is aligned with a reconstructed
neutral ECL cluster to within 15◦ , then the ECL and KLM cluster are associated, and the ECL’s
cluster direction overrides that of the KLM. Finally, a cut on the cluster size is imposed: to beclassified as a KLM-only KL candidate, the cluster must have hits in at least two distinct layers;
to be classified as a KLM+ECL KL candidate, the cluster must have a hit in the ECL and at
least one KLM hit.
Because of large fluctuations in the shower development of a KL –nuclear collision, the number

318

CHAPTER 10. KL0 AND µ DETECTION (KLM)

1

0.98

0.98

0.96

0.96

0.94

0.94

0.92

0.92

0.9

0.9

efficiency

1

0.88

0.88

Whole KLM

0.86

0.86
20

30

40

50
period

20

1

1

0.98

0.98

0.96

0.96

0.94

0.94

0.92

0.92

0.9

0.9

efficiency

Endcap Fwd

0.88

0.88

Barrel

0.86

30

40

50
period40

50
periodEndcap Bwd

0.86
20

30

40

50
period20

30

Figure 10.6: Experimental-number dependence of the muon detection efficiency in Belle for thewhole KLM, the forward endcap, the barrel, and the backward endcap.

of hits within a cluster that is associated with a KL meson is a poor measure of the incident
energy. Therefore, this cluster gives only the direction of the KL candidate. The resolution is3◦ for KLM-only candidates or 1.5◦ for KLM+ECL candidates. The KL detection efficiency
rises almost linearly with momentum from zero at 0 GeV/c to a plateau of 80% at 3 GeV/c; itis nearly flat in polar angle within the detector’s acceptance.

10.4

Backgrounds in the endcap RPCs

Since muon identification requires hit information from the KLM, the muon identification efficiency is a good monitor of KLM performance. The long-term history of the muon identification
efficiency in Belle is shown in Fig.10.6. The efficiency for the barrel RPCs is stable, while thatfor the endcap RPCs shows a gradual degradation.
Due to the intrinsic dead time associated with the recovery of the RPC electric field neara discharge, the particle detection efficiency depends on the ambient hit rate per unit area.
319

CHAPTER 10. KL0 AND µ DETECTION (KLM)(b) backward KLM detector

1
0.9
0.8
0.7
0.6
0.5
0.4

2

hit rate(Hz/cm )2

hit rate(Hz/cm )(a) forward KLM detector

0.3
0.2

0.1

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2

0

2

4

6

8

10

12

0.1

14

layer number

0

2

4

6

8

10

12

14

layer number

Figure 10.7: Hit rates in each layer of the endcap RPC for four LER current ranges: 400–600mA (•), 500–650 mA (), 600–800 mA (N), and 900–1300 mA (H). Left and right plots are forthe forward and backward endcap, respectively. In these plots, layer number increases from theoutside inward, starting at #1 for the outermost layer.
Figure 10.7 shows the distribution of this quantity for each endcap-RPC superlayer module
during KEKB operation for four intervals of the LER beam current, using RPC hits in the areaof 1.044 × 105 cm2 that overlaps the interior of the concrete shielding structure surrounding thebeam lines. The hit rate per unit area exceeds 1 Hz/cm2 in the outer-layer RPCs, resulting in a
sag in the RPC efficiency to between 70 and 80%. Figure 10.8 shows the hit rate per unit areafor endcap layer 3 (counting from the outside in) for the same LER currents as in Fig. 10.7.
The correlation between the measured flux and the LER current demonstrates the associationof this flux with beam-induced background.
To identify the source of the ambient hits, we performed a simulation study using Geant4 in
which we generated either low-energy neutrons or bremsstrahlung photons originating upstream
along the beamline. For the transportation of low energy neutrons in matter, we used datadriven models based on the data formats of ENDF/B-V1 [5]. Since the energy coverage of thesemodels is from 0.025 keV (thermal) to 20 MeV, the parametrization-driven models based on the
GHEISHA package were used for the more energetic neutrons. Figures 10.9(a) and 10.10(a)show the distributions of expected hit rates in each endcap RPC layer for selected values ofthe mean energy of the incident neutrons and photons, respectively. (The energy of incident
particles is distributed exponentially.)
To compare the simulation and experimental results, the data in Fig. 10.7 (for real data) and
Figs. 10.9(a) and 10.10(a) (for simulated particles) are fitted to the empirical function y(ℓ) =p1 e−p2 ℓ +p3 , where ℓ is the layer number and p1 , p2 , and p3 are free parameters. The exponential
term in the function corresponds physically to the attenuation of the particle with increasing
depth into the endcap iron flux return. From the fits to the real data, the exponential damping
parameter p2 falls between 0.29 and 0.40. Figures 10.9(b) and 10.10(b) show the fitted value ofp2 for each energy of the simulated neutrons and photons, respectively. Clearly, the exponential
320CHAPTER 10. KL0 AND µ DETECTION (KLM)

0.8

2

hit rate(Hz/cm )

0.7
0.6
0.5
0.4
0.3
0.2
400

600

800

1000

1200

1400

current in LER (mA)
Figure 10.8: Hit rate per unit area in forward () and backward (•) endcap RPC layer 3—
counting inward—for the four LER current intervals of Fig. 10.7. The error bars indicate therange of the beam current interval.

1
0.9
0.8
0.7
0.6
10

p2

hits/neutron

10

-3

-4

0.5
0.4
0.3

10

0.2

-5

0.1
0

2

4

6

8

10

12

0 -5
10

14

layer number

10

-4

10

-3

10

-2

10

-1

1

10

average kinetic energy(MeV)

Figure 10.9: Left: hits per generated neutron as a function of layer number—counting inward—
for incident mean energy of 100 eV (•), 1 keV (), 10 keV (N), 100 keV (H), 1 MeV (◦), and 10
MeV (). The curves are fits to the empirical function p1 e−p2 ℓ + p3 . Right: fitted exponential
damping parameter p2 as a function of simulated incident neutron energy.
321

CHAPTER 10. KL0 AND µ DETECTION (KLM)

1.2

hits/γ

10

10

10

10

-2

1.15
-3

1.1
1.05

-4

p2

10

-5

1

0.95
0.9

-6

0.85
10

-7

0

2

4

6

8

10

12

0.8

14

0

10

20

30

40

50

energy(MeV)

layer number

Figure 10.10: Left: hits per generated photons as a function of layer number—counting inward—
for incident mean energy of 5 MeV (•), 10 MeV (), 15 MeV (N), and 50 MeV (H). The curves
are fits to the empirical function p1 e−p2 ℓ + p3 . Right: fitted exponential damping parameter p2
as a function of simulated incident photon energy.
damping rates seen in the real data lie far below those extracted for photons of any energy. On
the other hand, the real rates are quite consistent with the damping rates extracted for neutronsof energy between 10 and 100 keV.
We conclude from the above studies that the ambient flux illuminating the endcap RPCs originates outside the Belle detector, is associated with the accelerator beams, and is dominated byneutrons with an energy of about 10 to 100 keV.
To test this conclusion, we placed neutron shielding in the form of polyethylene sheets on theoutside surface of the Belle endyoke and within the concrete shield surrounding the beamline(Fig. 10.11). We observed a partial recovery in the endcap muon detection efficiency (Fig. 10.6)
starting at experiment number 51 for the forward endcap and at number 55 for the backward
endcap.
In spite of the efficiency recovery over most of the endcap RPC area after the installation of thepolyethylene shield, we noticed that there was no improvement in the area nearest the beamline and surmised that there was an unshielded neutron source in the beamline near the Belle
detector. To test this, an additional polyethylene shield (Fig. 10.12) was installed on the lower
azimuth of the tapered part of the forward yoke. Later, the gap between the original planar
shield and this tapered shield was filled with polyethylene bricks.
The ambient noise reduction associated with the installation of this additional shielding wasmeasured by the ratio of after and before rates (in experiments 67 and 61, respectively, forthe tapered shield, and in experiments 69 and 67, respectively, for the gap shield) in each ofthirty areal sections of the endcap RPCs, with radial boundaries at r = 135, 150, 165, 180,
195, and 210 cm and six azimuthal sections labelled “Covered,” “Transition,” and “Reference”(Fig. 10.13), according to their overlap with the new shielding. The Reference region was322

CHAPTER 10. KL0 AND µ DETECTION (KLM)

Figure 10.11: Polyethylene shield.

Figure 10.12: Tapered shield.

expected to display no effect from the new shielding, and so would monitor the influence ofother environmental factors such as beam current or beamline vacuum condition. Each ratio
was normalized by the number of events in the before and after experiments to obtain a value
near 1.
The quadrant boundaries of the endcap RPCs appear as dead regions near x = 0 and y = 0
Fig. 10.13 The tapered and gap shields are expected to reduce the ambient rate in the lowerazimuth quadrants (sector 2, with x < 0 and y < 0, and sector 3, with x > 0 and y < 0).
For the tapered shield alone, the after-to-before normalized ratios are shown in each of the thirty
areal regions for each RPC layer in Fig. 10.14. The double ratios of Covered-to-Reference andTransition-to-Reference, shown in Fig. 10.15, indicate that the ambient-rate reduction is mostprominent in the small-radius regions.
The patterns of minima as a function of radial region in Fig. 10.15 were speculated to be due tothe shading by the tapered shield of particles incident from a pointlike source. We extracted theminimum for each radial region (by a fit to a double Gaussian as a function of layer number),then fitted these minima to a straight line as a function of radius. The minima and this fitted
straight line is shown in Fig. 10.16; the intercept lies at the QC1E beamline magnet.
323

CHAPTER 10. KL0 AND µ DETECTION (KLM)

300

200

y (cm)

100

0Reference

Reference

-100

-200
Transition

Transition

-300
-300

-200

-100

Covered0x (cm)

100

200

300

Figure 10.13: Radial and azimuthal segmentation of the endcap RPCs to test the ameliorationof the ambient hit rate by the tapered polyethylene shield (in gray) and, later, the interstitialpolyethylene bricks (in black). The area of each small square is proportional to the ambient hit
rate in its vicinity.

324

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

Exp67/Exp61(Norm. by Ev.)

1.2

0.8

Exp67/Exp61(Norm. by Ev.)

Exp67/Exp61(Norm. by Ev.)

1.2

1

1.2

1.2

Exp67/Exp61(Norm. by Ev.)

Exp67/Exp61(Norm. by Ev.)

1.2

Exp67/Exp61(Norm. by Ev.)CHAPTER 10. KL0 AND µ DETECTION (KLM)

1.2

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

Figure 10.14: After-to-before ambient-rate normalized ratios for the tapered shield as a functionof endcap layer number. Left column: endcap sector 2; right: sector 3. Top row: Reference
azimuthal wedge; middle: Transition; bottom: Covered.
325

Exp67/Exp61(Norm. by Ev.)

Exp67/Exp61(Norm. by Ev.)CHAPTER 10. KL0 AND µ DETECTION (KLM)

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

0

5

10

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

0

5

10

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

0

5

lyr
Exp67/Exp61(Norm. by Ev.)

Exp67/Exp61(Norm. by Ev.)

lyr

10

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

lyr

0

5

10
lyr

Figure 10.15: After-to-before ambient-rate normalized double ratios for the tapered shield, asa function of endcap layer number. Left column: endcap sector 2; right: sector 3. Top row:
Transition-to-Reference double ratio; bottom: Covered-to-Reference.

326

CHAPTER 10. KL0 AND µ DETECTION (KLM)

Figure 10.16: Fitted minimum-rate points in each layer and their straight-line extrapolation tor = 0. The red shape is the tapered shield; the cyan shape is the planar shield.

The same technique was applied after installation of the gap shield to measure its effect. The
corresponding results are shown in Figs. 10.17 and 10.18. From the upper half of Fig. 10.18,
we observe no change in the Transition region due to installation of the gap shield: this is not
surprising, since the gap shield does not overlap with either Transition region. The lower halfof this figure, however, shows a dramatic reduction in the ambient noise rate, particularly forthe larger-radius regions. From the increased width (in layers) of the minimum as a function ofradius, it appears that the gap acted like a pinhole camera for the incident particles before it
was plugged with the polyethylene bricks.
One overriding conclusion from these studies is that low-Z neutron shielding is quite effective
in reducing the ambient rate in the endcaps: regardless of the detector technology, as much ofthis shielding as possible should be installed in Belle II.

10.4.1Capability to operate at SuperKEKB luminosity

Though we have not identified all sources of background neutrons, it is likely that they are
generated by secondary interactions following processes such as the backscattering of a radiativeBhabha photon, beam-gas collisions, and the Touschek process (Ch. 2).
We extrapolate the measured hit rates in each region of the Belle KLM to Belle II by fittingthese data to the sum of four terms, each linearly proportional to a beam-related quantity: theluminosity L (correlated with the backscattering of radiative-Bhabha photons), the product of327

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

Exp69/Exp67(Norm. by Ev.)

1.2

0.8

Exp69/Exp67(Norm. by Ev.)

Exp69/Exp67(Norm. by Ev.)

1.2

1

1.2

1.2

Exp69/Exp67(Norm. by Ev.)

Exp69/Exp67(Norm. by Ev.)

1.2

Exp69/Exp67(Norm. by Ev.)CHAPTER 10. KL0 AND µ DETECTION (KLM)

1.2

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

1
0.8
R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0

5

10
lyr

Figure 10.17: After-to-before ambient-rate normalized ratios for the gap shield as a functionof endcap layer number. Left column: endcap sector 2; right: sector 3. Top row: Reference
azimuthal wedge; middle: Transition; bottom: Covered.
328

Exp69/Exp67(Norm. by Ev.)

Exp69/Exp67(Norm. by Ev.)CHAPTER 10. KL0 AND µ DETECTION (KLM)

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

0

5

10

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

0

5

10

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

0

5

lyr
Exp69/Exp67(Norm. by Ev.)

Exp69/Exp67(Norm. by Ev.)

lyr

10

1.2
1.1
1
0.9
0.8
0.7

R=135-150 cm
R=150-165 cm
R=165-180 cm
R=180-195 cm
R=195-210 cm

0.6
0.5

lyr

0

5

10
lyr

Figure 10.18: After-to-before ambient-rate normalized double ratios for the gap shield, as afunction of endcap layer number. Left column: endcap sector 2; right: sector 3. Top row:
Transition-to-Reference double ratio; bottom: Covered-to-Reference.

329

CHAPTER 10. KL0 AND µ DETECTION (KLM)
Layer
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14

KEKB
1.07
0.74
0.43
0.28
0.21
0.16
0.14
0.13
0.12
0.11
0.09
0.13
0.09
0.12
0.09

BarrelSuperKEKB
3.6
2.3
1.6
1.1
0.67
0.60
0.63
0.43
0.73
0.47
0.29
0.39
0.44
0.42
0.48

Endcap forward
KEKB SuperKEKB
0.29
2.4
0.25
2.4
0.23
2.4
0.23
2.0
0.23
2.2
0.26
2.7
0.24
2.7
0.26
3.3
0.27
3.1
0.21
3.9
0.36
4.7
0.47
5.3
0.55
3.7
0.56
XX
N/A
N/A

Endcap backward
KEKB SuperKEKB
0.31
3.4
0.31
2.9
0.31
2.8
0.31
2.8
0.32
2.8
0.35
2.9
0.34
1.5
0.36
2.6
0.38
3.0
0.41
2.8
0.46
3.5
0.50
3.0
0.49
XX
0.55
XX
N/A
N/A

Table 10.1: Ambient rate (Hz/cm2 ) measured in KEKB and extrapolated to SuperKEKB.
vacuum pressure and LER current Vc × ILER (proportional to the rate of beam-gas collisions
in the LER), the product of vacuum pressure and HER current Vc × IHER (proportional to the2rate of beam-gas collisions in the HER), and the square of the LER current ILER
(proportional
to the rate of background associated with Touschek scattering within each bunch of the smallbunch LER beam). The expected hit rates in SuperKEKB, with an instantaneous luminosity of
L = 5 × 1035 cm−2 s−1 , are listed in Table 10.1
The expected efficiencies are obtained by converting these extrapolated hit rates according to
the dependences shown in Fig. 10.19. Differences in the characteristics of the glass used in thebarrel and endcap RPCs account for the distinct dependence of efficiency on ambient rate. The
slope of the efficiency vs hit rate for the barrel (endcap) is about −0.08 (−0.5), with hit ratemeasured in Hz/cm2 .
The expected efficiencies are listed in Table 10.4.1. The innermost layers of the barrel exhibit asomewhat reduced efficiency, but are still operable in Belle II. On the other hand, all layers of
the endcap are projected to be completely inefficient. We therefore consider a full replacementof the endcap KLM and the replacement of few innermost barrel layers with scintillator strip
detector described in the next section. We note that the low-Z material of scintillator layers
provides additional neutron background shielding of the remaining RPC which is not taken into
account in the above estimates for being conservative.

10.5

Scintillator Endcaps

Because of the projected inefficiency of RPCs at high ambient rate, the Belle II endcaps are
instrumented with scintillator strips [6]. Charged particles detection with such detectors, where
the scintillation light is trapped in embedded wavelength-shifting (WLS) fibers and delivered tophotomultipliers or other sensors, is a well-established technique [7, 8, 9].
In Belle II, the limited space and strong magnetic field do not allow us to use photomultipliers.

330

CHAPTER 10. KL0 AND µ DETECTION (KLM)

efficiency vs hitrate for endcap
efficiency

efficiency

efficiency vs hitrate for barrel
1

1

0.9

0.9

0.8

0.8

0.7

0.7

0.6

0.6

0.5

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.5

0

0.05

0.1

0.15

2

0.2

0.25

0.3

0.35

0.4

0.45

0.5

2

hitrate(Hz/cm )hitrate(Hz/cm )Figure 10.19: Efficiency vs ambient rate for the barrel (left) and endcap (right) RPCs.

Layer
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14

KEKB
0.91
0.94
0.96
0.98
0.98
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99

BarrelSuperKEKB
0.70
0.81
0.87
0.91
0.94
0.95
0.95
0.96
0.94
0.96
0.98
0.97
0.96
0.97
0.96

Endcap forward
KEKB SuperKEKB
0.91
0.0
0.93
0.0
0.94
0.0
0.94
0.0
0.94
0.0
0.92
0.0
0.93
0.0
0.92
0.0
0.92
0.0
0.90
0.0
0.87
0.0
0.82
0.0
0.78
0.0
0.77
0.0
N/A
N/A

Endcap backward
KEKB SuperKEKB
0.90
0.0
0.90
0.0
0.90
0.0
0.90
0.0
0.89
0.0
0.88
0.0
0.89
0.0
0.87
0.0
0.86
0.0
0.85
0.0
0.82
0.0
0.80
0.0
0.81
0.0
0.76
0.0
N/A
N/A

Table 10.2: RPC efficiency measured in KEKB and extrapolated to SuperKEKB.

331

CHAPTER 10. KL0 AND µ DETECTION (KLM)
As a photodetector, we consider multipixel silicon photodiodes operating in the Geiger mode,
which were developed in Russia [10, 11, 12, 13] in the 1990s. They are now produced by many
companies that use different names for their products: SiPM, MRS APD, MPPC, MAPD, etc.
Here, we use the generic term Silicon PhotoMultiplier (SiPM). These sensors are compact andoperate in a strong magnetic field.
The first experience of large-scale SiPM use was obtained by ITEP in the production of the 8,000
scintillator tiles with WLS fiber and SiPMs for the CALICE hadron calorimeter prototype [14].
Now, the contemporaneous T2K experiment uses SiPM readout in many components of the neardetector (FGDs and SMRD), with 65,000 channels in total [9]. This technology is mature andour group has a lot of direct experience with it. The scintillator-based endcaps meet the physics
requirements of Belle II, and can cope with a background rate that is at least two orders ofmagnitude higher than in Belle and well above that expected in Belle II.

10.5.1

General layout

Scintillator-based superlayers are installed in all 14 existing gaps in the magnet yoke in bothforward and backward endcaps. The whole system consists of 16,800 scintillator strips with
WLS readout, arranged in two orthogonal planes to form a superlayer within each gap. The
independent operation of two planes reduces the combinatorial background in comparison withthe present RPC superlayer design, where one background hit produces signals in both readout
planes.
The scintillator strips have a cross section of (7–10) × 40 mm and a length of up to ∼ 2.8 m. The
strip width is a compromise between the desire to limit the total number of channels and needfor reasonable spatial resolution for muon and KL0 reconstruction. This granularity is similar
to the average cathode-strip granularity of the RPCs. Individual scintillators are covered witha diffuse reflective coating. The strip has a groove in the center to accommodate a WLS fiber.
Scintillator light is caught by this fiber and transported to the SiPM. The WLS fiber is read out
from one side. The far end of the WLS fiber is mirrored to double the light yield at the SiPM.
The WLS fiber is glued to the scintillator to increase the efficiency of the light collection. The
SiPM is coupled to the fiber end. It is fixed and aligned with the fiber using a plastic housing.
One layer of scintillator strips, arranged in a quadrant that fits into the existing gap in the ironyoke, is shown in Fig. 10.20. The sector frame is identical to the existing one used for the RPC
mounting. The dead zone around the inner arc is estimated to be ∼ 1% of the total sector
area, due to the inscribing of the rectangular structure into the circle. The inner dead zone isapproximately the same as in the present RPCs. Around the outer circle, the dead zone is 4%,
because of location here of cables and the eschewal of very short scintillators. The acceptanceloss at large radii is not critical for muon or KL0 reconstruction. In the central area of the sector,
the small dead zones (< 1%) are due to support structures. In addition, the insensitive area
between strips due to the reflective cover is only 0.3%. In total, the geometrical acceptance ofthe proposed system is slightly better than that of the present RPCs.

10.5.2

Scintillator strips

The scintillator strips are made of polystyrene doped with PTP (1.5%) and POPOP (0.01%).
The strips are produced by the extrusion technique. This technique provides the possibility to
produce long strips. Different producers use slightly different ingredients and production techniques, but generally they achieve quite similar quality and request a similar price. Among the
known producers are Fermilab and “Uniplast” (Vladimir, Russia), which produced the scintillator strips for the T2K experiment [9], and “Amkris-Plast” (Kharkov, Ukraine), which produced
332

CHAPTER 10. KL0 AND µ DETECTION (KLM)
The shortest strip
885
Supportstructure

Longest strip
2820

to
ot

od

et

ec

Green light

Bluhe t
lig

ph

Fiber
Mirror

To

5
130
7

R

40

r

Track

R 3105Figure 10.20: a) One layer formed by scintillator strips. b) Scintillator light detection in the
strip.
the strips for the Opera experiment [8]. We tested the characteristics of the scintillator strips
from three producers. All strips had a width of 40 mm. The thickness of the Fermilab andKharkov strips was 10 mm, while that of the Vladimir strips (surplus stock for T2K) was 7 mm.
In all strips, the Kuraray WLS multi-cladding 1.2-mm diameter fibers were glued using SL-1 gelproduced at SUREL, St. Petersburg. This fiber provides more light output than other fibers andhas a large attenuation length. This fiber was used in many detectors with similar scintillator
plastic and geometry [7, 8, 9]. The light emission spectrum of the Kuraray Y11 fiber matches
well with the SiPM spectral efficiency.
The strips have been tested using a cosmic-ray test bench. The cosmic trigger is provided by apair of short trigger strips (L = 16 cm) placed above and below the strip under consideration.
The trigger strips were moved along the tested strip to measure the light yield depending on
the distance to the photodetector. All strips were tested using the same SiPM to avoid apossible spread in the SiPM efficiency. To determine the average number of detected photons,
we correct the measured number of fired pixels by the cross-talk (factor 1/(1 + δ) ∼ 0.85) andconservatively use a truncated mean of the Landau distribution, discarding 10% of the lower
part of the distribution and 30% of the higher part and then taking the average. In this way, theLandau tail is discarded. The averaged number is then corrected for the slanted incidence of thecosmic muons using a toy Monte Carlo simulation. In the case of the Vladimir scintillator, thereflective coating is very thin (∼ 50 µm, compared with ∼ 150 µm for the FNAL and Kharkov
strips). Their light yield is improved by about 15% by using a reflective layer of white paper(Tyvek).
The distribution of the average number of detected photons at the SiPM is shown in Fig. 10.21(a).
For comparison, the light yield of the FGD of the T2K experiment, collected from the Fermilab
strips (10 × 10 mm2 ), is shown in Fig. 10.21(b). As can be seen from these distributions, weachieve a slightly better light yield in√ spite of our four times larger strip width. (The light yield
is approximately proportional to 1/ width.) This is due to the larger diameter of our fiber andthe gluing of this fiber to the strip.
We measure the time resolution using the cosmic trigger for a strip equipped with two SiPMs,
one at each end of the fiber. From the time difference dispersion, we derive the time resolutionof σt ≈ 0.7 ns. The measured velocity of the light propagation in the WLS Y11 Kuraray fiber333

CHAPTER 10. KL0 AND µ DETECTION (KLM)
26

Vladimir with paper coverFermilab
VladimirKharkov

Number of fired pixels

24
22
20
18
16
14
12
10
8
0

50

100

150

200

250

300

Response,ADC ch.

Distance to SiPM, cm

500
400
300
200
100
0

-60

-50

-40

-30

-20

-10

0

10

20

30

Y-coordinate, mm

Figure 10.21: The distribution of the average number of detected photons at SiPM as a functionof the distance to the photodetector for a) our study b) FGD at T2K experiment. c) ADC
response, which is proportional to the light yield, for two neighboring strips.
with the diameter of 1.2 mm is v = 17 cm/ns.
The transverse uniformity of the strip response was measured at the ITEP proton beam. Figure 10.21(c) (upper plot) shows the ADC response, which is proportional to the light yield, for
two strips connected to each other. The nonuniformity of the response is ∼ 15%. From theseresults, we conclude that the light yield is sufficient no matter where a particle hits the strip.
The long-term stability of the light collection efficiency of the strips with glued WLS fibers wastested using the test module of 96 strips (1 meter long) that was manufactured in 2006. The
strips were equipped with CPTA’s SiPMs. The test module was used for the measurement of
the neutron background in the KEKB tunnel over a six-month span. In 2009, these strips werestudied again. No degradation of the light yield, within the 10% accuracy of the measurements,
was observed in the three years since their production.

10.5.3SiPMs

A SiPM is a matrix of tiny photodiodes (pixels) connected to a common bus and working in the
Geiger mode. Typically, there are ∼ 100 − 1000 pixels in an area of 1 × 1 mm2 . Connection to
the common bus is done usually by a ∼ 106 Ω resistor. This resistor limits the Geiger discharge
developed in a pixel by photo or thermal electrons. In this mode, the SiPM response depends
on the number of fired pixels and is proportional to the initial light until the number of fired
pixels is much less than the total number of pixels.
As compared with conventional vacuum photomultipliers, SiPMs have low operational voltage

334

CHAPTER 10. KL0 AND µ DETECTION (KLM)of a few tens of Volts. This is higher than the breakdown threshold by several volts. The
values of the overvoltage and the capacitance of a single pixel determine the photodetector gain
(typically of order of 106 ). The values of the quenching resistor connected in series to eachpixel and the capacitance of a single pixel determine the dead time of a pixel, which is typically∼ 100 ns. The photon detection efficiency (P DE) depends on overvoltage and reaches 25–30%
for modern devices. SiPMs with a smaller number of pixels have higher P DE because of thesmaller non-sensitive area between pixels. SiPMs are not affected by a magnetic field of up to
4 T [15]. Among the disadvantages of SiPMs are a high level of noise (∼ 106 Hz/mm2 at thethreshold of one p.e.), an optical inter-pixel crosstalk producing a tail of higher amplitudes at
random spectrum, and a high sensitivity of the SiPM response to ambient temperature (thebreak-down voltage depending on temperature according to ∼ 60 mV/K for Hamamatsu and∼ 20 mV/K for CPTA).
A comparison of SiPMs from different manufacturers is depicted in Fig. 10.22. The photon
detection efficiency (for green light), gain, crosstalk, and noise rate are shown as a function of
overvoltage for detectors produced by MEPhI/PULSAR, CPTA (Russia), Hamamatsu (Japan).
SiPMs produced by CPTA and Hamamatsu meet our requirements of high MIP registration efficiency, low crosstalk, and low noise frequency. Both producers have the experience of producing
thousands of SiPMs and can produce SiPMs matched with the 1.2-mm diameter fiber. (BothCPTA and Hamamatsu were considered as the main producers for T2K experiment.)
SiPMs demonstrate a very high long-term stability. The experience in the operation of the 7620channel CALICE hadron calorimeter prototype during three years of beam tests at CERN and
FNAL [14, 16] showed no significant problem. Only eight dead channels (0.1%) were observed,
while the characteristics of remaining channels did not change. The long-term stability of theHamamatsu SiPMs was tested in the T2K experiment, where ∼ 65, 000 channels were studied
during more than one year of operation. They observed failure in only ∼ 20 channels—less than
0.03%—mostly because of mechanical damage.

10.5.4

Radiation hardness

Scintillator counters with WLS fiber are used in many existing detectors, even at hadron machines where the radiation dose is a few orders of magnitude higher than those expected at
SuperKEKB. In particular, the light collection at the electromagnetic calorimeter for the HERAB experiment is based on the Vladimir scintillator tiles read out by Kuraray Y11 fibers [17].
During six years of operation, no deterioration of the electromagnetic calorimeter performance
was observed. However, the proposed method of light detection by SiPM is a new method that
required detailed radiation hardness tests. In particular, the radiation hardness of the SiPM
is measured to be high in case of irradiation with electrons and photons, while neutrons andprotons cause significant damage after a moderate integrated dose of ∼ 1 krad [14]. The fluxof harmful particles through the SiPM results in defect formation in the thin area from whichcharge carriers are collected. This results in an increase of the SiPM noise rate and, consequently, the dark current. The SiPM dark current grows linearly with the particle flux as inother silicon detectors.
The damage effects from proton and neutrons are energy dependent and, without knowledgeof the beam background spectra, it is difficult to predict the radiation damage. Therefore, tomeasure the possible damage to SiPMs due to the radiation level at SuperKEKB, we performed
radiation tests directly in the KEKB tunnel. Eight Hamamatsu SiPMs and eight CPTA SiPMs
were placed in the KEKB tunnel for six weeks during accelerator operation. The integrated
neutron dose in the tunnel, measured with Luxel dosimeters (J-type badges), was ∼ 1.2 Sv.
335

CHAPTER 10. KL0 AND µ DETECTION (KLM)

Gain (x10-6)

PDE to green light

0.3
0.25
0.2
0.15

- Hamamatsu 1600

1.6

- MEPhI/PULSAR

1.4- CPTA- Hamamatsu 400

1.2
1
0.8

0.1

0.6
0.4

0.05
0

1.8

0.2
0

2

4

0

6

0

2

Overvoltage, V

4

6

Overvoltage, V

Noise frequency, kHz

Cross talk

0.6
0.5
0.4
0.3
0.2

10

10

3

2

0.1
0

0

2

4

6

0

Overvoltage, V

2

4

6

Overvoltage, V

Figure 10.22: Overvoltage dependence of a) efficiency, b) gain, c) crosstalk and d) noise frequency for SiPMs from different manufacturers: Hamamatsu 1600 pixels (◦), MEPhI/PULSAR(N), CPTA (⋆), Hamamatsu 400 pixels (H).
After irradiation, the SiPM dark current increased for both manufacturers’ devices by a factorof 3.6, with a small dispersion (∼ 15%) in the eight specimens.
The neutron dose was also measured near the proposed installed position of the SiPM using
Luxel dosimeters. The measured dose varies from 0.8 to 2.0 mSv/week at the luminosity ofL ∼ 1.7 × 1034 cm−2 s−1 . Assuming the neutron dose increases linearly with the luminosity, theexpected neutron dose integrated over ten years of operation at L ∼ 8 × 1035 cm−2 s−1 does notexceed 40 Sv. The extrapolated factor of dark current increase after ten years of operation ofSuperKEKB is therefore 150, resulting in an expected final dark current of ∼ 14 µA (∼ 200 µA)
for Hamamatsu’s (CPTA’s) SiPM. The difference between the Hamamatsu and CPTA SiPMs
can be explained by the different thickness of the sensitive zone, to which both initial noise andthe damage effect are proportional.
The study of SiPM properties after irradiation was done at ITEP. The SiPMs were subjected to
fast irradiation in the 200-MeV secondary proton beam of ITEP synchrotron (∼ 1010 p/cm2 /hr).
One month after the irradiation, the Hamamatsu SiPM dark current was 16 µA for two specimens
336

CHAPTER 10. KL0 AND µ DETECTION (KLM)

(kHz)

1

10 3

0.98

10 2

Noise rate

MIP efficiency from far end

1.02

0.96

10

0.94
0.92

1

0.9

10

0.88

10

0

5

10

Threshold(Np.e.)

-1
-2

0

5

10

Threshold(Np.e.)

Figure 10.23: Dependence on the threshold in number of photoelectrons of a) the detection
efficiency for MIPs striking the strip’s far end, and b) the SiPM internal noise rate. The triangles
correspond to the virgin SiPM, the circles to the SiPM irradiated with a dose of 7.4 × 1010 p/cm2(five years of operation at SuperKEKB), and the squares to the SiPM irradiated with a dose of
2.0 × 1011 p/cm2 dose (more than ten years of operation at SuperKEKB).
subjected to an integrated proton flux of 2.0 × 1011 p/cm2 and 6.5 µA for two other specimens
subjected to an integrated proton flux of 7.4 × 1010 p/cm2 .
We studied the light yield from MIPs passing through the strip at the far end (∼ 3 m from thephotodetector) detected with virgin and irradiated SiPMs. The average number of photoelectrons from the MIP signal using irradiated and control SiPMs is unchanged, though, for theirradiated SiPMs, the MIP signal is slightly smeared because of noise. The dependence of theefficiency for the far end of the strip and the noise rate on the threshold (in number of fired pixels) is presented in Fig. 10.23. We conclude that the light detection efficiency is not significantly
changed after irradiation, while the internal noise rate increases significantly. However, at thethreshold of ∼ 7.5 fired pixels, the background rates from the increased SiPM noise remains
smaller (. 10 kHz) than the physical background rate due to neutron hits in the scintillator(. 200 kHz). The MIP detection efficiency is similar to that of irradiated CPTA’s SiPM, but
the latter’s noise rate is too high (100–500 kHz).
We therefore conclude that the Hamamatsu’s SiPM radiation hardness is sufficient for successful
KLM operation at the designed luminosity for at least ten years. The significantly increased darkcurrent, however, should be considered in the design of electronics, HV supplies, slow control,
and the calibration procedure.

10.5.5

Measurement of the background neutron rate

As RPC and scintillator have different responses to the beam background, the extrapolation of
the measured background rates in the RPCs (Sec. 10.4) to the expected rate in the scintillator
endcaps at SuperKEKB is difficult. Therefore, we have performed measurements of the neutron
flux using a scintillator test module installed in the KEKB tunnel near the KLM endcap. The test
module contained four layers, each surrounded by a shielding box for protection from external
light and assembled from 24 strips. Each scintillator strip with a WLS fiber and SiPM readout
had a size of 1000 × 40 × 10 mm3 . During KEKB operation, the signals from 96 channels were337

CHAPTER 10. KL0 AND µ DETECTION (KLM)
collected by a random trigger using a CAMAC ADC. The gate was set to be 100 ns.
The shielding box could not protect the module from numerous charged tracks and showers. To
discriminate the neutron signals from other sources, different hit patterns in the four layers wereused. The significant part of the observed events (where at least one SiPM signal exceeds thethreshold of 0.5 MIP) has multiple hits from charged tracks or showers. We require the veto in
the two outer layer and require a single hit in on of the two inner layers. The calculated neutron
rate at 0.5 MIP threshold at the luminosity of L ∼ 1.4 × 1034 cm−2 s−1 was 6 Hz/cm2 . We use
this number to estimate the occupancies in the readout electronics (maximum 160 kHz from thelongest strip, 60 kHz averaged) and trigger, as well as to estimate the expected backgrounds forKL0 reconstruction.

10.5.6

Electronics

The SiPM has excellent time resolution and high output-rate capability. Signals with different
number of photoelectrons are well separated, which gives the possibility of accurate calibrationof the device. To use these advantages fully, the front-end electronics should comply with SiPM
characteristics and provide fast processing of the SiPM signals with low noise and short deadtime.
The core of the front-end electronics is the 16-channel TARGET ASIC chip (Ch. 13), a waveform sampling device (“oscilloscope on a chip”). Amplifiers, fine HV control, and an ammeter tomonitor SiPM aging are also installed on the readout board. An FPGA is used for slow control,
analysis of the digitalized signal, and implementation of the interface with COPPER boards.
Two possible layouts are considered, each with its advantages and drawbacks:
1. Each SiPM is equipped with a preamplifier, while the rest of the electronics is locatedoutside of the detector. If a preamplifier fails (e.g., because of irradiation), it may bereplaced only during long shutdowns, when a partial disassembly of the endcap is possible.
Many cables are needed to connect every SiPM with the readout board in this case.
2. Electronics is completely installed outside of the detector. One twisted pair in a ribbon
connects each SiPM, reducing number of cables to the minimum. In this layout, failed parts
are replaced during regular maintenance. However, pick-up noise may pose a problem, sothat readout board should be located as close to the detector as possible.
The second layout option was tested in the KEKB tunnel during accelerator operation. No
significant pick-up noise was observed under the present conditions. A schematic sketch of thislayout is shown in Fig. 10.24( a).
The amplified input signal, with a gain of ∼ 15, is digitized with a sampling rate of ∼ 1 GHz
by the TARGET. The FPGA scans this stream, searching for a typical SiPM signal pattern.
Figure 10.24(b) shows the amplified SiPM one-photoelectron pulse, fitted by a simple function.
The fit provides accurate time and amplitude information. Due to the steep leading edge of thepulse, the time resolution is very good (σ ∼ 1 ns), which is useful for the rejection of combinatorial background. We are interested in two characteristic SiPM outputs: small-amplitude signals,
which are due mainly to noise and are used for calibration, and large-amplitude signals that areassociated with muons and KL0 mesons.

10.5.7

Slow control and monitoring

To ensure good data quality, the slow control and monitoring uses hardware measurements
as well as fast data analysis. The SiPM response is sensitive to the ambient temperature,338

Common HVSiPM

TARGET

Amp

Dark current
measurementAmp

10−bit ADC

Amplitude x 0.62 mV

CHAPTER 10. KL0 AND µ DETECTION (KLM)

10
5
0
-5

-10

FPGA

-15
8−bit DAC
0−5V

HV fineajustment

-20

25

50

75

100

Time

125

150

175

200

ns

Figure 10.24: a) Schematic sketch of the front-end electronics for the endcap KLM. b) Amplified
SiPM pulse readout for one photoelectron by the TARGET ASIC chip.

so ten temperature sensors are placed near the SiPMs in each quadrant. Temperatures arepermanently recorded. The possibility of adjusting the SiPM bias voltages to compensate fordrifts in temperature is under study.
The SiPM current is recorded for each channel. During luminosity runs, the currents are sensitive
to the background level and spatial distribution (after the channel-by-channel dark current
subtraction). Dead (disconnected) channels manifest themselves as zero-current readings. The
SiPM currents from calibration runs are used to monitor the long term stability and correlatedwith the accumulated radiation dose.
Ten thousand random triggers during each calibration run provide reliable pedestal measurements for each channel. The pedestal width is a good measure of the SiPM and electronics noise.
With a virgin SiPM, it is possible to determine the position of the one-photoelectron peak andhence the gain. This determination will probably disappear after a few years of operation as the
SiPM dark current increases with radiation damage. The muon detection efficiency for every
channel can be determined on-line. At L = 8×1035 cm−2 s−1 , one expects more than 1000 muons
per strip per hour. KLM online histograms show the current and efficiency for every channel aswell as the muon trigger rate and angular distribution.

10.5.8

Production

In this section, we describe the assembly procedure for the option with Vladimir’s scintillatorand Hamamatsu’s SiPM, which seems the most attractive. However, the assembly procedure is
identical for any other producers.
10.5.8.1

Manufacturing of strips

The cross section of the strip is 7 × 40 mm2 ; the length varies from 50 to 280 cm depending on
the strip position inside the layer (Fig. 10.20). At the Vladimir enterprise, scintillator plates
are extruded with a thickness of 7 mm and a width of about 25 cm. The edges of the extruded
plates are slightly rounded. The plates are sawed into 40-mm wide strips using special machinery
developed at Vladimir. After sawing, the strips are subjected to chemical etching that produces
339

CHAPTER 10. KL0 AND µ DETECTION (KLM)a diffuse reflective covering of their surfaces. The thickness of the covering is about 50 µm. A
1.3-mm wide and 3-mm deep groove is milled in each strip to hold the WLS fiber.
10.5.8.2

Assembly of strips

The WLS fiber is fixed at the strip ends with a two-component epoxy, Bicron BC600. In the
middle part, the groove with the fiber is filled with an optical gel SL-1 produced at SUREL,
St. Petersburg. The gel is cheaper and more elastic than BC600, which is useful to compensate
for differences in the thermal expansion coefficients of the gel and the scintillator.
One WLS fiber end is connected to a photosensor while the other is mirrored using a silver-shine
paint. The reflectivity of the paint is measured to be above 90%. The SiPM is attached to the
1111
0000
0000
1111
SiPM
0000
1111
0000
1111
0000
1111
0000
1111
Spring
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
1111
0000
0000
1111
1111
0000
111111111111111111111
000000000000000000000
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111
0000
1111

Scintillator strip

1
0
0
01
1
0
1

Fiber

Connectors

Figure 10.25: Schematic cutaway view of the strip end.
WLS fiber using the connector shown in Fig. 10.25. The connector is made of plastic and is
produced using casting in Vladimir. The fiber is glued into the hole in the male part of theconnector and this male part is glued to the strip. We use BC600 for the gluing. The WLS
fiber end sticking out of the optical connector is cut away using a milling machine. The SiPM
is placed into the female part of the connector above a spring made of micro-porous material.
When the connector is closed, the spring presses the SiPM face against the WLS fiber end. The
female part of the connector has holes for the SiPM pins. A twisted pair connects the SiPM
pins with the preamplifier.
We plan to perform tests of all strips using a cosmic-ray test stand.
10.5.8.3

Layer Segment

The x and y planes of the superlayer are each divided into five segments (Fig. 10.20). The
segments of the x and y planes are identical. Each segment consists of 15 strips. The strips are
glued to a 3-mm thick plastic plate using Plexus MA550 glue. Glue from the same producer
was used for the FGD detector at the T2K experiment [18]. The MA550 glue includes TiO2 dyethat improves the light reflectivity of the strip. The other side of the segment, which contains
the grooves with the WLS fibers, is covered by white paper to further improve the reflectivity.
10.5.8.4

Support structure

The segments are supported by aluminum I-beams that run along the segment boundaries(Fig. 10.26). The I-beams supporting the x- and y-plane segments are welded together intoa grid. The segments are inserted into the grid and fixed using wedges. The grid with segments
is attached to the outer frame that is located along the perimeter of the layer. We plan to
use the existing RPC frames from the Belle endcaps. The photosensors, cables, and amplifiers(optionally) are installed after the segments, I-beams, and outer frame are assembled.
340

CHAPTER 10. KL0 AND µ DETECTION (KLM)

A view
strips (Y)I-beam (Y)welding

111 111
000
000
000
111
I-beam (X)

A

5
600

Figure 10.26: Supporting structure for one layer: grid from I-beams and outer frame.
Finally, the frame is covered by 1.5-mm thick aluminum plates to protect the detectors from theexternal light. Again, we plan to use existing RPC-module plates.
10.5.8.5

Mounting at KEK

The segments are produced at ITEP, while the I-beam grids are produced at KEK. All SiPMs
are tested at KEK before they are connected to the scintillator strips. After the assembly andcabling of one superlayer, it is tested using the cosmic-ray stand. The frames are installed into
the gaps of the iron absorber with a crane using the same procedure as for the RPCs. We plan
to use flat signal cables that are placed between the module and the cover plates.
10.5.8.6

Schedule

The extrusion of all strips at Vladimir enterprise will take about three months. Further operations at Vladimir—cutting the scintillator plates into strips, matting of the strips, and milling
the groove for the WLS fiber—will take about half a year. All these operations can be done inparallel with the strip assembly at ITEP. The goal is to assemble 75 strips per day, which willallow us to complete the mass production within one year. Four technicians at ITEP will glue
the fibers into the grooves and two more technicians will glue the strips into the segments. The
other operations, such as cutting the fiber, mirroring the fiber ends, etc., will require one more
technician. The shipment of the strips into KEK in four batches will allow an early start of
the assembly work at KEK. Assembly of two quadrants per day seems feasible, for which three
persons are required. In this case, the assembly of the complete system at KEK will require halfa year.
341

CHAPTER 10. KL0 AND µ DETECTION (KLM)

10.5.9Physics performance

To estimate the muon reconstruction efficiency, the charged-hadron fake rate, the KL0 meson
reconstruction efficiency, and the fake-KL0 veto efficiency, we perform a Monte Carlo detector
study. To estimate the backgrounds, we extrapolate the neutron background rate measurementwith the scintillator test module as well as the Belle data collected with random triggers.
10.5.9.1

Monte Carlo simulation

The endcap geometry is modelled within the Geant4 package. The energy deposition of signal
hits in each strip is simulated by Geant4. The SiPM response to a given energy deposition issimulated using the empirical functions obtained from our test measurements. The arrival time ofthe signal to the SiPM is smeared according to the measured time resolution of the detector. We
assume that the multiple hits at the same strip are correctly resolved by the readout electronics
if their arrival time difference is greater than 10 ns; otherwise, they are merged into one hit. The
hit information is stored if its amplitude exceeds the threshold of 7.5 p.e..
The background induced by neutrons is simulated by adding the random hits to the events.
The energy spectrum and rate of the hits from background neutrons are estimated from thedirect background measurements in the KEKB tunnel using scintillator KLM test module(Sect. 10.5.5). The background hits are distributed uniformly in time while their spatial distribution is tuned to match that of the Belle random-trigger data. We use the same procedure to
digitize the background hits and the signal ones.
10.5.9.2

Hits reconstruction

The raw-hit reconstruction procedure is similar to that used in the Belle reconstruction software.
We exploit the better time resolution that can be achieved with new electronics and DAQ.
Neighboring hit strips in the same plane with time difference of 10 ns or less are grouped toform a 1D hit whose geometric coordinate is defined as the equal-weighted mean of the grouped
strips. In principle, the SiPM amplitude could be used for the weighting factor to improve theposition resolution. The crossing of 1D hits in the orthogonal planes of one superlayer form a
2D hit with x and y coordinates inherited from the 1D hits, a z coordinate located between
the two scintillator planes, and a time that averages the two 1D times after correction for the
propagation delay in the WLS fiber.
10.5.9.3

Muon identification

The granularity of the detector is not changed, while the expected efficiency of the scintillatorbased detector is slightly higher the the RPC-based detector, so we expect that the muon
identification performance should be similar or slightly better in our design. The detailed study
requires modification of the reconstruction programs and will be done later.
10.5.9.4

KL0 reconstruction

The KL0 clusters are reconstructed as a group of 2D hits within a cone of 5◦ half-angle relative
to the IP that are compatible in time with having been produced by a single nuclear shower.
As in the RPC-based algorithm, we require 2D hits in two or more superlayers. The time of thecluster is defined as the average of the times of its individual 2D hits, projected to the innermost
superlayer with a hit. The efficiency of finding a KL0 cluster in the standalone KLM (where the
ECL is ignored) is shown in Fig. 10.27 a) as a function of KL0 momentum.
342

CHAPTER 10. KL0 AND µ DETECTION (KLM)

1

0.08
b)

a)

arbitrary units

0.8

0.5
c)

0.4

0.06

0.6

σp/p

efficiency

GeV/c

We measure the KL0 angular resolution by comparing the angle between the true KL0 momentum
and the direction of the reconstructed KL0 cluster [Fig. 10.27(b)]. The angular resolution isfound to be ∼ 10 mrad in the wide-momentum region, which is approximately the same as in
the present framework.
We could also take advantage of the good scintillator time resolution to determine the KL0momentum using a time-of-flight determination, at least for medium-momentum kaons. The
obtained momentum resolution as a function of the KL0 momentum is shown in Fig. 10.27(c).
We observe that the time measurement provides useful information for kaons with momenta up
to 1.5 GeV/c.

0.04

0.4
0.2

0.02

0

0

0

0.5

1

p(KL)

1.5

2

GeV/c

0.3
0.2
0.1

0

0.02

0.04

σ(φ)

0.06

0.08

0.1

rad

0

0

0.5

p(KL)

1

Figure 10.27: KL0 reconstruction: a) efficiency; b) angular resolution; c) momentum resolution.
The main source of KL0 fake candidates is the accidental coincidence of 1D hits induced byneutrons. After SiPM irradiation, some small contribution to fake candidates comes from theincreased SiPM noise. We find < 0.01 fake KL0 candidates per event at the designed luminosity.
Based on the simulation, we conclude that the proposed detector provides better performancefor KL0 reconstruction than the RPC-based one in Belle.

10.5.10

Cost estimate

A cost estimate for the option with Vladimir strips and Hamamatsu SiPMs is presented inTable 10.3.

343

GeV/c

CHAPTER 10. KL0 AND µ DETECTION (KLM)

Table 10.3: Cost estimate for the scintillator KLM with Hamamatsu SiPM readout.
Strips9500kg285k$
WLS fibers
34km
136k$
Optical gel
400kg
28k$
Epoxy Bicron BC600
50kg
15k$
Silver paint
20kg
2k$
Glue
400kg
8k$
Machinery for gluing
30k$
SiPM
#17000340k$
SiPM housing#1700012k$
Preamplifier#1700034k$
Power supplies
70k$
Cables80km
50k$
Readout board
#1100
110k$
Labour (strips)
200k$
Transportation
80k$
Mechanical structure
40k$
Labour (structure & mounting)
50k$
Total
1490k$

344

References[1] A. Abashian et al.,9002(99)01383-2.

Nucl. Instrum. Meth. A 449, 112 (2000),

DOI: 10.1016/S0168-[2] A. Abashian et al.,9002(01)02013-7.

Nucl. Instrum. Meth. A 479, 117 (2002),

DOI: 10.1016/S0168-[3] K. Abe, RPC and Muon Detection at BELLE, talk given at Belle-BaBar Workshop;
February 14-16, 2002, Vancouver, Canada, 2002.
[4] A. Abashian et al.,9002(02)01164-6.

Nucl. Instrum. Meth. A 491, 69 (2002),

DOI: 10.1016/S0168-[5] GEANT4, S. Agostinelli et al., Nucl. Instrum. Meth. A506, 250 (2003), 10.1016/S01689002(03)01368-8.
[6] S. Hashimoto, (ed. ) et al., KEK-REPORT-2004-4.
[7] MINOS, I. Ambats et al., NUMI-L-337.
[8] R. Acquafredda et al., Journal of Instrumentation 4, P04018 (2009).
[9] Y. Kudenko, Nucl. Instrum. Meth. A 598, 289 (2009), Instrumentation for Collding Beam
Physics - Proceedings of the 10th International Conference on Instrumentation for Colliding
Beam Physics, DOI: 10.1016/j.nima.2008.08.029.
[10] A. Akindinov, A. Martemianov, P. Polozov, V. Golovin, and E. Grigoriev, Nucl. Instrum.
Meth. A 387, 231 (1997), New Developments in Photodetection, DOI: 10.1016/S01689002(96)01201-6.
[11] G. Bondarenko et al., Nuclear Physics B - Proceedings Supplements 61, 347 (1998),
Proceedings of the Fifth International Conference on Advanced Technology and Particle
Physics, DOI: 10.1016/S0920-5632(97)00585-9.
[12] G. Bondarenko et al., Nucl. Instrum. Meth. A 442, 187 (2000), DOI: 10.1016/S01689002(99)01219-X.
[13] Z. Y. Sadygov et al., Nucl. Instrum. Meth. A 504, 301 (2003), Proceedings of the 3rdInternational Conference on New Developments in Photodetection, DOI: 10.1016/S01689002(03)00783-6.
[14] M. Danilov, Nucl. Instrum. Meth. A 581, 451 (2007), VCI 2007 - Proceedings of the 11th
International Vienna Conference on Instrumentation, DOI: 10.1016/j.nima.2007.08.025.

345

REFERENCES[15] V. Andreev et al.,Nucl.
10.1016/j.nima.2004.12.002.

Instrum. Meth.

A

540,

368

(2005),

DOI:[16] F. Sefkow, PoS PD07, 003 (2007).
[17] A. Zoccoli, Nucl. Instrum. Meth. A 446, 246 (2000), DOI: 10.1016/S0168-9002(00)00070-X.
[18] T2K, A. Ferrero, AIP Conf. Proc. 1189, 77 (2009), 10.1063/1.3274192.

346

Chapter 11

Detector Solenoid and Iron Structure
11.1

Iron Yoke

The iron structure of the Belle detector (Table 11.1) serves as the return path for the solenoid’s
magnetic flux and an absorber for the KLM. It also provides the overall support for all of thedetector components. It consists of a fixed barrel part (Fig. 11.1) and movable end-cap parts(Fig. 11.2), both on a base stand. The barrel part consists of eight KLM blocks and 200-mm
thick flux-return plates surrounding the outermost layers of of the KLM blocks. Neighboring
KLM blocks are joined using fitting blocks. Each end-cap part can be retracted for access tothe inner detectors.
The weight of the iron yoke is 608 and 524 (= 262 × 2) tonnes for the barrel yoke and end-cap
yokes, respectively.
The precision of the construction was confirmed to be ±0.3 mm to ±0.5 mm for the machinedparts and ±1 mm to ±2 mm for the assembly of the octagonal blocks. The final inner diameters of
the octagon in which most of the sub detectors are installed were measured to be ±4.5 mm fromthe design value. The location of the structure with respect to the accelerator was confirmed inplace within ±0.5 mm with the telescope survey’s 0.2 mm precision.
The guideline of the mechanical design against earthquakes was established to follow the reported
seismic wave in the Miyagi-ken oki earthquake (M 7.4) on June 12, 1978. From the analysis, theequivalent maximal horizontal static force was defined to be 0.3G, which should be applied all
the mechanical tolerance evaluation.

11.2

Solenoid Magnet

A superconducting solenoid provides a magnetic field of 1.5 T in a cylindrical volume 3.4 m indiameter and 4.4 m in length [1]. The coil is surrounded by a multi-layer structure consisting ofiron plates and calorimeters, which is integrated into a magnetic return circuit. The main coilparameters are summarized in Table 11.2. The overall structure of the cryostat and a schematic
drawing of the coil cross section are shown in Fig. 11.3.
For the last ten years, the power supply that had been used in the TRISTAN-era TOPAZ
experiment was used also for the Belle solenoid. In 2009, it was replaced with a new unit.
Although the performance of the output power is same (5000 A/15 V), the ripple of the current
is halved to 150 mV p-p and the stability is improved by an order of magnitude, from 1.8 × 10−4
to 1.5 × 10−5 .

347

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

Table 11.1: Main parameters of the iron structure.
Items
Belle Iron Yoke
HeightBeam level
Total Weight
Barrel yoke
ShapesMaterial
HeightWidth
LengthTotal Weight
Number of iron plates
Thickness of iron plate
Thickness of gap
End Yoke
Material
HeightWidth
Length in beam direction
Total Weight
Number of iron plates
Thickness of iron plate
Thickness of gap

11.3

Parameters9.57 m5.72 m11740 kNoctagonal
S10C iron
7.7 m
7.7 m
4.4 m
6240 kN
15
47 mm
44 mm
S10C iron
7.7 m
7.7 m
1321 mm5254 kN
15
47 mm
44 mm

Cryogenic System

The fundamental flow diagram for the Belle II cryogenic system is shown in Fig. 11.4. Mostof the hardware, such as the compressor, the refrigerator and the sub-cooler, will be reused,since the heat load of the solenoid is the same as in Belle. From the viewpoint of efficiency, theoperating conditions should be improved as follows. In the normal mode, 120 W of heater poweris supplied steadily into the liquid helium buffer tank in the sub-cooler to offset redundant coolingpower. Since the COP (Coefficient of Performance) is 0.01, if the heater power can be reducedby 90 W, the overall power would be reduced by 90 kW, corresponding to almost 1 MY/monthof cost reducttion, given the cost of electricity. A power-saving operation has been developed for
the J-PARC neutrino cryogenic system [2], and a similar improved cryogenic operation should
be possible in Belle II.
11.3.0.1

Control and Interlock

Except for the power supply and monitor of the magnet, all the control of the cryogenic systemare established by the Distributed Control System by Hitachi Ltd. All the sequence control
was specially programed for the Belle solenoid operation and operated thru the terminal in the
Nikko cryogenics control room.
The normal operation sequence consists of the following 11 modes: initialization of valve condi348

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

7700

7070

4440

Figure 11.1: Barrel part of the iron yoke.

tion, start of compressor, gas circulation and charge, circulating purification, solenoid pre-cooling
1, start of turbine, solenoid pre-cooling 2, normal cooling operation, stop of turbine and liquid
withdrawal, raising system temperature, and system shutdown. There are several recovery
sequences defined for solenoid quench, abnormal stop of compressor, and abnormal status in
turbine to protect the equipment from possible damage. Another sequence is defined for theperiod while raising the current in the solenoid magnet to control the flow of liquid helium atthe current lead.
Since the system clock is 1 Hz—much slower than the response necessary for the quench
protection—another interlock system works independently inside the power supply to shut down
and dump the current flowing in the solenoid coil when a quench is detected.
11.3.0.2

Old components to be maintained

As mentioned for the power supply, there are several existing components that will be replaced,
overhauled, or maintained. They are summarized in Table 11.3
A field map of 100,000 points was made over a period of one month [3]. Figure 11.5 shows acontour plot of the field measured inside the tracking volume for the nominal magnet settings.
The field strength is shown in Fig. 11.6 as a function of z for various radii. The tracking
performance was evaluated from the reconstructed J/ψ mass peak in B meson decays. The fitted
value of the peak mass was 3.089 GeV/c2 , compared with the accepted value of 3.0969 GeV/c2 .
Thus, the uncertainty in the absolute calibration of the present measurement is estimated to beapproximately 0.25%.

349

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

Table 11.2: Main parameters of the solenoid coil.
Items
CryostatRadius: outer/innerCentral field
Total weight
Effective cold mass
LengthCoil
Effective radius
LengthConductor dimensions
Superconductor
Stabilizer
Nominal current
InductanceStored energy
Typical charging time
Liquid helium cryogenics
Cool down time
Quench recovery time

Parameters2.00 m/1.70 m
1.5 T
23 t
∼6t
4.41 m
1.8 m
3.92 m3 × 33 mm2
NbTi/Cu
99.99 % aluminum
4400 A
3.6 H
35 MJ
0.5 h
Forced flow two-phase≤ 6 days≤ 1 day

Table 11.3: Major components of the cryogenic system.
Items
Power supply
Cryogenics control system
Turbine for refrigerator
Control unit for Turbine
Chiller for Turbine
Compressor
Chiller for compressor
Evacuation unit for refrigerator
Evacuation unit for solenoid cryostat
Liq N2 tubing of radiation shield
Automated valves
Transducers/sensors
Data loggers

Statusreplacedneeds replacement
needs overhaul
replacement purchased
replacement purchased
needs overhaul
needs replacement
replacement purchased
needs overhaul
needs examinationneed replacement
need replacement/adjustment
need replacement350

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

㻝㻞㻡㻜
㻞㻝㻞㻜

㻞㻡㻟㻡

㻟㻢㻣㻡

㻟㻡㻟㻡

㻝㻜㻜㻜

㻣㻜㻣㻜

㻢㻜㻜

㻟㻡㻟㻡

㻣㻡㻜

㻣㻟㻣㻜

㻢㻜㻜

㻞㻜㻥㻜

㻞㻡㻜㻜

㻞㻜㻥㻜

㻡㻜

㻠㻡㻡

㻤㻢㻢

㻟㻡㻞

㻝㻟㻞㻝㻚㻡

Figure 11.2: The iron endyoke.

11.4

Possible rotation of the Belle II structure

There is a possibility that SuperKEKB will require a dramatic change in the configuration of
the IR with respect to the Belle solenoid axis. In the KEKB IR, the axis is aligned along the
LER direction, which is tilted by 22 mrad from the KEKB tunnel axis, as shown in Fig. 11.7.
In the new configuration, the entire 1500 ton Belle II structure might be aligned to the medianline of the LER and HER directions. This will be accomplished by rotating the structure by
several tens of milli-radians, as shown in Fig. 11.8. From the technical point of view, the rotation
could be made at the floor level with special hydraulic jacks and rollers to be inserted under theplatform on which the structure is mounted, as depicted in Fig. 11.9. The final decision will bemade during the optimization of the accelerator design.

351

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

Service port

Cooling Tube

Chimney

15

Support Cylinder

1

33

Superconductor
with Al Stabilizer

Cryostat
Pure Al strip(a) Outlook of the magnet

3(b) Cross sectional view of the coilFigure 11.3: Perspective view of the solenoid and cross sectional view of the coil.

Figure 11.4: Flow diagram of the cryogenic system.

352

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

0 .02 Tesla/ liner(mm)1 .5 28 00
1 .5 Tesla

1 .4 81 .5

7 00

1 .5 46 00

5 00

1 .5 6

1 .4 8
1 .5

1 .5 8
1 .4 64 00

1 .6
1 .4 4

3 00

1 .4 2

2 00

QCS-L

QCS-R

1 00

-5 00

0

5 00

1 00 01 50 0z(mm)Figure 11.5: Contour plot of the magnetic field measured in the Belle coordinate system withthe origin at the interaction point.

353

Bz (KGauss)

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

16
15.5
15
14.5
14
13.5

r = 0 cm13

r = 50 cm

12.5

r = 80 cm

12

Br (KGauss)

11.5
1
11
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1

-750

-500

-250

0

250

500

750

1000 1250 1500

Figure 11.6: Field strength (top: axial component; bottom: radial component) as a function ofz for r = 0, 50, and 80 cm.

354

17.476
mrad

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTURE

040m

Figure 11.7: Plan view of the IR and Tsukuba experimental hall.

㻠㻜㻠㻜
㻟㻠㻜㻜
㻞㻡㻢㻜 㻝㻠㻤㻜㻢㻥㻠㻞㻚㻣

㻢㻤㻠㻜㻢㻣㻢㻟㻚㻤㻝㻝㻡㻚㻥㻢㻤㻚㻥㻝㻣㻢㻚㻞 㻡㻢㻜

㻢㻤㻠㻜
㻡㻥㻝㻚㻝
㻢㻢㻜

㻞㻝㻤㻚㻣

㻟㻤㻢㻜㻚㻤
㻟㻠㻜㻜㻞㻟㻤㻝㻚㻟

㻜㻚㻜㻜㻥 㼞㼍㼐㻜㻚㻜㻝㻣 㼞㼍㼐

㻣㻜㻣㻜

㻣㻡㻠㻞

㻠㻞㻝㻢㻚㻡
㻟㻠㻜㻜
㻞㻡㻞㻣

㻝㻟㻢㻤㻜

㻠㻜㻠㻜
㻟㻠㻜㻜
㻝㻢㻥㻜 㻞㻟㻡㻜

Figure 11.8: Comparison of the present and rotated detector placement.

355

CHAPTER 11. DETECTOR SOLENOID AND IRON STRUCTUREKEKB Beam level

Belle Endyoke

Belle Platform

Roller system
to be replaced

Figure 11.9: Detector support structures356

References[1] Y. Makida et al., Development of superconducting solenoid magnet system for the B-factory
detector (BELLE), in ADVANCES IN CRYOGENIC ENGINEERING, VOL 43 PTS A
AND B, edited by Kittel, P, , ADVANCES IN CRYOGENIC ENGINEERING Vol. 43, pp.
221–228, 233 SPRING ST, NEW YORK, NY 10013 USA, 1998, PLENUM PRESS DIVPLENUM PUBLISHING CORP, Joint Cryogenic Engineering / International Cryogenic
Materials Conference, PORTLAND, OR, 1997.
[2] T. Ogitsu et al., IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY 15,
1175 (2005), 2004 Applied Superconductivity Conference, Jacksonville, FL, OCT 03-08,
2004, 10.1109/TASC.2005.849525.
[3] N. Tan et al., IEEE TRANSACTIONS ON NUCLEAR SCIENCE 48, 900 (2001).

357

Chapter 12

Trigger
The total cross sections and trigger rates at the goal luminosity of 8 × 1035 cm−2 s−1 for several
physical processes of interest are listed in Table 12.1. Samples of Bhabha and γγ events will be
used to measure the luminosity and to calibrate the detector responses. Since the Bhabha andγγ cross sections are very large, these triggers are pre-scaled by a factor of 100 or more; this isstraightforward due to their distinct signatures.
Physics process
Υ(4S) → B B̄Hadron production from continuumµ+ µ−τ +τ −
Bhabha (θlab ≥ 17◦ )γγ (θlab ≥ 17◦ )2γ processes (θlab ≥ 17◦ , pt ≥ 0.1 GeV/c)
Total(a) rate is pre-scaled by a factor of 1/100

Cross section (nb)
1.2
2.8
0.8
0.8
44
2.4
∼ 80
∼ 130

Rate (Hz)
960
2200
640
640
350 (a)19 (a)∼ 15000∼ 20000

Table 12.1: Total cross section and trigger rates with L = 8 × 1035 cm−2 s−1 from various physics
processes at Υ(4S).

The requirements for the trigger system are
0. high efficiency for hadronic events from Υ(4S) → B B̄ and from continuum;
1. a maximum average trigger rate of 30 kHz;
2. a fixed latency of about 5 µs;
3. a timing precision of less than 10 ns;
4. a minimum two-event separation of 200 ns; and5. a trigger configuration that is flexible and robust.
358

CHAPTER 12. TRIGGER

To meet these requirements, we adopt the Belle triggering scheme [1] with new technologies.
In the Belle triggering scheme, the trigger system consists of sub-trigger systems and one finaldecision logic. A sub-trigger system summarizes trigger information on its sub-system, and sends
it to the final-decision logic, which then makes combinations of sub-triggers and issues a trigger
when its criteria are satisfied. This was quite successful in the Belle experiment to achieve highefficiency for hadronic events. In Belle II, we use this concept but replace all components andconnections with new technologies. Each component has a Field Programmable Gate Array(FPGA) so that the trigger logic is configurable rather than hard-wired. All data flow alonghigh speed serial links, not parallel (ribbon) cables, which enables us to funnel a huge amountof information—the equivalent of O(1000) channels—to one FPGA.
The schematic overview of the Belle II trigger system is shown in Fig. 12.1. The CDC subtrigger provides the charged track information (momentum, position, charge, multiplicity, andso on). The ECL sub-trigger gives energy deposit information, energy cluster information,
Bhabha identification, and cosmic-ray identification. The Barrel PID (BPID) sub-trigger gives
precise timing and hit topology information. The Endcap PID (EPID) sub-trigger is expected
to give precise timing information.1 The KLM sub-trigger gives muon track information. The
Global Decision Logic (GDL) receives all of this sub-trigger information and makes the final
decision. A positive decision is sent to SEQ as a trigger signal. The total latency in the trigger
system is about 5 µs.2 To achieve high efficiency for hadronic events, we use two independent
sub-triggers: CDC and ECL.
In Belle II, the background condition is expected to be worse than in Belle due to the higher
instantaneous luminosity and the beams’ smaller transverse dimensions. In addition, from Belle’s
experience, we expect much worse background condition at the beginning of the accelerator
operation when the vacuum condition and other accelerator parameters are not yet optimal. To
satisfy the trigger system’s requirements in the face of such backgrounds, it is important to haveseveral independent, effective trigger strategies to reduce the Level 1 trigger rate. In this way,
we can tune the collection of triggers to minimize the deadtime of the data acquisition operation
without sacrificing our efficiency for recording events of physics interest. These strategies aredescribed in the following sections.

12.1

CDC 2D Trigger

The CDC sub-trigger (Fig. 12.2) finds and characterizes the charged tracks detected by the drift
chamber. Because of the limited solid angle coverage of the CDC, this sub-trigger is not sensitive
to charged tracks in the far forward or backward regions. In the present design, we measure pt ,λ, dz , φ, and the charge of tracks. The CDC sub-trigger should be sensitive only to the charged
tracks coming from the vicinity of the interaction point (|dz | . 4 cm and |dr | . 4 cm.).

12.1.1

CDC Trigger Front-end

Discriminated signals from each of 48 CDC wires are generated in the front-end board in eachpulse of the 1 GHz clock. These precise wire-hit signals are down-sampled by a 62.5 MHz clock.
A one-bit hit state of the 48 wires on this board is sent to the multiplexer (Fig. 12.3) by thehigh speed serial links, whose data transfer capacity is 12.5 (3.125 × 4) Gbps. The actual data
rate is 3 Gbps. The multiplexer can receives four sets of such serial links. Each line in Fig. 12.3
1
2

This is under discussion.
The precise value of the latency is not yet decided.

359

CHAPTER 12. TRIGGER

CDC〜2000 TSF bits

TSF
r-φ(2D) Track

Track Count
Opening Angle
Back-to-back

3D Track〜2000 TC bits

4x4 Trigger Cell
Cluster

Cluster Count
TimingEnergy Sum

High Threshold
Low Threshold
BhabhaBPID〜100 hit bits

Hit
Multiplicity
Topology

Global Decision Logic

ECL

L1 Trigger

Fine Timing

EPID

Hit

KLM

μ hit

〜100 hit bits

ForwardBackward
Barrel3D Muon Track

New in Belle II〜5μsec after beam crossing

Figure 12.1: Schematic overview of the trigger system. The output from the five sub-trigger
systems are sent to the Global Decision Logic (GDL). The final trigger decision is made in the
GDL. The lines in red are newly added information paths in the Belle II trigger system.

360

CHAPTER 12. TRIGGER

CDC Front-end

Track Segment Finder(TSF)

2D TRK Finding

2D TRK Fitting

3D TRK Finding

3D TRK Fitting

GDL
Figure 12.2: Logical overview of the CDC sub-trigger system.
corresponds to a superlayer in the CDC. There are three to six multiplexers per superlayer,
depending on the number of sense wires.

12.1.2

Track Segment Finder

The merged wire hit information by the multiplexer is sent to the next stage, the Track Segment
Finder (TSF). The TSF is realized using one Universal Trigger Board (UT3) per CDC superlayer,with nine such boards in total.
In each TSF, the geometric regions for Track Segments (TS) are defined (Fig. 12.4). The numberof TS in a superlayer depends on the number of wires in a single wire layer. Each TS overlaps
the neighboring TS except for the innermost cell of the innermost TS or for the center cell forother TS. There are 2336 TS in total. At each tick of the 62.5 MHz clock, the pattern of wire
hits in each TS is examined. The hit patterns expected for a charged track are predefined andstored in a memory. By the memory look-up method, the presence of a TS hit is determined.
The TS hit information (2336 bits total) is sent to the 2D Track Finding stage (Fig. 12.2) ateach clock tick.

12.1.3

2D Track Finding

In the 2D track finding stage, we use a conformal transformation and Hough transformation [2]to search for charged tracks. The schematic image of the conformal transformation is shown in
Fig. 12.5. A point (x, y) in the plane transverse to the CDC’s axial wires is transformed into
(X, Y ) in the conformal plane using the following equations.

361

CHAPTER 12. TRIGGER

System Clock : 125MHz
One optical link : 40(10x4) Gbps
CDC S. Layer 0

160 x 6 wires= 20 x 48

Multiplexer
384
(x3)

Multiplexer
384
(x3)

960 ch3

200 Gbps

Multiplexer
384
(x3)

3

120 Gbps

Multiplexer
384
(x4)

1152 ch3

144 Gbps

Multiplexer
384
(x4)

1344 ch4

168 Gbps

Multiplexer
384
(x5)

1536 ch4

192 Gbps

Multiplexer
384
(x5)

1728 ch5

216 Gbps

Multiplexer
384
(x6)

1920 ch5

240 Gbps

Multiplexer
384
(x6)

UT3
Board

3D Track Finder

160 ch
5 Gbps

12

UT3
Board

2336 ch73 Gbps

UT3
Board
(x6)

CDC Trigger Output
3D tracks

192 ch
6 GbpsUT3
Board

224 ch
7 GbpsUT3
Board

256 ch
8 GbpsUT3
Board

288 ch
9 GbpsUT3
Board

320 ch2

10 Gbps2

352 ch2

11 Gbps2

384 ch2

12 Gbps2

TSF Layer 72112 ch6

264 Gbps

CDC S. Layer 8

384 x 6 wires= 48 x 48

CDC Trigger Output
All TSF
2D tracks

TSF Layer 6

CDC S. Layer 7

352 x 6 wires= 44 x 48

12+1

TSF Layer 5

CDC S. Layer 6

320 x 6 wires= 40 x 48

73 Gbps

UT3
Board

TSF Layer 4

CDC S. Layer 5

288 x 6 wires= 36 x 48

5 Gbps

2336 chTSF Layer 3

CDC S. Layer 4

256 x 6 wires= 32 x 48

12160 chTSF Layer 2

CDC S. Layer 3

224 x 6 wires= 28 x 48

UT3
Board

TSF Layer 1
960 ch

CDC S. Layer 2

192 x 6 wires= 24 x 48

2D Track Finder

TSF Layer 0

CDC S. Layer 1

160 x 6 wires= 20 x 48

System Clock : 31.25 MHz
One optical link : 10 Gbps

UT3
Board

TSF Layer 82304 ch480 Gbps

6

UT3
Board

CDC Trigger Flow 1.07

Figure 12.3: Hardware configuration of the CDC sub-trigger system. The data flows from left
to right. The CDC front-end is omitted here.

362

CHAPTER 12. TRIGGER

Inner TSF

Outer TSF

Figure 12.4: The geometric shape of a track segment (TS). Each square corresponds to a wire
cell in the CDC (the sense wire being at the center of the square); the IP is downward. Left: a
TS for the innermost superlayer. Right: a TS for other superlayers.

X=

2xand Y =

x2 + y 2α2yx2 + y 2.

(12.1)

α(a) real plane(b) conformal plane

Figure 12.5: Schematic view of the conformal transformation: (a) in CDC transverse plane, (b)in the conformal plane.

RΦ

Figure 12.6: The distance R and angle Φ of the point of closest approach to the origin of astraight line in the conformal plane.
In this transformation, the angle α of point (x, y) on the arc (Fig. 12.5) relative to the CDC
origin is preserved. An arc of a circle passing through the CDC origin is transformed into a363

CHAPTER 12. TRIGGER

straight line segment in the conformal plane. This line segment is parametrized by the quantities
R and Φ (Fig. 12.6); these are related to the arc’s radius and center via
r

B2
=
R =
2
A +1
b
1
tan Φ = − = .
A
a

r

1
a 2 + b21
= ,r

(12.2)(12.3)The polar equation of the straight line though the point (X, Y ) in the conformal plane is
R = X cos Φ + Y sin Φ.

(12.4)The plane with (R, Φ) on orthogonal axes is called the Hough plane. A single point in theconformal plane has an infinite number of straight lines through it and, therefore, an infinite
number of curves through it in the Hough plane. However, a collection of points (Xi , Yi ) thatlie on a straight line in the conformal plane are mapped by Eq. 12.4 to curves that pass througha common point (R, Φ) in the Hough plane. We therefore obtain a solution of the straight linein the conformal plane as the intersection point of the curves in the Hough plane.
We performed r − φ fits to track hits in the Belle II CDC configuration using the tsim-cdc
package. This package provides the drift-time integrated TS hits based on a Geant4 simulationof the track in the CDC. The tsim-cdc package assumes 100% hit efficiency. The tsim-cdc
algorithm is coded in c++ with normal float-pointing precision; the Hough-finding minimization
is based on the linear regression method.
An event display of a simulated event with a µ− µ− like-charge pair is shown in Fig. 12.7. The
upper left figure shows the TS hits in the CDC’s transverse plane, with two curved tracks passing
through the interaction point (0, 0). These TS hits are then transformed into two distinct straightlines in the conformal plane and, finally, into the family of curves in the Hough plane (one curve
per TS hit). The two intersections of these Hough-plane curves, at R ≃ 0.015 and Φ ≃ 1.9, 5.1,
represent the solutions of the reconstructed tracks.
The distribution of reconstructed transverse momenta for single-muon events is shown in Fig. 12.8;
each muon was generated with pt = 0.5 GeV/c. There is no apparent bias observed in the fit tothis distribution. We also fitted single-muon samples with other input pt values and found no
obvious bias in the fits. However, as expected, the fitted pt resolution rises with pt .

12.2

CDC 3D Trigger

We describe here a possible implementation of a three-dimensional (3D) CDC track trigger
system, based on the measurement of the axial coordinate of a track at its closest approach tothe interaction point (IP). This coordinate, labelled z0 , lies near the IP for a track originatingfrom an e+ e− collision but is not localized for a track associated with any background process.
Figure 12.9 shows the z0 distribution from real data recorded with a random trigger by the
Belle experiment. From various simulation studies and our accumulated understanding of the
background near the IP, we are confident that the peak at z0 = 0 cm is associated with e+ e−
collisions while the broad distribution at other values of z0 corresponds to beam-gas and beamwall backgrounds.
Note that Fig. 12.9 reflects the physics-to-background distribution after ten years of KEKB
operation; the background condition was much worse in the first year. Therefore, during the364

CHAPTER 12. TRIGGER

Figure 12.7: An event display of the 2D track finding stage for a simulated µ− µ− event. Upper
left: TS axial hits (dots) in the r-φ plane in the CDC; the horizontal (vertical) axis is x (y).
Upper right: the corresponding TS axial hits (dots) in the conformal plane; the horizontal(vertical) axis is X (Y ). Bottom: the corresponding TS axial hits (pixellated curves) in the
Hough plane; the horizontal (vertical) axis is R (Φ).
early stages of Belle II, an efficient rejection of beam-gas and beam-wall backgrounds will provequite valuable in maintaining high physics performance with minimal deadtime. This can bedone if z0 information for each track is available within the global Level 1 trigger latency of∼ 5 µs. After accounting for the latencies associated with the TSF and GDL, only ∼ 2 µs is
available to calculate z0 . This is beyond the capability of conventional CPUs, so our design uses
FPGAs for z0 reconstruction.
This type of computation has been proven to work since 2004 in the BaBar experiment [3].
They use the TS information from their drift chamber’s stereo wires to calculate z0 for eachtrack candidate. Their computation is done purely within an FPGA, running at 120 MHz forthe core part of the algorithm.
We will implement 3D tracking in the Belle II Level one trigger with a concept based on BaBar’s.
There are substantial differences in implementation due to the fact that the information available
in our TS is somewhat different; we may have to run the FPGA at a higher clock frequency tocarry out the computation within the aforementioned latency.

12.2.1Strategy

The 3D track reconstruction is a two-step process. The first part involves “finding” a track
candidate; the second requires “fitting” the track to get the 3D information of the track underconsideration. We will re-use the 2D track-finding algorithm described in Sec. 12.1. To improve
the fitter performance, we may augment the 2D finder with a fast auxiliary algorithm thatprovides an initial value of the polar angle of the track candidate under consideration. The
overall 3D algorithm structure, including the 2D finder and fitter, is illustrated in Fig. 12.10.
The 3D fitter is itself a two-step process: an r-φ fit followed by an r-z fit.
365

CHAPTER 12. TRIGGER

2 / ndf = 89.77 / 6
Prob

3.378e-17

Constant

500

400

550.3 ± 14.5

Mean

0.5044 ± 0.0003

Sigma

0.01394 ± 0.00019

300

200

100

0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9
1
pT (GeV)Figure 12.8: Transverse momentum distribution from the 2D fit of tracks in single-muon events.
Each muon was generated with pt = 0.5 GeV/c.

delz# of Tracks

Z distribution

Entries

36019

Mean

0.03838

RMS

17.58

1000

800

600

400

200

0
-40

-30

-20

-10

0

10

20

30
40
z0(cm)

Figure 12.9: The offline z0 distribution for random-triggered data in Belle’s experiments #57
and 59. The dominant peak at z0 =0 cm is from e+ e− collisions; the smaller peak at z0 =−10
cm is due to beam collisions with a beamline structure at that location.

12.2.2r-φ fitIn the first step of the 3D fit, the 2D r-φ track fitter provides a list of track candidates, eachwith its own list of TS hits. This duplicates the functionality of the standalone 2D track fitter
described in Sec. 12.1. In this step, one can average two U-V stereo TS hits to form an additional
pseudo-axial TS. According to our studies, using such pseudo-axial TS hits does not change ther-φ fit itself but does improve the z0 resolution in the next step—the r-z fit—by ∼ 5–10%. The
results of the r-φ fit are passed to the r-z fit.

366

CHAPTER 12. TRIGGERTSF information

optional
tan info

2D finder

2D
3D

2D track information for 2D Triggering (+optional tan
n info)Send 2D
triggering (sameas Belle) to GDL

r- fitr-z fit

GDL

Figure 12.10: The track-reconstruction algorithm structure. In the initial stage, the 2D finder
may be supplemented with an algorithm (dashed-boundary arrow) that provides polar angle
information to the fitter.

12.2.3r-z fit

The second step of the 3D fit uses the stereo TS information. A charged track from the IP
appears as a cycloid in the r-z projection; this can be approximated as a straight line for all TS
hits from an energetic track or for the TS hits near the IP from a soft track. For a given stereo
TS with index i,ri tan (φfit − φi ) = zi tan θstereo(12.5)

is satisfied, where ri is the radius, φi is the azimuthal angle, and zi is the axial coordinate of thestereo TS; θstereo is the angle of stereo wire of the stereo TS with respect to axial wires. The
azimuthal angle φfit is provided by the r-φ fit; φfit − φi should be the residual from the stereo
angle effect. We construct a goodness of fit
χ2 =X (zi − z0 − ri cot θ)2
σi2

stereo367(12.6)

CHAPTER 12. TRIGGER

where the free parameters z0 and θ represent the axial coordinate (nearest the IP) and the polar
angle, respectively, of the track candidate. The “uncertainty” σi is defined asσi =ri × stan θstereo(12.7)

where s is an arbitrary scale factor. By minimizing this χ2 , the r-z fit is performed in the r-z
plane using the straight-line approximation to the cycloid. Note that the resolution of the fitted
z0 depends on the precision of φi measurement, according to Eq. 12.5.
The distribution of fitted z0 values for a sample of single-muon events (generated at the origin
with pt = 0.5 GeV/c and a range of polar angles) is shown in Fig. 12.11. The Gaussian resolutionof this distribution is slightly less than 10 cm and, from our studies using other generated event
samples, is roughly independent of transverse momentum.

2 / ndf = 201.1 / 10

Prob

400
350

9.547e-38

Constant

311.3 ± 10.7

300
250
200

Mean

0.3789 ± 0.2289

Sigma

9.309 ± 0.250

150
100
50
0
-100

-80

-60

-40

-20

0

20

40

60

80

100

Figure 12.11: The z0 distribution (in cm) of the r-z fit to the track in single-muon events.

12.2.4

Possible improvements

Comparing with Fig. 12.9, the z0 resolution of ∼ 10 cm is about twice the desired value needed todiscriminate IP-originating tracks from backgrounds. It is clear that improvements are needed
for this 3D track trigger to be effective. Three areas of investigation are presented below.
12.2.4.1

TS information

The Belle II TSF sends a single bit per TS, stating whether it has fired or not. On the other
hand, the BaBar TSF sends the estimated φ location as well as its error, representing the possible
range of φ for the TS [4]. To implement something similar, the Belle II TSF firmware must be
altered. Before doing so, we will investigate the degree of improvement in the z0 resolution using
the tsim-cdc simulation.
12.2.4.2

Geometry of stereo superlayers

The Belle II CDC superlayers are configured as AUAVAUAVA from the inner radius outward, witha total of 5 axial and 4 stereo superlayers. The BaBar configuration is AUVAUVAUVA, with a total
368

CHAPTER 12. TRIGGER

of 4 axial and 6 stereo superlayers. BaBar’s drift chamber has 50% more stereo layers, and U-V
superlayers are adjacent. If the Belle II configuration were changed to AUVAUVAUV, to have 3
axial and 6 adjacent stereo layers, the tsim-cdc simulation predicts an improved z0 resolutionof 7.4 cm. Further investigation will clarify whether this improvement is associated with theincreased number of stereo superlayers or to their adjacency, and to model other superlayer
configurations.
12.2.4.3

Usage of DSP chip hardware

So far, our track-fitting studies have been carried out with c++ and floating-point calculations.
We expect that, in implementing the present algorithm into FPGA, the z0 resolution is degradedsomewhat due to integer-only calculations and the usage of look-up tables in some steps. We may
also have to sacrifice precision to fit within the Level 1 trigger’s latency (including TSF and GDL
overhead). We plan to host at least one DSP chip—to permit floating-point calculations—in thenext prototype of the trigger board to avoid the degradation inherent in fixed-point calculationsin the 3D fitter.

12.2.5

Summary

A very rough, qualitative sketch of the 3D fitter algorithm is presented here. We plan toimplement the algorithm in FPGA by the end of the year 2013.

12.3

ECL Trigger

The calorimeter is a very important component to generate fast signals for a fully efficient trigger
for both neutral- and charged-particle oriented physics events. Two trigger schemes are envisaged: a total energy trigger and an isolated-cluster counting trigger. These are complementary:
the former is sensitive to physics events with high electromagnetic energy deposit while the latter is sensitive to multi-hadronic physics events that have low energy clusters and/or minimum
ionizing particles. In addition, the system should identify Bhabha and γγ events, which areneeded to measure the online luminosity; this information is only available from the calorimetersystem.

12.3.1

Trigger scheme

We have ten years’ experience in the operation of the similar Belle calorimeter trigger system [5].
The dominant issue to be considered in Belle II is the increased trigger rate due to the muchhigher luminosity and beam background. We plan to adopt the Flash-ADC (FADC) and FPGA
scheme. The former digitizes a trigger analog signal called the Trigger Cell (TC), formed by
4 × 4 crystals, and the latter determines the amplitude and timing of the TC and performs the
final ECL sub-trigger decision by a firmware algorithm that is easily modifiable. The merits,
compared with the Belle trigger system, are (1) the simplicity of the electronics hardware andsignal cabling and (2) the ease of upgrading in the case of the endcap calorimeter replacement.
At present, three kinds of trigger modules are planned: Fast shaper in the main shaper board;
FADC trigger module (FAM); and Trigger and Monitor module (TMM). The block diagram of
ECL trigger readout electronics system is shown in Fig. 12.12.
The allocated trigger timing latency for the ECL sub-trigger is about 4 µs. Good timing resolution is needed in the endcap region that is not covered by the barrel PID trigger that provides

369

CHAPTER 12. TRIGGER

Figure 12.12: Block diagram of ECL trigger readout electronics system
the most precise trigger timing. The ECL timing latency is less than the requirement, as estimated in Table 12.2, and the timing resolution is expected to be same as in Belle: 20 ns at the1σ level.
To construct the total energy and isolated-cluster triggers, we will prepare 26 final trigger bits,
described in Table 12.3. Other useful trigger bits will be added after trigger simulation (TSIM)
study.
The beam-gas background is expected to be high at early stage of operation, while the otherbackgrounds that scale with beam current or luminosity will grow later. To cope with thisevolution, several tuning knobs are incorporated: (1) TC threshold, (2) total energy threshold,(3) number of isolated clusters, (4) the possibility of excluding a part of endcap from the trigger,and (5) enabling/disabling the cosmic veto. Option (4) will require a detailed trigger simulation
study. We plan to run without the cosmic veto because the machine luminosity is one orderof magnitude higher than KEKB; thus, cosmic events do not harm the DAQ bandwidth, while
enabling the cosmic veto might sacrifice some fraction of interesting low-multiplicity processes
such as initial state radiation (ISR) events, two-photon collisions and tau pair production. On
the other hand, since the cosmic veto can also suppress a part of beam background events, we
may enable it during extreme beam-background conditions.

12.3.2

Trigger electronics

12.3.2.1

Fast shaper

Sixteen fast-shaping signals from individual crystals, with a shaping time of 200 ns, are mergedin the fast shaper circuit. This is implemented on the main shaper board to form an analog
trigger sum called the trigger cell (TC). This reduction in the number of signals reduces thetrigger timing latency and suppresses coherent electronics noise in the high beam backgroundenvironment. In the fast shaper, each crystal’s signal is corrected before the merge for the370

CHAPTER 12. TRIGGER

Item
Peaking time of TC
ADC pipeline @ FAM
Peak finding process @ FAM
Programmable delay @ FAM
Gbit transfer( 200 bits)
Optical cable length
Trigger input alignment @ TMM
Stage-1 to stage-2 bit transfer @ TMM
Trigger decision @ TMM
Total latency

Latency (ns)700
100
300–400
300
100
200–300
100
700
200–300
2700–3000

Table 12.2: Estimate of ECL trigger timing latency based on expected performance
Item
Trigger timing (Final, Fwd, Barrel, Bwd)
Total Energy (>0.5, 1.0, 3.0 GeV)
Isolated cluster
Bhabha-type
OR-ed Bhabha
Barrel Bhabha
Prescale Bhabha
Cosmic veto
TC hit pattern
Total

Number of bits
4
3
4
11
1
1
1
1
576
26+576

Table 12.3: Final ECL trigger output to GDL
crystal-to-crystal variation in light yield (for equal-energy incident particles).
WWe have performed a test of the noise level, signal shape, and pulse-gain adjustment on a
prototype of the main shaper, including the fast shaper circuit. Figure 12.13(b) shows the noiselevel of 1.58 channels, equivalent to 10 MeV, for the TC; this is well below the threshold of 100
MeV corresponding to the passage of a minimum-ionizing particle (MIP) through the length ofa crystal. We have confirmed that the fast shaper is almost ready for mass production.
12.3.2.2

FAM

The FAM module determines the pulse height and time at the peak of each TC signal. Each FAM
has 40% pulse gain reduction attenuators, baseline adjustment and anti-aliasing filters in frontof four 12-bit and 100-MHz sampling quad-FADCs (ADS6424). Channel-by-channel digitized
pulse information from the FADC is recorded by digital signal processing logic, implemented
in an FPGA (XC5VLX50T). The FPGA logic finds the pulse’s peak value by examining thesliced pulse values within a 400-ns window that straddles the peak. The pulse-peak value andtime of each TC are recorded in a data buffer memory inside the FPGA. When any pulse
peak out of 12 TC signals is larger than a predetermined (downloaded) threshold, the FAM
371

CHAPTER 12. TRIGGER

Figure 12.13: Measurement of fast shaper characteristics at the cosmic stand. (a) Cosmic rayenergy distribution, where the peak corresponds to a MIP passing through the 30-cm lengthof a crystal. (b) Pedestal distribution of TC. (c) TC analog signal shape by test pulse. (d)Individual-crystal gain adjustment.
aligns the stored records for the 12 TC information to the earliest above-threshold signal, thensends this information (including the 12-bit peak value, the 1-bit discriminator value, and thealigned time value with a 300-ns programmable delay) for all 12 TCs to a TMM module in
the Electronics Hut via an optical link. The trigger timing is determined by the arrival at
the TMM. Figures 12.14 and 12.15 show the block diagram and photograph of FAM prototype
board, respectively. Altogether, 52 FAM modules are needed to cover the 576 TC signals.

Figure 12.14: Block diagram of 6U-VME type FAM prototype board
372

CHAPTER 12. TRIGGER

Figure 12.15: A photograph of 6U-VME type FAM prototype board

12.3.2.3

TMM

The TMM module receives the digitized and time-aligned FAM signals and determines the
final ECL trigger outputs. A two-stage TMM is needed for the 52 FAM inputs because of thelimited front-panel space on each TMM board. Both stages use the same module but havedistinct firmware algorithms on the FPGA. The first-stage module receives 13 FAM signals andgenerates two kinds of output. One output is sent to second-stage module and the other to the
Global Decision Logic (GDL). The module has an FPGA (XC5VLX50T) and performs input
signal alignment based on the external clock provided from the beam-collision clock system.
The TC hit pattern output—the discriminated TC signals—are sent directly to the GDL to be
used for matching with the CDC trigger hit pattern. The single second-stage TMM receives the
TC information from all of the first-stage modules and calculates the final ECL trigger outputs
in its FPGA, then sends this to the GDL. Based on the current design architecture, 4+1 TMM
modules are needed. A pre-prototype of the TMM, shown in Fig. 12.16, has been produced.

12.3.3

Schedule

The fast shaper will be prepared according to main shaper production schedule. Until 2012,we
will perform trigger integration tests with the entire readout electronics chain setup and final
versions of FAM and TMM modules will be ready. Mass-produced modules will be installed by
2013. In parallel with hardware production, the FPGA firmware algorithms of these modules will
be developed in the VHDL hardware description language. To optimize the trigger algorithms,
we will continue our studies with the TSIM simulator package.

12.4

Barrel PID Trigger

The Time-Of-Propagation (TOP) counter that will be used for the barrel PID (Ch. 7) has
an intrinsically good time resolution of under a nanosecond. However sub-100 ps timing is373

CHAPTER 12. TRIGGER

Figure 12.16: A photograph of the 6U-VME TMM pre-prototype board. The final design will
be implemented on a 9U-VME board to accommodate the input/output connectors.
usually only obtained in offline reconstruction, and is more than is needed at the trigger level,
where a couple-ns time resolution for the GDL trigger would help to reduce the data volume
from out-of-time hits in the SVD. An algorithm for determining the event time resolution fromtracks that hit the TOP detector is studied below, based upon a full GEANT4 simulation of
the detector configuration described in Ch. 7. Single-photon hit times are time-encoded using
available programmable logic devices, and the resource requirements are evaluated and shown
to be acceptable.

12.4.1

Trigger Configuration

The readout electronics and integrated trigger functionality are shown for the detector and frontend readout modules in Fig. 12.17. Giga-bit fiber links carry the position and time informationof hit signals from the 16 detector staves to dedicated trigger processing boards in a flow diagram
indicated in the figure.

12.4.2

Trigger Performance Estimates

A preliminary study based on Monte Carlo generated data was used to identify the most effective
detection techniques that could be efficiently implemented in real-time hardware. As seen in
Fig. 12.18, the detected pattern of photons in both space and time depend upon the track impact
position and this information can be used to evaluate the track flight length and determine andevent time.
Statistical estimates of the obtained timing errors are reported, where a comparison was madebetween a system that uses time and space information of detected pixels versus timing only toestimate the trigger timing error. Such a time estimate is computed as follows:
1. For all incoming data, we record the timing difference between the first pixel received andall the others, as well as their spatial position.

374

CHAPTER 12. TRIGGER

16 detector sectors
Combine hits:- time resolution- back-back, mult., etc.

16 logical staves:-16 only for 1-bar case
-2x16 for 2-bar case

Each logical stave
Is 8 fiber links

1x global bPID

“front-end trigger”

2x “combiners”

Focus mirror(sphere, r=5000)
z=1830z=1070Forward

R=1180z=-780

Backward

16x modules

Figure 12.17: Overview of the barrel PID trigger system.

120°

e-

90°

40°

e+

Example PDFs
at 3 GeV/c

Figure 12.18: A graphical representation of the information available to differentiate the time(position) of hits on the barrel PID detector.

375

CHAPTER 12. TRIGGER

Figure 12.19: Estimate of timing errors: use of time and space information.
2. We compute the log-probability of the timing and spatial profile for 10 different positionsof interaction in the bar. For the timing case, this in fact requires computing also—foreach of the 10 positions—the optimal shift of the time PDF with respect to the time of
the first sample; this is equivalent to computing n different log-probabilities and picking
the highest value.
3. For the case in which both space and time information is used, the two log-probabilities
are added and the maximum value is used as an estimate for the position; otherwise, only
the maximum of the 10 log-probability for timing is used.
4. The “shifting” time corresponding to the optimal position is used as an estimate for thetime of interaction.
Experiments were run on 5000-track samples using Probability Distribution Functions computed
on a distinct set of 5000-track events. For this initial study, all tracks are 2.5 GeV/c kaons andincident on the center of the long axis of the 1-bar detector configuration. There should be
minimal difference in the result with respect to pions or higher momentum tracks. Interactions
at the bar extremities will introduce somewhat larger errors, though full reconstruction studies
indicate that the effect should be small. The results follow.
• Figure 12.19: error distribution in case both time and space information is used in the estimate. The two curves correspond to an input time resolution of 2 ns and 1 ns. The average
error is ≈ 0.8 ns and ≈ 0.2 ns, respectively (the estimate being slightly asymmetrical—aconsequence of the asymmetries of the angles). What is more important, the standard
deviation is ≈ 1.9 ns and ≈ 1.7 ns, respectively. Furthermore, the curves are not describedby a single Gaussian due to the long tails, and ≈ 90% of the errors are within ±2 ns and±1 ns, respectively.
• Figure 12.20: in this case the previous 1-ns distribution is compared with the distribution
obtained using the time information only. In this case, the asymmetry is slightly more

376

CHAPTER 12. TRIGGER

Figure 12.20: Estimate of timing errors: use of time information only.

8x60

Queuer/Encoder

LUT1

ADC

9

LUT2

ADC

LUTn

ADC

Queue

ARGMAX[1:n]

9

Figure 12.21: Barrel PID Trigger: Conceptual Block Diagram.
pronounced (≈ 0.25 ns) and the standard deviation higher (≈ 2.1 ns), yet more than 85%of the cases have errors within 1 ns.
These studies support the conclusion that an accurate identification of the interaction time
can be obtained based on the timing information only, thus reducing the trigger algorithm
complexity.

12.4.3

Proposed Trigger Block Diagram

From the block diagram of Fig. 12.21, a succinct description of the behavior of the system is asfollows:
1. The 60 × 8 detector (or a FF-image of it), provides at every clock cycle a sampled view of377

CHAPTER 12. TRIGGER

the arriving photons (if any). This occurs at the detector front-end.
2. A queuer/encoder orders the hits and encodes them to 9 bits of resolution. This operation
is implicitly performed by the communication protocol between the front-end board (thatreceives and packetizes the detector information) and the trigger board. As the communication is time asynchronous due to a random time lag introduced by the protocol, asynchronization is performed to indicate when all hits corresponding to a possible eventare received. This mechanism uses both a timeout (tuned to the average features of thesignals) and information about maximum effective delay between interaction events.
3. A queue models the communication between the two boards. All detector hits are enqueued
by arrival order, and received in order by the trigger board. This guarantees that a signal
with a timestamp older than the previously enqueued signal represents later events, andgenerates a hard decision point to conclude the triggering decision.
4. At the trigger board, a series of n lookup tables (LUTs) select, in parallel, the correctlog(p) corresponding to the position of the pixel for their own PDF.
5. In parallel, these are added and accumulated to existing values.
6. A maximum is computed among all the accumulated sums, and the index of the maximum
returned.
The core of the detection consists of the calculation of the most likely time of interaction basedon the probability distribution of different interaction positions on the quartz bar. As theabsolute time of first interaction is not known, it is necessary to calculate a maximal value ofthe correlation between the received times and the PDFs of each of the 10 positions in which theinteraction position on the bar is quantized. In practice, the first sample received constitutes thereference point for times, while all the successive samples are evaluated in terms of their relative
difference with respect to the first, and compared with the PDFs that correspond to each positionon the bar. The highest value of the highest correlation is used to identify the position, and thedelay with respect to the first reception time. Some of the computation can be performed inparallel: in practice, at least all 10 correlations are computed at the same time. In the worst casescenario for throughput, when the time correlations are computed sequentially, the throughput
equals the correlation length multiplied by the cycle time (correlations of around 32 need tobe performed). The decision on the best estimate is therefore provided after a maximum of 32
cycles from the receipt of the last sample. The best throughput solution is analyzed below: insuch a case, maximum throughput is possible as the entire correlation is computed in parallel,with the LUTs storing the PDFs being duplicated.
Further work is still required to optimize the performance and will be evaluated with extensiveMonte carlo simulations to optimize the parameters for ideal detection.

12.4.4

Resource Estimation

A possible detailed implementation of the trigger algorithm is shown in Fig. 12.22.
12.4.4.1

Block Diagram

In the diagram, the signals may be interpretated as follows:• Sample Timing Info: time when a sample arrives.
378

CHAPTER 12. TRIGGER

Figure 12.22: Trigger: Detailed Block Diagram.
• Sample Strobe: Indicates whether Sample Timing Info is valid.
• Event Strobe: Indicates detection of an event.
• Event Position Judgement: Position of the bar interaction.
• Event Timing Judgement: Time of interaction.
12.4.4.2

Resource usage and timing performanceAn estimate of the resources required to implement a completely parallel estimator is:• Block Rams: 100 × 32 × 10 × 10 = 320, 000 bits
• Flip-Flops : 7 × 10 × 10 + 32 × 10 × 10 + 128 × 32 + 128 × 7 = 4992 bits
• Adders: 200 32-bit adders (comparators).
If Xilinx Virtex 4 series FPGAs are used, the design requires 2496 slices for the flip-flops and3200 slices for the adders.
Even the smallest Virtex 4 is able to implement this design.
Latency: Since all the correlations are done simultaneously, the latency is only determined by
the MAX operation which would need 7 clock cycles if implemented as a pipeline.
Throughput: The throughput is 1. This means the output speed is the same as the input
speed of the samples.

12.5

KLM Trigger

In the Belle experiment, the KLM sub-trigger was mainly used for the logic to take µ pair events,
which is necessary for the detector calibrations. Because the KLM sub-trigger was independent
379

CHAPTER 12. TRIGGER

from the CDC sub-trigger, for example, it was very useful to measure the efficiencies of otherelements of the trigger logic. For these reasons, the KLM sub-trigger in the Belle II experimentwill be very useful. The trigger logic boards developed for other sub-trigger system, with theirprogrammable FPGAs and high-speed serial links, can be adopted for the KLM sub-trigger. In
fact, three-dimensional tracking of a muon may be possible in the KLM sub-trigger if enoughinformation is read out. Such 3D tracking is expected to increase the trigger efficiency of very
forward/backward low-multiplicity events such as e+ e− → µ+ µ− and e+ e− → τ + τ − while being
insensitive to backgrounds. The feasibility of the KLM sub-trigger is under discussion.

12.6

GDL
Sub-trigger
summary info.
# tracks# clusters
energy sum
Bhabhatimingetc.

Global Decision Logic~ 100bits

Sub-Trigger~ 4000bits
finner info.
Track segments
Cluster energy
PID hit patterns
KLM segments

Timing Adjustment

Trigger Decision

Pre-Scaler

Timing Decision

SEQ

UT3

Timing Adjustment

Low Level Recon.

Trigger Decision

UT3

Figure 12.23: Schematic view of GDL.
The global decision logic (GDL) is the final arbiter of the Level 1 trigger decision. It receives
all sub-trigger information, makes logical calculations and pre-scaling, and then issues the Level
1 trigger on appropriate timing. The GDL works as a pipeline so there must be no dead-time
logically. We will use a 62.5 MHz (or higher) clock as the system clock. The schematic view of
GDL is shown in Fig. 12.23. GDL receives two types of information:
0. summary information from sub-triggers (O(100) bits);
1. fine information from sub-triggers (O(4000) bits).
The summary information is used in the main logic that identifies events of physics interest andfor calibration triggers. (These inputs are very similar to the sub-trigger summary informationof the Belle experiment.) The fine sub-trigger information consists of, for example, the track
segments (TS) in the CDC sub-trigger and the energy deposits (TC) in the ECL sub-trigger.
This information is used for low-level reconstruction within the GDL: the association of a charged
track with an ECL cluster, the identification of a neutral ECL cluster, etc. The detail of the
low-level reconstruction is under simulation study now.
The GDL processes the sub-trigger information in four stages. In the first stage, the GDL applies
a timing adjustment to compensate for the different latencies of each sub-trigger. In the second
stage, the GDL makes the trigger decision. The following capabilities are under consideration.
0. Physics triggers– Υ(4S) and continuum: “three-track,” “total energy,” and “four-cluster”– τ pair: “two-track”
380

CHAPTER 12. TRIGGER

1. Calibration triggers– Bhabha : “bhabha”– γ-γ : “gamma-gamma”– µ pair : “two-track”– Random trigger : “random”
2. Veto logic– beam injection : “inj”– two photon events : “two-photon”
The “three-track” (“two-track”) logic is satisfied by the presence of more than two tracks (onetrack) in the CDC sub-trigger; the “total energy” logic is satisfied by an energy deposit ofgreater than 1 GeV in the ECL sub-trigger; the “four-cluster” logic is satisfied by the presenceof more than three isolated clusters in the ECL sub-trigger. These comprise the main triggers
for physics events. They are almost independent so that quite high efficiency for the physics
events is expected. For τ pair events, we have only the “two-track” logic and the efficiency islimited because of the coverage of the CDC sub-trigger. (This coverage may be extended formuon tracks by the implementation of a 3D KLM sub-trigger.)
For the detector calibration purposes, the GDL must trigger cleanly on Bhabha events, γ-γ
events, and µ pair events; it must also provide a random trigger. The “bhabha” logic is formed
using the ECL sub-trigger inputs; the “gamma-gamma” logic is formed by the “bhabha” logic
without any matching tracks in the CDC sub-trigger. The “random” logic is a delayed “bhabha”
trigger, to take events proportional to the luminosity. Events taken by the “random” trigger
are used to record minimum-bias events that are overlapped with simulated physics events tomimic the beam-related background in the Monte Carlo simulation.
The “inj” signal is active during accelerator beam injection, when the beams are unstable anddeliver high background to the Belle II detector. When active, “inj” vetoes all physics triggers.
The “two-photon” logic vetoes two-photon events.
In the third stage, the GDL reduces the overall trigger rate by prescaling the calibration triggers.
Bhabha events, for example, are necessary to measure the luminosity and to calibrate the ECL
system. However, the cross section for this process is so high that the GDL would generate
100 or more Bhabha triggers for each hadronic-physics trigger in the absence of prescaling. To
address this imbalance, the GDL issues only one “bhabha” trigger for every N that it finds; N
is called the prescale factor. The GDL logic permits us to choose the prescale factor for each of
the calibration triggers.
In the fourth and final stage, the GDL makes the trigger-timing decision using information fromthe BPID and ECL sub-triggers. We expect the best timing precision from the BPID sub-trigger(on the order of 1 ns) and somewhat worse resolution from the ECL sub-trigger (about 30 ns).
The timing decision logic issues the Level 1 trigger after a fixed delay upon receipt of the BPID
timing signal. In the absence of the BPID timing signal, this logic issues the Level 1 trigger
after a fixed delay upon receipt of the ECL timing signal. If neither timing signal arrives, the
GDL issues the Level 1 trigger after a fixed delay from the time that the trigger was generated.

381

References[1] A. Abashian et al.,9002(01)02013-7.

Nucl. Instrum. Meth. A 479, 117 (2002),

DOI: 10.1016/S0168-[2] Machine analysis of bubble chamber pictures, 1959.
[3] S. Bailey et al., Nucl. Instrum. Meth. A 518, 544 (2004), Frontier Detectors for Frontier
Physics: Proceedings, DOI: 10.1016/j.nima.2003.11.081.
[4] F. A. Kirsten et al., BaBar Level 1 Drift Chamber and Global Trigger Implementation,
http://www.slac.stanford.edu/BFROOT/www/Detector/Trigger/Kirsten42.ps, 1998.
[5] B. G. Cheon et al.,9002(02)01547-4.

Nucl. Instrum. Meth. A 494, 548 (2002),

382

DOI: 10.1016/S0168-

Chapter 13

Data Acquisition System
13.1

Global Design

The goal of the data acquisition (DAQ) system is to read out detector signals upon the Level-1(L1) trigger decision given by the trigger system. The system transfers the data from the frontend electronics through several steps of data processing, and finally to the storage system. The
main components of the data flow are the unified data link called the Belle2Link, the common
readout platform called COPPER, the event builder system, and the high level trigger (HLT)
system.
Figure 13.1 shows the global design of the Belle II DAQ system. The detector front-end boards
with digitizers are placed near or inside the detector structure and the digitized signals aretransferred into COPPER systems through long optical fibers using the Belle2Link. A simple
data reduction is performed on each front-end electronics board or on the receiver module of
COPPER, while the data formatting and module-level event building is done on COPPER using
the on-board CPU. The further event building and reduction are done on the readout PCs andthe event builder, and finally processed by the HLT farms for the software event selection.
The Belle II DAQ system is designed with the following policy:
1. Smooth transition from Belle
The existing Belle DAQ system already includes the key component, the COmmon Pipeline
Platform for Electronics Readout (COPPER), which is designed to be used in the Belle IIenvironment. The digitization system of Belle has been upgraded from a system based on
FASTBUS TDC to a system based on COPPER modules. Experiences acquired during thetransition will be indispensable at the construction stage. Keeping the COPPER system
as the basis of the DAQ system certainly makes the transition to Belle II smoother.
2. Unification
In the Belle DAQ system, the readout system for all the detector subsystems except
the SVD is implemented using the charge-to-time (Q-to-T) conversion combined with amulti-hit FASTBUS TDC. This “unified” detector readout scheme has drastically reduced
the development and maintenance cost in hardware, software and human resources. The
DAQ design for Belle II inherits this concept. The use of COPPER is the baseline ofthis unification. In addition, the data link from the front-end electronics placed near thedetector to COPPER, which we call the Belle2Link, is unified to use the same FPGA
logic in the transmitter side, the same hardware, firmware and software for the receiverside with a common data transfer protocol. The transmitter side logic also includes thetiming specific logic that enables the unified control over the entire system at the level of383

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.1: Conceptual design of Belle II DAQ system.
the frontend boards. The other unification is the software framework for the data flow,which runs on each COPPER, readout PC, event builder node, and high level trigger nodewith a common data transfer protocol. A new software framework, “roobasf” [1], is being
developed for the common use in DAQ and offline. The “roobasf” is to be used at the alllevels of DAQ nodes as well as offline.
3. Scalability
The luminosity at the beginning of the Belle II experiment will be several times lower
than the design, and it will take a few years to reach the design luminosity. On the other
hand, the trigger rate may be at or near the design level from the beginning due to theinitial vacuum condition. Therefore, the total bandwidth of Belle2Link may stay almost
constant. Since it is hard to change later, the bandwidth of Belle2Link is designed to havea large margin over the full-luminosity expectation and is capable of handling an increasein the occupancy. However, even if the trigger rate is high at the beginning because of
the high rate of junk background triggers, the required processing power for such eventsat the high level trigger is significantly less than those for multi-track B-decay events, andless CPU power is needed. It matches with the budget profile, in which the CPU poweris added later when needed and when the CPU cost is drastically reduced. Therefore, thehigh level trigger and related down-stream components are designed to have a modular
architecture so that the processing power is scalable by adding more units.

384

CHAPTER 13. DATA ACQUISITION SYSTEM

13.2

Requirements

Challenges in the Belle II DAQ system are the expected high trigger rate and the required
processing time; either could lead to a high deadtime, corresponding to an effective waste ofluminosity. There are constraints from the digitization hardware of state-of-the-art technologies
for which some of the relevant parameters cannot be modified. Other requirements are related
to the data size, which determines the necessary number of datalinks, size of the network, andprocessing power at the later stages.

13.2.1

Timing Requirements

We set our timing-related requirements mostly based on the constraints given by the SVD
readout system. Here, we do not base our parameters on the PXD system, since it takes
significantly longer to read out the signal and the signals from more than one trigger often overlap
in the data stream. Also, there remain unsettled issues in the PXD data acquisition, including its
maximum trigger rate capability, handling of overlapped triggers, and the techniques to reducethe data bandwidth.
The nominal average L1 trigger rate is expected to be 20 kHz at the instantaneous luminosityof 8 × 1035 cm−2 s−1 . We set the design average trigger rate of the data acquisition system to be
30 kHz, which has a 50% margin.
Little DAQ deadtime should occur while processing all of the triggers in the pipeline fromthe frontend to the backend subsystems. In reality, there are limitations due to buffer sizes
and data-moving sequences, and the actual deadtime at the very frontend is determined by fourparameters: the average trigger rate, minimum interval between two triggers, number of triggers
that can be processed in the pipeline, and the latency of the readout system. The most severe
constraints comes from the SVD readout system, which handles multiple triggers in the pipelinesubject to the following constraints:• Minimum interval between two triggers — 190 ns (6 clocks in 31 MHz)
• Number of triggers in pipeline — 5• Latency of the readout system — 26.6 µs (840 clocks in 31 MHz).
With these conditions, the expected deadtime fraction is calculated to be 3.4% for the 30 kHz
trigger rate that follows a Poisson distribution, or a much higher deadtime fraction for a higher
trigger rate. This is the part of the reason for the choice of 30 kHz trigger rate for the design.
There is an additional and irreducible deadtime fraction in order to mask the background triggers
due to the continuous beam injection. The trigger is masked for at least 150 µs after the injection
over the entire ring and a longer window of a few ms after the injected beam bunch (Sec. 9.4.4).
At the anticipated beam injection rate of 50 Hz, this adds a few more percent to the deadtime
fraction.

13.2.2

Datalink and Data Size Requirements

The data size requirements are based on requests from subdetectors that are summarized inTable 13.1. The frontend datalink called Belle2Link bundles multiple channels to reduce thenumber of lines between the detector and backend DAQ system to a manageable level, and isoperated at a much lower rate than the capable maximum bandwidth. The number of datalinks

385

CHAPTER 13. DATA ACQUISITION SYSTEM

Table 13.1: Estimated average occupancy and data size and required number of subcomponents
such as the number of Belle2Link for data transfer and number of COPPER modules. In addition
to the listed subdetectors, trigger information is also planned to be read out in a similar way.
#ch
PXD
SVD
CDC
BPID
EPID
ECL
BKLM
EKLM

8M
243456
15104
8192
77760
8736
21696
16800

occ.
[%]
1
1.9
10
2.5
1.3
33
1
2

#link
40
80
300
128
138
52
86
66

/link
[B/s]
182M
6.9M
0.6M
7.5M
0.87M
7.7M
9.7M
19.5M

#COPPER
—
80
75
8
35
13
6
5

ch size
[B]
4
4
4
16
0.5
4
8
4

ev size
[B]
320k
18.5k
6k
4k
4k
12k
2K
1.4k

total
[B/s]
7.2G
555M
175M
120M
120M
360M
60M
42M

/COPPER
[B/s]
—
6.9M
2.3M
15M
15M
30M
10M
8.4M

is mostly determined by the hardware configuration, while the bandwidth in the later stage(except PXD, handled separately) is arranged according to the bandwidth.
The data size requirements are based on the limitations of the pipeline buffers as well as therequests from subdetectors. Here, we need three numbers: the average size, the maximum size
during the nominal data taking, and the absolute maximum size. The average size determines
the design of the overall structure and the size of the system, while the nominal maximum size
determines the allocation of buffers. At this moment,• Maximum data size per event per datalink — 16 kbyte
is requested for subdetectors. This is due to the buffer size limitation in Belle2Link.
The data size in Table 13.1 still has a large uncertainties which comes from the estimation of thedetector occupancy. For example, the data size of PXD in the table is estimated by assuming
an occupancy of 1%, however, it can easily be doubled depending on the background situation.
In our DAQ design, therefore, we take a safety factor of 2 and assume the data size from PXD
to be 1MB, while 100kB as a total size from other detectors.

13.3

Timing distribution and handshake

The main task of the timing distribution system is to distribute the reduced RF clock for thesystem-wide synchronization, the trigger signal, and several fast control signals to the entire
data acquisition system including frontend readout boards and the COPPER readout system ina unified way. In the FPGA of readout boards, there is a unified logic core that receives andhandles these signals. As some of the readout boards are located inside the detector, the longest
path will be 30 to 40 m from the central timing source to the destination. By placing a middle
station on or near the detector, the longest single-cable path for signal transmission is halved.
The clock signal is distributed as a 127 MHz clock, which is one-quarter of the RF clock. The
high precision clock source is provided by the barrel PID system, which requires the smallest
jitter clock. After distribution, the necessary clock speeds for readout are generated inside theFPGA. The clock speeds requested by subdetectors include 127, 101, 63, 42, 32, and 2 MHz (theRF clock divided by 4, 5, 8, 12, 16, and 256, respectively), and they are synchronized to therevolution signal of the accelerator.
386

CHAPTER 13. DATA ACQUISITION SYSTEM

The trigger signal has to be blocked when the readout systems cannot handle it due to theirlimitations as described in the requirement section, i.e., two trigger signals should not be issued
with an interval less than 190 ns and no more than 5 triggers should be delivered to be processedin the pipeline at the same time. The first condition is always fulfilled due to the restriction in
the L1 trigger system. For the second condition, the system has to know when the processing
for the first trigger has completed and is ready to issue the sixth trigger (or stop blocking thetrigger). The method proposed here is based on following three key conditions:
1. The end of processing of an event by every readout system is notified to the timing system,and this information is quickly collected by a central trigger distribution system.
2. The data is sent through the datalink to the COPPER with no flow control (i.e., no backpressure towards the front-end side).
3. The buffer-full status at the COPPER is notified to the timing system to block the trigger.
This buffer can become full when the COPPER CPU is busy. Since it is computer driven
from this point on, the latency of processing is unpredictable.
To distribute and collect necessary signals, we use a small-latency serial-link. This serial-link
is not required to have the high bandwidth of the Belle2Link. We do not require a clock
recovery feature, which is usually one of the latency sources for serial links, since we distributea clock signal to all the nodes of the distribution tree. To maintain flexibility and compactness,
serialization and deserialization are performed inside the FPGA. One limitation is that one
serial data sequence has to be shorter than the 200-ns trigger interval. The actual trigger
timing, which is synchronized to the 127 MHz clock at the L1 trigger system, is recovered fromthe phase information embedded in the serial data.
Currently, 32-bit word serialized to the line rate of 254 Mbps (length of 126 ns), or 24-bit word
encoded with 8b10b and serialized to the line rate of 159 Mbps (length of 189 ns) is underconsideration. Encoding such as 8b10b or another homemade one has to be made to guarantee
a sufficient number of polarity flips for the AC coupling connection, the bit synchronization in
the word, and the insertion of control words in the stream.
The clock and serial-link signal is distributed over an off-the-shelf CAT7 LAN cable, directly
driven by the LVDS driver of the FPGA. Various types and lengths of LAN cable have beentested for signal integrity. We found that a 15-m flat LAN cable or a 30-m thick CAT7 cable
can be used without inserting additional driver or receiver chips in front of the FPGA. The
clock jitter increases up to about 50 ps, but this could be reduced to 20 ps using the built-in
PLL circuit of the FPGA. The maximum serial link rate is based on a test that successfully
established a serial data link at 254 Mbps over a 15-m cable using the serializer and deserializer
function of the Xilinx Virtex5 FPGA. It is confirmed that an additional equalizer circuit is notnecessary for our requirements.
In the single LAN cable, there will be a distributed clock signal, a distributed serial-link signal
in which the trigger timing information is embedded, and a collecting serial-link signal. The
distributed signals can be fanned out without encoding and decoding, and this will be theoperation mode during a run. The same line can be configured to decode and encode at every
step and, by doing so, one can use the line for the node-by-node control. The encoding patterns
will be chosen so that the trigger timing signal and the response signal can be decoded within
one clock cycle to reduce the latency.
The clock and trigger signal distribution is made by a FTSW (Frontend-Timing-SWitch) module
shown in Fig. 13.2, which has 24 RJ-45 ports; one port is used as input and 20 ports as output.
387

CHAPTER 13. DATA ACQUISITION SYSTEM

20100623 version

JTAG LAN

Ethernet
PHY

Timing signals over a LAN cable
AUX

O1

O2

O3

O4

O5

O6

O7

O8

O9

O10

O11

O12

O13

O14

O15

O16

O17

O18

O19

O20

1-2 pair
3-6 pair
5-4 pair
7-8 pair

CLK: 127 MHz (derived from 508 MHz RF clock)
TRG/ACK: serialized, 254 Mbps

JTAG-on-LVDS over a LAN cable
TCK
TMS
TDI
TDO

1-2 pair
3-6 pair
5-4 pair
7-8 pair

JTAG
receiverjittercleaner

XilinxSpartan3
FPGA

VME

XilinxSpartan6
or Virtex5
FPGA

FMC mezzanine
connector (VITA57)

ACK
TRG
RSV
CLK

IN

Figure 13.2: LAN cable usage and the Frontend Timing Switch module.
This module is a double-width 6U VME board, and is also designed for standalone operation
without a VME crate. Cascading this module three times will cover all the readout boards.
It is being discussed whether one can drive the Belle2Link using the distributed reduced RF
clock, for simplicity and to avoid extra noise source inside the detector. The quality of therecovered clock is at least within the specification of the Xilinx RocketIO.

13.4

Belle2Link

Belle II DAQ system uses the RocketIO GTP technology over optical fibers for the data transmission between front-end electronics (FEE) and the backend system. GTP is a cost-effective
version of the RocketIO which can handle up to 3.125 Gbps line rate on LXT series of the Xilinx
Virtex5, Virtex6 and Spartan6 FPGAs and can also intercommunicate with older versions ofRocketIO in Virtex II pro and Virtex4 FPGAs. For simplicity of development of the front-end
systems and reliability of the operation, an unified high speed link which we call the Belle2Link
has been defined for use in all connections between each of the subsystems. The Belle2Link
provides1. unification of the hardware design,
2. unification of the firmware design,
3. electrical isolation,
4. high speed data transmission,
5. versatileness for different input data rates, and6. home brew transmission protocol.
The Belle2Link comprises the high speed transmission lines based on the RocketIO technology
over optical fibers and various interfaces to the FEE(IF FE), to the trigger timing distribution
388

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.3: Belle2Link connecting front-end electronics and back-end COPPER based DAQ
system.

Figure 13.4: Block diagram of the Belle2Link .
system (IF TTC) and to the FIFO buffer of COPPER (IF CO) (Fig. 13.3). The Belle2Link
accepts data in FIFO FE via IF FE from FEE for transmission and receives trigger and timing
signals from timing distribution system via IF TTC in the sender part (BLSNDR), and at
the receiver part (BLRSVR) it saves the received data in the FIFO BL and moves data afternecessary processing to the FIFO CO in IF CO which is on the COPPER platform (Fig. 13.4).
As the unified link for all sub-detector systems, Belle2Link provides a single type (or at mosttwo different types) of the receiver FINESSE boards and all the unified firmware for sender partand receiver part.

13.4.1

Unification in hardware

The BLSNDR is implemented in a Virtex-5 FPGA in the FEE readout boards and shares its
resources. The FEE readout of each sub detector systems provide the FPGA and the BLSNDR
part of the unified Belle2Link firmware will be integrated with the readout firmware. When
389

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.5: The state machine of the sender part.

Figure 13.6: The state machine of the receiver part.
multiple readout channels have to be combined before sending out through the Belle2Link,
necessary signal mergin has to be performed before the BLSNDR. A unique frequency will bechosen for the high precision clock CLK LK for the RocketIO transmission for all Belle2Link
lines. This CLK LK is preliminarily chosen to be 200MHz for a line rate of 2Gbps and be
produced by a high precision crystal for the prototype of the FEE board and FINESSE receiverboard (BLRB). BLRD board is a FINESSE board which fits the general requirements of highspeed transmission and also some data processing for system like B-PID and electrically andmechanically fit to the COPPER board.

13.4.2

Unification in firmware and protocol

The circuitry of the Belle2Link will be implemented by firmware in the Xilinx FPGA. The
development of the link will be based on Xilinx ISE 11 development software. The firmware for390

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.7: The state machine of the data processor.
BLSNDR will be unified and provided to all system for integration to the system. The firmware
for BLRSVR will also be unified and can be online configured for use in system like in B-PID.
The working status can be checked by registers and displayed on some LED on the front panel.
The interface with FEE is a FIFO (FIFO FE). The FIFO FE is a 32bit write and 16bit read
FIFO and will be filled with data by FEE readout under control of clock CLK FE and then be
moved to GTP under sender clock CLK LN after adding some control and error checking data
by BLSNDR state machine (Fig. 13.5).
In the BLRSVR, another state machine checks for the GTP line (Fig. 13.6). The data on theline will be first received and stored in a FIFO LN under control of clock CLK LN. If it is error
free this data will be moved to a FIFO LN (N EV will be incremented). If there is an error
occurred in the transmission, an error flag is added in the header part of data frame for later
use in the online data monitoring. In most of the systems the data in FIFO LN will be direct
moved to another fifo FIFO WR, but for systems like B-PID the date must be first moved to apipeline(Fig. 13.7), and part of the data in a time window will be fetch after receives a trigger
and be processed accordingly, then be stored in FIFO WR in the data form showed in table 13.9.
Special error bits are allocated to indicate if a data transmission error occurred.
Another state machine (Fig. 13.8) checks the NEV WR, if there is an event in the FIFO WR,
then send the data for this event to FIFO CO under control of clock CLK CO and decrease the
NEV WR if the COPPER is ready to read. This condition should not occur since the almost
full status of FIFO CO (FFUL signal) is asserted and received by the timing receiver (TT-RX)
that is attached on the COPPER in order to block further triggers when there is still room toreceive predefined number of all events in the trigger distribution and readout chain.
After FFUL is asserted, the number of event NEV WR is counted and if it exceeds the predefined
number a BUSY signal is generated to TT-RX. The BUSY signal is removed two CLK CO clocks
after FFUL is cleared. The error checking scheme will be kept for the online checking of thetransmission between Belle2Link and COPPER.

13.4.3ClocksThree key clocks will be needed by Belle2Link, CLK FE which is converted from central trigger
and timing distribution, CLK LK for the high speed transmission which is a high precision clockfrom a crystal on the board, and CLK CO received from TT-RX via COPPER connector. The
391

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.8: The state machine of the data writing to COPPER.

Figure 13.9: Data format to be written to COPPER.
clocks for data transmission on the RocketIO will be composed by the DCS in Virtex-5 core.
For the prototype system, we have used a CLK LK of 200MHz and successfully operated at aline rate of 2Gbps. This clock can be changed to a 125 MHz (or other frequency up to 156.25
MHz) for a line rate of 2.5 Gbps (or up to 3.125 Gbps) which will be further studied.

13.4.4Further studies

The protocol will include bidirectional communication for online slow control command anddata transmission. This is needed since the Belle2Link is the only connection for example to set
the parameters of the frontend readout board.

13.5

Detector front-end interface

The transmission side of the unified Belle2Link is implemented in an FPGA that is used mainly
for subdetector-specific purposes. To share the same FPGA, we define the requirements forthe board for the datalink purpose as given in Fig. 13.10. Implementing the datalink part into
a separate chip or another daughter card may help to clearly define the interface, but it isunacceptable in terms of space for most, if not all, of the subdetector systems.
First, we define the FPGA type to be a Xilinx Virtex5 FPGA with a RocketIO GTP transceiver(LXT series). We are also investigating the possibility to use the less expensive Spartan6 FPGA.
392

CHAPTER 13. DATA ACQUISITION SYSTEM

Belle2link / timing signal physical interface at the frontend readout board
20100623 version

Xtal

REFCLKEPSON EG2121 LVDS or PECLFrequency has to be decided
and may be dropped in the final design

Tx

GTP capable FPGA
(e.g., Virtex5 LXT,
Spartan6 LXT)

SFP

Rx
moddef2
moddef1

Pin assignment
to be partiallycompatible with
Timing Distribution
modules of Belle2

I C protol pins to access the opticaltraceiver information

ACK (out)

1-2
RJ-45
3-6
5-4 CAT5E
7-8 (or better)

TRG (in)
RSV (out)
CLK (in)Don’t make 3-4 and 5-6 pairs!
TCK
TMS
TDI
TDO

3ch LVDS→LVTTL
1ch LVTTL→LVDS(e.g., SN65
LVDT14)1-2 RJ-45
3-6
5-4 CAT5E
7-8 (or better)
100 ohm termination is in SN65LVDT14
no AC coupling for JTAG

jumper to enable / disable remote JTAG function
local JTAG programming connector

Figure 13.10: Definition of the Belle2Link and timing signal interface at the frontend.
Second, we define the necessary connectors. For the GTP datalink, a SFP connector and a highquality Xtal oscillator are placed on the board and appropriately connected to the FPGA. To
receive the timing signal, we use an RJ-45 connector with the LAN cable pair definition (1–2,
3–6, 5–4 and 7–8 pins are paired).
In addition to these two connectors, we are investigating the possibility of having a unified
JTAG extension connector and a set of necessary driver and receiver chips to permit remote
reprogramming of the FPGA. The main reason is that we worry about the stability of a flash
memory as the firmware storage device in the radiation-hard environment.
For the unified datalink purpose, two firmware cores, one for the datalink and the other for
timing-signal handling, will be included in the FPGA. The specification of the set of the signals
from and to these cores will be similar to the set of signals between FINESSE and COPPER,
but they are yet to be defined. For the timing signal, the reduced RF clock(s) of the requested
frequencies, trigger timing signal, trigger tag, and reset signal at the run start will be provided.
For the data transfer, the data bus, the writing clock and other functions are still undefined.
It has been requested that the many parameters be downloadable from COPPER through thedatalink to the FPGA, e.g., to set the threshold or gain of the digitization circuits, and a set ofsmall local data and address line for such registers as is available for FINESSE and COPPER
would be useful.

13.6

COPPER Readout System

To reduce the total cost of development and maintenance of the readout system, we designed
the system based on COPPER (COmmon Pipelined Platform for Electronics Readout) [2]. It
is a general purpose pipelined readout platform developed at KEK and is designed so that the393

CHAPTER 13. DATA ACQUISITION SYSTEM

PCI

VME
)

32

FIFO

FINESSEFIFO

FINESSE

FIFO
FIFO
control

FIFO
control

PCI

Trigger Rx

PrPMC

Data out

FINESSELocal

PCI bus

FIFO

Local bus

FINESSEL1 trigger in

Bus control
Ethernet

FIFO fullL1 trigger
Busy

Data in

32

VME

COPPER

Figure 13.11: Block diagram of the COPPER board, with four FINESSE cards indicated.
detector interface is mounted on the platform as daughter cards called FINESSE. The Belle2link
receiver (BLRSVR) is equipped as a FINESSE card to receive the data from the front-end via
optical cables. Up to four FINESSE cards can be mounted on a COPPER board.
A commercial CPU card (PrPMC) is also mounted on the platform and the data from FINESSE
cards are fed through the PCI bus. The data formatting and reduction are performed by the
CPU and the output are then sent to the event builder through the FastEthernet connection.

13.6.1

Data flow in the COPPER readout system

Figure 13.11 shows a block diagram of the COPPER readout platform together with the FINESSE interface cards. A typical data stream from the detector to the event building PC,
through the FINESSE cards and the COPPER board, is as follows.
The detector signals received by Belle2link receiver are fed into four 1024-kB FIFOs corresponding to each FINESSE card on the COPPER board in 32-bit data width. The data transfer tothe FIFO is performed asynchronously with the L1 trigger timing.
The FIFOs are connected to the 32-bit local bus on the COPPER board. The event data sizein each FIFO is counted by the local-bus controller. Once the data size exceeds a predefined
threshold (typically a few hundred events), a PCI interrupt is issued by the local-bus controller
to a CPU card through a local-to-PCI bus bridge to indicate the arrival of data in the FIFOs.
The data stored in the FIFOs are then transferred to the memory on the CPU card by thechained direct-memory-access (DMA), initiated by a local-to-PCI bus bridge. During the DMA
procedure, the data from four FIFOs are combined and formed as event records. The data
formatting and data size reduction/feature extraction are performed on the CPU card using theunified software framework. Finally, the formatted data are sent to the readout PC through a
100 Mbps or 1000 Mbps ethernet link.

13.6.2

FINESSEThe FINESSE is a 76.0 × 186.0 mm2 daughter card [Fig. 13.12(top)] that is mounted on a
COPPER board. Up to four FINESSE cards are mounted in this way, with a 2-mm gap between
neighboring FINESSE cards. The height of the FINESSE card is required to be less than 10 mm,
as indicated in Fig. 13.12(bottom).
The FINESSE card and the COPPER board are connected with 116 pins on three connectors.
Table 13.2 lists the connector pin assignments. The data drain from the FINESSE card to the394CHAPTER 13. DATA ACQUISITION SYSTEM

Table 13.2: The list of the connector pin assignments between the FINESSE card and the
COPPER board.
pin#

row-A

row-B

row-C

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

FF[00]
FF[01]
FF[02]
FF[03]
FF[04]
FF[05]
FF[06]
FF[07]
FF[08]
FF[09]
FF[10]
FF[11]
FF[12]
FF[13]
FF[14]
FF[15]
FF[16]
FF[17]
FF[18]
FF[19]
FF[20]
FF[21]
FF[22]
FF[23]
FF[24]
FF[25]
FF[26]
FF[27]
FF[28]
FF[29]
FF[30]
FF[31]
GATE
FRST
FWEN
FWCLK
FFUL
NWFF
ABRT
BUSY

−3.3V
−3.3V
−3.3V
−3.3V
−3.3V
−3.3V
GND
GND
GND
GND
GND
GND
+3.3V
+3.3V
+3.3V
+3.3V
+3.3V
+3.3V
GND
GND
GND
GND
GND
GND
+5V
+5V
GND
GND
−5V
−5V
GND
GND
+12V
GND
−12V
GND
–
–
–
–

IRSTB
IENA
IO2
TYP[0]
TYP[1]TYP[2]TYP[3]
TAG[0]
TAG[1]
TAG[2]
TAG[3]
TAG[4]
TAG[5]TAG[6]
TAG[7]
LD[0]
LD[1]
LD[2]
LD[3]
LD[4]
LD[5]
LD[6]
LD[7]
LA[0]
LA[1]
LA[2]
LA[3]
LA[4]
LA[5]
LA[6]
LWR
CSB
TRG+
TRG−
REV+
REV−
RCK+
RCK−
SCK+
SCK−

395

CHAPTER 13. DATA ACQUISITION SYSTEM

A40
A39
B1
B2

A2
A1

Connector C
C39
C40

B35
B36

Connector B

Connector A

C1
C2< 10 mm
FINESSE module

Figure 13.12: The dimensions of the FINESSE card.
event
FWENB

FINESSEFIFO
on COPPER

FWCLK
FF[0:31]

Figure 13.13: The usage of the FWENA and FWCLK signals.
→ FF[0:31]
32-bit-width data drain→ FWENA
indication of a event start/end
FIFO is maintained by:→ FWCLK
write action to the FIFO
← FFUL and NWFF
FIFO full condition on the COPPER board
where the → symbol indicates a signal from the FINESSE card to the FIFO and vice versa forthe ← symbol. The usage of the FWENA and FWCLK signals is shown in Fig. 13.13. The FWENA
signal indicates a single start/end to the local-bus controller on the COPPER board so that theevent separation can be properly treated. At every activation of the FWENA signal, the local-bus
controller assumes the event sequence starts. All FF[0:31] signals at FWCLK timings until the
FWENA signal negated are considered to belong to a same event record.
The FINESSE is connected to the local bus of the COPPER, and is accessible from the CPU card
to monitor its status and to configure its registers. The communication between the FINESSE
card and COPPER is maintained by:→ LD[0:7]
8-bit-width address bus→ LA[0:6]
7-bit-width data bus← LWR
data direction← CSB
FINESSE card selector
The register map in the FINESSE is listed in Table 13.3.
The FINESSE card also communicates with the timing system. The communication is maintained through the timing interface card (TT-RX) via following signals:

396

CHAPTER 13. DATA ACQUISITION SYSTEM

Table 13.3: The register map of the FINESSE card on the local bus.
Address
Description
Mandatory
0x00 - 0x77 user definedno0x78
CSR (active H)
nobit 0: card initializationyes
bit 1: busy-out emulationnobit 2: reserved
yes
bit 3: FWCLK emulation
bit 4: FEWNB emulation
bit 5: reservednobit 6: abort signal emulation
bit 7: enable bit for bit-1 to bit-6
0x79
data emulation for FF[0:7]no0x7a
firmware version number
no0x7b
serial number [7:0]no0x7c
serial number [15:8]
no0x7d
card type [7:0]yes
0x7e
card type [15:8]
yes
0x7f
reserved
yes← TAG[0:7]8-bit event tag← TRGlevel-1 trigger timing for backup use→ BSYB
response to TRG for backup use← REV
revolution signal← SCK
42.3 MHz system clock
The TT-RX labels event tag to every L1 trigger signal. The FINESSE card is required to include
the event tag in the data record.
The electric power, at ±3.3 V, ±5 V, and ±12 V, is provided to FINESSE through the row-B
connector.

13.6.3

COPPERThe COPPER is a 9U-VME size board with dimension of 366.7 × 400.0 mm2 . A photograph of
the COPPER board is shown in Fig. 13.14.
A COPPER board is equipped with four FINESSE slots, four 1024 kB FIFOs connected to each
FINESSE slot (4-slots × 2 × IDT 72V36110L15PF), an A32D32 local bus operated at 33 MHz,a local-bus controller (ALTERA Cyclone III), an A32D32 PCI bus operated at 33 MHz, a localPCI bus bridge (PLX 9054), three PrPMC slots (for the PrPMC, TT-RX card, and genericpurpose), one network port directly connected to the PrPMC network port, and one 100BaseT(Intel 82559 for the COPPER-II board) or 1000BaseT (Intel 82541 for the COPPER-3 board)
network port on the PCI bus.
The COPPER board has the capability to interface with the VME A32D32 bus as a slave
module. We only use VME bus to reset the COPPER board using the sysreset signal; nodetector signal transfer is intended over the VME bus. The VME bus is bridged with the PCI
bus by a 4 kB dual port memory (ALTERA EP20K100QI240-2V).
A COPPER board has three connectors on its rear side; two for the VME bus, and one forelectric power supply. The pin assignments of the power connector are listed in Table 13.4. The
397

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.14: A photograph of the COPPER board.

Table 13.4: The pin assignments of the COPPER power connector. Two all-GND rows (row-z
on the left to the row-a and row-f on the right on the row-e) are omitted.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

row-a
GND
GND
GND
+3.3V
+3.3V
+3.3V
+3.3V
GND
GND
GND
−3.3V
−3.3V
GND
−5V
GND
S[1]+
S[3]+
S[5]+
S[7]+

row-b
GND
GND
GND
+3.3V
+3.3V
+3.3V
+3.3V
GND
GND
GND
−3.3V
−3.3V
GND
−5V
GND
S[1]−
S[3]−
S[5]−
S[7]−

row-c
GND
GND
GND
+3.3V
+3.3V
+3.3V
GND
GND
GND
GND
−3.3V
−3.3V
GND
−5V
GND
GND
GND
GND
GND

398

row-d
GND
GND
GND
+3.3V
+3.3V
+3.3V
GND
GND
GND
−3.3V
−3.3V
−3.3V
GND
−5V
GND
S[2]+
S[4]+
S[6]+
S[8]+

row-e
GND
GND
GND
+3.3V
+3.3V
+3.3V
GND
GND
GND
−3.3V
−3.3V
−3.3V
GND
−5V
GND
S[2]−
S[4]−
S[6]−
S[8]−

CHAPTER 13. DATA ACQUISITION SYSTEMFIFO-A almost full
FIFO-B almost fullOR

OR

FIFO-C almost full

PCI
interrupt

FIFO-D almost full

FIFO-A thresholdAND

FIFO-B thresholdAND

FIFO-C thresholdAND

FIFO-D threshold

AND

ADD

CMPR

FIFO A,B,C,D
ignore mask

Figure 13.15: The logic in the local-bus controller on the COPPER to issue the PCI interrupt
to initiate the data transfer from the FIFOs to the PrPMC main memory.
S[1:8]± signals are not used in Belle II.
An interrupt is generated at the arrival of data in the FIFO and its condition is configurable
to match with the characteristics of data from each detector. The logic is shown in Fig. 13.15.
Each FIFO issues the almost-full signal when the data size in the FIFO exceeds a predefined
configurable watermark (the default being 1023 kB). Once one of four FIFOs gets almost full,the PCI interrupt for the data transfer is immediately issued. When the data size in the FIFO
exceeds another watermark, typically configured smaller than the almost-full watermark (thedefault being 768 kB), the FIFO issues the excess-threshold signal. This signal can be buffered
before the PCI interrupt until other FIFOs also issues their excess-threshold signal as well.

13.6.4The VME crate housing the COPPER boards

The COPPER board is housed in a VME 9U crate with a special backplane equipped with two
normal VME connectors and one special power connector per slot. The crate can house up to
17 COPPER boards.
The CPU card on each COPPER is supposed to be network-booted with a unique host namederived from the slot-ID and the crate-ID. Dip switches on the COPPER board are used to
specify the slot and crate IDs, at which it resides.

13.6.5CPU card

There are commercially available CPU cards following the industrial standard called PrPMC.
COPPER is designed to accept a CPU card compatible with this standard. In the Belle DAQ
system, we use the RadiSys EPC-6315, which is equipped with an Intel Pentium III processor(800 MHz) and 256 MB of main memory. However, the commercial life of this product is nearits end, and the market trend of the PrPMC-compatible CPUs is hazy. We have thus decided
to develop our own PrPMC to ensure a sufficiently long product lifetime.
Table 13.5 lists major features of the PrPMC under development. Figure 13.16 shows a prototype
CPU board with an area of 170 × 170 mm2 ; this must be shrunk to the PMC size. The CPU
card is network-booted and operated by Linux.

399

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.16: A prototype CPU board with 170 × 170 mm2 area.
Table 13.5: The list of major features of the new PrPMC under development.
CPUIntel Atom 1.6 GHz processor (Z530P)
main memory
4 × 128 MB DDR2 SDRAM
chip-setIntel US15WP
on-board storage
4 GB Solid State Disk
network I/FIntel 82574L (1000BaseT)user I/F
1 × serial port
PS/2 keyboard and mouse
2 ch × USB
VGA
operating system
RHEL 3 or CentOS 3 or laterbootable from SSD, USB, and network
electric power
less than 15 W

13.6.6

Data format of the COPPER readout system

Figure 13.17 shows the format of the raw data output from the FINESSE card. The FFAA andFF55 are event header and event trailer, respectively. The FINESSE event counter is a 24-bit
event counter incremented upon the L1 trigger signal from the TT-RX card. The ttrx-ev is an
event tag provided by the TAG[0:7] signal. The checksum is an 16-bit xor checksum from the
FFAA to the FF55.
Figure 13.18 shows the format of the data record sent to the CPU card, which is formatted
by the local-bus controller. The FFFFFAFA and FFFFF5F5 are event header and event trailer,
respectively.

13.6.7

Readout PC

The data from COPPERs housed in a VME 9U crates are sent to a Readout PC through a
100Base-T or 1000Base-T network connection via a network switch. There data are alreadyformatted by the software processing on the CPU on COPPER and directly fed into the event
building framework described in the next section. The first level data monitoring is done on the
Readout PCs using the unified software framework.
400

CHAPTER 13. DATA ACQUISITION SYSTEMFINESSE Raw Data
FFAA (16)reserved (6)FINESSE event count (24)ttrx-ev (8)data #0 (32)data #1 (32)...

data #n (32)
FF55 (16)checksum (16)Figure 13.17: The raw data format output from the FINESSE card.

COPPER Raw Data
FFFFFAFA (32)
total data length with header & trailer (32)
FINESSE Ch#A data length (32)
FINESSE Ch#B data length (32)
FINESSE Ch#C data length (32)
FINESSE Ch#D data length (32)
FINESSE Ch#A data (32) x n
FINESSE Ch#B data (32) x n
FINESSE Ch#C data (32) x n
FINESSE Ch#D data (32) x n
FFFFF5F5 (32)

Figure 13.18: The format of raw data fed into CPU card.

We will have up to 50 Readout PCs in total to read out all Belle II detector components.

13.6.8

Data transfer performance

We study data transfer performance inside the COPPER board. Figure 13.19 shows a block
diagram of the test setup for the performance study.
The FINESSE emulator card outputs predefined data sequence to the FIFO on the COPPER
board at every arrival of the emulated L1 trigger signal from the TT-RX card. The data size
per event can be adjusted to one of 2n bytes (n = 4 or 8 . . . 12).
We used a CPU card called PSL09 for the test, which is equipped with an Intel PentiumM
processor (1.1 GHz) and 256 MB of main memory. The performance of the CPU card is expected
to be similar to that of the new CPU card that is being developed.
The data transfer performance is studied by measuring the total throughput inside the COPPER
board by varying the generated data size and the trigger rate. Table 13.6 lists the results of theperformance study. In case of the trigger at 50.0 kHz (marked with the ⋆ in the table), the CPU
idle time is measured to be 78.4%. The throughputs marked with the † are close to the PCI-bus
limit of 133 MB/s. We conclude that the COPPER and its CPU ensures enough performance401

CHAPTER 13. DATA ACQUISITION SYSTEM

COPPER board
FINESSEemulator

PrPMC
GE-Fanuc PSL09

FINESSEemulator

TT-RX

FINESSEemulator
FINESSEemulator

Figure 13.19: Block diagram of the test setup for the performance study of the COPPER readout
system.
Table 13.6: List of measured throughputs inside the COPPER board with varying the generated
data size and the level-1 trigger rate.
accepted rate [kHz] data size [kB/ev] throughput [MB/s]
50.0 ⋆
1.1
53
70.0
1.1
74
102.3
1.1
108
61.9
2.1
128 †
31.6
4.2
128 †
15.9
8.3
127 †
8.0
16.5
129 †

for the operation at the L1 trigger rate of 50 kHz.

13.7

Event Builder

The task of the event builder is to collect data pieces from all detectors, merge them into one
block, and send it to the high level trigger for the data reduction. The number of event builder
inputs in the Belle II DAQ system is estimated to be about 50, corresponding to the number ofreadout PCs, and the number of outputs is of an order of 10, corresponding to the number of
HLT units.
The event builder in the present Belle DAQ system is based on the concept of “switchless event
building,” where the event is built step by step using a number of PCs connected point-to-point
via Gigabit Ethernet[3]. Each PC receives event fragments from all upstream nodes, assembles
them into one record, and then sends it to a downstream node. These steps are repeated in
multiple layers of PCs. The PC in the final layer receives all event fragments from all detectors
and builds one complete event.
In the Belle II DAQ system, the estimated data rate reaches 9 GB/s at most under the averagetrigger rate of 30 kHz. The total flow rate is almost 500 times higher than that of Belle. The
approach based on the switchless event building is not cost-effective for such a high rate because
it would require far too many PCs.
The other approach to build the event builder is to use a large network switch as already adopeted402

CHAPTER 13. DATA ACQUISITION SYSTEM

src
src

dest
300kB/ev

src
src
src

dest
dest

Big Switch

dest

src

dest

src

dest

src

dest

Figure 13.20: Network switch for the event builder requires deep buffer at each output port.

by many other experiments. Modern network switches are equipped with many gigabit ethernet
ports that can connect a large number of PCs. When a trigger signal issued, data fragments from∼50 readout PCs are transmitted simultaneously to the event builder when a trigger is issued.
Since these data have to be sent to one receiver PC node to build the event, a heavy network
congestion is expected in the receiver. It causes the TCP restransmission which deteriorates
the data transfer performance. To avoid the TCP restransmission caused by the congestion, thenetwork swich has to have enough large buffers for each network port.
Recently large scale switches that are equipped with a deep buffer for each port become commercially available from several vendors, such as Force10, HP, and ARISTA. One has a 16MB
buffer for each port, which can be found in ARISTA products.
We studied the network performace using an ARISTA 7120T switch and observed the occuranceof the TCP restansmission. The testbench consists of four transmitter PCs and one receiver PC.
They are connected together by GbE links through the ARISTA switch. The transmitter PCs
send data packets to the receiver PC at a full speed. The result shows no TCP retransmission
is observed and the data transmission rate of four transmitter PCs are correctly balanced. We
are continuing the test by increaing the number of transmitters to 16 or more. If this scheme isconfirmed to work in such a large configuration, we will adopt the large network switch option
for our eventbuilder as shown in Fig. 13.20.
As a backup, we are also considering a layered event builder design combining PCs and small
network switches as building blocks of the barrel shifter[4, 5]. A large buffer can easily be
implemented on PCs to avoid the TCP retransmission in this design, however, its cost might
be slightly higher than that of the network switch. Using a switch component with 16 inputs
× 16 output, a large switch with 64 inputs × 64 outputs can be implemented as shown in
Fig. 13.21. Network switches are used in the upstream layer while downstream layer consists ofPCs, because the event data at the upstream layer is partially built and required buffer depth
is shorter than that at downstream. In order to reduce the number of PCs, one PC is desired
to house many GbE links, but it consumes more CPU power to transmit data.
We studied the CPU consumption of a PC connected to four transmitter PCs and four receiver
PCs connected through GbE. It is measured to be 75% of 1 CPU core of the PC (Intel W5590),
and we conclude that this option is feasible. The case with 10GbE link is also tested andfound that it provides a faster transmission with a little more CPU consumption. Since a fastertransmission from the switch to PC reduces the probability of the buffer full, we might use
10GbE link from a 16×16 switch component to PCs.

403

CHAPTER 13. DATA ACQUISITION SYSTEM

4 of 16x16

16 of 4x4

16x16

16x16

...............

16x16

16x16

Figure 13.21: 64×64 event builder by 16×16 and 4×4.

13.8

Data Processing Framework

13.8.1

Data processing in Belle II DAQIn the Belle II data stream, the following real-time data processing tasks are required at eachstage:
1. Detector front-end and data-link:a) the data reduction by zero suppression, the feature extraction from wave-form, etc.,
and b) the data collection and formatting at the channel level.
2. COPPER:a) additional data compression by sophisticated software processing, b) data collection
and formatting at the module level, and c) data monitoring.
3. Readout PC:a) data collection, formatting, and reduction at the subsystem level, and b) data monitoring.
4. High Level Trigger:a) event selection by full event reconstruction, and b) detailed data monitoring.
Except for the front-end processing that is performed on FPGAs, the processing platforms are
all Linux-based. The total processing power of these platforms is huge.
• COPPER: Each COPPER module is equipped with a Linux-operated Intel Atom chiprunning at 1.6 GHz. The expected data rate per module is 106 words/s. We will have anorder of a few hundred COPPERs for the DAQ.
• Readout PC: This is possibly a PC server equipped with dual Intel Core i7 running at
3.3 GHz, which is equivalent to eight cores. A total of ∼ 50 servers are connected to
COPPERs. A typical data rate per core is estimated to be ∼ 2 × 106 words/s.
404

CHAPTER 13. DATA ACQUISITION SYSTEM• High Level Trigger (HLT): The HLT consists of multiple units of PC clusters in which one
cluster consists of ∼ 20 PC servers with dual Core i7. With 10 units of PC clusters, thetotal number of cores is estimated to be ∼ 1600, with a data rate of ∼ 0.5 × 106 words/s.

13.8.2

Unified framework for data processing

Since the data processing after the Belle2link is performed on the same Linux platform, it isdesired to have a common software framework for this processing. We prefer that this framework
be compatible with the Belle II offline software so that the software development can be done
identically in the offline environment.
The DAQ software framework is required to have the software bus structure, where various
software components developed independently are plugged into the framework and work together
to process a common data stream. For the common data access by different software components,
the data should be formatted and managed using the same scheme.
Such a framework already exists in the Belle DAQ system. It is composed of the B.A.S.F.
framework [6] and the Panther [7] data management system. B.A.S.F. and Panther are developed
as the standard offline analysis framework for Belle. To use them in Belle’s DAQ data processing,the I/O interface of B.A.S.F. is modified so that it can send and receive event data throughthe UNIX socket to pass the data stream over the network, and the execution control of theframework is implemented externally through NSM [8]. This framework is commonly used on
COPPERs, event builder PCs, and reconstruction farm nodes. The processing software for theseplatforms is developed solely in the offline environment and then ported to the DAQ elements
without any modifications; this is found to be useful to minimize the development cost.
For the common framework in Belle II, compatibility with readily available modern offline software technology is key. The Belle II software should be fully object-oriented and based on
ROOT IO, so the framework must be capable of reading and writing ROOT IO objects. A new
framework named “roobasf” [1] is being developed for this purpose. This framework is designed
to meet the requirements of real-time processing; the socket I/O interface can be easily implemented as one of the selectable I/O packages for roobasf. Therefore, the unified DAQ frameworkfor Belle II can be realized by combining roobasf with the NSM interface. Figure 13.22 shows
the design of the unified data processing framework for the Belle II DAQ.

13.8.3

Object-oriented data flow

The object-oriented approach to data handling in Belle II is essential to realize the unified andoffline-compatible software environment. ROOT IO is the basis of our object-oriented data
handling, and the raw data from the detector frontends are required to be formatted in ROOT
objects at the very early stage.
Figure 13.23 shows the schematic view of the object-oriented data flow. The raw data fromdetectors are fed into COPPERs through the unified data link and formatted in ROOT objects.
The unified framework with roobasf runs on each of DAQ components and the processing results
are passed through UNIX socket connections.
To send an object’s data through a socket, the object has to be “serialized” to a plain byte stream
by the “streamer.” ROOT has the capability of generating the streamer code automatically fromthe class definition. However, since the raw data structure can vary widely across subdetectors,
the processing time for the streaming may become critical for complicated structures. A careful
treatment is required in the design of the class structure of the raw data to optimize the streamer
performance.

405

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.22: Unified processing framework

Figure 13.23: Object oriented data flow in DAQ

406

CHAPTER 13. DATA ACQUISITION SYSTEM

13.9

High Level Trigger

13.9.1Requirements and Global Design

In the high level trigger (HLT), a full reconstruction using the event data from all detectors is
performed and the software trigger for the event is made using the physics-level event selection
software.
Based on the experience with the real-time reconstruction farm (RFARM) [9] in the Belle DAQ,
two levels of software trigger are being considered for the HLT. The first is the so-called “Level3” trigger. After a fast track reconstruction (using the CDC data only) and a fast ECL cluster
reconstruction, this trigger makes a rough cut on the track multiplicity, the event vertex position,and the total energy deposition. Its expected reduction factor is estimated to be around 50%,
according to the Belle’s experience. The pre-selection by this trigger is useful to shorten the
average processing time for an event.
The second is the physics-level event selection using the full event reconstruction results. Almost
100% of the physics analyses in Belle are performed using the skimmed data set with the hadronic
event selection (for B and D physics analyses) or with the low-multiplicity selection (for τ lepton and two-photon physics). These event selection codes are used offline in the Belle dataprocessing, and their reduction factors are 14.2% and 9.6%, respectively, under typical beam
conditions for the events that have passed Level 3. We also need some pre-scaled samples of
Bhabha-scattering and µ-pair events for monitoring purposes; their pre-scaling rate can be as
low as ∼ 1%. With all of these selections, an overall reduction factor of ∼ 25% beyond Level 3
is expected. By combining these two reductions, the rate reduction factor by the HLT selection
is estimated to be ∼ 12.5%. In the design of the DAQ system, we assume the reduction factor
by HLT to be 1/5 = 20% considering the safety margin.
The actual trigger software on HLT is supposed to be the same offline software used in theoffline reconstruction to avoid introducing additional systematics different from that in offline
processing. The tracking and clustering software are developed as modules which can be directly
plugged into the HLT framework as well as offline framework. The physics analysis modules suchas the hadronic event selection and the low multiplicity skim are used as the real trigger software.
These software modules are well tested using the Monte Carlo simulations in offline and thenported to HLT without any modifications. Fig. 13.24 shows an expected data processing chain
at HLT and offline.
The trigger processing of an event data should be done, ideally, on a single CPU core in the
PC clusters of HLT. Its processing time (i.e., the latency) depends on the performance of thefull reconstruction software. Our experience at Belle shows the average (peak) time for all theL1-triggered events is about 0.5 (10) s/event on a single Intel Xeon core running at 3.0 GHz.
Therefore, about 15,000 such cores are required to process the Belle II events at a 30 kHz trigger
rate. By using a PC server housing sixteen cores, the total number of such servers required for
the HLT is about 1000, which can be accommodated in about 25 racks. We may consider theuse of GPUs to increase the processing power and to reduce the processing latency.

13.9.2Cluster Configuration

The accelerator luminosity is expected to increase gradually and the HLT processing power is
to be implemented on a demand basis. The HLT is modularized into a set of small PC cluster
units. Each unit is equipped with about 20 PC servers with > 10 cores per server running at
a >3 GHz clock, and is expected to process events at a rate of ∼ 1 kHz. We will start from407

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.24: The data processing chain at HLT and offline.

Figure 13.25: The High Level Trigger.
a configuration with ∼ 10 units, and add add units whenever more processing power becomes
necessary.
Figure 13.25 shows the structure of one PC cluster unit. L1-triggered events are fed into theevent distributor node through a 10GbE connection. The 20 PC servers (processing node) areconnected via network switch and the events are distributed to the nodes via a GbE connection.
A full event selection chain is performed on roobasf in each node and the selected events aresent to the output server node via the GbE connection. The output server node is connected
to a fast RAID system to record the raw data of selected events. In some cases, the processing
results are also recorded together with the raw data. The events are recorded in the “streamed”
format.

408

CHAPTER 13. DATA ACQUISITION SYSTEM

13.9.3

HLT software framework

To process the 30 kHz event data flow without delay, parallel processing is essential. Since theparallelization of the processing of a single event requires a special software treatment and ischallenging to implement, we consider instead the trivial event-by-event parallel processing in
HLT.
Two types of parallel processing mechanisms are implemented in the HLT software framework.
The first is the mechanism to utilize multiple CPU cores in a PC server. The Linux operating
system on the server treats the cores as SMP processors. A mechanism to distribute events tothese processors and run the actual processing software on each of them in parallel is necessary toutilize the multiple cores. The other is the parallel processing to make use of the PC cluster withthe 20 servers connected via a network. The event data from the event distributor connectedto the event builder are distributed to different servers through the network and processed inparallel. The processing results are gathered again by collector nodes in a reverse way andrecorded in the high speed RAID system. The software framework to control such a distributed
parallel processing in the cluster is necessary.
This “type 1” parallel processing is already implemented in the core of roobasf and each HLTprocessing node utilizes the capability. The second type will be implemented by extending thetype 1 parallel processing in roobasf. The “event server” and “output server” processes in theroobasf core can accept data from and feed data to the network socket; the events from the event
distributor node are directly fed into the roobasf core on each node and vice versa to the output
collector node. The current design of this “type 2” parallel processing in the HLT is shown in
Fig. 13.26.
There are several candidates for the overall control scheme of the PC cluster for type 2 parallel
processing. The baseline design is to recycle the scheme used for the Belle RFARM, which isbased on NSM [8].

13.10

Slow control

The slow control system must
• control the start and stop sequence of the entire data acquisition system,• collect the status and messages of the data acquisition subsystems,• control the HV system, and• collect various monitor information.
These functions are realized by a software package called the “Network Shared Memory” (NSM).
This software handles point-to-point message passing using TCP and shared memory over a
network segment using UDP broadcast.
The expected number of systems to be controlled is not expected to increase over that in Belle,so the existing system can be used without modification.

13.11

PXD integration

Since the expected event size from the PXD is very large (∼ 1 MB/event), it is quite difficult
to manage its readout using COPPERs. Therefore, its integration into our DAQ is mismatched
409

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.26: Type 2 parallel processing in HLTwith our global design of Fig. 13.1. In addition, it is also very hard to leave such a huge amountof data in offline storage as is because of the limitation in the storage and computing cost. It
behooves us to consider methods for data reduction from the PXD by a factor of ten or more
before this stream is combined with the data from other subsystems.
There are two ways to reduce the PXD data flow rate. One is to reduce the size of each event.
The raw data from the PXD contains many noise hits in addition to the hits associated withreal tracks. If we send only the PXD hits that are near bona fide tracks to the event builder, thedata size is dramatically reduced. The other way is to reduce the number of events sent by the
PXD. If we send the PXD data only for triggers tighter than L1 trigger (after HLT selection,for example), the PXD data flow rate is reduced.
Figure 13.27 shows these two solutions for the PXD integration into the DAQ: the upper figure
shows the option 1, while the lower shows option 2.
Here, we describe each integration option.
• Option 1
A number of special modules in a ATCA crate[10], which were originally developed foruse in the HADES and PANDA experiments, receive data from the PXD DHH over the
RocketIO link together with the SVD and possibly CDC, where the SVD and CDC data
are branched from the main data stream. In each module, five Virtex 4 FPGAs performthe track finding, track reconstruction, and association with PXD hits. The track finding
and reconstruction is done using the SVD and CDC hit signals. The module send out only
the PXD hits associated with tracks to the event builder over the GbE link.
410

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.27: Two options for the integration of the PXD data stream into the DAQ system.
Top: baseline option, in which the size of each PXD event is reduced. Bottom: substituteoption, in which only selected PXD events are read out.

411

CHAPTER 13. DATA ACQUISITION SYSTEM• Option 2 and 2’
The PXD data are fed into either the same ATCA boards as in option 1 (called Option2) or into PCs (called Option 2’) from the PXD DHH over the RocketIO link, whereas
the SVD and CDC data are not fed into them. Instead, the processing result of the
HLT, containing the event tag and parameters of the tracks in the event, are sent to the
ATCA boards (or PCs). Since the full event reconstruction is performed by the HLT using
the offline software, the track parameters can be obtained therefrom without additional
software. The track parameters are sent to all ATCA boards (or PCs) and the hit-track
association is performed. The selected hits are sent to the second-level event builder
through GbE connection so as to combine with the data from other detectors.
In this option, because of the large latency—up to 5 seconds—of the HLT processing, alarge memory to buffer the PXD data stream during this latency is required. The memory
size is estimated to be at least 3 GB for each of the 40 DHH data streams.
The design of the second-level event builder has different aspects from the one describedin the previous section. Since the event sequence in the HLT output is disordered becauseof the parallel processing nature, and also the event number from the output of each HLTunit is not the same, a different approach to the event building is required. The design is
now in progress.

13.12

Data reduction

There are two aspects to data reduction: the reduction of the event size and the reduction of thetrigger rate. The data size reduction is expected to be done primarily by the FPGA processingin the front-end readout. The data size after this reduction is estimated to be 100 kB/event, aspreviously described. We can expect more reduction by the software processing on COPPERs
and readout PC’s; however, we currently do not consider the latter reduction in the design of
the DAQ system.
The reduction of the PXD event size depends on the integration option. In the case of option
1 where the track reconstruction is done by the fast FPGA processing, we currently estimate
the reduction factor to be 1/5 due to the limited performance of the hardware tracking. In
the case of option 2 or 2’, the factor is expected to become 1/10 or less thanks to the precise
measurement of track parameters made possible by the HLT software processing. The event size
from PXD after the reduction is, therefore, estimated to be 200 kB for option 1 and 100 kB for
option 2.
The reduction of the trigger rate solely relies on the HLT in our DAQ design, as described in
the previous section. The reduction factor is estimated to be 1/5 or less.
Table 13.7 shows the estimated data flow for several cases. The detail of the data reduction
steps is also shown in Figs. 13.28 and 13.29 for the two PXD integration schemes.

412

CHAPTER 13. DATA ACQUISITION SYSTEM

Event size of PXDEvent size of other detectors
PXD reduction factor
Event size of PXD after reduction
Total event size
Level1 trigger rate
HLT reduction
Rate at storage
Bandwidth at storage

Worst I
1 MB
100 kB
1/5
200 kB
300 kB
30 kHz
1/5
6 kHz
1.8 GB/sec

Worst II
1 MB
100 kB
1/10
100 kB
200 kB
30 kHz
1/5
6 kHz
1.2 GB/sec

Modest I
0.5 MB
50 kB
1/5
100 kB
150 kB
20 kHz
1/5
4 kHz
600 MB/sec

Modest II
0.5 MB
50 kB
1/10
50 kB
100 kB
20 kHz
1/5
4 kHz
400 MB/sec

Table 13.7: Estimates of data flow for several cases. Worst I and II cases are obtained with theassumptions of the maximum event size with a safety factor 2 and the trigger rate of 30 kHz.
Modest I and II are with the typical event size and trigger rate. I and II are the cases for the
option 1 and 2(2’) PXD integration schemes, respectively.

Figure 13.28: Data reduction steps for option 1 PXD integration (Worst I).

413

CHAPTER 13. DATA ACQUISITION SYSTEM

Figure 13.29: Data reduction steps for option 2 PXD integration (Worst II).

414

References[1] S.H.Lee, R.Itoh, and N.Katayama, Proceeding of CHEP2009, Prague, 21-27 Mar. (2009).
[2] T. Higuchi et al.,IEEE
dx.doi.org/10.1109/TNS.2005.856913.

Trans.

Nucl.

Sci.

52,

1912

(2005),[3] M. Nakao et al., IEEE Trans. Nucl. Sci. 48, 2385 (2001), dx.doi.org/10.1109/23.983273.
[4] O.Sasaki et al., IEEE Trans. Nucl. Sci. 40, 603 (1993), dx.doi.org/10.1109/23.256625.
[5] S.Y.Suzuki et al., IEEE Trans. Nucl. Sci. 47, 61 (2000), dx.doi.org/10.1109/23.846118.
[6] R.Itoh, Proceeding of CHEP1997, Berlin, 7-11 Apr. (1997).
[7] S.Nagayama, Panther User’s Guide, http://belle.kek.jp/group/software/panther/,
1997.
[8] M. Nakao and S. Suzuki,
dx.doi.org/10.1109/23.846161.

IEEE

Trans.

Nucl.

Sci.

[9] R.Itoh, Proceeding of CHEP2004, Interlaken, 27 Sep. - 1 Oct. (2004).
[10] Z.-A. Liu et al., Talk at Real Time 2009, Beijing, 10-15 May (2009).

415

47,

267

(2000),

Chapter 14

Computing and Software
14.1

Overview

The Belle experiment [1], over its ten-year operation [2], was supported by a centralised computing facility at KEK, where almost all data processing, MC production and physics analysis
was performed. The system was well designed for the amount of data and worked smoothly.
However, the Belle II computing system has to handle an amount of data eventually corresponding to 50 times the Belle level by the end of 2020. This means an amount of raw data of theorder of 1010 events per year. It is required that this data be processed without any delay to theexperiment data acquisition, in addition to the production of MC events corresponding to atleast 3 times of real data. Moreover, computing power for physics analysis has to be provided.
To ensure sufficient computing resources to carry out our physics program, we have to enable
all Belle II member institutes to contribute. Therefore, a distributed computing model basedon the grid will be adopted. KEK will host the main center that is responsible for raw dataprocessing. Grid sites allow users to produce ntuples from skimmed datasets; they also handle
MC production, possibly complemented by Cloud Computing facilities. Finally, users analyze
ntuples on local resources. The computing model is discussed in detail in Sec. 14.2.
The data management system is essential to enable users to effectively and smoothly analyze
datasets. Due to the limited resources and short time-line in the preparation of Belle II computing, distributed computing concepts from other successful experiments have been adopted. The
key ideas reused are metadata and project structure from D0 and CDF experiments, keeping
the system as simple as possible, and the use of grid (gLite) services as much as possible, as in
the LHC experiments. The technical details of the data management system are described inSec. 14.3.
C++ has been adopted as the programming language for the offline software, but the use ofpython is also allowed when it shows clear advantages. Physics analysis is supported by providing
a framework that allows users to ‘plug in’ appropriate reconstruction modules for their specificneeds. To realize this, a common software framework, where each module can handle the event
data through an unified method such as ROOT I/O based object persistency, is desired. Other
processes, such as DST processing, simulation, and data skimming, are done within this common
framework. The simulation and reconstruction tools are developed mainly by Belle II computing
group members, supplemented with the standard tools in the field of high energy physics. Offline
software issues, including the geometry handling method, are covered in Sec. 14.4.
In Sec. 14.5, the required human resources to support and maintain the proposed distributed
computing system and associated software are discussed. Additionally, the requirements forcomputing hardware based on the design luminosity of the SuperKEKB accelerator are esti416

CHAPTER 14. COMPUTING AND SOFTWARE

mated.
In summary, Belle II has decided to employ a world-wide distributed computing system andto use state-of-the-art tools and concepts in the offline software. To develop, establish andoperate this system successfully, substantial resources are needed, both human and hardware,at the main computer facility at KEK and at grid sites at the local institutes of the Belle II
collaborators.

14.2

Computing Model

This section details the Computing Model for the Belle II experiment. The purpose of the model
is to provide all members of the collaboration easy access to experiment data and facilities
on which to process it, in addition to ensuring the resources for processing and storage are
distributed accordingly.

14.2.1

Basic Considerations and Outline

To reach our goal of publishing high-quality physics results in a timely manner, the Belle IIcomputing system has to accomplish several tasks. The raw data taken by the detector andrecorded by the data acquisition system has to be stored. After calibration constants dependent
on the condition of the accelerator and detector have been determined, the raw data is processed
and the derived higher-level information is stored in smaller files (mDST). Subsets composedof selected events are the input to physics analyses, which usually create files containing evenhigher-level, more condensed analysis-specific information in a user-defined format. While theproduction of these files, called ntuples, is typically done only a few times, the ntuples themselves
are processed frequently, requiring the turn-around time for this step to be fast.
In addition to the real data, high-statistics samples of simulated data (Monte Carlo, or MC) areneeded to derive physics quantities from the real data. Generic MC samples corresponding toseveral times the statistics of real data are created so that they reproduce the conditions in real
data as faithfully as possible. Much smaller samples of simulated signal events are generated forindividual analyses. The output of the MC simulation are mDST files, from which ntuples areproduced that are analyzed in the same way as is done for real data.
To accomplish these tasks, the Belle II computing model uses a grid-based approach, with adispersed set of facilities connected by a common software layer (the ‘middleware’). This is afundamental change compared to the computing model of Belle, where almost all computing
resources for raw data processing, MC production and physics analysis were provided by KEK.
With an anticipated data sample of about 50 times the size of the Belle data over ten years,
the computing resources required to process and analyze it increase faster than the projected
performance of CPUs and storage devices. Therefore, we cannot expected KEK to provide allcomputing resources for the whole Belle II collaboration. In addition to sharing the responsibility
for the construction of the detector, we have to share the allocation of computing resources among
the Belle II institutions.
However, not all tasks described above are equally suited for a distributed system. Because theraw data is produced at KEK—the location of the Belle II detector—this site is distict fromother centers. It will play the role of a main center and be responsible for the processing andstorage of raw data as well as the operation of central services. Thus, it has to provide a highavailability of at least 98%. As MC production can be distributed easily, we will use grid sites
for this task. We also envision analyzing the produced MC samples and replicated real data
samples on the grid. The distribution of grid sites should reflect the geographical distribution
417

CHAPTER 14. COMPUTING AND SOFTWARE

of Belle II collaborators. The fractions of resources will be determined by a Memorandumof Understanding. Together with KEK, the remote grid sites form the bulk of the Belle IIcomputing resources and their deployment and operation is coordinated centrally. For efficiency
and scalability, experiment-specific services will most likely to be distributed globally to selected
grid sites.
While ntuple-level analysis could be done on the grid as well, a fast turn-around time usuallyrequires having the ntuples available on resources local to the user. These local resources are
ideally grid-enabled, but we explicitly include non-grid resources, like private clusters at institutes, desktops or laptops, for which we will provide means to install the software needed for
ntuple analysis and for access to the Belle II grid system.
The classification into main center, grid, and local resources describes the tasks for which theresources are used. Physical sites may contribute to more than one task. For example, KEK will
provide resources for raw data processing, MC production and data analysis, and ntuple-level
analysis. Figure 14.1 illustrates the relation between physical sites and their function.

Figure 14.1: Tasks of computing facilities.
We will use grid technology, based on the EGEE middleware gLite [3], to manage the increased
complexity due to a distributed computing model. This allows us to benefit from the infrastructure that was developed and is maintained for the LHC experiments. By the time the BelleII experiment will start taking data, the LHC experiments will have collected data for a few
years. We will profit from their experience and will have well-established and mature solutionsat hand.
While the operation of a distributed computing system requires more human resources than acentralized one, the application of standard grid technologies will help to minimize the additional
effort. Moreover, many Belle II member institutes already have running grid sites and the
addition of support for Belle II requires much less effort than the setup and operation of dedicted
remote computing systems, a solution that was adopted for the distributed MC production at
Belle.

14.2.2Cloud Computing

An important fact we have to consider in the design of the computing model and the planningof resources is the variation of resource demands with time. Two effects on different scales are
involved. First, there is a steady increase of required resources because of the growing data size.
418

CHAPTER 14. COMPUTING AND SOFTWARE

This is taken into account in the planning on a yearly basis. Second, there are variations on ashorter time scale of months or weeks.
One reason for the short-term variability is that the raw data processing and the MC production
can only start after a data taking period (which usually lasts several months) has finished andcalibration constants have been determined. To have the data and MC ready for analysis ina timely manner, it is advantageous to save CPU resources during the data taking phase andspend them when the processing phase starts. However, CPU resources can not be easily saved
because idle CPU time is lost and can not be regained. To some extent, this issue can be solved
by fair-share mechanisms when several virtual organizations on the grid share CPU resourcesat the same site. However, it is unlikely that the resource demands of all virtual organizationsbalance each other at all times.
Another case of varying resource demands comes from the physics analysis. Experience has
shown that the request for CPU resources usually increases before important physics conferences.
In this particular case, the fair-share mechanism will probably not provide additional resources
because the conference deadline typically applies to all high energy physics experiments.
Computing system are usually designed to match the expected peak demand. This has the riskof a resource shortage if the demand exceeds the expectation. This situation is illustrated inFig. 14.2 a). Cloud computing can provide a solution by offering the possibility to purchase CPU
resources for a limited amount of time. This mitigates the problem of a CPU resource shortagedue to unexpectedly high demand, as financial resources can be transformed into CPU resources
almost instantaneously. Figure 14.2 b) demonstrates the advantages of cloud computing.

Figure 14.2: Comparison of a classical system a grid sites (a) and a system utilizing cloud
resources in addition (b) for the case of varying resource demands.
In contrast to publicly funded grid sites, the cloud computing facilities are usually operated bycommercial companies. This may change in the future, as a clear trend towards cloud computing
technologies can be observed in the grid computing development. Although more and more cloud
facilities funded by governments may emerge, the aspect of buying resources from a company
that aims for financial profit deserves special attention. There is, in particular, the issue of apotential vendor lock-in, which we must avoid. For this reason, we do not plan to use cloud
resources for permanent storage of real data or MC. In the worst case of a disappearing vendor,
relying on cloud storage could result in the unacceptable risk of data loss.
The risk of a vendor lock-in is less severe for CPU resources, as no commitment to buy fromthe same vendor in the future is involved. However, we have to design our software in a way
419

CHAPTER 14. COMPUTING AND SOFTWARE

that the technical issues of a vendor change are solvable with reasonable effort. The technicalaspects of making cloud computing resources available to Belle II are discussed in Sec. 14.3.6.
An evaluation of the cost of cloud resources is presented there as well.
To summarize our strategy concerning cloud computing, we see that this technology has a highpotential and we feel obliged to keep the possibility of using it for Belle II. While our baselinecomputing resources will be provided by grid sites, cloud computing will be an option for peakdemands in MC production or physics analysis.

14.2.3

Raw Data Processing

As outlined in Sec. 14.5, the expected raw data size is of the same order of magnitude or evenlarger than the one of LHC experiments. The storage and processing of raw data therefore
require considerable resources. Given the amount of data, the cost of storage is an importantparameter. Currently and in the foreseeable future, the best ratio of cost/PB is provided bytape systems. Compared to disks, tapes also have the advantages of being storable in libraries
and consuming no power when idle. Their drawbacks are their inherently sequential access andthe high latency associated with the mechanical mounting of tapes in an available tape drive.
Since raw data is stored only once and read only very few times for the (re)processing, andbecause this is done in a managed way, these limitations are acceptable. Thus, we use magnetic
tape libraries as the storage technology for raw data.
The raw data has a well-defined source: the Belle II detector. Therefore, the raw data processing
chain has to start at KEK. While HEP experiments traditionally perform all data processing
steps at the site where the detector is located, LHC experiments decided to ship raw data toremote Tier1 sites for reprocessing.
Given the similar order of magnitude of total raw data size compared to LHC experiments, we
explored a distributed raw data processing model as well. However, we decided against thisapproach for the following reasons.
The distribution of raw data shares the load of storage and processing among sites, but it does
not reduce the overall resource requirements. On the contrary, the maintenance effort for theoperation of a raw data processing center scales with the number of sites. Each site has tooperate a tape system, which has been shown in the past to be a labor-intensive task. The
requirements are exacerbated if the raw data has to be imported almost synchronously with its
production at the detector. An operation with an efficiency close to 100%, 24 hours a day, 7days a week, is needed in such a case. Such a quality of service has to be ensured for the tapesystem and for the network connection. Moreover, the network traffic caused by the distributionof raw data is huge. Therefore, the storage and processing of raw data is concentrated at KEK
in our computing model.
Having no backup copy of the raw data increases the risk of raw data loss, for example in thecase of a fire. This risk has been taken by most pre-LHC experiments, including Belle. Since thereconstructed mDST data will be copied to remote sites, we will still have all data for analysis
available in case of a complete data loss at KEK. The possibility of reprocessing would be lost in
this situation but, given the additional effort of a raw data backup, this risk seems acceptable.
Of course, if the resources for a raw data backup would become available to us, we would revise
our decision.
In addition to the tape system with appropriate disk buffers, the CPU resources to process theraw data are needed at KEK. The number of required CPU cycles depends on the time period inwhich we want to finish the reconstruction. This enters our computing model via the parameter
TData , the time anticipated for the processing of the data taken in one year. In the interest of a420

CHAPTER 14. COMPUTING AND SOFTWARE

timely analysis, this parameter should be as small as possible.
The possibility of reprocessing data in case of updated calibration constants or new reconstruction code has to be taken into account in the computing model as well. One option is to utilize
the idle CPU resources between phases of processing new raw data. As the reprocessing will
likely happen more frequently in the start-up phase of the Belle II experiment, we may store theraw data during this period not only on tape, but also on disk, to achieve a fast turn-aroundtime.
The first step in the processing chain is the determination of calibration constants. Only a small
fraction of the total data sample is needed to perform this task. The calibration data files (DST)
will be written to disk in parallel with the storage of raw data on tape. After the calibration
constants have been determined and written to the central database, the raw data is read fromtape and the reconstruction software is run on it. The output of the reconstruction are mDST
files that are stored on disk. Several samples of preselected events, called skims, are created andstored in mDST format on disk as well. The selection criteria are adjusted to different classesof analyses. The mDST files are the input for all physics analyses, described in Sec. 14.2.5.

14.2.4Monte-Carlo Production

For most analyses, it is essential to have an accurate simulation of signal and background events.
To provide this, generic, run-dependent MC datasets are produced. To limit the systematic
uncertainty associated with the number of simulated events, a MC sample corresponding to
Nstreams times the data size is created, where Nstreams is a parameter of the computing modeland should be at least 3. At Belle, Nstreams is usually set to 10, a reasonable value to havesufficient MC statistics.
In contrast to the raw data processing, the production of MC data requires no input data,
except for some constants and a few background files. This makes this task very well suited fora distributed environment. We plan to share the MC production work among the grid sites.
The production will be planned and managed by a MC production coordinator in collaboration
with the Distributed Computing and Data Management Group Convener. If appropriate, cloudcomputing resources may be used as well.
In addition to the integrated luminosity and Nstreams , the needed CPU resources depend on thetime period, TM C , in which the MC corresponding to one year of data taking is produced. The
parameter TM C should be of the same order as TData to avoid delay in physics analyses due tomissing MC samples.
The output of the simulation jobs are files in the same format as processed real data. The MC
mDST files are stored on disk at the storage element close to the site where they are produced.
Cloud computing jobs need a nearby storage element, too. Their output will not be stored on
the cloud, but transferred to storage elements at grid sites. Like the data mDST files, the genericMC samples are the input for physics analyses.
Some analyses need further specific samples of high statistics simulated signal events. If thesesignal MCs are of interest for several people, they will be produced at one or more grid sites ina managed way, like generic MC. The output is made available to all collaborators on a nearby
storage element. The production of very specific signal MC samples is treated as part of thephysics analysis and is not coordinated centrally.

14.2.5

Physics Analysis

The aim of the Belle II experiment is to produce physics results. Thus we have to provide
efficient, reliable, and user-friendly access to data and CPU resources so that people can focus
421

CHAPTER 14. COMPUTING AND SOFTWAREon the physics analysis.
Since the processing of mDST data files is an essential part of all analyses, we will replicate
mDST data skims to grid sites. The replication process is managed by the Distributed Computing and Data Management Group Convener and the Site Representatives, but not triggered
automatically by the user. The decision of which dataset to be copied where depends on thesize of the site and the physics topic(s) the users at that center are interested in. If it seems
beneficial, generic and signal MC samples can be replicated in a managed way as well.
The usual method to analyze the data and MC samples is the creation of ntuples. For this task,
the user submits grid jobs that run at the grid sites. A front end will be provided to facilitate
the bulk submission of jobs to the centers that have the dataset of interest. We pursue two
approaches: a simple push model and a more sophisticated pull model that allows for a better
steering of assigned resources.
It is essential for an analysis that each input file of a dataset is processed exactly once. To
achieve this, we consider two options: a static and a dynamic assignment of files to jobs. The
details of both options, as well as of the job submission tool, are described in Sec. 14.3.
The output of the analysis job, the ntuple, is eventually stored on resources local to the userthat initiated it. This could mean that local storage space has to be made accessible from gridjobs, typically via a grid storage service; alternatively, grid sites may provide limited temporarystorage to buffer the job output until the user can copy it to their local storage space.
The analysis of the ntuples can then be done entirely on local resources. No grid infrastructureis needed at this stage.

14.2.6

Summary

The Belle II computing model assumes the following structure based on grid technologies:• The main center is located at KEK and is responsible for the raw data storage and processing. In addition, it provides several central experiment-specific services, like the conditions
database, and grid services, like the file catalog and the virtual organization management.
The main center is expected to have 24x7 operations, designed for extreme reliability. Staff
dedicated to maintaining grid services, supporting users, managing the virtual organization, liaising with other sites are required.
• Grid sites provide computing resources geographically close to the users. KEK will havethe role of a grid site, in addition to the role of the main center. Grid sites provide resources
for the managed production and storage of generic MC samples. They also host replicas
of data skims and allow users to produce ntuples from data and MC samples.
• Ntuple-based analyses are usually performed on local resources (desktops and instituteclusters).
Additional processing resources for MC production and analysis may be provided by cloudcomputing in case of peak demands. Figure 14.3 illustrates the Belle II computing model.

14.3

Distributed Computing and Data Management

14.3.1

Overview

Belle II will make extensive use of distributed computing solutions built upon gLite[3] middleware. By doing this, we leverage the many hundreds of man-years of development from the
EGEE [4] and WLCG [5] projects and their predecessors.
422

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.3: Concept of the Belle II computing model.

The gLite middleware enables both data and CPU resources to be located at a variety of sitesaround the world. It also enables the movement of data between storage resources and allows
jobs to run at sites with CPU resources.
We plan to deploy most pieces of the gLite middleware used by the LHC experiments. In
addition, we plan to develop a new piece of middleware, the “Project Server,” to steer particulartasks amongst Belle II’s distributed compute and data resources.
To simplify the model and ensure only data of interest is located at grid sites, we do not intend
to automatically distribute data. Instead, administrators will migrate selected data to sites at
the request of users.
Since the centers will provide substantial computational resources beyond that of KEK, we
expect that data skims in high demand may be duplicated across the Belle II network.
Consequently, it is essential that all data, whether real or generated from MC, along with dataskims be registered in a central database, called the LCG File Catalogue (LFC). The LFC willrecord the location of the every physical location (PFN) against a logical reference (LFN/GUID).
In addition, each logical data item (files, datasets) will have associated metadata recorded in
an AMGA metadata catalog. The metadata catalog will greatly increase the ability of users toquickly find data of interest.

14.3.2Analysis Model

An important part of physics analyses, and raw data processing, is the processing of a set of
selected files with a given piece of (user-written) analysis code. We call this task a project. To
obtain correct physics results, it is essential that each input file is processed exactly once. If files423

CHAPTER 14. COMPUTING AND SOFTWARE

are missed or files are processed twice, the obtained result of the analysis is most likely wrong.
Thus, we have to design a system that minimizes the risk of failing this requirement.
As the number of files belonging to a project is usually large, their processing is done in several
jobs. From the system’s point of view, all these jobs are independent and unrelated. However,from the user’s point of view, they belong to one project. This means we have to provide acomponent on top of the grid job layer that allows the user to interact with it on the level ofa project. This includes the job submission, the monitoring of the progress, and the recovery
of failed jobs. The last part is of particular importance to fulfill the requirement of processing
each file exactly once.
Our strategy for the development of the project component is to start with a simple system andthen investigate further options that would increase the convenience for the user, but also thecomplexity of the system.
The first problem we have to solve is to identify the right files that should be used as input fora project. For this task, we set up up an AMGA metadata server, described in the next section.
It allows the user to get a list of files, in form of GUIDs, that match certain physics-motivatedcriteria. For example, the user may wish to “run over all full reconstruction skims of datacollected between June 2013 and January 2015.”
The next issue is to determine where the files are located on the grid and, thus, to which sites
the jobs that process these files should be submitted. The first part is solved by the LCG File
Catalog (LFC). It matches GUIDs to physical locations of files in form of Storage URLs (SURL).
To shield the user from the interaction with the AMGA server and the LFC and to manage
the grid jobs on a project level, we will provide a project client. The client will be part of theBelle II offline software and installed on the local machine of the user. Authorization will be
performed with proxy certificates. When the user wants to start a project, they call the clientand provide the following information:• A string with a metadata query to identify the input files.
• A tarball containing the analysis code.
• The name of the script inside the tarball that should be executed.
• The release version of the Belle II software that should be used.
• The desired number of jobs, or alternatively the desired number of input files per job.
The project client then talks to AMGA and the LFC to get the list of GUIDs and matching
SURLs. Based on the SURL, it determines the sites where the data file are available. Then it
submits the desired number of jobs to these grid sites. All jobs may be submitted to one siteor they may be split across several sites. Optionally, the user can provide a list of preferredsites. The job submission system will be based on some lightweight service for job management
operation at the Computing Element (CE) level. A candidate for this is the CREAM (Computing
Resource Execution And Management) [6] service.
The input files are distributed equally to all jobs. The assignment of files to jobs is realized bycreating a script for each job and setting an environment variable in this script to the assigned
SURLs. The script that is run at the CE then executes the user code after setting up the rightsoftware version. An input module in the analysis framework will evaluate the environment
variable and process the assigned files.
To store the output file(s) on an SE and register them in the LFC and AMGA, a tool will be
provided within the Belle II software. It selects either the nearest SE or a predefined one that424

CHAPTER 14. COMPUTING AND SOFTWARE

the user specifies at job submission. A fall-back solution, if the selected SE is unavailable, may
be implemented.
In addition to submitting the grid jobs, the project client will store the list of GUIDs, selected
SURLs, and corresponding job identifiers in a local file. This allows one to identify the project
via the local project file.
Now the user can query the project client for the status of their jobs by providing the name ofthe project file. From the project file, the client reads in the job identifiers and determines theirstatus via standard grid mechanisms. The status of successfully finished and failed jobs will berecorded in the project file to avoid further unnecessary queries.
Based on the status information in the project file, the client can also easily either resubmit
all failed jobs or generate a new project containing only the unprocessed files. This recovery
mechanism simplifies the bookkeeping effort for the user enormously.
Figure 14.4 summarizes the procedure of starting a project. Not shown in the diagram is theconditions database used to provide the calibration and alignment constants. This database will
be distributed to each site.

Figure 14.4: Outline of user interaction with the project client to submit jobs to grid sites forthe analysis of a dataset defined by a metadata query.
As an extension of this baseline system, we investigate the idea of a dynamic assignment of
input files to jobs, inspired by the success of this concept in the SAM [7] system employed by
the CDF and D0 experiments. To realize this mechanism, the project bookkeeping has to be
moved from a local file to a central service known as the project server.
Now, the project client just passes on the metadata query to the project server when the user
starts a project. The project server contacts AMGA and the LFC as the client did in the simple
model. Instead of a local file, a database is used to store the list of GUIDs. The list is identified
by a unique number, the project ID. It takes over the role of the project file name. The project
server returns the project ID to the client together with a list of sites on which the data is425

CHAPTER 14. COMPUTING AND SOFTWARE

available.
The client prepares a single job script with the project ID in an environment variable. The
desired number of jobs is submitted to the site (or sites) indicated by the project server withthe same single job script. The procedure up to this point is illustrated in Fig. 14.5.

Figure 14.5: Start of an analysis project in the case of a dynamic assignment of files to jobs.
Upon execution at the CE, an input module of the analysis framework contacts the project
server with the project ID obtained from the environment variable. From the project ID, theserver knows which input files should be processed. It picks a file that is available at the sitewhere the job runs and returns the SURL to it. This mechanism of dynamic assignment of afile to a running job is depicted in Fig. 14.6.
In the database, it is noted that the file was given to a job by assigning the job ID to the file.
The analysis job processes the delivered file and contacts the project server again when it is donewith the file. The successful (or unsuccessful) processing of the file is recorded in the databaseand another file name is returned if requested. Once the job has processed a maximal numberof input files or there are no unprocessed files left, the analysis program stops, the output fileis written to a SE, and then the job informs the project server about a successful completion of
its task.
The project client returns the project ID to the user when the project is started. With thisID, the user can request the status of their project from the client or ask it to generate arecovery project. The client then talks to the project server to accomplish both tasks as shownin Fig. 14.6. From the user’s point of view, the static and dynamic file assignment systems differ
only by the way how projects are identified (local file vs. ID).
The extended approach is certainly more complex and introduces a further possible single pointof failure, the project server. But it has several advantages:• The job submission preparation is much easier. It is no longer necessary to have many
individual jobs with a static assignment of input files to jobs. All jobs are identical. They
just have to know the project ID, which is common to all jobs.
426

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.6: Interaction between a grid job and the project server to dynamically assign an
input file, and (in italic font) the handling of a user query to obtain the status of a project.
• A more fine-grained monitoring is possible. The progress can not only be measured interms of finished jobs, but also in terms of processed files.
• It is ensured that only properly running jobs get data assigned. If a site is misconfigured
so that the analysis program cannot be executed, no files are assigned to jobs at this site.
Thus no recovery of these jobs is needed. In case of a resubmission, in the simple model therecovery procedure would not work for misconfigured sites. In the system with dynamic
file assignment, only properly working sites are used for processing.
• The overall time to finish a project is reduced. In the diverse grid environment, the timethat jobs wait in a batch system queue and the performance of the execution host can varysignificantly. In the simple model, the end of a project is reached when the slowest job has
finished all its input files. In case of a dynamic file assignment, there is an automatic loadbalancing between jobs that start earlier or run on a faster host and jobs starting later oron a slower host. The former will request and process more files than the later ones. In
this way, the time to finish a project is no longer determined by the slowest job.
Both systems, with static and dynamic file assignment, can be easily extended for the purpose of
run-dependent MC production, as explained in Sec. 14.3.5. In this case, the file is just replacedby the input information for the MC job: experiment number, run number, and total numberof events that should be generated (Fig. 14.9).
14.3.2.1

Pilot Model

Keeping track of the availability and status information of every resource in a virtual organisation
in a timely fashion is a challenge. Furthermore, using this data to schedule jobs optimally froma central location is an NP-complete problem [8].
427CHAPTER 14. COMPUTING AND SOFTWARE

Recently, many large grid users have moved toward a late-matching job submission model, or
pilot model. In this approach, ‘pilot’ jobs containing a script to obtain real jobs from a central
task queue once executing on a worker node are submitted to all grid sites. This moves thematching of resources to jobs to the worker nodes themselves, greatly reducing the load on
central services.
There are several auxillary benefits to this approach, including allowing the assignment of priority to user jobs on a virtual-organisation wide basis, verification of environment suitability
and confirmation of resource availability. The only disadvantage of the pilot model is that it
requires additional components for the job management that are not provided by the genericgrid middleware. However, many experiments have working solutions, and we are evaluating
how these can be adapted to Belle II.

14.3.3

Metadata

An essential requirement for the Belle II computing system is the ability to select a set of files
for processing according to physics criteria. For example, users may want to analyze the dataof certain data taking periods, called experiments. Other frequently used selection criteria are
the type of preselected sample, called a skim, and the version of code with which the data wasreconstructed. Such information has to be known for each file to decide whether it should be
included in the input data of the processing jobs using it. Information about the type of datacontained in a file is called metadata.
For the Belle II experiment, we need a reliable and efficient metadata service that translates
selection criteria into a set of files. There is already a metadata service at the Belle experiment. However, the existing metadata service has problems with performance, scalability, androbustness, which makes it inappropriate for Belle II. Moreover, the solution applied by Belleis not intended to be used in a distributed environment. Therefore, we design our metadata
service based on AMGA (Arda Metadata catalog for Grid Application) [9] in order to solve these
problems.
AMGA is the official metadata service for EGEE, which is designed to allow high performanceaccess to metadata suitable for the demands of applications in high energy physics. AMGA isdesigned to ensure good performance and scalability, grid-based authentication, database connection pooling, a hierarchical table structure and a replication mechanism. We have designed
an AMGA schema, with which the metadata service has been implemented for the Belle IIexperiment. In addition, we have implemented a user-friendly command line tool for metadata
queries.
The metadata is extracted from the data files that are written to storage resources and used tofill the AMGA metadata catalog. Using the catalog, a user query is translated into a file list anda list of sites where the data is available. This information is used to submit jobs that process
the requested data as shown in Figs. 14.4 and 14.5.
In addition to this file-level metadata, we are also investigating the idea of using AMGA forthe selection of events based on event-level metadata. This may considerably speed up analyses
that select only a small fraction of events in a large dataset. Unfortunately, the large number of
events increases the size of the metadata catalog by at least one order of magnitude comparedto the file-level only solution.
14.3.3.1

Metadata Schema Definition

AMGA uses a relational database back-end to store the metadata. Several database products
are supported, as shown in Fig. 14.7. AMGA provides a tree-like structure to arrange different
428

CHAPTER 14. COMPUTING AND SOFTWARE

kinds of metadata. The leaves of the structure contain the attributes of the metadata and are
implemented by tables in the relational database.

Figure 14.7: Possible AMGA back-ends.
For the directory structure of the file catalog (LFC) we envision the following scheme:/belle2/data/e[exp #] /[dataset name] //belle2/MC/generic/e[exp #] /[dataset name] //belle2/MC/signal/e[exp #] /[dataset name] //belle2/user/[username] /[dataset name] /where [exp #] is the number of the data-taking period (experiment), and [dataset name] isa name identifying the type of data. The extent to which users will be allowed to register theirfiles in the metadata catalog is not yet decided.
The LFC structure is not well suited for AMGA because it would create too many databasetables, which may degrade the search performance. For example, assuming that there areseveral tens of experiments and dataset types, then there could be more than ten thousand
tables created. In PostgreSQL [10], one of the AMGA back-ends, each table is stored in a fileand all the tables in a database are managed in a single directory. If there are ten thousand files
in a directory, then accessing a file in the directory will consume a large amount of time, sincemost file systems search through filenames sequentially.
To solve the above problem, the depth of the directory structure is reduced by one layer. The
implemented metadata structure is:/belle2/data/e[exp #] /FC/belle2/MC/generic/e[exp #] /FC/belle2/MC/signal/e[exp #] /FC/belle2/dataset/belle2/skim/belle2/user info
/belle2/site/belle2/software/belle2/config/path

file-level metadata for real data
file-level metadata for generic MC data
file-level metadata for signal MC data
metadata for datasets
metadata for skims
metadata for users
metadata for sites
metadata for software versions
path information for metadata

The attributes of the file-level metadata are listed in Table 14.1. It includes a LFN attribute,which is redundant because the LFC service has a mapping between GUID and LFN. At this429

CHAPTER 14. COMPUTING AND SOFTWARE

time, it is included to allow us to test the metadata service using the existing Belle data, which
do not support the grid services.

Attribute
guidlfn
statuseventsdatasetidstreamrunH
eventHrunL
eventLparentid
softwareidsiteiduseridlog guid

Table 14.1: File-level attributes.
Typedescription
varchar(40)grid unique ID (hex format)
varchar(1024)
logical file namevarchar(16)good/bad/and so on
int
total number of events
int
dataset ID
intstream number
inthighest run number
inthighest event number
int
lowest run number
int
lowest event number
int(128)
IDs of parent files
int
ID of software version
int
ID of site where it was createdint
ID of a user who created it
varchar(40)GUID of log file (hex format)

exampleaaaaa.root
good
3913
5
0
1490
3913
1490
1
0
1
1
1

The metadata attributes on datasets, skims, users, software versions, and sites can be found in
Ref. [11].
14.3.3.2

Estimation of Metadata Size

To judge the feasibility of this metadata scheme, in particular for the event-level option, it isimportant to estimate the total size of the data that has to be stored in a database. Table 14.2
summarizes the following rough calculation.
According to our estimate of required hardware resources presented in Sec. 14.5.2, we will haveabout 400 PB of real data (see Table 14.8) and about 50 PB of MC data (see Table 14.9) in
2020. In order to efficiently use our resources, we aim to store the data in large files of similar
size. For our calculation, we assume an average file size of 4 GB. Taking these numbers, we
expect to have about 100M data and 12.5M MC files for which we have to store metadata in the
AMGA database. From the metadata attributes listed above, a size of 600 bytes per file entry
in the database is determined.
The expected total number of physics events (bb̄, continuum, τ + τ − , 2-photon) in 2020 is about
500×109 , according to Tables 14.6 and 14.4. If we produce MC events corresponding to six times
the amount of hadronic events, we obtain 1500 × 109 events in 2020. Thus, an efficient storageof event-level metadata is essential. This is achieved by using the variable-bit data format thatis only supported by PostgreSQL. If Oracle or MySQL were used as a back-end, the size would

data
MC

Table 14.2: Estimation of metadata size.
# of files Size for file level # of events Size for event level
100 × 10656 GB
0.5 × 1012
5.5 TB6
1212.5 × 10
7 GB
1.5 × 10
16 TB

430

CHAPTER 14. COMPUTING AND SOFTWARE

increase by about a factor of six. With the variable-bit data format, a metadata size of 12 bytes
per event was reached.
While the size of the file-level metadata seems manageable, the feasibility, benefits and drawbacksof the event-level metadata option require further investigation.
14.3.3.3

Metadata Access

There are two main roles in the access of metadata: manager and user. The manager role is
responsible for creating conforming metadata when a file is created, and is the only role withwrite access to the database. Once the metadata is created, it is not expected to be modified
under normal operation. The metadata will be replicated to many grid sites, depending on
the AMGA replication configuration. If the manager of metadata deletes an entry, it should
be removed at the replica sites automatically. Normal users only have read-only access to themetadata catalog. If metadata for user files is allowed to be registered in the central file-level
metadata catalog, the above scenarios will be modified.
Users can retrieve information from either a command line metadata access tool or via a web
portal. A prototype of the command line tool has already been implemented based on AMGA
client version 2.0. The prototype allows a user to query either the file-level or the event-level catalog at their choosing. The prototype applies strong security measures based on grid certificates.
Its usage will be optimized by detailed studies of end-user access patterns.
Convenient tools should be provided for the metadata manager, allowing the management ofmany files with minimal effort, since there may be thousands of files created at the same time.
The LFC service will interface with the metadata catalog, using the GUID attribute in the
file-level metadata.
14.3.3.4

Metadata Server

One of the notable features of AMGA is the ability to replicate the metadata catalog, or partsof it, to remote sites. The replication was successfully tested with a master database at KISTI
and a slave at Melbourne, using metadata of the Belle experiment.
For the event-level metadata case, the size of the metadata becomes too large for a single
database. A multi-server setup is considered to guarantee scalability and performance. It
employs a redirection system, as illustrated in Fig. 14.8, to allow end-users to access the full
data in their analysis.

14.3.4

Data Management System

We will employ the standard data management systems used by the WLCG, although we will
not employ automatic data distribution to remote grid sites. As raw data is generated by theexperiment, it is stored in the main center SE and registered with the LFC and AMGA. Remotegrid sites may choose to transfer all or some of the derived data sets created from the main
center processing of the raw data.
All subsequent data generations or replications to any SE will also be registered in the LFC
and AMGA. We envision numerous derived data skims. These will be replicated around the
distributed computing system to match the needs and interests of physicists. Popular data skims
like the Full Reconstruction skim may be replicated on all sites.
It is clear that both the LFC and AMGA play a critical role in the correct and efficient operationof the computing model. Experience from the WLCG shows both have proved to be stable,
reliable and scalable to our needs.
431

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.8: The concept of the redirection system.

14.3.5Monte Carlo Production

MC simulation is the most CPU intensive and least data intensive aspect of the Belle II computing requirements. We wish to employ the least-cost but still effective solution. Consequently,
we plan to employ both data-grid and virtualized cloud resources to generate our MC data. A
number of governments are investigating making virtualized cloud resources available at no (orlow) cost to the academic community. The idea would be use as many resources as we can findat low cost, with a fall-back to employ commercial cloud providers for time-critical needs.
We plan to employ the same project-based control flow for MC production on both grid or cloudprovider. This situation is depicted in Fig. 14.9.

Figure 14.9: MC production on both grid and cloud via the project system.
The user requests MC production with a specific physics model, run number range, numbers
432

CHAPTER 14. COMPUTING AND SOFTWAREof events, etc. The project client once again translates this request to a physical collection of
resources and submits the requested number of jobs. In the static model, each job has fixedparameters for the simulation (experiment and run number, number of events per run) assigned.
In the dynamic model, the job receives this information at run time from the project server.
An additional requirement for MC production is that appropriate “Random overlay data files”
are provided. These are real data collected along with physics events but recorded with a random
trigger and with no filtering software. These data were successfully employed to simulate realbeam background for the Belle experiment; we plan to use this technique for Belle II (see alsoSec. 14.4.6.4).
The generated data is registered with AMGA and the LFC and stored in the SEs. It is thus
made available to users who can easily locate and use the data as needed.

14.3.6

Cloud Computing and Virtualization

Cloud computing’s recent rise to popularity is derived from the novel utilisation of a software
technique called virtualisation. In virtualisation, host software running on physical hardware
creates an abstracted, simulated computer environment—a virtual machine—for some guest
software, usually an operating system. Due to the abstraction, from the perspective of the guest
software, it has an entire computer platform to itself. Access to physical hardware is mediatedby the host software, of which there are two types (shown in Fig. 14.10). Type 1 has the host
software integrated into the host operating system, whereas Type 2 has the host software as anapplication running on the host operating system. The benefits of either approach is outside
the scope of this document.

Figure 14.10: Components in virtualisation.
There are more than a dozen providers of cloud services in existence today. However, for the
purposes of the Belle II experiment, where we require a specific operating system and custom
libraries, many are less appropriate due to restrictions on access to the virtual machines created.
Therefore, we utilise the set of providers known as Cloud Infrastructure-as-a-Service Providers.
When you use a cloud service, you are in effect running software within a complex virtual
machine—software that appears like an entire system, but is actually one of potentially manyrunning on the same physical hardware. Various types of virtual machines, which vary in
specification and cost—typically paid for by the hour—are available.
Though the hardware resources can be purchased easily from the cloud in this manner, additional
software is required to control this process. Previously, we ran several successful tests using an
open source product known as Lifeguard that we modified.
433

CHAPTER 14. COMPUTING AND SOFTWARE

Subsequently, we have been working with the creators of DIRAC (Distributed Infrastructurewith Remote Agent Control) to utilise their stable product as a solution for our cloud computing
needs, in addition to integrating grid and local cluster resources.
14.3.6.1

Prototype solution

Figure 14.11: Architecture of cloud-computing solution
As cloud computing is a relatively new technology, we have felt the need to test our concepts
in action prior to considering it as a solution. The results of our testing to date using the
production of MC data on the Amazon Elastic Compute Cloud (Amazon EC2) are described
below.
Figure 14.11 gives an architectural view of the most recent exercise, where a new DIRAC component was created, providing ability to control cloud resources.
14.3.6.2

Control Flow

The most important part of control that is unique to the cloud is the management of the fleetof virtual machines running on the cloud. Since each virtual machine costs money when it isrunning, it is important to only run a new machine when necessary, terminate idle machines
promptly and minimise overhead such as time wasted during start-up.
In our solution, this is controlled by a piece of software known as the “Virtual Machine Manager,” which uses information from the central task queue in the Workload Management DIRAC
component to make these decisions.
The Virtual Machine Manager constantly monitors the queue, and takes action by starting andstopping EC2 instances based on the number of jobs in the queue and several configuration
options, including:• the maximum number of instances to have running;434

CHAPTER 14. COMPUTING AND SOFTWARE• time increments by which to step up the number of instances running;• timeout values before shutting down idle or unresponsive instances
Once an instance is started, it will first download and setup the International Grid Trust Federation Certificate Authority configuration that is used to secure connections with grid resources.
Following this, DIRAC is installed and the Virtual Machine Manager and Job Agents are started.
Subsequently, the jobs will download the files they need from storage elements defined in the filecatalog, simulate and generate Monte Carlo events, then upload the result files to grid storage
elements. Status information about virtual machines and running jobs, including an excerpt of
the job output, can be gathered from the Web Portal.
14.3.6.3

Data Flow

As previously mentioned, the avoidance of vendor lock-in with regards to data storage isparamount. Therefore, we only use cloud facilities for temporary storage.
In our tests so far, we have used MC production. Recall from Sec. 14.3.5 that this task takes indata of different types and produces output files in the form of mDST. We need to have all ofthese inputs easily accessible to cloud nodes.
We have tested three methods of staging input to/from cloud virtual machines.
• Temporary use of Amazon Simple Storage Solution (S3)• Running a dedicated virtual machine as a storage element• Direct-copy to/from grid to cloud resources
Of these, only the first was deemed intractable: S3 was unable to sustain the transfer rates
required, and the cost overhead and use of provider-specific APIs is undesirable.
The second option is achievable as each virtual machine has a local disk of varying size. The
largest on Amazon is 1.7TB, which is enough to be a staging area for the relatively smallMonte-Carlo input data. Transfer rates of 40 Mbps per connection were measured.
Directly using grid resources for data input and output reduces the overhead of cloud services,and the modifications required to allow computing jobs to run on the cloud. The weakest pointis the typically lengthy network connection to the external resources. However, despite this, wewere able to achieve over 400 Mbps inbound and outbound.
14.3.6.4

Run
1
2
3
4
5

Results of Testing

Table 14.3: Cost of full production runs on EC2.
Cost in $Number of Events
CPU Storage Transfer
Total
752,233
80.00
0.20
6.65
86.85
1,473,818
108.11
0.25
7.12
115.37
10,000,998
724.801.42
39.96
766.18120,000,000 5198.60
0.0
415.68 5614.28
101,478,333 1566.76
0.0
349.52 1916.28

435

per 104 events
1.16
0.78
0.76
0.46
0.20

CHAPTER 14. COMPUTING AND SOFTWARE

Table 14.3 summarizes the costs of the MC production on the cloud. It can bee seen that the
total cost is dominated by the investment in CPU cycles and that it scales roughly with thenumber of produced events.
Since we first started testing, the prices at EC2 have dropped by 15%, and—perhaps more
importantly—a new product (“spot instances”) was released that allowed us to access significantly discounted prices. The use of spot-instance pricing, which prices virtual machine hours
based on current market demand, allowed us to achieve savings of up to 50% (Run 5 in Table 14.3). Further tests are needed to verify that we can achieve these costs savings at the scalerequired for Belle II.

14.4

Offline Software

14.4.1Introduction

After having written the data to tape or disk, the offline software takes the data and performs the
final processing steps. Among them are the reconstruction of tracks, MC simulation, and physics
analysis. The offline software is designed as a framework, providing a software environment tothe user that allows access to all functions built into the framework. User code can be added toextend the functionality. A typical user-written module would be code that performs a physics
analysis.
This section discusses the way the offline software source code is managed, provides an overview
of the framework itself and takes a closer look on the event data model, the geometry description,
the simulation and reconstruction. At the end, a possible solution for an event display is given.

14.4.2

Code Management

As in other HEP experiments, the Belle II offline software is developed by a group of dedicatedpeople with different levels of experience who are distributed around the world. To create areliable, user-friendly, and well-maintainable software environment, we take the following organizational and technical measures.
All Belle II code is maintained in a central Subversion repository [12] located at KEK. The codeis structured in packages. A package is a container for source files that are later compiled andlinked into a shared library with the same name as the package. Each package has an assigned
librarian who is responsible for the code in the given package. By default, only the librarian
has the ability to change the package, but they can grant the right to commit code to otherdevelopers.
All Belle II members have read access to the full repository. A repository browser (ViewVC[13]) for inspecting and comparing different versions of source files in a web browser is provided
as well.
To help developers to identify integration issues between packages, nightly code builds will bedone automatically. In addition, regular integration builds will be performed that serve as abasis for further code developments. For the integration build, the release coordinator will collectpackage versions from the package librarians. The package versions are identified by tags thatare assigned by the librarian to a version of code they consider ready for a build.
This procedure of collecting tags from package librarians is also used to build releases. In contrast
to the deadline-driven integration builds, the releases are feature-driven. Moreover, a series ofquality tests have to be passed before code is released to users. For example, verification that436

CHAPTER 14. COMPUTING AND SOFTWARE

the software compiles and runs on different architectures and operating systems is undertaken.
We plan to support the following systems:• SL5 64bit, because it is used on the grid.
• CentOS 64bit, because it is used at KEK.
• Ubuntu 32bit and 64bit, because it is used by many people on their desktops and laptops,
and because it is a debian-based system, in contrast to the first two redhat-based ones.
• MacOS, mainly to ensure portability of our software as a measure of software quality
assurance, but also to permit users to run the software on their laptops.
The supported compiler is gcc 4. We may try other compilers, like the intel compiler, to checkthe portability of our code.
Documentation is generated from the source code with the doxygen tool [14] for all releases andbuilds. Further documentation can be provided on a wiki or in form of manuals.
To keep code maintainable, we have agreed on several essential issues that affect how code iscontributed. We agreed to use C++, the de-facto HEP standard, as the only programming
language. In cases where a scripting language has clear advantages, python can be used. A
consensus about the coding conventions has been established as well. The overall guideline isto keep the code as simple as possible. A formatting tool, astyle [15], is used to help developers
unifying the layout of source code. Furthermore, we will do code reviews and implement unit
tests to improve the software quality.
To facilitate the installation of the Belle II software on grid sites, institute clusters, and user’s
desktops and laptops, dependencies on external software should be minimized. Any additionof a third party library has to be well-motivated. The external packages will be provided via
the same channel as our software. Both can be obtained from svn and compiled locally. In
addition, we will provide tarballs and perhaps rpm/deb packages. For the management ofsoftware installations on grid sites, we plan to adapt the ATLAS tool [16].

14.4.3

Framework

The data analysis framework is the basis of the Belle II software. Various kinds of software components are be written as “modules” for the framework, and they are plugged into the framework
on demand. The application programs used in Belle II, such as the full event reconstruction,
the event skim, and the user analysis codes, are realized by combining a set of modules on theframework. The framework reads an event record from a file, then processes it by executing
a chain of modules, and stores the resulting event record into a file. The histograms, ntuples
and other data required to be accumulated in each module are also managed by the framework.
A new analysis framework called “roobasf” is being developed for use in Belle II. To benefit
from the experience made in other frameworks, several software frameworks from other HEP
experiments were evaluated. Therefore, the Belle II software framework combines the provenconcepts of the previous Belle framework together with ideas taken from the GAUDI, ILC and
ALICE software frameworks. This section describes the requirements for the framework in BelleII and the roobasf design that satisfies these requirements.
14.4.3.1

Object I/O

The event structure (event model) of Belle II is described as “objects” in C++, and as aconsequence, the framework is required to have the capability to read and write C++ objects
437

CHAPTER 14. COMPUTING AND SOFTWAREin data files. Since the event model can evolve as the software developments goes, the I/O
capability should not be restricted to a certain event model. To store C++ objects in a file,the objects have to be converted to a plain byte stream by “streamer” code, but it is desired to
avoid writing the codes by hand, which introduces an extra burden in the software coding.
To satisfy these requirements for the object I/O, we adopted ROOT IO [17] as the object I/Omodel for our framework. The ROOT IO is a part of the ROOT package, which is a collectionof object-oriented analysis tools. It has the object I/O capability, which can generates streamer
codes automatically by reading the C++ class definition files using rootcint or genreflex. The
ROOT IO object model is already the de-facto standard in many HEP experiments and isdesigned to keep up with the evolution of the event model (“schema evolution”). By using
ROOT IO for object I/O in the “roobasf” framework, the requirements are satisfied and thedevelopment of the event model are well separated from the framework.
14.4.3.2

Software bus

The framework accepts a set of modules plugged in it and controls the chain execution of them.
A simple software bus architecture is suitable for managing the chain. The execution chain isrequired to be stopped and restarted at any point by dumping and restoring the intermediateobjects in a data file (check-pointing). Figure 14.12 shows the software bus architecture for theframework.

Figure 14.12: Software bus concept.
Roobasf recycles the design for the previous B.A.S.F. [18] framework used in the Belle experiment
to implement the software bus. The modules are plugged into the framework via the dynamic
link and therefore each module can be compiled and debugged independently of the framework.
The well-defined event model and module functionality can provide the check-pointing capability
easily with the ROOT IO.
14.4.3.3

Belle Compatibility

There is a substantial accumulation of software experience for the B-physics experiment in theso-called Belle library. The maximal use of the Belle library in Belle II is desired to avoid reinventing similar software. The compatibility with the Belle software also enables the smoothtransition from Belle to Belle II for the software developers. Therefore, we require full compatibility with the Belle library in the new framework.
Roobasf realizes two levels of Belle compatibility. One is the module-level compatibility. The
modules written for the B.A.S.F. framework can be plugged into roobasf without any modifica438

CHAPTER 14. COMPUTING AND SOFTWARE

tions. The other is the capability to read Belle’s Panther data files by linking the legacy I/O
package. In some cases, it is useful to compare the performance of newly developed softwareon roobasf with that of Belle. However, the ability to write the processing output in Pantherformat is deliberately omitted, to urge people to move to object I/O based data handling.
14.4.3.4

DAQ compatibility

The software used in Belle II DAQ (Ch. 13) has a very close relationship with the offline software.
In particular, the high level trigger (HLT) software (Sec. 13.9) is supposed to be identical tothe offline event reconstruction code, and the same analysis framework is desired to be used in
DAQ.
The I/O package of roobasf is implemented as a shared library with a set of functions to provide
low-level I/O. The package is dynamically linkable/changeable. An I/O package dedicated to
the DAQ use, which can send/receive data through the UNIX socket, is provided to manage thedata flow in the DAQ system. The data between the I/O package and the event processing coreare passed via ring buffers so as to absorb the difference in the event processing time.
14.4.3.5

Parallel processing

The data processing is required to handle a huge amount of data and some kind of “parallel
processing” is necessary to analyze these data in a reasonable period. The parallel processing
capability is desired to be implemented inside the framework and concealed from users. It isapplied at the event level.
Recent CPU chips house multiple cores and these cores are normally seen as multiple CPUs in
an SMP server by an operating system like Linux. The parallel processing in the framework
is desired to make use of the multi-core CPU. In addition, the parallel processing using a PC
cluster, where a large number of processing nodes are connected via network, is also required.
This is necessary in the HLT for the real-time full-event reconstruction, and also for the data
reproduction with the updated software and/or calibration constants in off-line.
The event-by-event B.A.S.F. parallel processing models (shared-memory BASF and networked
dBASF and RFARM) are the starting point of the parallel processing design in roobasf. Figure 14.13 and 14.14 show the data flow in roobasf for the parallel processing. The event records
in a file are read by the “event server” and placed in a ring buffer on the shared memory. A
number of event processes pick up event records in the buffer and process them in parallel. The
resulting outputs are then stored in a separate ring buffer and collected by the output server
to store in an output file. The event server and output server can be connected to an external
node through a UNIX socket for the parallel processing with a PC cluster.
Roobasf has both single and parallel processing modes. When operated in the single processmode, all the processing is done within a single process; this is useful for the debugging ofmodule codes before the mass-processing.
14.4.3.6

Histogram management

The histograms, ntuples and ROOT trees are defined in the modules on the framework independently. They are typically stored in a single file for the further analysis.
Roobasf is designed to manage the histograms using ROOT calls. The histograms can be definedusing the standard ROOT functions in each module independently. The histogram manager ofroobasf takes care of the output histogram file in which the histograms are stored, and it manages

439

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.13: Parallel processing in roobasf.
the calling sequence of histogram definitions by each module. It also takes care of collection ofhistograms after the parallel processing is performed.
14.4.3.7

Scripting

Module execution in a framework can widely vary depending on the application, and has to be
described in a robust and versatile scripting language. The B.A.S.F. framework used a custom
command parser for this purpose that was closely tied to the framework; its cooperation withexternal programs was difficult. It is desired to use some “common” scripting language to drive
the module execution on the framework cooperating with other analysis tool like ROOT.
We adopt python [19] as the scripting language of roobasf. The framework execution can be
described by the python-roobasf interface. Python has become very popular in HEP, and other
HEP software applications are now equipped with a Python interface, like PyROOT. By using
Python as the scripting language for our framework, roobasf can easily co-operate with ROOT
through PyROOT for the full data analysis. Figure 14.15 shows the example of the python
script for roobasf.

14.4.4

Event Data Model

The event data model describes the in-memory representation and the storage of all data thatcomes from the detector. It is essential that this be done in a unified way, as it defines aninterface for the different sub-detector groups and the tracking and software groups. In Belle II,
this will be done in an object-oriented manner.

440

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.14: Event data flow in roobasf.

Figure 14.15: Example of a python steering script for the roobasf framework.
For the reader’s understanding, we define the terms persistency and serialization. The processof converting an object in memory to a string of bytes is called serialization. The serialized
object can then be sent across the network or saved into a file. The process of saving an object
into a database or a file using serialization is called persistency.
We describe the event data model in C++ instead of a meta-language, since this programming
language is used across the entire framework. We want to fully exploit the object-oriented
features of C++ and store data in lists, trees or maps. The data event model is designed to
fully utilize the standard template library (STL). This avoids the overhead of reimplementing

441

CHAPTER 14. COMPUTING AND SOFTWARE

very well optimized code. As a starting point, we assessed the existing Belle Panther banks fordata content and LCIO for object-oriented structure. To ease analysis, we are planning to use
ROOT as a persistency provider. ROOT provides tools to write arbitrary objects to a file andto read in the persisted objects into a program, which can be used in the online software tocreate a uniform framework.
The core element of the framework is the event class. To make it easy to write a whole event,the class inherits from the ROOT TObject class, which allows standard ROOT methods (e.g.,write) to be used for serialization. The serialized object can then be stored in a file or sent acrossthe network. The event class holds collections of data classes that represent the sub-detector
information. The collection class is based on the STL vectors, allowing fast access to the dataclasses. All data classes are required to inherit from a BelleObject class. This ensures that alldata objects can be saved in a collection. The design of the data classes is driven by the needs ofthe sub-detector groups. For example, for the storage of the Monte Carlo Particle information, adecay tree seems natural: pointers between the Monte Carlo Particle objects are used to form atree structure. To ensure that future changes in the persistency model do not affect the existingcode base, the use of BelleII pointers is suggested.
In addition to data objects, the collections in the event class should be able to store relations. All
three kinds of relations (one-to-one, one-to-many, many-to-many) can occur in the data model.
Therefore, a Relation object containing a “from” and a “to” member variable is suggested. To
create a one-to-many relation, one needs to create multiple Relation objects where all “from”
member variables point to the same data object. Sometimes one cannot define unbiased relations.
In this case, a weight can be applied to a relation. For example, consider a track that ismisreconstructed using two hits from one Monte-Carlo particle and three hits from anotherparticle. In this case, we could create two Relation objects: one with a weight of 40% and theother with a weight of 60%.
The ROOT persistency must save not only the member variables but also the pointers to otherclasses. As a default, ROOT follows the pointers to other objects and also saves the referenced
objects. This leads to problems if you want to store two sets of objects in different files thathave common elements. Our plan is to avoid such a scenario.
The persistency layer should, however, allow us to write out only those collections that are ofinterest. This allows us to define sets of collections that are saved; for example, analysis andalignment sets. It is also helpful to join streams of event data. Commonly, this is needed whennoise and background is merged with MC simulation. Therefore, the event data model must be
designed in a way to easily allow merging and discarding of collections in a given event.

14.4.5

Geometry and Conditions Database

The description of the detector geometry is an integral part and represents an essential ingredientfor the different stages of the offline software. In the following section, the requirements imposedon a geometry handling system are discussed and the approach taken for the Belle II detector
is presented in detail.
14.4.5.1

Requirements for a geometry handling system

From the simulation of the passage of particles through the detector to the simulation of the
response of the sub-detector hardware and finally the reconstruction (e.g., tracking) algorithms,
nearly all tools of the offline software chain need a geometrical description of the Belle II detector.
However, each tool requires a different view of the detector geometry. The full simulationof the detector (described in Sec. 14.4.6) takes a very detailed geometrical description of all
442

CHAPTER 14. COMPUTING AND SOFTWARE

detector parts as an input. Usually, the detailed geometrical description uses a collection ofprimitives (boxes, tubes, spheres, etc.) to compose a complicated detector structure. In addition,material properties like radiation length, specific energy loss are assigned to each primitive.
The simulation of the sub-detector hardware response, called digitisation (Sec. 14.4.6), requires
only a subset of the full geometrical description of the detector: hardware parameters and thetransformation matrices from global space (usually defined by the experimental hall) to the local
space of a sub-detector volume. An example is the digitisation of the PXD sub-detector: thetrack-finding and -fitting algorithms need a simplified view of the detector geometry. This isgiven as a collection of geometry primitives but, unlike the full detector simulation, does not
require the same degree of detail. Usually, it is sufficient to describe the detector roughly byusing basic shapes like planes, boxes, tubes, cylinders, cones, etc.
14.4.5.2

Basic geometry handling scheme

To make sure that all tools of the framework have access to the same version of the detector
description, it has to be stored centrally. From this central storage, the geometry for the full
simulation and for the reconstruction is created and the parameters for the digitisation aretaken. This leads to the basic architecture for the Belle II geometry handling system shown in
Fig. 14.16.

Figure 14.16: Basic architecture of the Belle II geometry handling system
The central repository stores all parameter values needed for fully describing the Belle II detector.
The concrete geometry used for the simulation and the reconstruction algorithms is created using
C++ source code from the stored parameters. The digitisation algorithms take the parameters
directly from the repository.
Storing parameter values instead of a concrete geometry in the central repository allows fora simple and generic way to handle an evolving geometry. For example, the position of themeasuring parts of the vertex detector have to be known with high precision. Various forces,
like gravitation, may change the position of these parts over time. The slow drift of the vertex
detector from its initial position can be measured and stored as time varying parameters in thecentral repository. These parameters are then used for correcting the initial values during theconstruction of the concrete detector geometry for the simulation and reconstruction. They arealso taken into account for direct parameter retrieval and the construction of transformation
matrices. Other examples for time varying parameters are calibration constants or slow control
values.

443

CHAPTER 14. COMPUTING AND SOFTWARE

14.4.5.3

Implementation of parameter storage and access

The central repository is realized using XML documents for the basic detector parameters anda PostgreSQL database [10] for the condition parameters. XML documents have the advantage
of being human readable and highly extensible. Furthermore, they are widely used in particle
physics and in industry, leading to the availability of high-quality libraries, tools and software(both open-source and commercial) to write, read and manage XML documents. For storinglarge datasets, like condition parameters, a database is more suitable. Therefore, a PostgreSQL
database is used in addition to XML documents. This leads to the following scheme: a timeindependent parameter is stored directly in an XML document and a condition parameter isstored in an XML document as a link pointing to the location in the database where all available time spans for that parameter are saved. Figure 14.17 shows a schematic drawing of theparameter storage solution.

Figure 14.17: The parameter storage solution. hparameter5i and hparameter6i are time independent parameters, which are returned directly. hparameter1i to hparameter4i are timedependent parameters. Their time spans are calculated from the given time and their values
are fetched from the PostgreSQL database. The parameter entries TP1 to TP4 in the databasecorrespond to the elements hparameter1i to hparameter4i in the XML document.
The combination of XML-based parameter storage and database condition parameter storage ishidden from the user by a common interface. This interface allows the user to send queries forparameters to the geometry handling system without having to worry about the time dependenceof certain parameters. Figures 14.18 and 14.19 show the process diagram for a typical timedependent and -independent parameter query, respectively.
Using a defined query language, which will be described in detail later, the user sends a request
for a parameter to the geometry handling system. If the requested parameter is not a condition
parameter, its value is directly taken from the XML document and returned to the user. If it isa condition parameter, the system follows the link to the location in the database and returns
the value of the time span evaluated using the given time value. This time value can either be
set manually by the user or automatically. The latter is especially useful for MC production.
The parameters describing the Belle II detector are stored in a tree-based hierarchical structure.
The root of the tree is the Belle II detector and the first level of branches describe the various subdetectors. Each sub-detector consists of an arbitrary number of branches, where each branch444

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.18: Process diagram of a query for a time-dependent parameter.

Figure 14.19: Process diagram of a query for a time-independent parameter.
groups parameters having a similar type or describing the same part of a sub-detector. The
actual parameter values are then saved as leaves of a branch. The tree structure is realized in
an XML document using elements as basic building blocks. Each element can either have an
arbitrary number of child elements or store a parameter value. Every XML document consistsof exactly one root element which serves as parent for all other elements. An arbitrary numberof elements, being either child of the root element directly or of another element, can then be
added to the XML document.
As explained in Sec. 14.4.5.1, the detector geometry description is based on the fact that thefull detector is composed from different sub-detectors. Therefore, the parameters of each subdetector are stored in a separate XML document and combined into a single document using
the XInclude technology [20, 21]. This keeps the size of each sub-detector XML document
reasonable small and allows the definition of different detector models, where each model isgiven by a specific set of sub-detectors.
To facilitate the process of locating and retrieving parameters from an XML document, query
statements very similar to file paths are proposed. This approach is motivated by the hierarchicalstructure of the detector parameters. The language used to express a query statement in the445

CHAPTER 14. COMPUTING AND SOFTWARE

geometry handling system, is known as the XML Path Language or shortly XPath. XPath is astandardized language developed by the W3C [22].
14.4.5.4

Creating geometry objects from parameters

Both the detector simulation and the tracking algorithms depend on a detector description basedon actual geometry objects like planes, cubes etc. The geometry handling system, explained sofar, only stores parameter values and optionally their development over time. The missing link
between parameter values and geometry objects is filled by C++ code. Figure 14.20 shows thebasic architecture of the geometry object building system.

Figure 14.20: The basic architecture of the geometry object building system.
Each sub-detector has C++ code associated with it, which is aware of the available parameters
for that specific sub-detector. The C++ code requests the parameter values that are neededin order to build the actual geometry of the sub-detector from the geometry handling library.
The geometry handling library automatically discriminates between time-independent and dependent parameters and returns the values from the XML document or from the PostgreSQL
database, respectively. Then, using the parameter values, each sub-detector C++ code creates
the actual geometry objects and writes the created geometry into an object hierarchy. The
geometry objects and their relationships within the hierarchy are implemented using ROOT [17]TGeo objects, a common standard for geometry objects. The hierarchy is shared between all
sub-detectors, leading to a single geometry object hierarchy for the whole Belle II detector. It
can then either be kept in memory, and directly used by the simulation/reconstruction software,or saved to disk for later usage.

14.4.6

Simulation

In high energy physics experiments, the term “simulation” refers to three steps: event generation,
the simulation of passage of particles through the detector, and digitisation. The first step
involves the generation of events for the various physics studies, for example B meson decays
or beam background simulation. The second step performs the simulation of the interactionof individual particles passing through the detector, described by all its different materials
and geometries, and records the particles’ energy deposits in “sensitive” volumes. The third
step simulates the response of individual sensitive-detector components, taking into accountdetailed physics processes of signal generation, electronics effects, and final hit creation. All
three steps will work as loadable modules within the software framework explained in Sec. 14.4.3
446

CHAPTER 14. COMPUTING AND SOFTWARE

and will exchange information through the event data structure described in Sec. 14.4.4 Here,each simulation step is described in detail.
14.4.6.1

Event Generator Software

In event generation, the information (the production point, momentum, particle species, and soon) of particles produced for a given process by the event generator is stored in ROOT I/O andfed into the detector simulation.
One of the purposes of the Belle II experiment is to search for new physics through the precise
measurements of CP asymmetry with B mesons. To simulate the physics of B decays, EvtGen [23], which was initially developed by the CLEO collaboration and is maintained at SLAC,
has been used in many experiments, including Belle. We will continue to use EvtGen, updating
the decay channels for the Belle II experiment, unless a better event generator is found.
For continuum (e+ e− → q q̄) events, EvtGen and Pythia are used.
Tau production and decay are modelled using the combination of KKMC [24] and tauola [25].
The former is a package for τ -pair production in e+ e− collisions and the latter for the decay ofτ produced in the generator.
14.4.6.2

Detector Simulation Software

For detector simulation, a package based on the Geant4 toolkit [26] is being developed, written
in C++ and designed to exploit advanced software techniques and object-oriented technology.
The flow of the program (Fig. 14.21) is intended to be controlled via a steering file, where all
simulation parameters can be defined by the user. The program itself is then run either in batch
mode, where no interaction with the user is expected or in interactive mode, where the program
flow is driven by Geant4 UI (User Interface) commands. If no steering file is provided or not all
required parameters are given by the user, the default values accessible via a singleton class G4Control are used instead. The main inputs of the simulation are the geometry description andthe primary particle(s) information. The first is accessible from the central geometry repository
via its interface (Sec. 14.4.5); the latter can be described either by single particle parameters—
used by G4 Primary Generator—or in an event generator file that is read using a suitable G4
Generator interface. The output of the chain is recorded in an object-based format describedby the event data model (Sec. 14.4.4) with a predefined persistency. In our case, the persistency
is based on ROOT I/O libraries [17].
The basic idea of the Geant4 design philosophy can be described in the following way. The
primary unit of an experimental run, represented by G4 Run, is an event (G4 Event) and consistsof a set of primary particles produced in an interaction and a set of detector responses tothese particles. Before each event is processed, it contains only primary vertices and primaryparticles defined in a steering file or provided by an external physics generator. After the event
is processed, it is augmented with created hits, generated trajectories and created secondary
particles. The hits are snapshots of a physical interaction in sensitive parts of the detector andare saved in hits collections.
14.4.6.3

Digitization Software

Digitization software performs for each detector component (PXD, SVD, CDC, etc.) a detailed simulation of in-detector physics processes together with electronics effects, taking into
account the desired detector geometry and magnetic field information accessible via the geometry interface. In this way, it transforms one or more individual Geant4 hits into so-called
447

CHAPTER 14. COMPUTING AND SOFTWARE

Steering File
# Batch mode
/Geant4/init/BatchMode true...
# Log system/Geant4/init/LogVerbosity Warning...
# Geometry model/Geant4/init/DetectorModel VTXBelleII...
# Particle gun properties/generator/generator ParticleGun/gun/momentum 1.0 GeV/gun/particle mu...
# Define number of events/run/beamOn 1000...
...

MC Generator File

Geant4 Simulation
main() {...
// Contruct run manager
G4Run * runManger = new ...
...
// Initialize detector geometry
runManager®SetUserInitialization(GeometryManager) ...
// Initialize physics processes
runManager®SetUserInitialization(PhysicsList) ...
...
// Set primary generator action
runManager®SetUserAction(PrimaryGeneratorAction) ...
// Set run, event, tracking, stepping, ... actions
runManager®SetUserAction(RunAction) ...
runManager®SetUserAction(EventAction) ...
runManager®SetUserAction(TrackingAction) ...
...
// Initialize run manager
runManager®Initialize() ...
...
// Construct visualisation manager
G4VisManager * visManager = new ...
...
// Access User Interface manager
G4UIManager * uiManager = new ...
...
// Run in user modeif (!batch_mode) {
...
}
...

Geometry interface
XML documents
PostgreSQL

Object-based Output
File}

Figure 14.21: The scheme of detector simulation software based on the Geant4 toolkit.
digits—measured detector signals. The resulting simulated data has the same format as real raw
data and can be processed further by the reconstruction modules of each detector component.
For detector design studies, special reconstruction algorithms may be used that are faster thanthe default reconstruction code for real data or that can read the underlying “truth” information
about the simulated event.
As the digitization procedure requires knowledge of how each sub-detector works and which
physics processes are relevant for signal formation, the software is completely written by anexpert from the sub-detector group in C++; a modular approach is used instead of a complete
integration of the code within the Geant4 toolkit. An advantage of such an approach is that,during the detector design phase, one can easily reprocess all the data with different settings, forexample voltages or noise characteristics, and avoid having to run the whole Geant4 simulation
again, which might be very time- and CPU-consuming. Another advantage is that, for one
sub-detector, several modules with different level of detail may exist and a user then selects
just the desired one. For instance, MC data production with full detector simulation requires
much less detail in digitization than detailed studies of a sub-detector prototype in a testbeam
environment.
As an example, a brief description of the SVD digitization is given here (see Fig. 14.22). Aftera particle crosses a detector volume, electron-hole pairs are generated along its path (calculated
from Geant4 hits) and naturally grouped into e–h pair clusters based on the spatial precision required. These clusters are then drifted in the presence of an electric field to collecting
electrodes-strips. The electrons drift to one side, the holes to the other. They are diffusedby multiple collisions, modeled by Gaussian smearing, and shifted by a Lorentz angle that is
calculated based on the information about the ambient magnetic field. Due to the fact that individual strips are connected to the circuit by DC/AC coupling and might mutually communicate

448

CHAPTER 14. COMPUTING AND SOFTWARE

Ci
+

+ +

+

-

Rbias

p+
- -

+ +

+

- + +

- + +

- - -

+ +

- -

+ +

Cb
- -

+ + +

n+

- -

+ +

- -

+ +

Cc

- -

Al

++ - - - -+ +nbulk + + + +- - - - - - - +- + ++++ ++ -+ + - ++ + - p++ + - +
+ + + -+ Cb
+ +

Ci

Rbias

Cc

Al

+V

Ci
Al

Figure 14.22: Signal digitization in silicon microstrip detectors: 1D projection, with deltaelectron generated.
by inter-strip capacitance, the collected charge is redistributed and a signal is also generated on
adjacent strips. Finally, the noise on each strip is randomly generated and added.
14.4.6.4

Beam Background EffectTo simulate the beam background effect, two approaches are pursued. One is to generate thebeam background particles based on the inputs from the accelerator design with considerationof the beam-gas interaction, synchrotron radiation, Touschek effect, and so forth. This is usefulto evaluate the performance during the sub-detector design phase before real data is available.
However, it is quite time-consuming to simulate all such particles, including the low energy
photons, and quite difficult to reproduce the realistic condition of the acclerator run-by-run
once the experiment starts. An alternative approach makes use of the real data that is takenwith a trigger that is not synchronized with the collision timing. In Belle, such random-triggered
events are embedded to the MC and works well to reproduce the run-dependent experimental
conditions. However, this is not available before the experiment starts. Therefore, we need both
approaches in Belle II. The former is treated as part of the event generators and the latter aspart of the simulation tools. Both should work as an independent loadable module in the BelleII software framework.

14.4.7

Reconstruction

The reconstruction of events acquired in the track-sensitive parts of a detector is a chain oftasks, each of which contributes to detector abstraction and data reduction. Starting with raw
measurements, these tasks are calibration, local pattern recognition in individual subdetectors(track search), global pattern recognition (track finding), track parameters fitting (based on an
appropriate track model), vertex finding, and geometric and kinematic vertex fitting, ending
with the estimation of the event parameters relevant for subsequent physics analyses.
Calibration and (in case of the CDC) local pattern recognition are tasks of subdetector-specific449

CHAPTER 14. COMPUTING AND SOFTWARE

software, and therefore will not be discussed in this section. However, they will be assumed tobe reliably available.
This section deals with the next steps of the reconstruction chain. Their implementations will
be based on established state-of-the art algorithms and techniques, and will take advantage ofavailable abstract interfaces to the framework (Sec. 14.4.3), to the data model (Sec. 14.4.4),
and to the geometry & materials information (Sec. 14.4.5). Access to the “simulation truth”(Sec. 14.4.6) and interfaces to the event graphics (Sec. 14.4.8) are required for software testingand optimization studies.
The reconstruction effort is still in a very early phase. This description of our approaches tothe tasks mentioned above is intended to show the broad range and sophistication of techniques
available; it is not exhaustive. For a thorough review, see Ref. [27].
14.4.7.1

Track Finding

The task of global pattern recognition, a.k.a. track finding, is to determine which hits in the
track-sensitive parts of a detector belong to a common track. Information from a preceding local
pattern recognition, yielding a track candidate with associated hits, is used if available.
There is a large variety of algorithms for track finding. Which one to choose depends, among
other things, on the track density, the background noise level, the distance to the interaction
point (IP), and the subdetector in question. For instance, the silicon detector hits have highspatial resolution but an appreciable amount of multiple scattering, whereas the CDC hits havelittle multiple scattering but lower spatial resolution. Some track finding algorithms rely on
the circular shape of the track in the transverse projection, and those will work only in regions
where the magnetic field is reasonably homogeneous.
Due to the smaller track density in the outer subdetectors, we propose to apply an “inwards/outwards” strategy:• Track candidates found by local pattern recognition in the CDC are extrapolated inwards
to the silicon detector PXD/SVD. Tracks that can be found by this technique have atransverse momentum high enough to cross most or all of the CDC.
• Each PXD/SVD hit is tested against each extrapolation. Those hits that can be associatedwith a track candidate are removed from the hit collection.
• The remaining PXD/SVD hits are the input to a local pattern recognition in the silicondetector. Various techniques can be used in this “silicon stand-alone track search.” Amongthem are the conformal transformation [27], the Hough transform [28], the elastic net [29,30], the combinatorial Kalman filter [31] and related methods of progressive track search.
• In the final step, track candidates found in this way are extrapolated from the silicondetector outwards into the CDC. If unused CDC hits are found that fit to the extrapolation,
they are associated with this track candidate.
We end up with a set of global track candidates, each consisting of a crude estimate of its parameters together with an ordered list of associated PXD/SVD/CDC hits, and a set of unassociatedhits. A more complex approach allows hits to be shared among two or more track candidates;in this case, the final hit association is relegated to the next step, track fitting.

450

CHAPTER 14. COMPUTING AND SOFTWARE

14.4.7.2

Track Fitting

The trajectory of a charged particle moving freely in a static magnetic field is determined by the
Lorentz force law. It is uniquely described by five parameters, representing the initial conditionsat (for example) the point of intersection with a chosen reference surface: two positions, two
directions, and a quantity depending on the momentum.
The global track candidates that have been found in the previous step are subjected to single
track fitting based on some track model, with the virtual measurements and their errors being
derived from the hit coordinates. The purpose of this step is twofold: (i) find a “best estimate”
for the track parameters, yielding a 5-tuple and a corresponding 5 × 5 covariance matrix; and(ii) test and possibly update the track hypothesis, i.e., the association of hits to this track, by
identifying and removing or down-weighting “outliers” (true measurements with errors larger
than shown, or false ones not belonging to the track at all) and, if present, resolving ambiguous
associations of hits. These two tasks are achieved by an iterative procedure.
The choice of an appropriate track model depends on the magnetic field. In Belle II, the field is
sufficiently close to being homogeneous in the central tracking detectors, thus implying a helix
track model. Moreover, the detector layout is approximately rotational symmetric with respect
to an axis parallel to the magnetic field. The track parameters suggested to be used internallyin this step are given in the appendix of Ref. [11].
The free particle trajectory is disturbed by material effects in the detector. Multiple Coulomb
scattering is a stochastic process that is well described by the Rossi-Greisen formula with Highland’s correction term [32].1 Since the material budget is concentrated in thin layers (PXD,
SVD, CDC walls), those may be approximated by zero geometrical thickness; in this case, nolateral displacement takes place, and only the two direction parameters are affected in the courseof track fitting.
The other material effect is energy loss. For minimal ionizing particles, this is dominated byionization; if taken into account (in particular for low momentum tracks), it may be described
deterministically by the Bethe-Bloch formula with Fermi plateau [27]. For electrons, energy loss
is dominated by bremsstrahlung, a stochastic process that can be described by the Bethe-Heitler
model [34]. As it is extremely non-Gaussian, this poses problems that can be solved by special
modifications of the fitting algorithm, e.g., the Gaussian Sum Filter [35] or alternatives [36].
State-of-the-art in track fitting are techniques based on the Kalman filter [37], a linear estimatorthat is statistically equivalent to the least squares method, but is superior in coping with therequirements of a complex modular detector. It is applied on a linear approximation to thetrack model, the expansion point being a “reference track” sufficiently close to the true track;
the crude estimate from track finding may be a good choice. If necessary, a Newton method canbe applied, with the new reference track being the one fitted in the previous iteration.
The best estimate of the track parameters is achieved only at the end of the filter, with allmeasurements having contributed. To obtain best estimates all along the trajectory, the filter
must be complemented by a smoother. This can be achieved with help of a second filter, runningin the opposite direction. The smoothed χ2 s may serve as test criteria for outlier measurements;
in the realistic case of multiple outliers, however, the power of these tests is limited.
Linear estimators are inherently sensitive to the influence of outliers. Robustification can beachieved by using non-linear estimators, which in the case of track fitting are most easily implemented as iterative extensions of the Kalman filter: measurements with “big” normalized
residuals are down-weighted in the next iteration. Such adaptive filters are largely resistantagainst wrong measurements; thus, they are able to defer the final association of hits from the1

except for extremely thin material with few scatterings; for details see [33].

451

CHAPTER 14. COMPUTING AND SOFTWARE

track finding step to the track fitting step, where more complete information about the track
is available for the test criteria. This final association need not be a “hard” one, as the final
weights of the measurements can be anywhere between 0 and 1.
There exist several adaptive filter methods. In particular, we intend to explore the Deterministic
Annealing Filter (DAF) [38] that has successfully been implemented and refined by the CMS
experiment at LHC.
In addition, a detector-independent skeleton toolkit for track reconstruction exists (GENFIT [39]);
its usefulness will be evaluated once a proven implementation is available. Another challenge
is flexible track propagation in complex sequences of cylindrical and plane detectors, as in theforward region of PXD/SVD; a detector-independent implementation (LDT [40]) may serve as
an example.
14.4.7.3

Alignment

During the detector alignment, the detector geometry is corrected for small displacements ofthe sensitive elements in the detector. As a general rule, the precision of the alignment should
be significantly better than the intrinsic resolution of the sensitive elements. To achieve this,various strategies can be used. Sensor positions can be measured in the lab or in situ by lasers.
To obtain the ultimate precision, however, reconstructed tracks have to be used.
The alignment task can be performed in several stages. The first is the internal alignment of
the individual subdetectors. This is followed by the global alignment, in which the position andorientation of the entire subdetectors with respect to each other is determined. This has theadvantage that the number of alignment parameters that are estimated concurrently is reduced.
A possible disadvantage is the problem of achieving a consistent global alignment while keeping
the internal alignments fixed. It may therefore be necessary to envisage a final adjustment of
all alignment parameters of all subdetectors.
The required frequency of realignment depends mainly on the mechanical stability of the various
components. The mounting of the PXD detector on the beam pipe may make it necessary to
do one or even several global realignments per day.
With a sufficiently large number of tracks, the statistical errors of the estimated alignment
parameters can be made as small as required. The challenge is to control the systematic errors
to the required level [41]. This is because, for any kind of tracks, there are several degrees of
freedom that are not constrained, usually referred to as weak modes. A mixture of tracks thatis as diverse as possible is required to constrain all or at least most of the weak modes.
The requirements of past and current collider experiments on alignment performance, bothin terms of precision and in terms of the sheer number of parameters to be estimated, haveinstigated the development of a generic algorithm called Millepede [42, 43, 44]. It has been used
and is being used by several large experiments. Clearly, Millepede is an excellent candidate forthe alignment task of Belle II. It is worth noting, however, that the two largest LHC experiments,
ATLAS and CMS, which have the most difficult alignment tasks, do not rely on a single alignment
method, but have implemented several methods. This is extremely useful for debugging andcross-validation [45, 46, 47].
Alignment can be complemented by a precise estimation of the material budget, using reconstructed tracks. This is particularly important for low momentum tracks, which are strongly
affected by energy loss and multiple Coulomb scattering. Estimation methods for this task are
currently under development.

452

CHAPTER 14. COMPUTING AND SOFTWARE

14.4.7.4

Vertexing

Vertex reconstruction consists of (i) vertex finding and track bundling (a pattern recognitiontask); (ii) geometric vertex fitting (statistical estimation of the vertex position and the trackparameters at the vertex); and (iii) re-fitting with the kinematic constraints of energy-momentum
conservation. These tasks are, in practice, intertwined.
The virtual measurements of the vertex fit are the tracks fitted in the previous step, and extrapolated inwards into the beam-tube; thus, no material effects need to be taken into accountany more. The track parameters and covariance matrix may be defined on a reference surface(e.g., the inside of the beam-tube), or as perigee parameters with respect to a fixed pivot pointclose to the beam interaction (see appendix of Ref. [11]). In the case of a primary vertex, thebeam interaction profile, if known, may be included as another virtual measurement.
A vertex fitted from n tracks consists of (3 + 3n) parameters: 3 position coordinates, and 3 trackparameters at the vertex for each track. For a subsequent kinematic fit, the full (3+3n)×(3+3n)covariance matrix is required; if this is not the case, only some 3 × 3 sub-matrices need to becomputed.
Geometric vertex reconstruction starts with a Kalman filter [37, 48], with the linear expansion point being chosen from the beam interaction profile and/or crude track intersections. A
smoother is required for obtaining the best estimates of all tracks added before the last one. The
smoothed χ2 s may be used as test criteria for outliers, i.e., tracks not belonging to this vertex;
however, the power of these tests suffers for the same reasons as discussed in the case of trackfitting above.
The remedy are robustified, non-linear, adaptive filters—in particular, the Deterministic Annealing Filter (DAF) [49], which down-weights the influence of outlier tracks on the fitted vertex. It
introduces an annealing schedule that serves two purposes: it prevents the fit from falling into
a local minimum, and allows progressively moving from “soft” to ultimate “hard” assignments.
This leads in a natural way to a technique of vertex finding, called Adaptive Vertex Reconstruction (AVR [50]): if the DAF is applied to all tracks, with the proper setting of the annealingschedule, it converges to the vertex with the largest number of tracks. The tracks attachedto this vertex are removed from the track collection, and the DAF is applied to the remaining
tracks. This is iterated until no more vertices can be found. The AVR will be evaluated against
other vertex finders, in particular, the topological vertex finder ZvTop [51].
The DAF can be further generalized by introducing a Multi-Vertex Filter (MVF) [52], simultaneously fitting n tracks to m competing vertices by “soft assignment” of each track to morethan one vertex.
The inclusion of electron tracks fitted with the Gaussian Sum Filter (GSF) causes the vertex
fit also to be modeled as a Gaussian sum. This may result in an exponential bloat unlesscompensated for by an appropriate “collapsing strategy” [53]. The GSF is fully compatible withthe adaptive methods (DAF, MVF).
Kinematic fitting imposes the constraints of energy-momentum conservation on each vertex.
The method used is that of Lagrangian multipliers [27, 54]. It can be achieved either as aseparate re-fit step after pure geometric vertex fitting, or directly by a simultaneous geometry& kinematic fit. Problems arise in cases of insufficient information (unknown masses, unseen
particles, etc). Complex cascade decay chains are difficult to handle in a general way. Kinematic
fitting may more likely be subject to the requirements of a subsequent physics analysis.
At Belle and Belle II, vertex reconstruction is of utmost importance for physics studies like
CP violation in B B̄ systems, which rely on precise measurements of ∆z between the two B
decay vertices. This can only be achieved if the high-resolution PXD and SVD detectors are453

CHAPTER 14. COMPUTING AND SOFTWARE

complemented by sophisticated reconstruction, based on statistical methods fully exploiting theinformation available.
Vertex reconstruction, being the last step in the event reconstruction chain, may be boxed in a
detector-independent toolkit. Such a toolkit exists (RAVE [55, 56]). Its algorithms are sourcecode compatible with those implemented for the CMS experiment at LHC. They include theKalman filter, the DAF, the MVF, the GSF, and the AVR; an interface to ZvTop also exists.
Kinematic vertex reconstruction is implemented but is limited to the Kalman filter; it allows foruser-defined decay topologies. Implementing RAVE for Belle II will require only minimal effort
for interfacing to our framework’s track propagator and data model.
Geometric vertex finding and fitting in RAVE are state-of-the-art. Its kinematic vertex reconstruction, however, will require a critical comparison with that of the old Belle framework. Given
the importance of kinematic fitting for the analysis of Belle II data, a symbiosis between RAVE
and ExKFitter could be feasible to attain the same functionality and quality in kinematics.

14.4.8

Event Display

The data, flowing through the offline software, is usually visualized by the user via histogramsor scatterplots or by direct printing of the values. But there are occasions where a more pleasing
visualization is advantageous. In the following, examples for data visualization and the requirements they impose on a visualization solution are given. Finally, the approach taken for the
Belle II offline software is presented.
14.4.8.1

Examples of data visualization needs

The need for proper data visualization starts in the early phase of the offline software life cycle.
During the development of algorithms, it is mandatory to consistently check that the algorithms
behave correctly. Besides the usual histogram/direct printing approach, event-visualization techniques are extremely helpful in doing this. For example, the development of pattern recognition/tracking algorithms is greatly supported by a three-dimensional visualization of tracks, theirassociated hits and the tracking geometry. In particular, it is often enlightening to compare thesimulated tracks with those found by the pattern recognition/tracking algorithms visually. Also,using visual tools to build the detector from its subdetectors can illuminate problems associatedwith the overlap of detector parts, uncovered gaps in the acceptance region, or cabling issues.
Later, during the running phase of the detector, event visualization is helpful to support thesurveillance and monitoring of the data acquisition and to provide a visual feedback for thecontrol room.
The fields of application mentioned above require a simple-to-use yet powerful software to visualize event-level data of the Belle II experiment. Therefore, its main purpose is to display thefollowing items in a three-dimensional view and in different two-dimensional projections:• detector geometry• tracks (simulated and reconstructed)• vertices (simulated and reconstructed)• reconstructed hits
• additional information like energy deposit, particle id ...

454

CHAPTER 14. COMPUTING AND SOFTWARE

The event display should be easily adjustable for various types of input data, should provide
tools to work and display this data in a physics-oriented way and allow the creation of highquality pictures for talks and public relations purposes. Therefore, a modular system was chosen
for the event display software. The next section provides a more in-depth view of the solution
found for the Belle II experiment.
14.4.8.2

The GenericEventViewer

The event display developed for the Belle II experiment carries the name GenericEventViewer(GeV). As the name suggests, the GeV was developed with a generic data- and task-independent
concept in mind. Therefore, the GeV is not based on the common software framework. Rather,
due to GeV’s modular design, the software framework will be tightly integrated into the event
display. This integration will allow the user to load a framework steering file into the Event
Display and run it there. The user has then the possibility to change parameter values offramework modules in the steering and will experience a visual feedback immediately. The
same holds for changes made to the source code of a framework library or module. The highmodularity of the GenericEventViewer is achieved by using plugins. In general, plugins are userwritten extensions to an already existing application and widely used in large software projects
to keep source code complexity moderate. In the language of software design, an applicationthat can be extended by plugins is called a plugin host. It provides a well-defined interface foraccessing and modifying data, stored inside the application, and a mechanism to dynamicallylink plugins at runtime into the application. New features can be added to the application
without having to recompile the application itself. In addition, plugins automatically benefit
from updates made to the core functions of the host application. Depending on the operating
system, plugins are stored in shared object files (*.so, Linux) or dynamic link libraries (*.dll,
Windows). The GenericEventViewer contains a newly developed, operating system independent,
plugin system capable of loading and executing user written plugins. There are different typesof plugins:• Import plugins
Load data into the GenericEventViewer by converting the data to geometry objects.
• Export plugins
Save the geometry data to files, which can then be used by external software.
• Render plugins
Render plugins create pretty looking pictures from the geometry data. Usually external
render engines are used.
Being the most important plugin type, the import plugin mechanism is now presented in moredetail. Using the import plugin, data from various sources can be brought into the GenericEventViewer. Inside the import plugin, data is read from a source and converted to geometry
objects. For example, hits in a subdetector are represented by three-dimensional points, tracks ashelices and detector geometry as a collection of boxes, cylinders and spheres. The GeV provides
all necessary geometry types and transformations (rotation, translation). All created geometry
objects are stored in a list. From this list, different hierarchical representations, called views, arederived. This concept allows GeV to present the same objects in different kinds of hierarchies tothe user. For example, one can think of a hierarchy showing the geometrical relationship of particles/tracks and another hierarchy concentrating on the parent/child relationship of particles.
455

CHAPTER 14. COMPUTING AND SOFTWARE

Each geometry object can carry additional information, called MetaData. This allows GeV toattach information like momentum, vertex position and particle type to tracks or energy deposit
and position to hits. Using this MetaData, the user of the event viewer can then interactively
apply cuts on certain values (e.g., momentum) to limit the number of objects visualized.

Figure 14.23: Screenshot of the GenericEventViewer. Shown are the tracking subdetectors andthe particle trajectories from a simulated B B̄ event
All objects are shown in a three-dimensional view (Fig. 14.23), which can be rotated, panned andzoomed in realtime. OpenGL is used for hardware accelerated and operating system independentdrawing of the three dimensional shapes. It is possible to select objects to display their MetaDataor perform per-object oriented tasks like hiding objects or applying specific actions to them.
The process of selecting objects is carried out either by selecting the appropriate entry in a tree
widget, which represents the internal object hierarchy, or by simply selecting the objects in thethree-dimensional view.
Special emphasis is put on a particle physics oriented visualization solution. Therefore, theGenericEventViewer supports various three-dimensional drawing modes (projection, orthogonal,
fish-eye), two-dimensional representations (e.g., x–y, r–z) and advanced event selection features
based on the geometrical topology of an event.

14.5

Resource Requirements

To develop, maintain, and operate the components of the Belle II computing system described in
the previous sections, considerable human resources are required. Because of the large expected
456

CHAPTER 14. COMPUTING AND SOFTWARE

data size, there is a high demand of computational, storage, and network resources as well. The
anticipated requirements for both types of resources are described in detail in this section.

14.5.1

Human Resources

The tasks that have to be covered to develop and run the Belle II computing system can beroughly classified into the following categories:• Code development• Operation of central (Belle II specific) services• Operation of grid sites and grid services• Data processing and MC production• Support and training• Management
Individual roles assigned to the task categories mentioned above are listed and described indetail in the Belle II Computing TDR [11]. An overview of the roles and their relations is given
in Fig. 14.24. There is no exact one-to-one matching between roles and persons. One person
can have several roles, and one role can be shared by more than one person.
In addition to the categorization of tasks according to the type of work, the computing groupis organized in working groups focusing on particular topics that can involve and provide aconnection between code development and operational tasks. The working groups are• Core Software Group: develops and maintains the analysis framework (Sec. 14.4.3),
the event data model (Sec. 14.4.4), the geometry and conditions database (Sec. 14.4.5),
and the event display (Sec. 14.4.8). It is also responsible for the operations of the central
conditions database.
• Distributed Computing and Data Management Group: responsible for the planning, deployment and operation of computing, storage, and network resources. It also
has to develop and operate a system to make these resources available to the Belle II
collaboration (Sec. 14.3).
• Simulation Group: mainly consists of experts from detector groups who develop thesimulation software for the Belle II detector components (Sec. 14.4.6).
• Tracking Group: based on the local detector component reconstruction provided bydetector experts this group develops and maintains global tracking and alignment code
(Sec. 14.4.7).
Some topics are not covered by groups, but by individuals. For example there are Coordinators
who takes care of the code management, the calibration, the raw data processing, and the MC
production.
Decisions on priorities of competing tasks will be taken by the Computing Steering Committee, composed of the Distributed Computing and Data Management Group Convener, theData Processing, MC Production, Physics, and Computing Group Coordinators.

457

CHAPTER 14. COMPUTING AND SOFTWARE

Figure 14.24: Roles involved in the development, maintenance, and operation of the Belle IIcomputing system. Envisaged management flows are indicated by lines. Not all relations areshown.

14.5.2

Hardware Resources

As described in Sec. 14.2, a hierarchical structure is considered for the Belle II distributed
computing system. KEK should be the main computer center, where all raw data is processedand stored. All produced DST and mDST files from the raw data are also archived at KEK.
Here, the DST file is stored in RAW data format and used for the calculation of calibration
constants for each sub-detector and sometimes for systematic error studies. On the other hand,mDST files have only reconstructed track/cluster/particle-ID information in an analysis-friendly
format. Analysis users can make any analysis using this mDST file format.
The remote grid sites are responsible for the MC production and for the user analysis. Furthermore, the produced MC data in mDST format is stored at the site where it was created. In
458

CHAPTER 14. COMPUTING AND SOFTWARE

particular, KEK serves not only as the main center but also as a grid site for MC production
and user analysis. In this section, we estimate the requirement for the hardware resources toestablish the proposed computing model.
14.5.2.1

Expected event rate and expected event data size

The expected event rate can be roughly calculated from the instantaneous luminosity and theevent production cross section. The SuperKEKB accelerator will be operated at the energyof the Υ(4S) resonance (= 10.58 GeV/c2 ) and the bb̄ production cross section at this energy
is roughly equal to 1 nb. Though the target instantaneous luminosity is 8 × 1035 /cm2 /s, theSuperKEKB accelerator will at the early stage of the experiment be operated with a lower
luminosity, which will then gradually increase.
In this estimation, we assume the instantaneous luminosity at around 2016 to be 2 × 1035 /cm2 /sand the running-time of the accelerator to be roughly two thirds of a year. The rate for bb̄ eventsis calculated to be ∼ 200 Hz and the number of bb̄ events is to be 4 × 109 events per year. The
current Belle experiment has accumulated an integrated luminosity of ∼ 950 fb−1 in ten yearsof operation, and this corresponds to roughly 1 × 109 bb̄ events. That is, four times the entire
Belle data will be accumulated in one year even in the early stage of the experiment.
However, bb̄ events are not the only events in the Belle II experiment. We need to take into
account other q q̄ events (∼ 3 nb) as well as τ + τ − pair production (∼ 1 nb). For these physics
events, we need to handle on the order of 1010 events per year.
For the moment, the amount of beam background due to lost beam particles, beam-gas interaction, synchrotron radiation, and intra-beam effects is still being estimated, and we do not quotea final value for our estimation. However, according to the Trigger group, after applying theHigh Level Trigger, the event rate to the storage is estimated to be 6 kHz at an instantaneous
luminosity of 8 × 1035 /cm2 /s in the worst case. Of this, 4 kHz comes from physics events andcorrespond to the cross section 5nb. The remaining 2 kHz arises from the beam background.
We follow this Trigger group’s estimation and adopt it in our calculation (see Table 14.4).
Table 14.4: Cross section for each physics event.
cross section (nb)bb̄
1
q q̄ (continuum)
3
+
−
1
τ τ
Subtotal (physics)
5
background2.5(cross-section equivalent)
total
7.5

The projected integrated luminosity per year is quoted from the luminosity prospect provided
by SuperKEKB and summarized in Table 14.5.
Based on Tables 14.4 and 14.5, we can calculate the expected number of events for each fiscal
year, summarized in Table 14.6.
The total event size is estimated by the Trigger group and ranges from 100kB to 300kB. The
event size easily varies by the data size from PXD in the current estimation. We take the worst
case, 300kB, for our resource estimation.

459

CHAPTER 14. COMPUTING AND SOFTWARE

Table 14.5: Expected annual integrated luminosity. (See also the luminosity prospect in
Fig. 14.25.)
Fiscal year
2014 2015 2016 2017 2018 2019
(Apr.1-Mar.31)
Projected Lint /year
1
2
8
11
13
13
−1
[ab ]
Total Lint
1
3
11
22
35
48

Table 14.6: Expected number of events by the end of each fiscal year.
Fiscal year
2014 2015 2016 2017 2018 2019
(Apr.1-Mar.31)bb̄[×109 ]
1
2
8
11
13
13
(events/year)
Hadronic [×109 ]
4
8
32
44
52
52
(events/year)
All [×109 ]
7.5
15
60
83
98
98
(events/year)
Integrated [×109 ] 7.5
23
83
165
263
360
(events)

14.5.2.2

Resource requirements for DST/MC production and user analysis

KEK, as a main computer facility, is responsible for the processing and storage of the raw data.
We adopted the event rate and event data size estimated by the Trigger group in our calculation.
But there are still many uncertainties in the event data size, effect of the beam background andoptimization of the High Level Trigger, and so on. To take these into account, we apply a safety
factor of 2 to the storage space for the raw data, which will be estimated more realistically inthe near future.
The procedure of processing of the raw data and preparing the mDST files for physics analysis isreferred to as a DST production, as explained in Sec. 14.2. Usually, the DST production follows
a certain completed experimental running period, since the final detector-calibration constants
are required for the raw data processing. We assign a time period of TData = 5 months for theprocessing stage in the resource estimation. The time estimate for the processing of a single
event is based on the current Belle CPU resources and the obtained value is 8.33 HepSPEC ·sec/event [57], which includes also the effect of the hyperthread technology. (A typical HepSPEC
value for Intel Xeon 3.6GHz 2core is roughly 14.)After the processing of the raw data, the physics skimming process is applied to produce themDST files. The ratio of events produced after the physics scheme is assumed to be 1/3 and thesize of the mDST is assumed to be 40 kB/event, which is again based on the Belle experiment.
This event size could be larger if the amount of data from the PXD can not be reduced enough.
For the calibration and sub-detector studies, like the determination of the alignment constantsfor the PXD and/or the SVD, the DST files are needed as well. However, it seems that 2% of
the processed raw data saved as DST files is enough for this purpose.
We need MC events corresponding to at least 3 times the real data to reduce the systematic error

460

CHAPTER 14. COMPUTING AND SOFTWARE

Table 14.7: Summary of the input parameters for the resource estimation.
parameter
setting value
Raw data size [kB/event]300
300
DST [kB/event]mDST(data) [kB/event]40
40mDST(MC) [kB/event]safety factor for the storage spaceof raw data
2
DST production period [months/year]
55
MC production period [months/year]
CPU resources for DST prod.
[HepSPEC·sec/event]8.33
CPU resources for MC prod.
[HepSPEC·sec/event]16.44# of MC streams
6
DST event output fraction
0.02
a fraction of CPU power
0.5
for user analysis wrt. DST production
a fraction of storage space
0.5
for user analysis wrt. mDST
Conversion factor of the CPU power
3.83
to power consumption [W/HepSPEC]
Conversion factor of the storage space24
to power consumption [kW/PB]

associated with statistical fluctuations in the produced MC events. In the Belle experiment, 10
streams of the MC were prepared. Therefore, as a baseline we adopt Nstreams = 6 streamsof the MC. To reproduce the condition when the data was taken, the MC event is producedwith the measured detector constants and with the embedding of real beam background thatwas taken during the experiment. Most of these are prepared after the experiment running
period and then the MC production starts at the grid computing facilities. We set a period of
TM C = 5 months for the MC production. The size of the mDST for MC events is assumed to
be 40 kB/event, which is the same for the real data. The mDST for MC events consists of thephysics analysis oriented information, e.g., track and particle ID, as well as the MC generator
level information. Roughly 10% of the mDST event is occupied by the generator information; inother words, the size of the mDST for MC becomes larger than that for data by 10%. However,this 10% increase is smaller than other uncertainties in the estimation of the storage space forraw data. Therefore, we use the same value for the mDST event size for both data and MC
cases.
In the current Belle experiment, the CPU is shared by the DST/MC production and user
analysis. This situation will not change in Belle II: 50% of the CPU resources assigned to the
DST production is assumed to be used for user analysis. For the storage, we just assume thata disk space corresponding to 50% of mDST is used by user analysis.
For the conversion factors to evaluate the power consumption due to the CPU power and thestorage space, we adopted 3.83 W/HepSPEC based on the current typical 8-core machine and
24 kW/PB based on the existing RAID server, respectively.
461

CHAPTER 14. COMPUTING AND SOFTWARE

By combining these inputs, summarized in Table 14.7, we obtained the requested power of
the CPU and amount of the storage for the DST production (Table 14.8), MC production(Table 14.9) and user analysis (Table 14.10).
Table 14.8: Expected amount of storage and CPU power for DST production.
Fiscal year
2014 2015 2016 2017 2018 2019
(Apr.1-Mar.31)
Raw data
size per year [PB]
4
8
32
46
54
54
Total size [PB]
4
12
45
90
143
196
mDST
(per one version)
size per year [PB]
0.2
0.4
1.5
2.0
2.4
2.4
Total size [PB]
0.2
0.6
2.0
4.0
6.4
8.7
DST
(per one version)
size per year [PB] 0.04
0.1
0.3
0.5
0.5
0.5
Total size [PB]
0.04
0.1
0.5
0.9
1.4
2.0
CPU [kHepSPEC]
5
10
38
52
62
62

Table 14.9: Expected amount of storage and CPU power for MC production.
Fiscal year
2014 2015 2016 2017 2018 2019
(Apr.1-Mar.31)
MC datasize per year [PB]
0.9
1.8
7.0
9.6
11.4 11.4
Total size [PB]
0.9
2.6
9.6
19
31
42
CPU [kHepSPEC]
30
60
240
330
390
390

Table 14.10: Expected amount of storage and CPU power for user analysis.
Fiscal year
2014 2015 2016 2017 2018 2019
(Apr.1-Mar.31)
user area
size per year [PB]
0.1
0.2
0.7
1.0
1.2
1.2
Total size [PB]
0.1
0.3
1.0
2.0
3.2
4.4
CPU [kHepSPEC] 2.4
7.1
26
52
83
114

14.5.2.3

Resource requirements for KEK

Here, a more concrete estimation of the required resources for KEK not only as a main computer
facility but also as a grid site is presented.
462

CHAPTER 14. COMPUTING AND SOFTWARE

The role of the main computer facility is the processing of the raw data, the archiving of the
produced mDST and DST data as well as the raw data, and the migration of the mDST data toremote grid sites. Because the raw data is not processed so frequently except in the early stageof the experiment, we assume that the raw data is stored on tape. On the other hand, mDST
is heavily accessed by users. Therefore, it is useful to keep the mDST data on disk.
When the reconstruction software is upgraded, e.g., upon implementation of better tracking andclustering algorithms, or we find that there is a serious bug in the code, we need to reprocess
the raw data and iterate the physics skimming process. In that case, we have to store the new
reprocessed data, while keeping the old one. Therefore, we set the number of mDST versions atshould be kept at 2.
The network bandwidth is estimated such that the mDST data can be transfered to four remotesites in parallel to its production.
KEK also plays a role as a grid site and has a responsibility to produce and to keep a certain
fraction of MC events, which is proportional to the number of assigned people to the KEK
grid site. We shall assume 25% for this fraction in this estimation. We assume that the MC
production will take place after DST production, because we need information of beam energy,
IP profile, and number of B B̄ events as inputs for MC production to reproduce the experimental
condition as much as possible. In that sense, we can effectively utilize the CPU power that is
assigned to DST production. This overlap reduces the need for additional CPU resources. In
this estimation, we estimated the CPU resources that are required for DST production and thosefor MC production, first. After comparing these two requirements, the larger resource value isadopted to be a required CPU resources for KEK.
Another task of the grid facility is to transfer copies of mDST datasets from KEK and keepthem on disk. However, for KEK, because all mDST datasets are kept as a concequence of the
DST production and no transfer is needed, we do not consider the network bandwidth in termsof MC production.
Table 14.11 shows the resource requirements for KEK.
Table 14.11: Resource requirements for KEK.
Fiscal year
2014 2015 2016 2017
(Apr.1-Mar.31)
Total tape size [PB]
4
12
45
90
Total disk size [PB]
0.9
2.6
9.5
19
CPU [kHepSPEC] for DST prod.
5
10
38
52
CPU [kHepSPEC] for MC prod.
8
17
67
96
+ User Analysis
Adopted CPU [kHepSPEC]
8
17
67
96
WAN (outward
0.5
0.9
3.7
5.1
from KEK)[Gbit/s]
Power (CPU) [kW]
31
64
255
366
Power (Disk) [kW]
10
29
107
214

463

2018

2019

143
30
62
118

196
41
62
126

118
6.0

126
6.0

453
340

483
466

CHAPTER 14. COMPUTING AND SOFTWARE

14.5.2.4

Resource requirements for a typical remote grid site

The role of the grid computer facility is the production and archiving of MC events. The amountof MC is proportional to the number of analysis users assigned to this facility relative to thetotal number of the Belle II members. Furthermore, the remote site serves also as an analysis
facility for these users. In the exemplary calculation presented here, we assume the fraction of
the Belle II members at the typical remote grid site is 15%.
Another important task of the regional computing facility is to keep the copy of the mDST
datasets that are transferred from KEK. Thanks to this, we can reduce the load of the network
at KEK when users access the mDST frequently during the physics analysis.
The current best estimation is summarized in Table 14.12.
Table 14.12: Resource requirements for a typical remote grid site.
Fiscal year
2014 2015 2016 2017 2018 2019
(Apr.1-Mar.31)
Total disk size [PB] 0.5
1.4
5.0
10
16
22
CPU [kHepSPEC]
5
10
40
57
71
76
WAN (inward
0.1
0.2
0.9
1.3
1.5
1.5
from KEK)[Gbit/s]
Power (CPU) [kW]
19
39
153
220
272
290
Power (Disk) [kW]
11
33
121
242
384
527

14.6

Schedule

To optimize the detector design and to check the sensitivity to the physics of interest, a full
detector simulation that works within a common software framework is essential. We alsoneed an event data model of each sub-detector to handle objects produced in the simulator.
As written in Sec. 14.4, we plan to have our own software framework so-called roobasf, on
which development has been progressing. The implementation of the GEANT4-based detector
simulation in this new framework has started. At this moment, a few sub-detectors related tothe tracking have decided the outline of their event data model and installed the basic geometry
into the simulator. For other sub-detectors, we will finish installing the geometry as soon as
possible with help from each sub-detector group.
Regarding the reconstruction tool, we have initiated an activity to develop a new track finding/fitting tool and we aim to release the 0-th version by 2013. In parallel, we will releasea benchmark of pattern recognition based on the track finding tool developed for the current
Belle. Until the new tracking tool is ready, the benchmark version can be used as a tracking
tool for Belle II. For the particle ID tools, the TOP and A-RICH groups have already developed
stand-alone reconstruction tools. They will now start to incorporate these tools within the newsoftware framework.
We have finished the design of the distributed Belle II computing system and summarized it inthis chapter. For now, we have started several tests for the basic components of the proposed
design. The started tests include the prototype of the data handling system utilizing the AMGA
metadata catalogue, the construction of the Belle II virtual organization on the grid, a test for464

CHAPTER 14. COMPUTING AND SOFTWAREFirst collision

Replacement ofBelle II Computer

x10

Belle II Computer installation

the establishment of the job handling, and a challenge for the cloud computing. We would liketo finish these tests by the middle of the Japanese fiscal year (JFY) 2011.
We also have to take into consideration when the new computing system will be installed at
KEK. Because of the expiry of the existing contract, the Belle computing system will be replacedwith a new system at the end of JFY 2011 (February or March in 2012). Though we are now
discussing the contract itself, the specification needs to be prepared by the summer of 2010
(Fig. 14.25). In this specification, we have to consider not only the hardware resources required
for the Belle II computing system by JFY 2015 or 2016 when the follow-on replacement will takeplace but also the transfer of the large amount of legacy data stored by the Belle experimentfrom the current system to the new one. In any case, the detailed schedule of the Belle IIcomputing system will be adjusted to the contract, the bidding process, and the KEK-wide
computing system.
Once the new computing system is installed, we would like to start the dress rehearsal of theBelle II computing system immediately. At that stage, we will have at least two year prior to
the first collision. Furthermore, we would like to start the systematic MC mass production totest the computing system and also the reconstruction procedure.

2012

2014

2016

35

70
60
50
40
30
20

Now we are here
Specification of
Belle II Computer

Integrated Luminosity

80

10
0
2010

2018

2020

2022

year

Figure 14.25: Important milestones for Belle II computing with a luminosity prospect465

References[1] Belle, A. Abashian et al.,9002(01)02013-7.

Nucl. Instrum. Meth. A479, 117 (2002),

10.1016/S0168-[2] Integrated luminosity: http://belle.kek.jp/bdocs/lum day.gif.
[3] E. Laure et al., Computational Methods in Science and Technology 12, 33 (2006).
[4] EGEE: http://public.eu-egee.org.
[5] WLCG: http://lcg.web.cern.ch/LCG.
[6] CREAM: http://grid.pd.infn.it/cream.
[7] SAM: http://projects.fnal.gov/samgrid.
[8] A. T. V. Garonne and I. Stokes-Rees, Computing in High Energy Physics and Nuclear
Physics 2004 1, 1041 (2004).
[9] AMGA: http://cern.ch/amga.
[10] PostgreSQL: http://www.postgresql.org.
[11] Belle II Computing Group, Belle II Computing Technical Design Report, 2010.
[12] Subversion: http://subversion.apache.org.
[13] ViewVC: http://www.viewvc.org.
[14] Doxygen: http://www.doxygen.org.
[15] Artistic Style: http://astyle.sourceforge.net.
[16] ATLAS, A. D. Salvo et al., J. Phys.: Conf. Ser. 119, 052013 (2008), 10.1088/17426596/119/5/052013.
[17] ROOT: http://root.cern.ch.
[18] R. Itoh, Talk given at Computing in High-energy Physics (CHEP 97), Berlin, Germany,
7-11 Apr 1997.
[19] Python: http://www.python.org.
[20] XInclude: http://www.w3.org/standards/techs/xinclude.
[21] E. Harold and W. Means, XML in a Nutshell, Third Edition (O’Reilly Media, Inc., 2004).
466

REFERENCES[22] XPath: http://www.w3.org/standards/techs/xpath.
[23] D. J. Lange, Nucl. Instrum. Meth. A462, 152 (2001), 10.1016/S0168-9002(01)00089-4.
[24] S. Jadach, B. F. L. Ward, and Z. Was, Comp. Phys. Commun 130, 360 (2000).
[25] S. Jadach, and Z. Was, Comp. Phys. Commun 85, 453 (1995).
[26] Geant4: http://geant4.web.cern.ch/geant4.
[27] R. Frühwirth et al., Data Analysis Techniques in High-Energy Physics, 2nd ed. (Cambridge
University Press, 2000), ISBN 0-521-63219-6 (hardback) and 0-521-63548-9 (paperback).
[28] P. V. C. Hough, Machine analysis of bubble chamber pictures, in Proceedings of theInternational Conference on High Energy Accelerators and Instrumentation, pp. 554–556,
CERN, 1959.
[29] I. Kisel, E. Konotopskaya, and V. Kovalenko, Nucl. Instrum. Meth. A 389, 167 (1997).
[30] S. Gorbunov and I. Kisel, Nucl. Instrum. Meth. A 559, 139 (2006).
[31] R. Mankel, Nucl. Instrum. Meth. A 395, 169 (1997).
[32] V. Highland, Nucl.Instr.Meth. 129, 479 (1975).
[33] R. Frühwirth and M. Regler, Nucl.Instr.Meth. A 456, 369 (2001).
[34] H. Bethe and W. Heitler, Proc. R. Soc. A 146, 83 (1934).
[35] W. Adam et al., J. Phys. G: Nucl. Part. Phys. 31, N9 (2005).
[36] ATLAS collaboration, V. Kartvelishvili, Nucl. Phys. B (Proc. Suppl.) 172, 208 (2007).
[37] R. Frühwirth, Nucl. Instrum. Meth. A 262, 444 (1987).
[38] R. Frühwirth and A. Strandlie, Comput. Phys. Comm. 120, 197 (1999).
[39] C. Höppner, S. Neubert, B. Ketzer, and S. Paul, Subm. to Nucl.Instr.Meth. A (2010).
[40] M. Regler, M. Valentan, and R. Frühwirth, LiC Detector Toy 2.0 user’s guide, HEPHYPUB-863/08 (version 2.0); Inst. of High Energy Physics, Vienna, Austria., 2008.
[41] D. N. Brown et al., Nucl. Instrum. Meth. A 603, 467 (2009).
[42] V. Blobel and C. Kleinwort, A new method for high-precision alignment of track detectors, in Proceedings of the 2002 Conference on Advanced Statistical Techniques in Particle
Physics, pp. 268–277, University of Durham, 2002.
[43] V. Blobel, Nucl. Instrum. Meth. A 566, 5 (2006).
[44] V. Blobel, Millepede II: Linear Least Squares Fits with a Large Number of Parameters,
http://www.desy.de/˜blobel/Mptwo.pdf, 2007.
[45] ATLAS Inner Detector Alignment Group, A. Morley, Nucl. Instrum. Meth. A 596, 32(2008).
[46] E. Widl and R. Frühwirth, J. Phys.: Conf. Ser. 119, 032038 (2008).
467

REFERENCES[47] W. Adam et al., JINST 4, T07001 (2009).
[48] R. Frühwirth, P. Kubinec, W. Mitaroff, and M. Regler, Comp.Phys.Comm. 96, 189 (1996).
[49] W. Waltenberger, R. Frühwirth, and P. Vanlaer, J.Phys.G 34, N343 (2007).
[50] W.
Waltenberger,
Adaptivevertexreconstruction,
http://cms.cern.ch/iCMS/jsp/openfile.jsp?type=NOTE&year=2008&files=NOTE2008 033.pdf,
2008.
[51] D. J. Jackson, Nucl. Instrum. Meth. A 388, 247 (1997).
[52] R. Frühwirth and W. Waltenberger,
Adaptive
http://cdsweb.cern.ch/record/803519/files/cr04 062.pdf, 2004.

multi-vertex

fitting,[53] T. Speer and R. Frühwirth, Comp.Phys.Comm. 174, 935 (2006).
[54] P. Avery,
Applied fitting theory VI: Formulas
http://www.phys.ufl.edu/˜avery/fitting/kinematic.pdf, 1999.

forkinematic

fitting,[55] W. Waltenberger, W. Mitaroff, F. Moser, B. Pflugfelder, and H.V.Riedel, The RAVE/VERTIGO vertex reconstruction toolkit and framework, in Proc. Int. Conf. on Computing inHigh Energy and Nuclear Physics (CHEP ’07), J. Physics: Conference Series 119 (2008)
032037.
[56] F. Moser, W. Waltenberger, M. Regler, and W. Mitaroff, Implementation and applicationof kinematic vertex fitting in the software environment of ILD, in Proc. Int. Linear Collider
Workshop (LCWS ’08), arXiv:0901.4020v1, January 2009.
[57] HepSPEC: https://hepix.caspur.it/processors/dokuwiki/doku.php?id=benchmarks:introduction.

468

Chapter 15

Organization
15.1

Collaboration members and organization

To pursue the R&D and design of the Belle II detector, a new collaboration has been formed.
It consists of 44 institutions as of January 2010. Table 15.1 lists all member institutions (asof January 2010) together with the number of collaborators at each institution; the number ofstudents is given in parentheses. The collaboration now consists of nearly 300 people from 44
institutions in 13 countries.
Open collaboration meetings are held regularly three times per year. By summer 2009, all theadministrative bodies of the Belle II Collaboration have been formed. As shown in Fig. 15.1,
the two main bodies are the Institutional Board and the Executive Board. The project is led
by the Spokesperson and Project Manager.
The Institutional Board gathers representatives of all collaborating institutes. This bodydefines and approves all major policy principles and documents (bylaws, etc.). It appoints a
Nominating Committee, responsible for nominating individuals to stand for election as Spokesperson. The Board is also responsible for carrying out the election of the Spokesperson.
The Executive Board advises the Spokesperson, appoints the detector subsystem coordinators and may appoint special committees when additional expertise is required. All decisions of
the Executive Boards must be ratified by the Institutional Board.
The Spokesperson is the scientific representative of the Collaboration and is responsible
for all scientific, technical and organizational affairs of the Collaboration. The Spokesperson iselected in a general collaboration-wide election.
The Project Manager assists the Spokesperson in keeping the KEK management apprisedof all Collaboration affairs and to informing the Collaboration of relevent KEK matters.
Individual aspects of the project are coordinated by the Physics Coordinator(s), Technical Coordinator and the Software and Computing coordinator(s), reporting to the Spokesperson.

15.2

Cost and schedule

The current estimates of the cost of detector components are in given in Table 15.2. The
construction schedule is shown in Fig. 15.2.
469

Executive Board
Chair : H. Aihara
aihara@phys.s.u-tokyo.ac.jp

A.E.Bonder, T.Browder,
P.Chang, T.Iijima, T.Muller,
H.Palka, Y.Sakai, M.Sevior,
C.Schwanda, E.Won C.Yuan,
T.Aziz, Z.Dolezal, K.Akai

Belle II Organization
Spokesperson : Peter Krizan

Institutional Board
Chair : L. Piilonen
piilonen@vt.edu

peter.krizan@ijs.si

Project Manager : M. Yamauchi
masanori.yamauchi@kek.jp

Speakers Committee
Chair : Y.Sakai
Yoshihide.Sakai@kek.jp

T.Iijima, T.Muller, A.Schwarz

Physics
Coordinator: B.Golob
bostjan.golob@ijs.si

Technical
Coordinator: Y.Ushiroda

Soft/Computing
Coordinator: T.Hara/T.Kuhr

ushiroda@post.kek.jp

takanori.hara@kek.jp
Thomas.Kuhr@kit.edu

PXD : H.G.Moser, C.Kiesling
SVD : T.Tsuboyama, M.Friedl
CDC : S.Uno
PID : I.Adachi, S.Korpar,
K.Inami, G.Varner
ECL : A.Kuzmin, I.Nakamura
KLM : K.Sumisawa, P.Pakhlov
DAQ/TRG : R.Itoh, Y.Iwasaki
IR : M.Iwasaki
STR : J.Haba

Figure 15.1: Belle II Organization

Distributed Computing: M.Sevior
Data Handling System: K.Cho
Database
Cord Management
Software Framework: R.Itoh
Reconstruction Software(pid, tracking, ...)
Simulation tools
Web, mail servers

Table 15.1: Institutions in the Belle II Collaboration (October 2010)
Persons Institute8
University of Sydney
University of Melbourne
Austria
11
Austrian Academy of Sciences (HEPHY), Vienna
China
17
Institute of High Energy Physics, Chinese Acad. Sci. Beijing
University of Science and Technology of China
Czech Rep.
6
Charles University in Prague
Germany
53
University of Bonn
University of Göttingen
University of Heidelberg
Karlsruhe Institute of Technology
Ludwig Maximilians Univ. and Excell. Cl. Universe, Munich
Technical University and Excellence Cl. Universe, Munich
Max-Planck-Institut für Physik, Munich
India
10
Indian Institute of Technology, Guwahati
Indian Institute of Technology, Madras
Institute of Mathematical Sciences (Chennai)
Panjab University
Tata Institute of Fundamental Research
Korea
34
Gyeongsang National University
Hanyang University
Korea Institute of Science and Technology Information
Korea University
Kyungpook National University
Seoul National University
Yonsei University
Poland12
Henryk Niewodniczanski Inst. of Nucl. Phys. PAN, Cracow
Russia31
Budker Institute of Nuclear Physics, Novosibirsk
Institute for High Energy Physics, Protvino
Institute for Theoretical Experimental Physics, Moscow
Slovenia
13
Jozef Stefan Institute, Ljubljana
University of Ljubljana
University of Maribor
University of Nova Gorica
Taiwan21
Fu Jen Catholic University
National Central University
National United Univ
National Taiwan University
U.S.A.
28
Pacific Northwest National Laboratory
University of Cincinnati
University of Hawaii
Virginia Polytechnic Institute and State Univ.
Wayne State University
Japan
102
Nagoya University
Nara University of Education
Nara Women’s University
Niigata University
Osaka City University
Toho University
Tohoku University
Tokyo Metropolitan University
University of Tokyo
KEK
Total
346
52 institutes from 13 countries
Country
Australia

Persons
4
4(2)
11(3)
10
7(5)
6(2)
9(4)
2(1)
4(2)
15(4)
2(0)
3(1)
18(7)
2
2
1
3(1)
2
1
6(4)
3
6(2)
7(3)
6(2)
3
12(1)
16(3)
4(1)
11(1)
6(1)
5(1)
1
1
4
2
2
13(2)
4
6
11(3)
5(2)
2(1)
13(4)
1
9
4(2)
4
2
15(3)
4(2)
4(2)
46
346

Table 15.2: Estimated cost of detector components (1 Oku yen=108 yen ≈ 1 M$).
Component
Estimated cost
(Oku yen)
Beam pipe
1.0
PXD
3.5
SVD
3.0
CDC
3.8
B-PID
7-8
E-PID
4-5
ECL (no crystals)
3.5
KLM
1.4
TRG
0.9
DAQ
4.3
Structure
4.5
Total
37.9

Figure 15.2: Belle II Construction schedule