IceCubeOctoberPreliminary
Design Document
11, 2001/ Revision: 1.24
The IceCube Collaboration

Simulated interactions of a 10 TeV  (top left), 375 TeV e (top right),
and 1 PeV  (bottom) in IceCube.

1The IceCube Collaboration
J. Ahrens12 , J.R. Alonso8 , J.N. Bahcall6 , X. Bai1 , T. Becka12 , K.-H. Becker2 , D. Berley13 , D. Bertrand3 ,D.Z. Besson, A. Biron5 , B. Bless16 , S. Boser5 , C. Bohm21 , O. Botner20 , A. Bouchta5;23 , S. Carius7 ,J. Cavin18 , A. Chen17 , W. Chinowsky8 , D. Chirkin10;2 , J. Conrad20 , J. Cooley17 , C.G.S. Costa3 , D.F. Cowen15 ,C. De Clercq22 , T. DeYoung17 , P. Desiati5 , J.-P. Dewulf3 , B. Dingus17 , P. Doksus17 , P.A. Evenson1 ,A.R. Fazely9 , T. Feser12 , J.-M. Frere3 , T.K. Gaisser1 , J. Gallagher16 , M. Gaug5 , A. Goldschmidt8 , A. Hallgren20 ,F. Halzen17 , K. Hanson15 , R. Hardtke17 , T. Hauschildt5 , M. Hellwig12 , P. Herquet14 , G.C. Hill17 , P.O. Hulth21 ,K. Hultqvist21 , S. Hundertmark11 , J. Jacobsen8 , G.S. Japaridze4 , A. Karle17 , R. Koch18 , L. Kopke12 ,M. Kowalski5 , J.I. Lamoureux8 , H. Leich5 , M. Leuthold5 , P. Lindahl7 , J. Madsen19 , P. Marciniewski20 ,H.S. Matis8 , C.P. McParland8 , P. Miocinovic10 , R. Morse17 , T. Neunho er12 , P. Niessen5;22 , D.R. Nygren8 ,H. Ogelman17 , Ph. Olbrechts22 , R. Paulos17 , C. Perez de los Heros20 , P.B. Price10 , G.T. Przybylski8 , K. Rawlins17 ,W. Rhode2 , M. Ribordy5 , S. Richter17 , H.-G. Sander12 , T. Schmidt5 , D. Schneider17 , D. Seckel1 , M. Solarz10 ,L. Sparke16 , G.M. Spiczak1 , C. Spiering5 , T. Stanev1 , D. Steele17 , P. Ste en5 , R.G. Stokstad8 , O. Streicher5 ,P. Sudho 5 , K.-H. Sulanke5 , I. Taboada15 , C. Walck21 , C. Weinheimer12 , C.H. Wiebusch5;23 , R. Wischnewski5 ,H. Wissing5 , K. Woschnagg10(1) Bartol Research Institute, University of Delaware, Newark, DE 19716, USA(2) Fachbereich 8 Physik, BUGH Wuppertal, D-42097 Wuppertal, Germany(3) Universite Libre de Bruxelles, Science Faculty CP230, Boulevard du Triomphe, B-1050 Brussels, Belgium(4) CTSPS, Clark-Atlanta University, Atlanta, GA 30314, USA(5) DESY-Zeuthen, D-15735 Zeuthen, Germany(6) Institute for Advanced Study, Princeton, NJ 08540, USA(7) Dept. of Technology, Kalmar University, S-39182 Kalmar, Sweden(8) Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA(9) Department of Physics, Southern University and A&M College, Baton Rouge, LA 70813, USA(10) Dept. of Physics, University of California, Berkeley, CA 94720, USA(11) Dept. of Physics and Astronomy, University of California, Irvine, CA 92697, USA(12) Institute of Physics, University of Mainz, Staudinger Weg 7, D-55099 Mainz, Germany(13) Dept. of Physics, University of Maryland, College Park, MD 20742, USA(14) University of Mons-Hainaut, 7000 Mons, Belgium(15) Dept. of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA(16) Dept. of Astronomy, University of Wisconsin, Madison, WI 53706, USA(17) Dept. of Physics, University of Wisconsin, Madison, WI 53706, USA(18) SSEC, University of Wisconsin, Madison, WI 53706, USA(19) Physics Department, University of Wisconsin, River Falls, WI 54022, USA(20) Division of High Energy Physics, Uppsala University, S-75121 Uppsala, Sweden(21) Fysikum, Stockholm University, S-11385 Stockholm, Sweden(22) Vrije Universiteit Brussel, Dienst ELEM, B-1050 Brussel, Belgium(23) Present address: CERN, CH-1211, Geneve 23, Switzerland

2

Contents

1 Document Overview

92 Executive Summary

10

3 Science Motivation for Kilometer-Scale Detectors

12

4 Status of High Energy Neutrino Astronomy

26

5 Expected IceCube Performance40

3.1 High-Energy Neutrinos Associated with Cosmic Particle Accelerators . . . . . . .
3.1.1 Energy Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.2 Estimates Based on Models . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.3 Neutrinos as a Diagnostic of TeV Gamma-Ray Sources . . . . . . . . . . .
3.2 Other Science Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1 WIMPs and Other Sources of Sub-TeV  . . . . . . . . . . . . . . . . . .
3.2.2 Atmospheric Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3 PeV and EeV Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.4 Tau Neutrino Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.5 Neutrinos from Supernovae . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1 Status of AMANDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.1 Atmospheric Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.2 Pointing Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.3 Search for a di use high energy neutrino ux . . . . . . . . . . . . . . . .
4.1.4 Point Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.5 Gamma-Ray Bursts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.6 WIMPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.7 Supernovae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.8 Magnetic Monopoles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.9 Summary of AMANDA Status . . . . . . . . . . . . . . . . . . . . . . . .
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 Atmospheric Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.3 Muon-Neutrino-Induced Muons . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.3.1 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.3.2 Reconstruction and Background Rejection . . . . . . . . . . . . . . . . . .
5.3.3 Sensitivity to Di use Sources of Muon Neutrinos . . . . . . . . . . . . . .
5.3.4 Sensitivity to Muon Neutrino Point Sources . . . . . . . . . . . . . . . . .
5.3.5 Sensitivity to Muon Neutrinos from Gamma-Ray Bursts . . . . . . . . . .
5.3.6 Possible Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4 Electromagnetic and Hadronic Cascades . . . . . . . . . . . . . . . . . . . . . . .
5.4.1 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3

13
14
17
17
18
18
20
20
21
23
24
29
29
32
33
33
36
37
38
38
39
40
40
40
40
42
47
49
49
54
56
56

5.4.2 Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.4.3 E ective Volume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.4.4 Sensitivity to Atmospheric  . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.4.5 Sensitivity to Point Sources . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.4.6 Sensitivity to Di use e Sources . . . . . . . . . . . . . . . . . . . . . . . 64
5.4.7 Sensitivity to GRBs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.4.8 Possible Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.5 Tau Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.5.1 Tau Neutrino Event Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.5.2 Tau Neutrino Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.6 Neutrino Flavor Di erentiation with Waveform Digitization . . . . . . . . . . . . 71
5.6.1 Photon Flux Distribution Generated by High Energy Cascades . . . . . . 73
5.6.2  Event Signatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
5.6.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
5.7 Lower Energy Phenomena and Exotica . . . . . . . . . . . . . . . . . . . . . . . . 87
5.7.1 Muon Neutrinos from WIMP annihilation . . . . . . . . . . . . . . . . . . 87
5.7.2 Neutrino oscillations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
5.7.3 MeV Neutrinos from Supernovae . . . . . . . . . . . . . . . . . . . . . . . 90
5.7.4 Relativistic magnetic monopoles . . . . . . . . . . . . . . . . . . . . . . . 92
5.7.5 Slowly moving, bright particles . . . . . . . . . . . . . . . . . . . . . . . . 95
5.8 IceCube Con guration Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.9 Calibration of High-Level Detector Response Variables . . . . . . . . . . . . . . . 96
5.9.1 Geometry Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.9.2 Calibration of Angular Response . . . . . . . . . . . . . . . . . . . . . . . 99
5.9.3 Calibration of Vertex Resolution . . . . . . . . . . . . . . . . . . . . . . . 99
5.9.4 Energy Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
5.10 IceTop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.10.1 Tagged Muon Bundles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.10.2 IceTop as a Veto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.10.3 Cosmic-ray Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

6 Experimental Requirements
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
6.9

104

Time Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Waveforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Dynamic Range and Linearity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Absolute Amplitude Calibration and Stability . . . . . . . . . . . . . . . . . . . . 107
Dead time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Sensitivity of optical modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Noise Rate and Noise Rate Stability . . . . . . . . . . . . . . . . . . . . . . . . . 107
Failure Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
IceTop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
4

7 Design and Description of IceCube

110

8 Data Handling163

7.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
7.2 Digital Optical Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
7.2.1 Pressure Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
7.2.2 Optical Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
7.2.3 PMT HV Generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
7.2.4 Optical Beacon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
7.2.5 Signal Processing Circuitry . . . . . . . . . . . . . . . . . . . . . . . . . . 122
7.2.6 Local/Global Time Transformation . . . . . . . . . . . . . . . . . . . . . . 128
7.2.7 Cable Electrical Length Measurement . . . . . . . . . . . . . . . . . . . . 136
7.2.8 Data Flow and Feature Extraction . . . . . . . . . . . . . . . . . . . . . . 136
7.2.9 Local Coincidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
7.2.10 System Design Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
7.3 Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
7.3.1 Copper Links . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
7.3.2 Time-Base Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
7.4 Surface DAQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
7.4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
7.4.2 DOM Hub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
7.4.3 String Processor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
7.4.4 IceCube and IceTop System Integration . . . . . . . . . . . . . . . . . . . 147
7.4.5 Experiment and Con guration Control . . . . . . . . . . . . . . . . . . . . 148
7.4.6 Security Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
7.4.7 DAQ Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
7.4.8 Calibration Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
7.4.9 DAQ and Online Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . 156
7.4.10 DAQ Computing Environment . . . . . . . . . . . . . . . . . . . . . . . . 157
7.5 AMANDA Data Transmission Techniques . . . . . . . . . . . . . . . . . . . . . . 159
8.1 System Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
8.1.1 Software Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
8.1.2 System Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
8.1.3 Development Environment . . . . . . . . . . . . . . . . . . . . . . . . . . 165
8.1.4 Analysis Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
8.1.5 Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
8.1.6 Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
8.1.7 Development Interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
8.1.8 Integration at Pole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
8.1.9 Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
8.1.10 Data Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
8.2 Oine Data Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
5

8.3 Data Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
8.3.1 High Multiplicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
8.3.2 Upgoing Tracks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
8.3.3 Cascades/Taus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
8.3.4 GRB Downgoing Muons . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.5 Icetop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.6 Supernova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.7 Prescaled Raw Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.8 Monitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.9 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
8.3.10 Full-Sky Summary Histograms . . . . . . . . . . . . . . . . . . . . . . . . 177
8.3.11 Un ltered Raw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
8.4 Data Sample Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
8.5 Latency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
8.6 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
8.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

9 Data Analysis

180

10 Drilling, Deployment and Logistics

185

9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
9.2 Analysis Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
9.2.1 Calibration Analysis and Data Quality Working Group . . . . . . . . . . 180
9.2.2 Simulation Working Group . . . . . . . . . . . . . . . . . . . . . . . . . . 181
9.2.3 Reconstruction Working Group . . . . . . . . . . . . . . . . . . . . . . . . 181
9.3 Computing Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
9.4 Physics Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
9.5 Internal Review Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
9.5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
9.5.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
9.6 Prerequisites and Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

10.1 Drilling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
10.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
10.1.2 Evolution of AMANDA Drills . . . . . . . . . . . . . . . . . . . . . . . . . 186
10.1.3 Performance Criteria and Design of the EHWD . . . . . . . . . . . . . . . 186
10.2 Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
10.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
10.2.2 AMANDA Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
10.2.3 AMANDA Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
10.2.4 IceCube Deployment Overview . . . . . . . . . . . . . . . . . . . . . . . . 196
10.2.5 IceCube String Deployment Procedure . . . . . . . . . . . . . . . . . . . . 196
10.2.6 IceCube Indoor Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . 201
6

10.2.7 IceCube Drill Hole Requirements . . . . . . . . . . . . . . . . . . . . . . . 208
10.2.8 Quality Assurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
10.2.9 Practice Deployments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
10.2.10 Surface Cable Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
10.3 Logistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
10.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
10.3.2 Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
10.3.3 Personnel and Taskings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
10.3.4 Medical/Dental Examinations . . . . . . . . . . . . . . . . . . . . . . . . . 217
10.3.5 Airline Travel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
10.3.6 Weights and Cubes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
10.3.7 Cargo Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218

11 Quality Assurance

221

12 Relationship of AMANDA and IceCube

224

7

Contacts/Authors of this Document
Section 1:

D. Cowen (Penn)

Section 2:

T. Gaisser (Bartol), F. Halzen (UW-Madison)

Section 3:

T. Gaisser (Bartol), F. Halzen (UW-Madison)

Section 4:

T. Gaisser (Bartol)

Section 5:

D. Cowen (Penn), K. Hanson (Penn),
G. Hill (UW-Madison), A. Karle (UW-Madison)

Section 6:

C. Spiering (DESY)

Section 7:

J. Jacobsen (LBNL), A. Karle (UW-Madison),
C. McParland (LBNL), D. Nygren (LBNL)

Section 8:

D. Cowen (Penn), P. Herquet (Mons), J. Lamoureux (LBNL),
C. McParland (LBNL), D. Schneider (UW-Madison)

Section 9:

P.O. Hulth (Stockholm)

Section 10:

A. Karle (UW-Madison), B. Morse (UW-Madison)

Section 11:

E. Richards (UW-Madison)

Section 12:

P.O. Hulth (Stockholm)

81Document Overview

This document describes a conceptual design for the proposed IceCube Neutrino Observatory
at the South Pole. An Executive Summary is provided in section 2. Section 3 gives the scienti cmotivation for constructing a kilometer-scale device optimized for detection of cosmologicalneutrinos with ultrahigh energies in the TeV to PeV range. Section 4 brie y reviews the current
status of the eld of neutrino astronomy, and section 5 details the expected performance of the
IceCube neutrino telescope, with emphasis on the scienti c goals outlined in section 3.
Most of the remainder of the document focuses on technical aspects of the IceCube detector.
Section 6 lists the technical requirements the IceCube detector must meet in order to attain thedesired scienti c goals, and section 7 gives a complete conceptual description of the IceCube
detector itself. Section 8 describes how the data produced by this detector will be processed andmade available for high-level analysis, and section 9 shows how the collaboration will organize
itself to perform these analyses.
An explanation of how drilling, deployment and the associated logistics will be handled isgiven in section 10. Section 11 describes what quality assurance procedures will be implemented
to ensure initial and continued success in deployment, data acquisition and data processing. Finally, section 12 shows how the AMANDA and IceCube detectors will be integrated to maximize
the overall science output.
This and other documents are on the Web at http://www.ssec.wisc.edu/a3ri/icecube/.

9

2

Executive Summary

The IceCube Project at the South Pole is a logical extension of the research and development
work performed over the past several years by the AMANDA Collaboration. The optical properties of ice deep below the Pole have been established, and the detection of high-energy neutrinos
has been demonstrated with the existing detector. This accomplishment represents a proof ofconcept for commissioning a new instrument, IceCube, with superior detector performance andan e ective telescope size at or above the kilometer-scale.
IceCube scienti c goals require that the detector have an e ective area for muons generated
by cosmic neutrinos of one square kilometer. The detector will utilize South Pole ice instrumented at depth with optical sensors that detect the Cherenkov light from secondary particles
produced in interactions of high-energy neutrinos inside or near the instrumented volume.
The design for the IceCube neutrino telescope is an array of 4800 photomultiplier tubes(PMTs) each enclosed in a transparent pressure sphere to comprise an optical module (OM)
similar to those in AMANDA. In the IceCube design, 80 strings are regularly spaced by 125 m
over an area of approximately one square kilometer, with OMs at depths of 1.4 to 2.4 km below
the surface. Each string consists of OMs connected electrically and mechanically to a long cable,
which brings OM signals to the surface. The array is deployed one string at a time. For eachstring, a hot-water drill creates a hole in the ice to a depth of about 2.4 km. The drill is thenremoved from the hole and a string with 60 OMs spaced by 17 m is deployed before the water
freezes. The signal cables from all the strings are brought to a central location, which houses
the data acquisition electronics, other electronics, and computing equipment.
Each OM contains a PMT that detects individual photons of Cherenkov light generated
in the optically clear ice by muons and electrons moving with velocities near the speed oflight. Signal events consist primarily of upgoing muons produced in neutrino interactions in
the bedrock or the ice. In addition, the detector can discriminate electromagnetic and hadronic
showers (\cascades") from interactions of e and  inside the detector volume provided they aresuÆciently energetic (a few 100 TeV or higher). Background events are mainly downward-going
muons from cosmic ray interactions in the atmosphere above the detector. The background ismonitored for calibration purposes by the IceTop air shower array covering the detector.
Signals from the optical modules are digitized and transmitted to the surface such thata photon's time of arrival at an OM can be determined to within a few nanoseconds. The
electronics at the surface determines when an event has occurred (e.g., that a muon traversedor passed near the array) and records the information for subsequent event reconstruction andanalysis.
At the South Pole site (see g. 1), a computer system accepts the data from the event
trigger through the data acquisition system. The event rate, which is dominated by down-goingcosmic ray muons, is estimated to be 1{2 kHz. This will produce a large amount of data andrequires ltering and compression of this data stream at the South Pole. There are two ways
for the data to be transported to the Northern Hemisphere. The rst and preferred method is
via satellite transmission. The second method is by hand-carrying the data tapes north oncethe station reopens in the austral summer. Even in this case, a reduced set of data must be10

transferred daily by satellite to monitor the detector and to access important data. Once at thedata archive, the data are catalogued, unpacked, checked, ltered, and calibrated. Interesting
events are reconstructed and distributed to the collaboration for scienti c analysis.
The technology that will be employed in IceCube has been developed, tested, and demonstrated in AMANDA deployments, in laboratory testing, and in simulations. This includes the
instrument architecture, technology, deployment, calibration, and scienti c utilization of the
proposed detector. There have been yearly improvements in the AMANDA system, especiallyin the OMs, and in the overall quality of the information obtained from the detector. In the
1999/2000 season, a string was deployed with optical modules containing readout electronics
inside the module. The information is sent digitally to the surface over twisted-pair electricalcable. This option eliminates the need for optical ber cables and simpli es calibration of thedetector elements. This digital technology is the baseline technology of IceCube.
For more details and references, see http://www.ssec.wisc.edu/a3ri/icecube/.

Figure 1: The South Pole site, showing the residential dome and associated buildings, the skiway

where planes land, the dark sector with the Martin A. Pomerantz Observatory in which the AMANDA
electronics are housed, and a rough outline of where IceCube strings are to be placed.

11

3

Science Motivation for Kilometer-Scale Detectors

The construction of neutrino telescopes is overwhelmingly motivated by their discovery potential
in astronomy, astrophysics, cosmology and particle physics. To maximize this potential, onemust design an instrument with the largest possible e ective telescope area to overcome thesmall neutrino cross section with matter, and the best possible angular and energy resolution
to address the wide diversity of possible signals. A well-designed neutrino telescope can search for high energy neutrinos from transient sources like Gamma Ray Bursts (GRB) or
Supernova bursts;

 search for steady and variable sources of high energy neutrinos, e.g. Active Galactic Nuclei(AGN) or Supernova Remnants (SNR); search for the source(s) of the cosmic-rays;
 search for Weakly Interacting Massive Particles (WIMPs) which may constitute dark matter; search for neutrinos from the decay of superheavy particles related to topological defects;
 search for magnetic monopoles and other exotic particles like strange quark matter; monitor our Galaxy for MeV neutrinos from supernova explosions and operate within theworldwide SNEWS triangulation network; search for unexpected phenomena.
In practice, the observed uxes of cosmic-rays and gamma rays set the scale of a neutrino
telescope. With minimal model-dependence, one can estimate the very high energy cosmic
neutrino uxes by scaling to the observed energy density in high-energy cosmic-rays, or to themeasured uxes of non-thermal high-energy gamma rays. The basic assumption in calculating
the expected neutrino uxes is that some fraction of cosmic-rays will interact in their sources to
produce neutrinos.
Although they are not yet identi ed, the sources of the highest energy cosmic radiation very
likely involve extremely dense regions with exceptional gravitational forces such as supermassive black holes, collapse of massive stars or mergers of black holes and neutron stars. Withaccretion and intense radiation elds as ingredients, some fraction of the particles accelerated
in such environments will likely produce pions in hadronic collisions with ambient gas and/or
by photoproduction. In either case, the neutral pions decay to photons, while charged pions
include neutrinos among their decay products with spectra related to the observed gamma-ray
spectra. In the rst part of this section, we discuss estimates based on this relationship andconclude that a km-scale detector is needed to observe neutrino signals from known classes ofhigh energy astrophysical sources.
12

The baseline design of the detector maximizes sensitivity to  -induced muons from below
with energies in the TeV to PeV range, where the acceptance is enhanced by the increasing
neutrino cross section and muon range but the Earth is still largely transparent to neutrinos.
Good angular resolution is required to distinguish possible point sources from background, whileenergy resolution is needed to enhance the signal from astrophysical sources, which are expected
to have atter energy spectra than that of the atmospheric neutrino background.
A standard technique to search for high energy neutrinos of astrophysical origin is to lookfor upgoing muons induced by  that have penetrated the Earth. The signal is given by the
convolution
Signal  Area R NA   ;(1)where R is the muon range in g/cm2 and NA is Avogadro's number. The range and crosssection both increase linearly with energy into the TeV region, after which the rate of increase
slows. Neutrinos with E < 100 TeV are not strongly attenuated by the Earth, and much of
the solid angle away from the nadir remains accessible up to 1 PeV [16]. Thus the optimum
range for  -induced upgoing muons is from a TeV to a PeV. Also in this energy range the muonenergy loss is greater than minimum ionizing, which is a potential way to discriminate against
the background of atmospheric neutrinos, which have a steeply falling spectrum. We will returnto the importance of energy measurement further on.
The generic cosmic accelerator is believed to produce neutrinos in the ux ratio e :  :  ::1 : 2 : 0. With neutrino oscillations, however, at the detection point this ratio becomes 1 : 1 : 1.
This is especially interesting for neutrino telescopes because the  is not absorbed in the Earthlike the e and  due to the charged current regeneration e ect (as discussed below). Instead, 's with energies exceeding roughly 1 PeV pass through the Earth and emerge with an energyof roughly 1 PeV. IceCube is well-suited to detecting neutrinos in this energy range and will
have full 4 sensitivity to this potential signal.
In the second part of this section we discuss several other important scienti c goals which
depend on the sensitivity of the detector to neutrinos of much higher energies and of much lower
energies. On the one hand, we will discuss detecting and measuring the energy of PeV{EeV e , and  interactions. On the other, we will consider the detection of low energy muon-neutrinos
from the annihilation of dark matter particles and the detection of MeV electron-antineutrinos
from galactic supernovae. We describe how the baseline design can address these objectives aswell.

3.1 High-Energy Neutrinos Associated with Cosmic Particle Accelerators
We estimate the range of possible neutrino signals in three ways: rst on the basis of an energetics
argument, second by referring to some particular models, and third by comparing to known
sources of TeV photons.

13

3.1.1 Energy Considerations
Models for the origin of the highest energy cosmic-rays typically predict associated neutrinouxes. A requirement on the sources is that they must provide suÆcient power to supply
the observed energy in the galactic or extragalactic component of the cosmic radiation. The
assumption that comparable amounts of energy go into high-energy neutrinos allows an estimateof the corresponding neutrino signal that is independent of the speci c nature of the sources,
but which depends only on their distribution in the universe.
In the case of galactic cosmic-rays, the energy ux carried by neutrinos is much lower thanthat carried by the parent cosmic-rays because the charged particles are trapped locally as
they propagate di usively in the turbulent galactic magnetic elds. Thus an observer inside
the galaxy has several chances to see a given cosmic ray particle, but only one chance to see aneutrino that passes directly out of the galaxy. Nevertheless, there is a chance that some nearby
galactic sources could be visible in neutrinos in a km-scale detector. Examples will be discussed
in the next section.
In contrast, the neutrino energy ux for a cosmological distribution of sources can be comparable to or larger than the observed cosmic-ray energy ux. The ux depends on how thesources have evolved over cosmological time scales{provided that the fraction of accelerated protons that interact near the source is large. One natural scenario that gives comparable energy inneutrinos and cosmic rays occurs when protons remain trapped in the acceleration region until
they su er inelastic collisions, while secondary neutrons escape and decay to become cosmic-ray
protons. It is generally believed that sources of the ultra-high energy cosmic-rays are indeed
extragalactic, or at least not con ned to the plane of the galaxy. There is some evidence fora transition from one particle population to another somewhere above 1018 eV as well as for atrend from heavy toward lighter composition. Measurements of the cosmic-ray spectrum above
1017 eV are summarized in g. 2.
We now wish to estimate the neutrino signal expected if the energy in neutrinos is comparable
to the energy in the extra-galactic component of the cosmic radiation. The rst step is todetermine what fraction of the observed spectrum is the extra-galactic component. It is generally
assumed that the acceleration processes produce a power-law spectrum / E with di erential
index = 2 or slightly higher [8, 10]. But the measured spectrum has an index close to = 3,
so it is not clear just how to normalize with an extra-galactic component with a much harder
spectrum.
As an illustration, the lower heavy line in g. 2 shows a spectrum with = 2 and an exponential cuto at 5  1019 eV to represent the Greisen-Zatsepin-Kuzmin (GZK) e ect [11].
Particles with energies above the GZK cuto have interaction lengths in the microwave background of order 50 Mpc or less and must therefore be from a local or exotic component (indicatedby Super-GZK in the gure), which we do not consider for the moment. If the excess of data
above the curve for E < 1019 eV in g. 2 is attributed to the tail of the galactic cosmic-ray
spectrum, then the energy in a universal component of the cosmic radiation may be estimated.
Integrating the energy content under the = 2 curve gives for the energy density in cosmic
rays of extragalactic origin, EG  2  10 19 eV. The estimated power calculated from EG is14

All-particle spectrum

10

1

0.1

α=2.25

E

2.7

dN/dE

-2

-1 -1

(cm sr s GeV

1.7)

Akeno [16]MSU [17]AGASA [18]Haverah Park [19]Yakutsk [20]Fly’s Eye (mono) [21]Fly’s Eye (stereo) [6]

0.01
17
10

α=2.0

Super-GZK
10

18

19

E

10
(eV / nucleus)

20

10

21

10

Figure 2: The high energy cosmic-rays spectrum. See text for explanation of curves. Data arefrom Refs. [1, 2, 3, 4, 5, 6, 7]
consistent with that observed from AGN and GRBs.
Shifting the normalization point lower (or higher) by half a decade in energy would increase(decrease) this estimate by roughly a factor of two. This is comparable to the systematic di erences among the di erent measurements of the spectrum. If the spectrum is steeper (indicatedby the upper solid curve in g. 2, as expected for acceleration by relativistic shocks [12, 13, 14])then the energy content will be somewhat [15] larger.
Using our estimate of the energy in the extragalactic component of the cosmic-ray spectrum
and assuming a spectral index  2:0 for the neutrinos as well as the cosmic-rays, one predicts
a neutrino event rate of f  30 events/km2/yr [17], where f is the eÆciency for productionof neutrinos relative to cosmic rays. For f = 0:3 this estimate gives a di use ux at thelevel of E2 dN=dE  10 8 GeVcm 2sr 1 , which is comparable to the \upper bound" estimateof Waxman & Bahcall [8] before accounting for the likely e ect of evolution of sources overcosmological times.
In a sense, this estimate is conservative, and there are several ways in which the neutrino
ux could be larger: When cosmological evolution is included, estimates based on association with sources of15

ultrahigh energy cosmic-rays would be expected to be a factor of ve higher if the sources
are assumed to evolve similarly to the rate of star formation [8, 9, 18]. This is because theultrahigh energy protons from high redshift would be attenuated by photoproduction andpair production while the neutrinos would not. Thus the neutrino ux would be greater
for a given cosmic-ray ux at the normalization point.

 If the spectrum of extragalactic cosmic-rays to which the normalization is made has >2:0, then the corresponding estimated neutrino ux and signal in the TeV to PeV range
could also be larger.

 If the sources are not transparent and the cosmic-rays are partially absorbed in the source,
the neutrino ux could be larger (assuming there is suÆcient power in the sources).

 If, for a class of sources, the particular sources that produce the highest energy cosmic-rays
are di erent from the ones that produce the highest neutrino uxes.

The above discussion is summarized in Fig. 3.
Upper Limits
obscured
AMANDA B10

eric
osph
atm

transparent

ICECUBE

Figure 3: Cosmic-ray bounds on extragalactic neutrino uxes. The generic bound obtained by
Mannheim, Protheroe and Rachen [18] for the optically thin (n < 1) and thick case (n  1)are shown together with the limit inferred from Waxman and Bahcall [8] with and without
source evolution. They are compared to the present AMANDA limit and to the limit expectedfrom three years of IceCube operation.

16

3.1.2 Estimates Based on Models
We may summarize the previous paragraphs by saying that an argument based on energetics
coupled with a natural association between cosmic particle accelerators and their secondary
neutrino beams suggests that a km-scale detector will be needed to see the neutrinos. A similar
conclusion is reached by relating the neutrino ux to the source of the highest energy cosmic-raysin the context of speci c models.
In a recent review [19] Learned and Mannheim have summarized recent work on models ofAGN, GRB and other sources of high energy astrophysical neutrinos. As relevant examples, wequote here just two new papers that appeared since ref. [19]. Schuster, Pohl and Schlickeiser [20]work out the consequences of a model of AGN blazars [21] in which the TeV -rays come fromdecay of neutral pions produced in proton-proton collisions as a relativistic cloud of dense plasma
plows into the ambient interstellar medium of the host galaxy. In this picture, there is a similar
ux of TeV neutrinos from decay of charged pions. They conclude that the neutrino ux from atypical bright TeV -blazar would be detectable at the 3  level above atmospheric backgroundin an exposure of a km2-year. During an extended are, such as occurred for Mrk501 fromMarch to September of 1997 [22, 23, 24], the rate would be correspondingly higher in this model(see below).
The frequently quoted estimates [25, 26] of neutrino production in GRB sources by collisionsof extremely energetic protons with MeV photons in the gamma-ray jets typically produces
 100 TeV neutrinos at a level suÆcient to produce a few events per km2-year. Now Meszaros
and Waxman [27] argue that in gamma-ray bursts that involve collapse of massive progenitors,
there will be an earlier phase of production of multi-TeV neutrinos from collisions of energetic
protons with X-rays as the jet pushes through the envelope of the progenitor. They predictthat there may also be a class of collapses so massive that the jets do not emerge. These would
not appear as visible gamma-ray bursts but would generate neutrino bursts. The event rates
estimated range from a few hundred to a thousand per year over the whole sky, depending on theratio of \choked" to \bursting" reballs. The northern hemisphere bursts would be detectable
by IceCube.

3.1.3 Neutrinos as a Diagnostic of TeV Gamma-Ray Sources
The question whether the intriguing sources of TeV -rays such as Markarian 421, 501 arecosmic proton accelerators has not yet been answered. Most experts argue that the photons areproduced by radiative processes from accelerated electrons. There are, however, some hints that
this may not be the case. For example, the spectrum of Mrk501 during the extended (six month)
are in 1997 [22] entends to above 20 TeV, which strains the electronic models because of theshort synchrotron loss time for electrons. However, only neutrinos can provide incontrovertible
evidence of proton acceleration.
For the case of the Mrk501 are, it is possible to estimate the associated neutrino ux andsignal that would be expected if the observed photons are produced from decay of neutral pions.
The neutrino ux is closely related to the photon ux at the source. If the pion production
17

mechanism is photoproduction by protons, then the energy in muon neutrinos will be about 1/4
the energy in photons. If the pions are produced in proton-gas collisions, then the energy inmuon neutrinos and the energy in photons will be comparable. To obtain the source spectrumof photons, it is necessary rst to account for the attenuation of photons during propagation
through the infrared background radiation. This has been estimated by Konopelko et al. [28].
They nd a source photon spectrum that extends from below a TeV to above 20 TeV with apower law di erential spectral index of = 2. Starting from the six-month average ux inRef. [22] and correcting for the infra-red absorption, one would expect 10{100  events per km2
of e ective area in four months, depending on the origin of the produced pions (photo-production
or proton-gas interactions).
In principle, high-energy neutrino astronomy has the potential to discriminate between
hadronic and electromagnetic origin of the TeV emission from objects as diverse as supernova
remnants, gamma-ray bursts and active galactic nuclei. The uxes are likely to be low, however.
Estimates for a variety of sources show that reasonable expectations are at the level of a few
events per km2-year. Moreover, the estimates depend on how many interactions the photons
experience in the source as well as whether all observed photons are hadronic in origin. As an
example of the latter point, the hadronic model of Bednarek and Protheroe [29] for the CRAB
nebula attributes only the high-energy end of the photon spectrum to decay of neutral pions.
For a range of parameters their model predicts a signal from < 1 to as much as 4 events per
km2 yr with E > 1 TeV. The corresponding rate from atmospheric background within a 1Æcone is  0:4.

3.2 Other Science Opportunities
So far we have focussed on detection of muons from below the horizon produced by muon
neutrinos in the TeV-PeV regime, such as may be associated with GRB sources, AGN or othercosmic accelerators observed as TeV gamma-ray emitters. Neutrinos of both higher and lower
energies can also be measured with IceCube. This capability will allow us to address otherscience that ranges from WIMP annihilation and supernova explosions to  appearance toneutrinos from topological defects of supermassive relic particles.

3.2.1 WIMPs and Other Sources of Sub-TeV 
So far we have assumed an IceCube energy threshold of 0.4 TeV or higher. It is important to notethat it will be possible to detect muon-neutrinos of signi cantly lower energy. If the track of thesecondary muon is close to an individual string, its length can be deduced from the arrival timesof Cherenkov photons detected by nearby PMTs. A good measurement requires nanosecond
timing in several modules. Requiring, conservatively, signals in ve modules separated by 17 m,
the minimum tracklength is  70 m for a muon energy of  15 GeV. Requiring further thatthe distance from the string to the track is signi cantly less than the scattering length, 10 m
for instance, yields a detection volume of 25 megaton with a threshold of less than 20 GeV fora source directly below the detector, in particular for neutrinos from annihilation of WIMPS
18

trapped in the center of the Earth. For other directions the energy threshold is higher and theeÆciency for a given energy is correspondingly lower. The cuts on track-length and proximity
to a string can be relaxed if the detector would be exposed to an accelerator beam. During theshort beam spills the detector is free of background and requirements on track measurement canbe reduced thus increasing the target volume. On the other hand, the neutrino beam would beat some angle to the strings, depending on the location of the accelerator, which would reduce
the acceptance.
Several science missions would bene t from a reduced threshold in a limited volume, e.g.
the search for dark matter. If Weakly Interacting Massive Particles (WIMPs) make up the dark
matter of the universe, they would also populate the galactic halo of our own Galaxy. They
would be captured by the Earth or the Sun where they would annihilate pairwise, producing
high-energy muon neutrinos that can be detected by neutrino telescopes. A favorite WIMP candidate is the lightest neutralino which arises in the Minimal Supersymmetric Model (MSSM).
In general, IceCube's reach as a dark matter detector is complementary to that of direct searchdetectors because of its good sensitivity to larger neutralino masses, typically higher than a few
hundred GeV. In addition, the rates depend on the capture and annihilation rates of the WIMPs
in the Earth or Sun rather than their cross sections for interaction in the detector. High energy
neutrinos produced in the annihilation of galactic neutralino dark matter have characterisitic
energies of 1=4  1=6 the mass of the parent particles. A reduction in neutrino threshold therefore results in increased sensitivity to lower masses. The standard IceCube geometry presents ane ective area of 0.7 km2 for WIMPs with mass > 50 GeV annihilating in the core of the Earth.
For WIMPS in the Sun, because of the less favorable geometry, the e ective area increases
from  :01 km2 for mW = 50 GeV and approaches 0:7 km2 for TeV WIMPS. The situation ismost favorable for WIMPS above the threshold for decay into weak intermediate bosons, where
IceCube is competitive with specialized future detectors such as GENIUS and CRESST in the
search for neutralino dark matter anticipated in supersymmetric theories [45].
Another reason for maintaining sensitivity to  10 GeV neutrinos is that these may be
produced in GRBs along with high energy neutrinos. Bahcall and Meszaros [46] have argued
that a gamma-ray burst \ reball" is likely to contain an admixture of neutrons, in addition to
protons, in essentially all progenitor scenarios. Inelastic collisions between protons and neutrons
in the reball produce muon neutrinos (antineutrinos) of 10 GeV energy as well as electron
neutrinos (antineutrinos) of 5 GeV, which could produce 7 events/year in km-scale detectors,
if the neutron abundance is comparable to that of protons. With a reduced threshold andexploiting coincidence in timing with the GRB, this ux may be observable.
A low threshold also preserves the capability discussed in connection with AMANDA (seesec. 12) to detect secondary muons from TeV-energy gamma rays produced in the atmosphereabove the detector. These are guaranteed uxes, calculable from the observed uxes. The
technique could be particularly revealing in GRB studies.

193.2.2 Atmospheric Neutrinos
Neutrinos produced locally by interactions of cosmic-rays in the atmosphere constitute the foreground for neutrinos of astrophysical origin. They are both background and calibration source.
The energy spectrum of atmospheric neutrinos is steep, falling approximately like E 3 andsteepening to E 3:7 for E  1 TeV. Above  10 GeV the ux of e falls even more quickly,
and above  100 e ects of oscillations are also negligible. Thus atmospheric muon-neutrinos
are a known calibration source up to a TeV and beyond. There is a characteristic factor of two
excess of neutrinos from near the horizontal as compared to the vertical. Measuring the rate andangular dependence of atmospheric  -induced muons is therefore a benchmark measurement
for IceCube.
The component of \prompt"  from charm decay has a harder spectrum than the component
from decay of charged kaons and pions. It is expected to become the dominant source of
atmospheric neutrinos above an energy of perhaps 100 TeV. The exact level of the prompt
component is rather poorly known, and it could present a signi cant background for di use
astrophysical neutrinos. If it is suÆciently large, it could be measured by IceCube as a hardening
the neutrino energy spectrum by one power of the energy.
With a suÆciently low energy threshold, IceCube could also play a role in con rming thecompelling indications that atmospheric neutrinos oscillate. Studies of systematics and backgrounds show, however, that signi cant progress would require smaller spacing of OMs alonga string than presently planned. Such a specialized e ort would be warranted only if ongoingexperiments fail to prove oscillation of atmospheric neutrinos before IceCube construction.

3.2.3 PeV and EeV Neutrinos
The interactions of neutrinos with PeV energies and higher will have spectacular signaturesin IceCube. (The simulated 6 PeV neutrino in g. 16 illustrates this point.) Since the Earthbecomes increasingly opaque to neutrinos with energy in the PeV range and higher, it is necessary
to use events from horizontal and downgoing neutrinos. Fortunately, setting an energy thresholdin the PeV energy region is high enough to be above atmospheric backgrounds. In this energy
region the observed muon events in IceCube will be dominated by muon neutrinos interacting in
the ice or atmosphere above the detector and near the horizon. PeV cascades from e interactionsin the detector volume also contribute at a somewhat lower rate. Tau neutrinos will also show
up as cascades, as described below. Upgoing neutrinos are suppressed by an order of magnitude.
Due to the Earth's opacity, the zenith angle distribution of neutrinos associated with EeV signals
will have a striking signature. For a detailed discussion, see [36, 38].
With a threshold for cascades below the PeV region, IceCube will be complementary todetectors such as Auger, OWL and RICE which have thresholds of 10 EeV and higher. The
lower threshold means that comparable event rates may be possible with IceCube even though
its e ective volume is much smaller.
The high-energy capability of IceCube will allow us to attack a major scienti c problem,the existence of particles whose energy apparently exceeds the GZK cuto . Speculations re20

garding their origin include heavy relics from the early Universe and topological defects which
are remnant cosmic structures associated with phase transitions in grand uni ed gauge theories [30, 31, 32]. Interactions of ultra-high energy neutrinos with massive neutrinos in the galactic
halo is also a possibility [33]. Such models would predict a sizeable ux of neutrinos in a muchhigher range of energy than the neutrinos associated with the GRB and AGN models mentioned
above. Some limits on the highest predictions of neutrino uxes are emerging from analysis ofhorizontal air showers, but there is still considerable phase space for exploration. Detection ofneutrinos produced in interactions leading to the GZK cuto is also a possibility, although theirlevel is relatively low. Speci c examples include: generic topological defects with grand-uni ed mass scale MX of order 1015 GeV and aparticle decay spectrum consistent with all present observational constraints[30] mightyield 10 events/year; neutrinos produced by superheavy relics whose decay products include highest energy
cosmic-rays[35], also 10 events/year; superheavy relics [31, 32], which we normalize to the Z-burst scenario[33] where the observed cosmic-rays with 1020 eV energy, and above, are locally produced by the interac-tion of super-energetic neutrinos with the cosmic neutrino background could give as manyas 30 events/year; the ux of neutrinos produced in the interactions of cosmic rays with the microwave
background[37]. This ux, which originally inspired the concept of a km-scale neutrino
detector, would only give one or two events per year, or less depending on how the sources
evolve over cosmological time scales.

3.2.4 Tau Neutrino Detection
Interest in detection of  neutrinos is motivated by the evidence for neutrino oscillations fromSuperKamiokande [39] and SNO [40]. Production of  in hadronic interactions or photoproduction is suppressed relative to e and  by several orders of magnitude. In the absence of new
physics,  of astrophysical origin would therefore be virtually undetectable. If, however, thereis large mixing in the  $  channel, then over astrophysical distances uxes of  would becomparable to  .
Tau neutrinos of suÆciently high energy can in principle be identi ed in several ways in
a km-scale neutrino detector. Perhaps the most striking signature would be the characteristic
double bang events [41] in which the production and decay of a  lepton would be seen as two
separated bursts in the detector. It may also be possible to identify \lollipop" events in which a with energy >PeV creates a long minimum-ionizing track that enters the detector and ends
in a huge burst as the  lepton decays to a nal state with hadrons or an electron. The entering , because of its large mass, would emit fewer bremsstrahlung photons than a muon of similarenergy. Such events would be detected from above or near the horizontal since the Earth isopaque to neutrinos with energies at or above the PeV region.
21

At still higher energies, the Earth becomes completely opaque to e and  uxes but it
remains transparent to  ux [42]. In essence,  charged current interactions create a tau
lepton, which decays before losing all its energy, and which always has a  as one of its decay
products. This ultimately results in an upgoing  ux in the 100 TeV energy range. In what
follows we discuss only the \double-bang" signature, which gives a conservative estimate ofpossible rates.
In a charged current  deep inelastic scattering (DIS) interaction with a nucleus, a  leptonof energy (1 y )E is produced as well as a hadronic shower of energy yE which is initiatedin the fragmentation of the nucleus. Here y is the fraction of energy transferred to the hadronic
vertex in the interaction. The  lepton travels on average a distance R along the medium before
decaying given by:E(1 y )E
R =  ct0 =
ct0
(2)
m
m
where E and m are the energy and mass of the  respectively and t0 is its rest lifetime. In its
decay it produces another  and an electromagnetic or hadronic shower  82% of the times.
Assuming a typical detector dimension D, there are several conditions that have to be ful lled
for the detection of a double bang event induced by a  :

 The  has to interact through a charged current DIS interaction producing a hadronic
shower contained inside the instrumented volume of the detector ( D3 ).
 The  lepton must decay inside the detector to a nal state that produces an electromagnetic or hadronic shower which again has to be contained inside the device.

 R has to be large enough so that both showers are suÆciently separated from each otherto be distinguished.

 The showers have to be energetic enough to trigger the detector.
Using these criteria we can estimate the probability of detecting a double bang event in aneutrino telescope of linear dimension D = 1 km such as IceCube using a simple Monte Carlo.
We take the energy threshold for detecting showers to be Eshower  1 TeV and x 250 m as theminimum distance the  has to travel to distinguish the Cherenkov light from both showers.
This (conservative) number is mainly determined by the 125 m separation between strings sincedetection by separated strings is needed to establish the double burst for a horizontal event. Thisdistance corresponds to a minimum energy of  5 PeV for the  lepton. The requirement thatboth bursts occur inside the detector sets an upper limit of  20 PeV. With these constraints,
one would expect at most a few events per year given current limits on neutrino uxes from
AMANDA. This conclusion is consistent with the result of Athar et al. [43], who nd some tensof double bang events per year in the original AGN model [44] which is somewhat above current
limits.

22

3.2.5 Neutrinos from Supernovae
A high energy neutrino telescope in deep Antarctic ice is sensitive to the stream of low energy neutrinos produced by a galactic supernova Although 10-20 MeV energy is far below the
AMANDA/IceCube trigger threshold, a supernova would be detected by higher counting rates
in individual PMTs over a time window of 5-10 s. The enhancement in rate of a single PMT isburied in PMT dark noise. However, by summing the signals from all PMTs a signi cant excess
would be observed. Limits obtained with AMANDA have been submitted for publication [47].
Relatively low background counting rates in ice (relative to water) make this possible.
Most of the energy released by a supernova is liberated in a burst lasting about ten seconds. Roughly equal energies are carried by each neutrino species with a thermal spectrumof temperature 2{4 MeV. Since the e cross-section on protons in the detector is signi cantly
larger than the interaction cross sections for the other neutrino avors, e events dominate thesignal by a large factor after detection eÆciency is taken into account. In this reaction, free
protons absorb the antineutrino to produce a neutron and a positron which is approximately
isotropically emitted with an energy close to that of the initial neutrino. A thermal spectrum of
temperature 4 MeV, when folded with an inverse beta decay cross section which increases withthe square of the neutrino energy, yields an observed positron energy distribution which peaksin the vicinity of 20 MeV. The track-length of a 20 MeV positron in ice is roughly 12 centimeters
and therefore over 3000 Cherenkov photons are produced.
AMANDA and IceCube can contribute to the SuperNova Early Warning Network [48]. A
recent analysis [47] shows that 70% of the galatic disk can be monitored for a supernova like
SN1987A using a selected set of low noise AMANDA PMTs. Given a known template for time
evolution of the pulse, the resulting accuracy in timing could be 14 ms for AMANDA-II andas good as 1-3 ms for IceCube. The resulting angular resolution depends on the orientation of
the triangulation grid with respect to the supernova. The three detectors SuperK, SNO and
IceCube will achieve typical resolution of 5 to 20 degrees. This is to be compared with theaccuracy of about 5Æ achieved from the measured electron direction in a detector like SuperK.
Simultaneous detection of high energy and lower energy MeV neutrinos from a supernova is
an exciting capability of a high energy neutrino telescope with supernova sensitivity. Loeb andWaxman [49] have shown that when a type II supernova shock breaks out of its progenitor star,it becomes collisionless and may accelerate protons to TeV-energy or higher. Inelastic nuclear
collisions of these protons produce a 1 hr long ash of TeV neutrinos about 10 hr after thethermal neutrino burst from the cooling neutron star. A Galactic supernova in a red supergiant
star would produce a neutrino ux of  10 4 erg=cm2 s. A km2 neutrino detector will detect100 muons, thus allowing one to constrain both supernova models and neutrino properties.
All these opportunities will be greatly enhanced by a low threshold associated with short tracks
detected by individual strings.

23

3.3 Summary
The main goal of the IceCube project is the detection of extraterrestrial sources of very highenergy neutrinos [19, 50, 51].
 IceCube will reach a sensitivity for di use uxes of a few 10 9  E 2 GeV 1 cm 2 s 1,
which is more than one order of magnitude below conservative \upper bounds" derived
from cosmic-ray observations, and three orders of magnitude below bounds derived fromgamma ray observations alone. The published AMANDA limit has already improved
previous experimental limits by more than a factor 10 and will be improved by AMANDAII and IceCube by roughly an additional 1.0 and 2.5 orders of magnitude, respectively.
Within this range of sensitivity, models predict between \several" and thousands of events
per year.
 Point source searches will reach a sensitivity of at least 10 12 cm 2 s 1 for energies greaterthan about 10 TeV. This is nearly two orders of magnitude below the observed Mrk501
TeV gamma-ray ux during its aring phase. Predictions for some steady or quasi-steadysources reach a few tens of events per year.
 Supernova models predict 10-100 events shortly before and after the SN burst.
 Gamma Ray Bursts are expected to yield 10-100 events per year.
 IceCube has also signi cant EeV capabilities. Event numbers predicted by top-down scenarios (like topological defects) lead to 1-30 events per year, comparable to expectations
for dedicated EeV experiments.
 IceCube has a realistic chance to identify tau neutrinos via \double-bang" events, with up
to 100 events per year expected for certain topological defect models.
IceCube is a multi-purpose detector. Beside high energy neutrino astronomy, it can be used
to investigate a series of other questions: Magnetic monopoles: Present limits for the ux of relativistic monopoles can be improvedby two orders of magnitude. This is a factor of 1000 below the Parker bound [52]. One
also can search for slow monopoles catalyzing proton decay, or for strange quark matter.
 Neutrinos from WIMP annihilation: IceCube can play a complementary role to future
direct detection experiments, particularly for high WIMP masses. The instrument is
unique for TeV dark matter.
 MeV neutrinos from supernova bursts: IceCube will detect a supernova burst over thewhole Galaxy, and as far as the Magellanic clouds.
 As a by-product, neutrino oscillations, physics (and gamma-ray astronomy) with downgoing muons, or even questions of glaciology can be investigated.

24

Discovery of any single one of the high energy signals listed above would unquestionably make
IceCube a resounding success. However, as a detector one hundred times larger than AMANDA
and one thousand times larger than any underground detector, IceCube will be opening a new
window on the universe, and as such holds out even greater promise: the exciting discovery ofunanticipated phenomena.

25

4

Status of High Energy Neutrino Astronomy

The science of high energy neutrino astronomy is compelling. The main challenge is therefore todevelop a reliable, expandable and a ordable detector technology. The diagram in g. 4 shows
1012e

Detector mass (tons)

r/ic

r

de

109

Un

te
wa

Acoustic,
Radio,Air Shower

106

103

100

1111111111
0000000000
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
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0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111
0000000000
1111111111

109

1012

Underground1015
E ν (eV)

1018

1021

Figure 4: Schematic representation [70] of the physics reach of various types of detectors in detector
mass versus neutrino energy space.

schematically the range of various detectors in the space of volume vs. neutrino energy. IMB and
Kamioka are so far the only detectors that have observed neutrinos from outside the solar system,with the detection of SN1987A. With its large volume and great sensitivity, Super-Kamiokande
has pushed the frontiers of the study of atmospheric neutrinos in the sub-GeV and multi-GeV
energy range, SNO and Super-Kamiokande have done the same with solar neutrinos, with SNO
recently providing the rst clear evidence of solar neutrino oscillations. There is signi cantactivity with several underground detectors, including Borexino and KamLand, pushing toward
lower energy and higher energy resolution on the solar neutrino frontier. Super-Kamiokande,
along with Frejus, MACRO and Soudan, have also provided important limits on uxes of highenergy neutrinos.
With the termination of the pioneering DUMAND experiment, the e orts in water are, atpresent, spearheaded by the Baikal experiment [71]. The Baikal Neutrino Telescope is deployedin Lake Baikal, Siberia, 3.6 km from shore at a depth of 1.1 km. An umbrella-like frame holds
8 strings, each instrumented with 24 pairs of 37-cm diameter QUASAR photomultiplier tubes(PMT). Two PMTs in a pair are switched in coincidence in order to suppress background fromnatural radioactivity and bioluminescence. Operating with 144 optical modules since April 1997,
the NT-200 detector has been completed in April 1998 with 192 optical modules (OM). The
Baikal detector is well understood, and the rst atmospheric neutrinos have been identi ed.
The Baikal site is competitive with deep oceans, although the smaller absorption length26

Events

Exp. - 35 events

105
MC expected - 31 events

0

-1

-0.8

-0.6

-0.4

-0.2

0

Cos(θ)

Figure 5: Angular distribution of muon tracks in the Lake Baikal NT-200 experiment after all nal cuts
have been applied [73].

of C erenkov light in lake water requires a somewhat denser spacing of the OMs. This does,
however, result in a lower threshold which may be a de nite advantage, for instance for oscillation
measurements and WIMP searches. They have shown that their shallow depth of 1 km does not
represent a serious drawback. By far the most signi cant advantage is the site with a seasonalice cover which allows reliable and inexpensive deployment and repair of detector elements froma stable platform.
With data taken with the Baikal NT-200 detector, the Baikal collaboration has shown that
atmospheric muons can be reconstructed with suÆcient accuracy to identify atmospheric neutrinos, as illustrated in g. 5. The neutrino events are isolated from the cosmic ray muon
background by imposing a restriction on the chi-square of the Cerenkov
t, and by requiringconsistency between the reconstructed trajectory and the spatial locations of the OMs reporting
signals.
In the following years, NT-200 will be operated as a neutrino telescope with an e ective
area between 103  5  103 m2, depending on energy. Presumably too small to detect neutrinos
from extraterrestrial sources, NT-200 will serve as the prototype for a larger telescope. For
instance, with 2000 OMs, a threshold of 10  20 GeV and an e ective area of 5  104  105 m2 ,an expanded Baikal telescope would ll the gap between present underground detectors andplanned high threshold detectors of km3 size. Its key advantage would be low threshold.
27

The Baikal experiment represents a proof of concept for deep ocean projects. These havethe advantage of larger depth and optically superior water. Their challenge is to nd reliable
and a ordable solutions to a variety of technological challenges for deploying a deep underwater detector. Several groups are confronting the problem; both NESTOR and ANTARES aredeveloping rather di erent detector concepts in the Mediterranean.
The NESTOR collaboration [74], as part of a series of ongoing technology tests, is testing
the umbrella structure which will hold the OMs. They have already deployed two aluminum\ oors," 34 m in diameter, to a depth of 2600 m. Mechanical robustness was demonstrated bytowing the structure, submerged below 2000 m, from shore to the site and back. These tests
should soon be repeated with fully instrumented oors. The actual detector will consist of a
tower of 12 six-legged oors vertically separated by 30 m. Each oor contains 14 OMs with fourtimes the photocathode area of the commercial 8 inch photomultipliers used by AMANDA and
ANTARES.
The detector concept is patterned along the Baikal design. The symmetric up/down orientation of the OMs will result in uniform angular acceptance and the relatively close spacings ina low threshold. NESTOR does have the advantage of a superb site o the coast of Southern
Greece, possibly the best in the Mediterranean. The detector can be deployed below 3.5 km
relatively close to shore. With the attenuation length peaking at 55 m near 470 nm the site is
optically superior to that of all other deep water sites investigated for neutrino astronomy.
The ANTARES collaboration [72] is investigating the suitability of a 2400 m-deep Mediterranean site o Toulon, France. The site is a trade-o between acceptable optical properties of
the water and easy access to ocean technology. Their detector concept indeed requires remotely
operated vehicles for making underwater connections. First results on water quality are very
encouraging with an attenuation length of 40 m at 467 nm and a scattering length exceeding
100 m. Random noise exceeding 50 khz per OM is eliminated by requiring coincidences between
neighboring OMs, as is done in the Lake Baikal design. Unlike other water experiments, they
will point all photomultipliers sideways in order to avoid the e ects of biofouling. The problem issigni cant at the Toulon site, but only a ects the upper pole region of the OM. Relatively weakintensity and long duration bioluminescence results in an acceptable deadtime of the detector.
They have demonstrated their capability to deploy and retrieve a string, and have reconstructed
down-going muons with 8 OMs deployed on the test string.
With the study of atmospheric neutrino oscillations as a top priority, they had planned
to deploy in 2001-2003 10 strings instrumented over 400 m with 100 OMs. After study ofthe underwater currents they decided that they can space the strings by 100 m, and possibly
by 60 m. The ANTARES detector will consist of 13 strings, each equipped with 30 storeys
and 3 PMTs per storey. The large photocathode density of the array will allow the study of
atmospheric neutrino oscillations in the range 255 < L=E < 2550 km GeV 1 with neutrinos inthe energy range 5 < E < 50 GeV. This detector will have an area of about 3  104 m2 for
1 TeV muons{similar to AMANDA-II{and is planned to be fully deployed by the end of 2003.
A new R&D initiative based in Catania, Sicily has been mapping Mediterranean sites, studying mechanical structures and low power electronics. One must hope that with a successful
pioneering neutrino detector of 10 3 km3 in Lake Baikal, a forthcoming 10 2 km3 detector near28

Toulon, the Mediterranean e orts will converge on a 10 1 km3 detector possibly at the NESTOR
site.
As in many other elds, high energy neutrino astronomy would ideally have two or more
independent experiments sensitive to the same energy regime. Such redundancy allows one
to perform vital crosschecks and (hopefully) discovery veri cation. It is therefore in the bestinterests of the community that projects other than AMANDA and IceCube succeed. In addition,a detector in the northern hemisphere would provide the community with full TeV{PeV neutrino
sky coverage, while at the same time having considerable coverage overlap regions.

4.1 Status of AMANDA
The AMANDA-B10 results presented below provide a proof-of-concept for a high energy neutrino
telescope at the South Pole. We focus rst on the detection of neutrinos and compare them tothe predicted ux of atmospheric neutrinos. Possible backgrounds will be discussed. We thenapply the results to the search for high energy neutrinos of astrophysical origin, such as a di use
ux of HE neutrinos, point-like sources and gamma-ray bursts.
It is important to note that due to its size and shape, AMANDA-B10 is not highly sensitive
to high energy neutrino uxes expected from sources such as AGN and GRBs. The much larger
AMANDA-II detector has signi cantly more sensitivity, and data from this device is currently
being analyzed. However, only with IceCube will the sensitivity levels be high enough to reachpredicted high energy neutrino ux levels.

4.1.1 Atmospheric Neutrinos
The results presented here are based on data taken during the austral winter of 1997. Thee ective livetime has been determined to be 130.1 days for the selected data. The methodof calibration and the characteristics of the optical sensors are very similar to the 4 string
prototype array described in ref. [53]. Simulations predict a rate of a few tens of events per day
from atmospheric neutrinos above a threshold of 30-50 GeV, compared to 6  106 events fromcosmic ray muons, as shown in g. 6.
The analysis of the atmospheric neutrino sample with the AMANDA-B10 array has been
performed independently by two working groups in the collaboration. Both groups come to very
similar and statistically consistent results while the methods are quite di erent and partiallyindependent. The gures and the method presented here are based on one analysis [56].
Neutrinos are identi ed by looking for upward going muons. We use a maximum likelihood
method [57], incorporating a detailed description of the scattering and absorption of photons
in the ice, to reconstruct muon tracks from the measured photon arrival times. Events arereconstructed with a Bayesian method [58], in which the likelihood function is multiplied by aprior probability function. The prior function contains the zenith angle information in g. 6. By
accounting in the reconstruction for the fact that the ux of downgoing muons from cosmic rays
is more than 5 orders of magnitude larger than that of upgoing neutrino-induced muons, thenumber of downgoing muons that are misreconstructed as upgoing is greatly reduced. A small
29

10 8

40

7

35

10

Data
Atmospheric ν MC

30

10 6

25
10 5
20
10 4

15

10 3
10

10

2

5

-1 -0.8 -0.6 -0.4 -0.20

0.2 0.4 0.6 0.8

01-1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1

cos(θ)

0cos(θ)

Figure 6: Left: The zenith angle distribution of AMANDA triggers. The solid line represents triggers

Events Passing

10 4

Data
Atmospheric ν MC
Downgoing µ MC

10 3

Data / Σ MCfrom downgoing cosmic ray muons. The dashed line shows triggers produced by atmospheric neutrinos.
Right: The zenith angle distribution of upward reconstructed events. The size of the hatched boxes
indicates the statistical precision of the atmospheric neutrino simulation.

10 2

11.33
A0

6

/ 14
0.57890.4693E-01

5
4
3

10

2
1
1
10

-1

0

2.5

5

0

7.5 10 12.5 15 17.5 20 22.5 25

Quality Cut

0

2.5

5

7.5 10 12.5 15 17.5 20 22.5 25

Event Quality

Figure 7: Event quality. Left: Passing rates of events above a certain quality level is shown for back-ground MC, atmospheric neutrino MC and experimental data. Right: Di erential presentation of theratio data/MC.

30

fraction of the downgoing muons (5  10 6 ) are reconstructed as upward and form a backgroundto the neutrino-induced events. This background is removed by applying quality criteria to thetime pro les of the observed photons as well as to their spatial distribution in the array. A
measure of the event quality has been de ned by combining six quality variables into a single
parameter. A high event quality is reached when the values of all six parameters agree withthe characteristics of a correctly reconstructed muon track. By making increasingly stringent
cuts on the event quality the background of a total of 1:2  109 events is reduced by a factor
of approximately 108 , while retaining about 5% of the neutrino signal. The distribution of thesingle quality parameter for experimental data and for a Monte Carlo simulation of atmospheric
neutrinos is shown in g. 7. It compares the number of events passing various levels of cuts; i.e.,
the integral number of events above a given quality. At low qualities, the data set is dominatedby misreconstructed downgoing muons, most of which are reproduced in the Monte Carlo. At
higher cut levels, the passing rates of data closely track the simulated neutrino events, and thepredicted background contamination is very low.

Figure 8: Neutrino sky of upgoing events as seen with AMANDA-B10. The background of non neutrino
events is estimated to less than 10%.

We can investigate the agreement between data and Monte Carlo more systematically by31

Experimental Data MC: Atmospheric Neutrinos
Triggered
1:2  109
4600
Reconstructed upward
5  103571
Upward going
204
279
Table 1: Event numbers are given at various cutlevels: Experimental data and atmnospheric neutrinoMonte Carlo.

comparing the di erential number of events, rather than the total number of events passing
various levels of cuts. This is done in g. 7 (right), where the ratios of the number of events
observed to those predicted from the combined signal and background simulations are shown.
One can see that at low quality levels there is an excess in the number of misreconstructed
events observed. This is mainly due to instrumental e ects such as cross talk which are notwell described in the detector Monte Carlo. There is also an excess, though statistically lesssigni cant, at very high quality levels, which is caused by slight inaccuracies in the descriptionof the optical parameters of the ice. Nevertheless, over the bulk of the range there is close
agreement between the data and the simulations, apart from an overall normalization factor. In
the range where the line is shown the ratio of Data/MC is about 0.6. Counting all events above
the quality cut (7.0) this ratio is 0.70. It should be emphasized that the quality parameter is acombination of all six quality parameters, and so the at line in g. 7 demonstrates agreement
not only in individual cut parameters but also quantitative agreement in the correlations between
cut parameters.
The zenith angle distribution for the 204 events is shown in g. 6, and compared to that forthe signal simulation. In the gure the Monte Carlo events were normalized to the observed
events. The achieved agreement in the absolute ux of atmospheric neutrinos is consistent withthe systematic uncertainties of the absolute sensitivity and the ux of high energy atmospheric
neutrinos. The shape of the zenith distribution of data is statistically consistent with theprediction from atmospheric neutrinos. The zenith distribution re ects the angular acceptanceof the narrow but tall detector. A skyplot of these events is shown in g. 8. 223 events were
found in an independent analysis. The overlap of 119 events with the sample presented here is
within expectations. The observation of atmospheric neutrinos at a rate consistent with Monte
Carlo prediction establishes AMANDA-B10 as a neutrino telescope.

4.1.2 Pointing Resolution
In order to establish AMANDA as a neutrino telescope, one more step is needed. That isthe veri cation that AMANDA does indeed reconstruct the direction of events correctly in sky
coordinates. This is done by analyzing events that are measured coincidently by AMANDA in
the deep ice and by surface air shower detectors. In the 1997 data set we have three independent
detectors at the surface in operation: the SPASE-1 air shower array, the SPASE-2 array, and
the GASP air cherenkov detector. All three experiments agree on the average absolute pointing
32

of the AMANDA array to within 1{2 degrees (sky coordinates) [55]. A full agreement with thetrue direction is achieved in azimuth, and a small o est of order 1 degree is observed in the in
the zenith angle (data and Monte Carlo). The o set is relatively small compared to the size ofa search bin ( 5 degrees half angle) for point sources. These instruments were also used toverify the angular resolution (median angular error) of about 3 degrees.
The observation of atmospheric neutrinos together with the veri cation of the angular resolution establishes AMANDA as a functioning neutrino telescope. From here we search theneutrino sky for various sources. Depending on the type of the investigated neutrino signal
hypothesis (di use ux, point sources, GRB, WIMPs, etc.), we re-optimize the backgroundrejection strategy.

4.1.3 Search for a di use high energy neutrino ux
The search for a di use neutrino ux of astronomical origin follows naturally from the observationof a di use ux of neutrinos generated in the atmosphere. Neutrinos from generic astrophysicalsources are expected to extend to higher energies while the energy spectrum of atmospheric neutrinos falls o steeply with increasing energy. A very simple and robust measure of the energyof the observed muons is the number of optical modules (OM) that observed at least one photoelectron in a given event. Figure 9 shows the energy distribution of events that pass the neutrinolter as predicted for a) atmospheric neutrinos and b) an assumed energy spectrum for astrophysical neutrinos following a power law of dN=dE = 10 5 E 2 cm 2 s 1 sr 1 GeV 1 . Whenusing the number of red OMs as a measure of energy we obtain the distributions given in g. 9.
The assumed astronomical neutrino ux would generate a signi cant excess at high multiplicities
of red photomultipliers. A preliminary analysis does not show such an excess. This leads to apreliminary upper limit [65] (90%C.L.) of dN=dE  10 6 E 2 cm 2 s 1 sr 1 GeV 1 . However,the systematics of this analysis with respect to the high energy sensitivity is still subject tofurther investigation. A re-analysis with an updated version of the Monte Carlo simulation isunderway.
This sensitivity on the di use neutrino ux is below previously stated upper limits by experiments such as BAIKAL [71], SPS-DUMAND [66], AMANDA-A [67], and FREJUS [68], andcomparable to a limit presented by BAIKAL [75].
It is comparable to the AGN prediction by Salamon and Stecker [63] and approaches theprediction of Protheroe [69].

4.1.4 Point Sources
The search for point sources allows us to measure the background o -source. Searches have been
performed for speci c point sources as well as all sky searches. The median angular resolutionof the AMANDA-B10 array is 3 degrees. Thus, one hemisphere consists of 319 bins. Again
the search strategy is optimized for the expected energy spectrum. The size of the search bins,
the e ective area and the livetime of the array enter the calculation of a neutrino ux limit.
In absence of a signal we calculate upper limits to a neutrino ux from point sources. The
33

No. of events

45
40
35
30
25
20
15
10
5
0

50

Atmos. MC
10 E

40Atmospheric MC±2E

spectrum MC

60

70

30

20

10

1

2

3

4
5
6
7
log neutrino energy

0

0

10

20

30

40

50

80

90

100

Number of Channels

Figure 9: Left: Monte Carlo simulation of the energy spectrum of atmospheric neutrinos shown in the
skyplot in g. 8. Also shown is the energy spectrum of neutrinos generated by a neutrino ux of aE 2 -type energy spectrum (see text).

34

E2 (dN/dE)ν (GeV cm–2 s–1)

10–4

Point Source Limits
10–6

3

1

AMANDA B-10

2

10

4

–8

5
8

6

10–10

IceCube3 years
10

3

7

104

105

106

Eν (GeV)Figure 10: Predictions of high energy  +  uxes from astrophysical sources are shown. Also shown

are the preliminary average upper limit as obtained with AMANDA-B10 (3), as well as the sensitivity ofthe proposed IceCube array after three years of operation. The atmospheric neutrino ux [59] in 2  2degree bin is given as reference: (1) horizontal, (2) vertical. Models: (4) 3C273 pp neutrinos [60], (5)Crab Nebula [61], (6) Coma Cluster [62], (7) 3C273 p neutrinos [63], (8) Supernova IC443 [64].

35preliminary average neutrino ux limits are at a level of dN=dE  10 6 E 2 cm 2 s 1 GeV 1 .
The limit in case of Mrk501 is of particular interest. Here our neutrino ux limit is only
about a factor of 10 above the gamma emission of this blazar, during its high state in 1997. The
sensitivity of the AMANDA array is thus beginning to approach observed uxes of gamma rays.
Figure 10 shows the expected neutrino uxes from various sources, together with the current
preliminary AMANDA upper limit (90% C.L.). The atmospheric neutrino background is given
for a 2  2 degree bin. Detailed simulations have been performed of IceCube, the proposed kmscale neutrino array. The achievable upper limit for an assumed E 2 -type spectrum for point
sources is indicated in the gure.

4.1.5 Gamma-Ray Bursts
According to the relativistic reball model, gamma-ray bursts (GRBs) are expected to be astrophysical sources of high energy neutrinos. The expected neutrino event rate in AMANDA has
been determined from a full MC simulation of the GRB signal and the detector. GRB neutrinos
are generated following a broken power law energy-spectrum [78]. Figure 11 shows the energy
spectrum of Monte Carlo events that triggered events in the AMANDA array. The search strategy has been optimized for this hypothetical signal. The number of expected events depends
strongly on the assumed Lorentz factor. This scenario predicts event rates ranging from 10 4
events ( = 1000) to 1 event ( = 100) for the given data sample.

-1

10

-1

dRate/dlog(Enu) [year • Gev • 2π]

GRB spectrum at trigger level - Γ=300

10
10
10
10
10
10
10

-2

-3

-4

-5

-6

-7

-8

-9

1

2

3

4

5

6
7
8
log(Energy) [GeV]

Figure 11: The energy spectrum of a neutrino ux as expected from gamma ray bursts triggered by
AMANDA (Monte Carlo simulation).

With  1=3 sky coverage, the BATSE satellite instrument detected 304 gamma-ray bursts
in 1997. AMANDA data for 78 gamma-ray northern hemisphere bursts detected on-board the
BATSE satellite were examined for coincident neutrino emission. Because the time window of36

coincidence is rather short, typically of order 10 seconds per burst, there is very little backgroundfrom cosmic rays and atmospheric neutrinos. No excess of neutrinos has been found above abackground of 17.2 events for all 78 bursts.

4.1.6 WIMPs

10 6

AMANDABAKSAN
MACRO
SUPER-Kth

E µ = 1 GeV-2-1

Muon flux from the Earth (km yr )AMANDA can be used to search for non-baryonic dark matter in the form of weakly interacting
massive particles (WIMPs). The non observation of an excess of vertically upgoing muons has
been used to set a limit on the ux of neutrinos from WIMP annihilations in the center of the
Earth [79]. With only 132 days of exposure in 1997, AMANDA has reached a sensitivity in theregion of high WIMP masses ( 500 GeV) that begins to constrain the theoretically allowed
parameter space. It is comparable in sensitivity to other detectors with much longer livetimes.
Figure 12 shows the present AMANDA limit after 132 days observation time in comparison
with the limits obtained from long-year exposure of MACRO, Baksan and SuperK [80]. Notethat the AMANDA limit is determined including (currently) large systematic uncertainties (theother experiments did not include their comparatively small uncertainties).

10 5

BAIKAL

*)

10 4
10 3
10 2
10
1
10

10

2

3

10
10
Neutralino Mass (GeV)

4

Figure 12: Upper limits on the ux of upgoing muons from WIMP annihilation in the Earth obtainedin AMANDA, Baksan, Macro, Super-K and and Baikal (normalized to 1 GeV threshold). (Note: The
Baikal limit is a muon ux limit from the center of the Earth, without MSSM model assumptions.)

37

4.1.7 Supernovae

Number of 10 sec intervals

By monitoring bursts of low energy neutrinos AMANDA can be used to detect the gravitational
collapse of supernovae in the galaxy. This method takes advantage of the low noise characteristics(300{1500 Hz/PMT) of the optical sensors in the deep ice.
Figure 13 shows, for 215 days of live time in 1997/98 and all stable AMANDA-B10 PMTs,
the distribution of the deviation  of the average noise rate from its mean value. Each data
point is the average over a 10 s interval. Accepting every 10 s interval with  > 4 Hz (see thevertical line) as a supernova event, would result in one fake alarm per year. This corresponds
to a 90% eÆciency for a SN-1987A-like supernova event loacted at a distance of 9.8 kpc (thedistance to center of Galaxy is about 8 kpc). A robust on-line monitor could be operated with aslightly higher threshold covering about 70% of the Galaxy. With AMANDA-II and an improved
supression of non-Poissonian noise we will monitor more than 90% of the Galaxy.

10

4

10

3

10

2

90% of SNaeat 9.8 kpc

10

8σ

1
-10

-5

0

5

10

15

20
∆µ [Hz]Figure 13: Distribution of the deviation  of the average noise rate from its mean value, for 215 daysof live time. The vertical line is set at the level where we get a rate of one background event per year.
90% of the supernova neutrino bursts located at 9.8 kpc distance would be seen above that cut.

4.1.8 Magnetic Monopoles
A magnetic monopole with unit magnetic Dirac charge and a velocity of close to 1 would emit
Cherenkov light along its path, exceeding that of of a bare relativistic muon by a factor of 8300.
From the non-observation of events with this clear signature, a limit of 0:62  10 16 cm 2 s 1 sr 1
for highly relativistic monopoles has been derived. This limit, illustrated in g. 53, is a factorof 20 below the Parker bound and a factor of four below other best limits.
38

4.1.9 Summary of AMANDA Status
The detection of atmospheric neutrinos in agreement with expectation and the calibration of
downgoing muons with surface detectors establish AMANDA-B10 as a neutrino telescope. Since
February 2000, the signi cantly larger and improved AMANDA-II array has been collecting data.
Its e ective area for high energy neutrinos is about three times that of the AMANDA-B10 array.
At the same time improved angular resolution and background rejection potential are available.
The analysis of these data is under way and will improve the given results signi cantly.

39

5

Expected IceCube Performance

5.1 Introduction
In this section we describe how well the IceCube detector will perform and show that it willreach the scienti c goals described in Section 3. This performance depends crucially on signal
detection eÆciency, background rejection, and calibration of the detector response to high-levelvariables such as energy and direction and low-level variables such as hit times and amplitudes.
Therefore, estimates of IceCube signal sensitivities and limit levels for a variety of potential
signals are given, as well as descriptions of techniques for high-level calibration of the detector
response (low-level calibrations are discussed separately in section 7). We also describe studiesof the detector con guration in order to maximize detector performance.

5.2 Atmospheric Neutrinos
The largest contribution to the  ux from non-transient sources in the energy range of several
hundreds of MeV to at least several hundreds of TeV is atmospheric neutrinos. The atmospheric ux is dominated by the muon component, increasing from a 2:1  : e ratio at low energiesE  1 GeV to 30:1 at E  100 TeV so that the atmospheric  \background" to UHE
cascades is somewhat smaller than for UHE muons. The following sections will address theuse of atmospheric neutrinos as a calibration source at lower energies, and their rejection as a
background source at higher energies.

5.3 Muon-Neutrino-Induced Muons
5.3.1 Simulation
Muon events have been generated with the neutrino simulation package nusim [133, 134]. Neutrinos, sampled from an E 1 spectrum, are propagated through the earth, taking full account of
the earth's density pro le. Neutral current regeneration of the neutrinos is treated exactly using
a recursive propagation algorithm. Simulation of a generic E 1 spectrum allows for the nal
events to be re-weighted to any desired neutrino source spectrum, whether it be an atmospheric
neutrino spectrum (E 3:7 ), a generic E 2 spectrum for AGN neutrinos, or any other spectrum
predicted in the literature.
The absorption of neutrinos in the Earth is an important e ect, see g. 14. For energies
below a few tens of TeV, the full lower hemisphere is visible, whereas at energies above a few
PeV the angular acceptance is reduced to zenith angles smaller than 30 degrees below horizon.
Neutrinos have been generated up to a maximum energy of 100 PeV which was set bytechnical limitations. Eight million events from downgoing muons which constitute the main
source of background have been simulated and are used to demonstrate eÆcient backgroundrejection. Muons were propagated with full simulation of stochastic energy loss. The detector40

Transmission

1.0
0.8

10 TeV
100
TeV

0.6
0.4

1 PeV
10
PeV

0.2
1 EeV
90 o

120o

150 o

180

o

Zenith angle
Figure 14: Left plot: Transmission coeÆcient of the Earth for electron and muon neutrinos as a functionof energy and zenith angle [126]. Tau neutrinos have a transmission coeÆcient of 1 due to  regeneratione ects, but their energies are degraded. Right plot: Energy of exiting  as a function of energy of entering , showing e ect of energy degradation due to passage through the Earth [42].

41simulation was performed with the AMANDA simulation package amasim. Ice inhomogenities
have been neglected for this study but will be included in the future. We simulated PMTs of
10 in diameter but did not take into account the possible increase in light collection eÆciency
due to a proposed wavelength shifter coating applied to the outer OM surfaces. The noise of
the PMTs has been conservatively assumed to be 500 Hz (i.e. higher than the design goal of
300 Hz). A trigger was de ned by the condition of at least 5 hits in a local coincidence. A local
coincidence is de ned with respect to the four nearest neighbors, and for a time window of 1 s.
Signal Monte Carlo muon events are shown in gs. 15 and 16, where the muon energies are
10 TeV and 6 PeV, respectively.

Figure 15: A simulated 10 TeV muon track in IceCube. Colored circles represent hit channels, with red
circles hit earliest and violet circles latest. Circle size corresponds to number of detected photons.

5.3.2 Reconstruction and Background Rejection
The reconstruction was done in several steps using the AMANDA reconstruction package recoos.
The start values for the full t are obtained from two simple fast approximations called line- t
and dipole- t (see [151] for details). As a rst reduction step with respect to downgoing muons,relatively weak cuts on the zenith angle obtained from these fast approximations have been
applied. These cuts have passing rates of 0.91, 0.78 and 0.04 with respect to the sample from
AGN neutrinos, atmospheric neutrinos and downgoing muons, respectively.
Next, a full likelihood t was performed (see [150] and [151]). This t yields a series ofparameters which can be used for selecting events with high quality reconstruction and forfurther reduction of background. The cuts chosen are the following: zenith angle  obtained from the likelihood t larger than 85Æ, and log L < 10, where L
is the likelihood;42Figure 16: A simulated 6 PeV muon track in IceCube. Colored circles represent hit channels, with red
circles hit earliest and violet circles latest. Circle size corresponds to number of detected photons.

43  5 hits with a time residual between {15 ns and +150 ns (\direct hits"), where the photon
did not undergo many scattering interactions);

 length of the projection of the direct-hit OMs to the reconstructed track larger than 150 m;
 di erence between the zenith angles obtained from line t and likelihood t smaller than
10 degrees; the absolute value of the smoothness, smaller than 0.5.1
Note that the standard cuts listed above result in a passing rate of 53% for AGN neutrinos
and reduce the background from downgoing muons by 3  10 6 . As shown in g. 17, thisbackground is concentrated close to the horizon. It can be easily rejected by a further zenith
cut (if lower energies should be accepted), or by cuts on the number of channels (if one focuses
to the separation of higher energies). Figure 17 also shows the background from uncorrelated
coincident air showers (bottom right) which can produce two hit clusters, and earlier one at thebottom and a later one at the top of the array. Such events are not rejected by a simple angularcut, giving the relatively high passing rate after angular cuts compared to muons from single
air showers. However, these events are easily identi ed by the subsequent cuts, in particular thecut on the smoothness.
Results are shown for the \standard con guration" (triangular pattern, 16 m vertical spacing2 , 125 m interstring distance). Numbers at the top corner give the number of events andthe passing rates. For AGN neutrinos, a ux of 2  10 7  E 2 GeV 1 cm 2 s 1 sr 1 has been
assumed, resulting in 4265 events.3
We have investigated the physics performance of the IceCube detector for di erent con gurations, starting from the default con guration and going into the direction of both smaller
and larger spacings [139]. Early results on similar IceCube simulations have been presented
in [124, 125]. Whereas in [139] only con gurations with about 5000 OMs and equidistant spacing are considered [124, 125] cover also options with twice or half the number of OMs, and nested
con gurations.
The basic pattern is shown in g. 18. Apart from the triangular pattern, we also simulated
rectangular patterns, which yield similar results. The circle in g. 18 indicates an area of one
square kilometer. The con guration includes 80 strings and 60 OMs per string. For a verticalspacing of 16 m, this results in an instrumented length of 944 m. The top layer of OMs was
assumed to be at a depth of 1400 m. Table 2 summarizes the studied con gurations.
The two following tables give the number of triggered and accepted events per year for thevarious con gurations. Table 3 gives results for atmospheric neutrinos. Numbers in table 4 arefor AGN neutrinos, again assuming a ux of 2  10 7  E 2 GeV 1 cm 2 s 1 sr 1 . The upper
1
The smoothness S measures the homogenity of the distribution of hits along the track. Exactly equidistanthits would give S = 0, all hits at the starting point of the track S = +1 and all hits at the endpoint S = 1.
2
The 16 m vertical spacing was chosen for this study before 17 m became the baseline design.
3
7
2
1
2
1
1

An AGN neutrino ux of roughly 10
sensitive. It is otherwise arbitrary.

E

GeV

cm

44

s

sr

is roughly the ux to which AMANDA isvertical / horizontal
12 m
16 m
20 m

100 m 125 m 150 m 175 m
X
X
X
X
X
X
X
X
X
X

Table 2: Simulated con gurations. Columns indicate di erent string spacings, rows di erent spacings of

10

5

10

4

10
10

events/year

events/year

OMs along a string. An \X" indicates that the particular con guration was simulated.

AGN ν

10

5

10

4

3

10

3

2

10

2

10

10

1

1
-1

0

12

10

11

10

10

events/year

10

10

9

10

8

10

-1

50

100

10

150
o
reco-zenith /Single Events

0

10

12

10

11

10

10

events/year

10

Atm ν

10

9

10

8

7

10

7

10

6

10

6

10

5

10

5

10

4

10

4

10

3

10

3

10

2

10

2

0

50

100

150
o
reco-zenith /

0

50

100

150
o
reco-zenith /Double Events

50

100

150
o
reco-zenith /Figure 17: Distribution of the reconstructed zenith angle after trigger (full upper line), and the 3 cutson the zenith angles (dashed line), the remaining four quality cuts (dotted line). The shaded histogram
gives the energy spectrum after an additional cut on the number of hit PMTs at Nch > 50. The dark
histogram corresponds to a cut at Nch > 180. The bottom histograms show the background expectedfrom single air showers (left) and from accidentally coinciding air showers (right). Note that neutrinos
have been generated only between 80 and 180 degrees, hence the cut-o at 80 degrees after quality cuts.

45

triang

rectang

g = 125 m

g = 125 m

Figure 18: Top view of the two principal string patterns investigated here. left: triangular pattern,right:

rectangular pattern (both shown for a string spacing of 125 m). Scales are in meters.

vertical/horizontal
12 m
16 m
20 m

100 m 125 m 150 m 175 m
2.9 k 3.6 k 4.3 k
1.5 k 1.8 k 2.2 k
3.4 k 4.3 k 5.5 k
1.9 k 2.3 k 2.5 k
4.0 k 4.9 k 5.7 k 6.5 k
2.1 k 2.4 k 2.6 k 2.8 k

Table 4: Number of triggered and accepted neutrino events per year (in thousands) assuming a ux of2  10 7  E 2 GeV 1 cm 2 s 1 sr 1 . The upper numbers refer to triggered events, the lower numbers
in italics to the events after quality cuts.

46

numbers refer to triggered events, the lower numbers (in italics) to events after reconstruction
and quality cuts.
vertical/horizontal
12 m
16 m
20 m

100 m
600 k
140 k
590 k
140 k
580 k
140 k

125 m
620 k
130 k
600 k
130 k
590 k
110 k

150 m 175 m
640 k
120 k
620 k
110 k
600 k 560 k
90 k
60 k

Table 3: Number of triggered and accepted events per year for atmospheric neutrinos (in thousands).

The upper numbers refer to triggered events, the lower numbers in italics to the events after quality cuts.

Clearly, larger spacing is preferable for the AGN case but tends to suppress more atmospheric
neutrinos after quality cuts. Going from 125 m string spacing to 150 m gives a 10% increasein accepted AGN events. The rectangular con guration gives a 5% increase in events rate.
Decreasing the spacing to 12 m/100 m gives 30% loss in AGN neutrinos, but a slight increase
for atmospheric neutrinos. The angular resolution for all con gurations is  1 degree.

5.3.3 Sensitivity to Di use Sources of Muon Neutrinos
We calculate the sensitivity of the detector to di use uxes of neutrinos with a generic E 2
spectrum, expected for sources such as active galactic nuclei (AGN). For the purposes ofthese calculations we assume a source strength for muon-neutrinos and antineutrinos of alevel E2 dN=dE = 10 7 GeV cm 2 s 1 sr 1 . We use the Model Rejection Potential formalism [132, 135], and the associated \model rejection factor" (MRF), to optimize the limit analysis.
Figure 19 shows the results of the minimization of the MRF for the hit multiplicity (Nch ) cut
and an exposure time of three years. The top left gure shows the di erential numbers ofevents expected for both the E 2 spectrum (blue solid line) and for the atmospheric neutrinos(red dashed line). The top right plot shows the same quantities as an integral distribution. Also
shown is the Feldman-Cousins 90% con dence level average upper limit. As the background falls
toward zero, this classical average upper limit converges toward a value of 2.44. The best limit
is obtained where the model rejection factor, ((nb )=ns ), is minimised (bottom left plot).This
occurs for a cut of 168 channels, where 120.9 signal events would be expected upon a backgroundof 17.2. The average upper limit for this background is 8.4, leading to a MRF = 6:9  10 2 ,and therefore to a ux limit of E2 dN=dE = 6:9  10 7 GeV cm 2 s 1 sr 1 . The bottom rightplot shows the parent neutrino energy distribution for those events with multiplicity above theoptimal cut of 168 channels. The multiplicity cut corresponds to a minimum energy of about
30 TeV, and to a typical neutrino energy of 1 PeV. Table 5 summarises the results of the MRF
optimization for exposure times of one and three years.
47

time (yrs) Nch cut S ( Nch ) B ( Nch ) (B ( Nch )) limit (= E 2 dN=dE  S )
1
175
53.1
5.4
5.3
1:0  10 8
3
221
93.1
3.2
4.5
4:8  10 9
Table 5: IceCube model rejection factor for an E 2 dN=dE = 10 7 cm 2 s 1 sr 1 GeV2 ux as a functionof exposure time.

Figure 19: Model rejection potential optimization for a di use ux: Top left: di erential Nch distribution

for atmospheric neutrinos (dashed histogram) and AGN neutrinos (full histogram), assuming a ux of
10 7 E 2 GeV 1 cm 2 s 1 sr 1 for AGN neutrinos. Top right: integral Nch distribution, with the average
upper limit shown as a solid line. Bottom left: Model rejection factor. Bottom right: Distribution ofneutrino energies for those events with hit multiplicity Nch greater than the optimal cut. We see that
the Nch cut corresponds to neutrino energies greater than  30 TeV and that the detector is sensitive todi use E 2 neutrinos of energy of order 1 PeV (solid blue line). The red dashed line shows the energiesof the atmospheric neutrinos that pass the cuts.

48

5.3.4 Sensitivity to Muon Neutrino Point Sources
The sensitivity of IceCube for point sources of neutrinos has been assessed. Since the background
may be greatly reduced by cutting to a small angular region about the direction of the point
source, the multiplicity cut (Nch ) can be relaxed. The sensitivity has been checked in two ways,
rst by averaging the sensitivity over the upward going hemisphere, and second by looking at apoint source from a speci c zenith angle.
For each exposure time tested, we optimise in both angular bin size and Nch . Figure 20
shows the pointing accuracy of the array. Ninety percent of events reconstruct to within 4Æ
of the true direction, and 60% to within 1Æ . The MRF results from varying angular bin andexposure time are shown in table 6. These show that a signal strength of the level dN=dE =10 7 cm 2s 1 sr 1 GeV2 would produce a very signi cant signal in IceCube, and in its absence,very constrained upper limits would be obtained. For both exposure times, the best choice ofangular cut is about 1Æ , but the limit is ultimately not very sensitive to the choice of angularcut, suggesting that a smaller cut, to enhance the signi cance of a possible observation, may be
warranted. Although the cuts have been optimised to minimise the MRF, thereby optimising
the limit setting potential of the detector, we can make some basic estimates of the level ofa point source ux needed to give a signi cant detection of a signal in the exposure time. A
chance probability of  10 7 for a background uctuation corresponds roughly to a \5 sigma"
observation. For any quoted background level, we can calculate the number of events needed
to get this chance probability. For the case of 1 year exposure with a 1Æ angular bin, theexpected background is 0.53 events. If 8 events were observed, this would give the required
chance probability of  10 7 . A signal strength of 8 0:5 = 7:5 events is about 1/5 of thenumber of events expected from the dN=dE = 10 7 cm 2s 1 sr 1 GeV2 ux, therefore a point
source of level dN=dE  2  10 8 cm 2s 1 sr 1 GeV2 would be required to produce a \5 sigma"
observation in one year of live time. Of course, this analysis assumes that we only look at asingle candidate source. If we do a full sky search, we must pay a penalty for statistical trials.
There are about 6500 bins of 1Æ radius in a half sky (upgoing neutrino) search, so a signi canceof  10 9 would be needed for an unknown point source to give a  10 7 result after the trials
are accounted for. This requires that about 10 events are observed (the chance probability toobserve 10 or more events from a backgrpound of 0.53 is 3  10 10 ), increasing the required
signal strength by about 30%.
Table 7 shows the MRF results for a point source at a zenith angle of 130Æ . The limit setting
potential is slightly less than the average seen in table 6. Figure 21 shows the model rejection
potential optimization for a point source.

5.3.5 Sensitivity to Muon Neutrinos from Gamma-Ray Bursts
Recently, Waxman and Bahcall [94] have proposed that gamma-ray bursts (GRBs) might besources of neutrinos. The search for neutrinos from GRBs is simpli ed over that of a point
source, due to the time stamp available from satellite observations of the gamma rays from theburst. In the Waxman-Bahcall model the neutrinos are expected to arrive within approximately49

t (y)  Nch cut S ( Nch ) B ( Nch ) (B ( Nch )) limit (= E 2 dN=dE  S )
1
0.5
25.5
43.1
0.53
2.9
6:7  10 9
1 1.0 32.5
60.6
0.91
3.2
5:3  10 9
1
2.0
42.5
55.6
1.10
3.4
6:0  10 9
1
5.0
55.5
43.9
2.20
4.0
9:0  10 9
3
0.5
32.5
110.2
0.67
3.0
2:7  10 9
3 1.0 42.5
137.6
0.82
3.1
2:3  10 9
3
2.0
53.5
128.8
1.25
3.5
2:7  10 9
Table 6: IceCube model rejection factor for a point source, averaged over zenith angles 90 180Æ with ux

E 2 dN=dE = 10 7 cm 2 s 1 GeV2 . The optimum choice of cuts for both exposure times are highlighted inbold.

time (yrs)  Nch cut S ( Nch ) B ( Nch ) (B ( Nch )) limit (= E 2 dN=dE  S )
1
0.5
24.5
36.6
0.71
3.0
8:2  10 91
1.0 33.5
47.7
1.0
3.3
6:9  10 9
1
2.0
41.5
45.8
2.2
4.0
8:8  10 9
1
5.0
64.5
25.6
1.6
3.7
1:4  10 8
3
0.5
29.5
98.0
1.2
3.4
3:5  10 93
1.0 33.5
143.2
3.0
4.4
3:1  10 9
3
2.0
42.5
132.8
5.8
5.5
4:1  10 9
Table 7: IceCube model rejection factor for an point source at 130Æ zenith angle, with ux E 2 dN=dE =10 7 cm 2 s 1 GeV2 .

50

Figure 20: IceCube angular resolution for E 2 point sources: 80% of events reconstruct to within 2Æ ofthe true direction.

51

Figure 21: Model rejection potential optimization for a point source: Top left: di erential Nch distri-bution for atmospheric neutrinos (dashed histogram) and AGN neutrinos (full histogram), assuming aux of 10 7  E 2 GeV 1 cm 2 s 1 sr 1 for AGN neutrinos. Top right: integral Nch distribution. Solidline { average upper limit Bottom left: Model rejection factor. Bottom right: Distribution of neutrinoenergies for those events with hit multiplicity Nch greater than the optimal cut. We see that the Nch
cut corresponds to neutrino energies greater than  1 TeV and that the detector is sensitive to di use
E 2 neutrinos of energy of order 100 TeV (solid blue line). The red dashed line shows the energies of theatmospheric neutrinos that pass the cuts.

52

10 seconds of the gamma rays. The IceCube detector will reconstruct neutrino-induced muons
from GRBs to less than ten degrees of the true direction ( g. 22).

Figure 22: IceCube angular resolution for gamma-ray bursts.
The Waxman-Bahcall ux corresponds to the expected neutrino ux from 1000 GRBs.
Within a 10Æ angular search bin and 10 second time window, we would expect a total of 15
upgoing muon events from 1000 GRBs after quality cuts were applied to remove the most obvious mis-reconstructed downgoing muons. The atmospheric neutrino background is negligible(total 0.32 events) but about 500 misreconstructed downgoing muons would remain. Tightening
the cuts to the nal cut set discussed previously removes the last of the muon background,
reduces the atmospheric neutrino background to 0.23 events, and retains 12 GRB induced neu53

trino events. It should be noted that more Monte-Carlo simulations are needed to further checkthe belief that the background of mis-reconstructed downgoing muons is indeed zero.
Optimising the Nch cut leads to a cut of Nch = 12:5 and model rejection factor of 0.22, a severe
constraint on the Waxman-Bahcall model. Since the GRB search is essentially background free,
the improvement in the limit goes nearly linearly with the increasing number of GRBs searched.
This behaviour is shown in table 8. It is interesting that the observation of only 210 GRBs isenough to rule out the Waxman-Bahcall model at 90% classical con dence.
Since the angular cut and time window search can be made so tight, the GRB searches areclose to background-free. Then the observation of even a few events would be very signi cant.
For 300 GRBs searched, and a 2Æ , window, the Waxman-Bahcall model predicts about 3 events,
on an atmospheric neutrino background of 0.003. The chance probability of observing 3 orgreater events given a background of 0.003 is about 5  10 9 .
Table 8 shows that the MRF is insensitive to the choice of angular bin size. In this case, achoice of a smaller search window would be preferred, in order to reduce the background (forlimited signal loss) and give a more signi cant observation of a potential signal. Ultimately
however, the uncertainty in the knowledge of the GRB direction (from the satellite observation)
will limit how small the angular search bin can be made. Figure 23 shows the model rejection
potential optimization for GRBs.

nbursts  Nch cut S ( Nch ) B ( Nch ) (B ( Nch )) limit (= E 2 dN=dE  S )
100
2.0
1.5
0.98
0.001
2.4
2.49
5.0
1.5
1.13
0.005
2.4
2.16
10.0
1.5
1.19
0.02
2.46
2.06
20.0
1.5
1.20
0.086
2.51
2.07
30.0 12.5
1.22
0.19
2.60
2.12
210
10
1.5
2.50
0.045
2.49
0.99
300
2.0
1.5
2.94
0.003
2.44
0.829
5.0
1.5
3.40
0.016
2.45
0.721
10.0
1.5
3.51
0.065
2.46
0.70
20.0
1.5
3.66
0.26
2.66
0.72
1000 2.0
1.5
9.81
0.009
2.45
0.249
5.0
1.5
11.34
0.05
2.48
0.219
10.0 12.5
11.9
0.215
2.62
0.22
20.0 20.5
11.3
0.471
2.83
0.25
Table 8: IceCube model rejection factor for a Gamma-ray burst search.

5.3.6 Possible Improvements
The sensitivities given above could change in reality. We estimate that uncertainties in ice
modelling might change them by up to 50%{in either direction. Use of an energy estimator
54

Figure 23: Model rejection potential optimization for gamma-ray bursts: Top left: di erential Nch

distribution for atmospheric neutrinos (dashed histogram) and WB GRBs (full histogram). Top right:
integral Nch distribution. Dotted line { average upper limit. Bottom left: model rejection factor. Bottom
right: Distribution of neutrino energies for those events with hit multiplicity Nch greater than the optimal
cut. We see that the Nch cut corresponds to neutrino energies greater than  1 TeV and that the detector
is sensitive to di use E 2 neutrinos of energy of order 100 TeV (dashed blue line). The red dashed line
shows the energies of the atmospheric neutrinos that pass the cuts.

55

better than Nch may result in an improvement of up to 30%. Use of wavelength shifter could
enhance the sensitivity of the OMs by up to 35% and result in higher signal eÆciency andimproved background rejection. The application of reconstruction methods which make useof the full waveform instead of using only the time of the rst arriving photon will lead to abetter angular reconstruction, in particular for high-energy events (see Section 5.6). We hope
to reach an accuracy of about 0.5 degrees for moderate cuts, resulting in a slightly better point
source sensitivity. Neutrinos with >100 PeV have not been taken into account in the present
simulation. Their inclusion will also result in a better limit. Other lines of improvement are
selection of cuts with a better passing rate for for AGN neutrinos (giving possibly a 10{15%e ect), and a change of the con guration to larger spacing, which is discussed in section 5.8.

5.4 Electromagnetic and Hadronic Cascades
The charged current interaction of UHE electron neutrinos and the neutral current interactionsof UHE neutrinos of all active avors will produce large localized depositions of energy in the
IceCube detector. The signature of these electromagnetic or hadronic showers (cascades) is abright, pointlike source of Cerenkov
light4 as shown in g. 24. To be detected, cascades mustoccur near or within the active detector volume, and consequently the e ective volume for theirdetection is substantially smaller than that of muons. However, cascades have the advantagethat their energies can be measured more accurately than muon events, making it easier toseparate UHE cascades from background. This is especially true for e charged current and\double bang"  interactions, where the resulting cascades give a fairly accurate measure of
the energy of the parent neutrino.

5.4.1 Simulation
Cascade events were generated using one of three generators depending on the study: Reconstruction studies and e ective volume calculations were performed using a very simple Perl script which throws isotropic cascade vertices uniformly throughout a cylindricalvolume 1.5 km tall and 1.5 km in radius surrounding the detector. These events are
generated with a Ecas1 energy spectrum from 100 GeV to 1 EeV.

 The atmospheric neutrino signal was generated by casim, a weighted Monte Carlo package which produces cascade events with a Ecas1 spectrum from 10 GeV to 100 TeV. The
atmospheric neutrino ux is taken from Lipari [95]. The weight of each event is recorded
to allow biasing back to the physical energy spectrum.

 The expected signal for ultrahigh-energy cascades from di use sources or GRBs was simulated using code which propagates a given neutrino ux through the Earth, taking into4
The pointlike approximation for cascades holds to very high energies as the logitudinal development of theshower is only logarithmically dependent on the shower energy.

56

Figure 24: A 375 TeV cascade in IceCube. Colored circles represent hit channels, with red circles hit
earliest and violet circles latest. Circle size corresponds to number of detected photons.

57

account both neutrino absorption and neutral-current regeneration and generates neutrinonucleus interaction vertices in a homogeneous volume of ice surrounding the detector overthe full 4 steradians of solid angle. In order to realistically simulate the overburden ofmaterial in the upper hemisphere, the simulation code models the south polar ice as aspherical cap on the Earth. This package generates unweighted events. Several energy
spectra were sampled for 100 GeV < E < 1 EeV, each corresponding to a distinct astrophysical source models. They are dealt with in ner detail in the appropriate sections.
These vertices are then passed to the detector simulation package, amasim, which generates
PMT hits in the array and builds them into events. Triggers were generated on a coincidence ofve hits in 2.5 s. Additionally, a feature of amasim was enabled that preserves pulse amplitude
information for each pulse in the event that a single OM receives multiple hits. 5 This additional
information approximated waveform readout in IceCube.

5.4.2 Reconstruction
Applying algorithms developed for AMANDA on simulated IceCube data, we have estimatedthe vertex, direction, and energy resolutions of cascades in IceCube. We have also estimatedthese resolutions using newly developed algorithms tailored to IceCube data. Estimates using
AMANDA algorithms are conservative since they rely primarily on the arrival times of the rst
photons in each PMT, while in IceCube we will have access to much more detailed waveform
information. Estimates using new algorithms are also conservative since we anticipate using the
waveform information in a more complete manner than presented here.
The AMANDA algorithm for reconstructing the vertex position and time is based on amodel of the scattering and absorption of Cerenkov
light in the ice. It maximizes a likelihood
function which depends on a parametrization of the probability distribution of observing one
photon with a given time delay at some distance from the source. The AMANDA algorithm forreconstructing direction and energy is also a maximum likelihood t which uses a parametrizationof the expected number of photons at each PMT as a function of cascade energy and the relative
cascade-PMT direction.
Applying these algorithms to simulated IceCube cascades with contained vertex positions(vertices at least 100 m from the edge of the detector), resulted in energy and zenith angle
resolutions which were better than in AMANDA. The resolutions are as follows: Energy: 11% in log10 E (AMANDA: >40%)
 Zenith: 27Æ in zenith angle (AMANDA: 27Æ)
 Vertex: 3 m in x; y; 2 m in z (AMANDA: 6.4 m in x; y; 5.3 m in z)
These resolutions are illustrated in g. 25.
5
In AMANDA, the peak ADC hardware only records a single peak value per ADC gate, and thus, normally,
the multiple pulse information is suppressed in amasim.

5814.9445.20
Constant
Mean
Sigma

60
EventsEvents/ 18
39.39
0.5255
3.062

Constant
Mean
Sigma

40

20

/ 18
58.16
-0.2785E-01
1.865

40
20

0

-20

0

0

20

-20

0

20

∆X (m)∆Z (m)

Events30

Z Vertex Resolution
27.65

Constant
Mean
Sigma

’log10(ECAS/GeV)X/Y Vertex Resolution
/ 32
21.17
-0.4598
26.60

20
10

8

6

4
0

-100

-50

0

50

θ Resolution

100

4

30

11.22

10

-0.5

0

10

0.5

12.58
Constant
Mean
Sigma

EventsEvents/ 8
18.44-0.6736E-02
0.9227E-01

20

-1

8

log10(ERECO/GeV)ECAS v ERECO

Constant
Mean
Sigma

0

6

∆θ (degrees)

/ 18
24.63
-0.7194E-02
0.1225

20

10

0

1

log10(ECAS/EREC)
Energy Resolution 1 TeV < E < 1 PeV

-1

-0.5

0

0.5

1

log10(ECAS/EREC)
Energy Resolution 1 PeV < E < 1 EeV

Figure 25: Vertex, direction, and energy resolutions for simulated IceCube cascades, using AMANDA
multiphoton reconstruction algorithms. These reconstructions are evaluated after all cuts which are listed
later in the subsection 5.4.2 on background rejection.

59

Ultimately, we anticipate that we will construct a likelihood function which uses the fullwaveform information from each PMT, maximizing the probability that each PMT observeda particular waveform as a function of cascade (~r,t,E,d~). Moreover, waveform readout will
dramatically increase the dynamic range of the PMTs. Cascade reconstructions in particularwould bene t from this enhancement due to the nature of the cascade signal: OMs very closeto the cascade vertex are expected to receive thousands of Cerenkov
s, but simultaneously
the detector must be able to resolve the single hits at large distances for accurate energy
reconstruction.
Techniques for suppressing the cosmic ray muon events in IceCube have been borrowed from
AMANDA cascade analyses. The very large instrumented volume of IceCube makes cosmic-ray
muon rejection very eÆcient using quick algorithms based on event topology and total charge
information. Once these fast lters have reduced the data volume down to manageable levels,
maximum likelihood ts are performed to reconstruct the cascade vertex, direction, and energy
and further cuts are made on these output quantities.
It should be noted that these cuts were contructed to optimize HE events (E > 10 TeV) andconsequently, they are not eÆcient at passing the lower energy atmospheric neutrinos. In fact,
in a search for high energy galactic or extragalactic neutrinos, atmospheric neutrinos themselves
constitute a background.
The selection criteria are now explained. First, the tensor of inertia is evaluated about thecenter of gravity of the hits and is diagonalized P
to nd its eigenvalues. The ratio of the smallest
eigenvalue to the sum of the eigenvalues, L1 = Li , provides an estimate of the sphericity ofthe event: muons tend towards enlongated hit patterns while cascades produce hits more or lessspherically symmetric about their centers. Next, a line t is performed. The line t is an analytic
approximation that all hits lie along a straight line moving at the speed of light. This heuristic
provides a measure of the time ow of the hits in an event. Cascades and muons separate
into two clearly distinct populations via the parameter jvLF j, the velocity of the line t. Monte
Carlo simulations indicate that cuts on these two variables suppress much of the backgroundand accept most of the cascade signal.
While the above criteria reduce the background by almost two orders of magnitude there still
remain at least four orders before the level of the signals isPapproached. An additional cut on
the total charge generated by the detected photoelectrons, Q, is applied which reduces eventhe high-energy Corsika-generated cosmic-ray muons almost another two orders of magntiude at
the expense of loss of signal sensitivity below about 10 TeV. A cut was applied on the likelihoodof the cascade reconstruction, Lcas < 6, eliminating all but two events of the (admittedly small)simulated high energy background sample. Finally, a containment cut was made which required
the center of gravity of the hits, weighted with ADC amplitude, to fall within a cylindricalvolume centered on the detector center, 750 m in height, 450 m in radius (0.48 km3 ). Thiseliminates all background events in the sampled sets.
Background was estimated using two di erent physics generators for cosmic ray muons:the basiev program generates proton primaries up to energies of 1 PeV. Beyond that, heavier
elements constitute a large portion of the cosmic-ray primaries and the Corsika air shower package
is used which accurately simulates the composition of the cosmic-ray primaries and the high60

energy interactions up to very high energies, exceeding 1020 eV. The calculated live times of theatmospheric muon samples are 80 seconds and 16 hours, respectively for the basiev and Corsika
sets. Therefore, background was estimated for higher cut levels which left no background in thesample sets. This was done by tting background versus a cut variable well below thresholdand integrating the extrapolated variable above threshold. Clearly, a more thorough study
necessitates additional background sampling. The results of the background suppression cutson these data sets as well as signal acceptance on di use (E 2 ) and atmospheric neutrino uxes
are presented in table 9.
Cut Level
TriggerP
L1 = LjPvLF jQ
Lmpe < 6
 < 450 m; jz j < 375 m

Di use ATM 
basiev
Signal Signal ECR < 1 P eV
981
22500
1:17  1011
842
10650
8:03  108
676
5470
1:47  108
461
470
13
447
397
0
180
217
0

Corsika
ECR > 1 P eV
2:22  108
7:76  106
2:34  106
5:68  104
1:96  103
 50

Table 9: Event rates of various sources of signal and background versus cut level. The numbers quoted
are in units of expected events per year. In the case of the di use neutrino ux, the rate is scaled for aux of E 2  = 10 7 (GeV  cm  s  sr) 1 .

There is also the possibility for strong cosmic-ray muon background suppression with thesurface array, IceTop. In the high-energy region where muon bremsstrahlung begins to look likea signal the surface array becomes relevant in two ways. Air showers with energy in the PeV
range and above will trigger the surface array with high eÆciency, and this trigger can be used
to veto and study this source of background. At higher energy the surface array will also havesome veto power for showers with cores outside the physical boundary of the array.

5.4.3 E ective Volume
The e ective trigger volume, Veff , is de ned as the equivalent volume in which the detector
achieves 100% eÆciency and is calculated from a simulation of cascades thrown in a much larger
volume, Vgen , byn (E )
Veff (Ecas ) = trig cas  Vgen
ngen (Ecas )and ranges from about 1 km3 at 1 TeV to 4 km3 at 100 PeV (see g. 26). A more realistic
e ective volume has been calculated that takes into account the background rejection criteria
discussed in the previous section. \Background Rejection I" refers to cuts made that remove
background that is expected to remain after vetoing cosmic-ray events that trigger the IceTopsurface array. The e ective volume drops to zero below about 1 TeV because of a high charge
61

4.5

Triggered
Background Rejected
Background Rejected and Contained

4

3.5

3

VEFF (km )

3

2.5

2

1.5

1

0.5

0

2

3

4

5

6

7

8

9

log10(ECAS/GeV)

Figure 26: E ective volume for neutrino induced cascades at trigger level (circles), after backgroundsuppression cuts (upward triangles), and both background cuts and requiring that the cascade falls within
the volume of instrumented ice (downward triangles). The trigger is here de ned as ve hits within amultiplicity window of 7.0 microseconds.

62requirement, reaches 1 km3 at 10 TeV, and grows to about 2.5 km3 at 100 PeV. \Background
Rejection II" cuts further require that the center of gravity of the hits be contained well insidethe detector instrumented volume. This additional cut reduces cosmic-ray muon background tozero independent of any IceTop veto at the cost of reducing the ducial volume to  0:5 km3.

5.4.4 Sensitivity to Atmospheric Examination of table 9 shows that there is a very prominent signal of atmospheric  (ATM  ) at
trigger level ( g. 27). Since they are produced with a much softer spectrum than the expected
spectra of extragalactic neutrinos, most of this signal populates the medium and high energy
regions from the lower energy thresholdof IceCube ( 100 GeV to several tens of TeV) and isP
reduced by more than 90% by the Q cut. It may possible to recover some of this lost signal bytuning the cuts for low energy neutrinos. For example, the high charge cut could be lowered andsupplemented with a cut on the zenith angle of the muon reconstruction to reject downgoingfakes.

10

3

Trigger Level
After HE Cuts

Events per year

10

2

10

1

-1

10

2

2.5

3

3.5

4

4.5

5

5.5

6

log10(ECAS)

Figure 27: Triggers versus energy and events passing background rejection cuts versus energy for atmospheric neutrinos (Lipari ux [95].)

63

5.4.5 Sensitivity to Point Sources
With present reconstruction techniques, the poor angular resolution of  -induced cascades in the
IceCube detector makes it diÆcult to perform a point source search in these channels. However,
new reconstruction techniques which take advantage of waveform information may improve uponthis situation.

5.4.6 Sensitivity to Di use e Sources
Earth absorption plays a signi cant role in the UHE neutrino ux at the IceCube detector.
Figure 28 shows the zenith angle dependence on the event rate and demonstrates the e ect:
Earth shadowing begins attenuating the event rate below the horizon at several tens of TeV.
The shadowing steepens with energy until, above energies E > 10 PeV, the earth is almost
totally opaque to neutrinos. Fold into this the fact that the target volume for  ! cascade,being closer to the detector than for  !  vertices, is symmetrically distributed both aboveand below the detector so that cascades do not su er a reduced amount of target material for
downgoing events. These two observations together imply that the upper hemisphere is especially
important for the detection of UHE  -induced showers and the ability to cleanly separate UHE
neutrino-induced showers from cosmic-ray muon background is another trump held by cascade
analyses. The di erential event rate of UHE cascades in IceCube versus energy for a ux ofE 2  = 10 7 (GeV  cm  s  sr) 1 is shown in g. 29. The squares represent the trigger rate andthe triangles represent the event rate after all background rejection cuts have been applied.

5.4.7 Sensitivity to GRBs
GRBs are another hypothesized source of UHE extragalactic neutrinos. For these sources,
Waxman and Bahcall [127, 128] propose a ux that is very soft, falling as E 1 until a breakenergy of several hundred TeV when the spectrum turns down to fall as E 2 . Folding in the 
cross-section, one obtains the result of an increasing interaction rate (in log E ) until the breakenergy, and thus a very high-energy source of  -induced cascades in the detector visible above
the background ( g. 30). The authors also predict that the  and bursts are very closely
correlated in time so that the IceCube detector can restrict searches to time windows centered on
burst events observed by one of the several gamma-ray satellites. However, if the GRB uenceis close to the W&B prediction, IceCube could still detect a cluster of cascade events from sucha burst without \triggering" on satellite observations.
A GRB search in the cascade channel has a distinct advantage over the muon channel searchwhich o sets the smaller e ective volume of high-energy cascades versus muons: backgroundrejection is based on event topology. That is, cascades do not look like atmospheric muons,
therefore the upper hemisphere does not need to be excluded from a cascade GRB search,making IceCube sensitive to both northern and southern hemisphere GRBs.

64

Events per year

10

3

10

2

10

1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1
cos θ

Figure 28: Distribution of UHE  -induced cascades versus zenith angle at generator level for a genericE 2

ux. The assumed source ux is E 2  = 10 7 (GeV  cm  s  sr) 1 .

65

Events per year

10

3

10

2

3

Interactions (per km )IceCube Triggers
Events after all cuts

10

1

10

3

10

4

10

5

10

6

10

7

10

8

10
Eν (GeV)9

Figure 29: UHE  interactions (circles, scaled to km 3  year 1 ), triggers in IceCube (squares), and events

passing background rejection cuts (triangles), versus energy for ux E 2  + = 10 7 (GeV  cm  s  sr) 1 .

66

-1

10

Events

-2

10

-3

10

10

3

10

4

10

5

10

6

10

7

10

8

Γ=100

10
Eν (GeV)

9

-1

10

-2

Events

10

-3

10

-4

10
10

3

10

4

10

5

10
Γ=300

6

10

7

10

8

10
Eν (GeV)9

Figure 30: GRB  -induced cascade event rate predictions following the Waxman-Bahcall model for two
choices of the Lorentz factor, . The y-axis is in units of s 1 making the integrated expected rate ofevents in a km3 detector about 0.5 Hz and 0.9 Hz for the choices = 100 and = 300, respectively.

675.4.8 Possible Improvements
High energy cascade reconstruction will bene t greatly from the waveform readout of IceCube
which is not yet fully simulated. Many improvements could be made to the reconstruction
algorithms which are currently not equipped to make use of the detailed hit information thatcomes with waveform readout. These are likely to improve cascade identi cation at high energies.
At lower energies, better cuts need to be developed that reject background but preserve theneutrino signal. Containment cuts that use the outer portion of IceCube as a veto shield should
allow sub-TeV cascade events to be identi ed.

5.5 Tau Neutrinos
In this section we expand on the discussion found in secs. 3.2.4 on  kinematics, detection
probability and event rates in IceCube. High energy tau neutrinos can be distinguished fromother signals by either their \double bang" or \lollipop" topologies. These topologies are diagrammed in g. 31. Preliminary studies of the lollipop topology have only just begun, so wewill focus on the double bang topology in what follows. Double bang events are those in which

A

B

Figure 31: The \double bang" (A) and \lollipop" (B) signatures which tau neutrino interactions cancreate. These signatures are also discussed in section 5.6.1.

the production and decay of a  lepton can be identi ed [118]. Figure 32 shows a simulated CC double bang event in IceCube.
We have calculated the probability of detecting a double bang event in a neutrino telescopeof linear dimension D = 1 km such as IceCube. We have developed a very simple Monte Carlofor this purpose in which the detector is considered as one dimensional. We have taken theenergy threshold for detecting showers to be Eshower  1 TeV. We have conservatively xed to
250 m the minimum distance the  has to travel to clearly distinguish the Cerenkov
light fromboth showers. This number is determined by the separation between strings which is 125 m.
(In principle this number could go much lower if other double bang topologies are considered.)
Our Monte Carlo accounts for the uctuations in the fraction of energy transferred to the  inthe interaction, as well as for the uctuations in its range. The result of the Monte Carlo isshown in g. 33 along with the probability of observing a  -induced muon. Also shown is the68Figure 32: A double-bang  event with an energy of a few PeV in IceCube. Colored circles represent
hit channels, with red circles hit earliest and violet circles latest. Circle size corresponds to number ofdetected photons.

69

probability of observing a double bang event as obtained in [119] using the expression:

Z 1 EEminP (E; Emin ) = NAdy [D R ]d CC (E; y )
;
dy

(3)

where  is the density of the medium and NA is Avogadro's number. Emin is the minimum
energy of the  , it is automatically xed imposing that R  250 m. This expression uses
average values for R and hence at E  Emin the probability of observing a double bangvanishes since the average range of the  is smaller than 250 m. The probability calculatedwith this expression has a broad maximum which is determined by the condition that R hasto be larger than 250 m but smaller than the size of the detector. Assuming an average value ofy  0:25 at these energies and using eq. 2 this corresponds to E between roughly 7 PeV and
27 PeV.

Figure 33: Probability of detecting  induced double bang events in IceCube obtained with Monte

Carlo simulation and using the analytic expression given by of [119] (Eq.2). The probability is shown forR = 100 m and 250 m. Also shown is the probability of detecting a  -induced muon.

70Due to uctuations in R , even  's with energy below Emin are going to produce  's thattravel more than 250 m. This explains why our probability doesn't vanish at E < Emin as
happens to the one given by eq. (3). It also has a longer tail at high energies because uctuationsin the  range and in its energy prevent a fraction of high energy  's from producing a  thattravels a distance larger than the dimension of the detector.

5.5.1 Tau Neutrino Event Rates
We calculate the number of  events in the standard way [93], convoluting the probability ofobserving the double bang events with the  +  ux:Nevents = AeZ + (E )P ! double bang (E )dE(4)where we will take Ae = 1 km2 . P ! double bang is the probability of observing a double bang
event as shown in g. 33.
By far the largest uncertainty in this expression is the  +  ux. Tau neutrino production
is expected to be very small in most astrophysical scenarios where  's are produced in pp or
p collisions. Several calculations suggest a ratio [119] F =  10 5 . Oscillation scenarios
in which  's convert themselves into  's may be the most promising sources of  's. Making
the assumption that F = = 0:5 we obtain the number of events in table 10 for representative + uxes in the literature. In g. 34 we also show the energy distribution of the events. They
all resemble the shape of the probability function of g. 33. For more details and references, seereference [83].
It is important to note that with neutrino oscillations a generic cosmic accelerator which
produces neutrinos in the ux ratio e :  :  :: 1 : 2 : 0 will result in neutrinos in the ux ratioof 1 : 1 : 1 at the detection point. With a 1 : 1 : 1 ratio the numbers of double bang events intable 10 would grow by a factor of two.

5.5.2 Tau Neutrino Simulations
Although tau neutrinos are clearly a promising analysis to pursue, at present no IceCube simulations of tau neutrinos have been run, due to lack of time and manpower. Many of the simulation
tools used for muons and cascades are applicable, so it is anticipated that this de cit will be
remedied in the near future.

5.6 Neutrino Flavor Di erentiation with Waveform Digitization
Waveform digitization will provide a wealth of information which undoubtedly will lead to
improvements in many aspects of event reconstruction. Since work in this area has only justbegun, this section presents a qualitative picture of what can be achieved with waveforms, witha focus on neutrino avor di erentiation. The signatures produced by electron, muon and tau
neutrinos are as follows:71

Table 10: Double bang events per km2 per year in 2 stereoradian for representative  +  uxes in

the literature assuming F = = 0:5. Attenuation has been taken into account to calculate  events
but not for  events. The GRB event rate takes into account uctuations in distance, gamma factor
and energy of the GRB's normalizing to 1000 GRB's/year. The TD's models correspond to maximal
predictions of g.2 in reference [103]. The neutrino ux from the decay of Superheavy Relics is takenfrom reference [104]. The numbers of double bang events grow by a factor of two if one takes into accountrecent neutrino oscillation results and uses instead F = = 1.
Flux
10 6 E 2 (cm2 s sr) 1
GRB (Fluctuation model)
TD, MX = 1014 GeV, Q0 = 6:31  10 35 , p=0
TD, MX = 1014 GeV, Q0 = 6:31  10 35 , p=1
TD, MX = 1014 GeV, Q0 = 6:31  10 35 , p=2
TD, MX = 1015 GeV, Q0 = 1:77  10 34 , p=0
TD, MX = 1015 GeV, Q0 = 1:58  10 34 , p=1
TD, MX = 1015 GeV, Q0 = 1:12  10 34 , p=2
Superheavy Relics MX = 1014 GeV

Double Bang events  +  (upgoing) events
6
10,7791
43
146
58,6656  10 2
12
1:5  10 2
3120
48,605
5:5  10 2
9
1:1  10 22
3  10 2
4  10 4

Figure 34: Di erential  induced double bang event rates for di erent uxes assuming F = = 0:5.

The upper lines at 107 GeV for the Topological Defect models correspond to MX = 1014 GeV and thelower ones to MX = 1015 GeV.

72

 Charged current electron neutrino interactions and neutral current neutrino interactions

produce an electromagnetic and/or hadronic shower at the point of interaction. The
cascade generated in this reaction will, depending on energy, extend from a few to morethan 10 m, a scale small compared to the spacings of IceCube strings. Therefore, cascades
will be treated as pointlike events in what follows. As seen in g. 24, cascades produce acharacteristic spherical pattern.

 Charged current muon neutrino interactions produce an initial hadronic shower, which

may or may not be detected, and a muon. At energies exceeding roughly 500 GeV, themuon loses substantial amounts of energy stochastically in radiative processes.

 Tau events can have the characteristic \double bang" signature, which originates from theproduction and then decay of a tau particle. The rst shower comes from the charged
current interaction of the  with a nucleon. The products of this interaction are a tau
lepton and a hadronic shower. The dissipation of the energy in the hadronic shower
produces the rst \bang."
The second shower happens when the tau travels a short distance and then decays into a
tau neutrino. This reaction also causes a hadronic shower. The dissipation of this shower
is what produces the second \bang." This energy range at which these event signatures
are generated are from a few PeV to a few tens of PeV.
Alternatively, tau events can have the characteristic \lollipop" signature, which is created
when the rst bang described above is not detected but the tau lepton and the secondbang caused by its decay are. These events can be distinguished from muons by the lower
level of light produced by the heavier tau lepton in ight.

The energy regimes best-suited to the detection of each neutrino avor are illustrated in g. 35.
Figure 36 shows the average photoelectron density observed at an OM as a function of the
distance of closest approach of the muon track. Stochastic energy losses have been excluded
from the calculation. As expected, the closer the muon is to an OM, the more photoelectrons
the OM sees.
Figure 37 shows the photoelectron density as a function of the distance between an OM andthe high energy cascade vertex. In this case, the shower has inital energy of 1 PeV. Again, thecloser the shower occurs to an OM, the more photoelectrons that module will see. At distances
greater than 150 m, the photon ux drops by about one order of magnitude every 60 m.

5.6.1 Photon Flux Distribution Generated by High Energy Cascades
In this section we discuss the spatial photon ux density distribution as generated by highenergy cascades. The light pro le of electromagnatic and hadronic cascades can be assumed tobe identical as shown by [105]. Simulations in this report are based on electromagnetic cascades.
Hadronic cascades di er only in the absolute light output, which is roughly 20% lower than forelectromagnetic cascades. The simulations include the orientation of the optical sensor. The
73

ντ
νµ
νe

νe
6

9
12 15 18
log(Energy/eV)

21

Figure 35: Energy regimes best-suited to the detection of each neutrino avor.

74

Figure 36: Average photoelectron density observed at an OM as a function of the distance of closest
approach of the muon track. Stochastic energy losses are excluded. The number of photoelectrons isbased on the Cerenkov
radiation of the relativistic charged particle in the medium ice.

75

photoelectrons

1 PeV Shower
10

7

10 6
10 5
10 4
10 3
10 2
10
1
0

50

100

150

Distance Profile

200

250
m

Figure 37: Average photoelectron density as a function of the distance from the vertex of an electromagnetic cascade of 1 PeV energy.

76

Figure 38: Integrated number of photoelectrons over a 2.5 s period from a 1 PeV cascade as seen by
downward facing OMs.

quantum eÆciency is assumed to be 20% and the diameter of the PMT 25 cm. The spectral
sensitivity is based on the Hamamatsu datasheet. The glass transmission of the pressure housing
is based on the instrument housings manufactured by Benthos Co. which are currently in use
by AMANDA.
In the following we focus on the integrated number of photoelectrons observed by an opticalsensor in 2.5 s of recording time. The time window of 2.5 s is long enough to integrate over thefull length of the expected pulses for cascades in the energy range discussed in this document (upto 100 PeV). (N.B.: The integrated number of photoelectrons scales linearly with the cascadeenergy.)Figure 38 shows the spatial distribution of the integrated number of photoelectrons overa 2.5 s time period. The light emission generated by the 1 PeV cascade is assumed to becylindrically symmetric. Therefore we can project the density pro le in a two dimensional graph,using cylindrical coordinates (rho, zet). In this and the following gures the light emission occurs
at the origin (0,0). The shower itself is assumed to be pointlike. The direction of the shower
points to the right (positive z). Thus the density is peaked in the forward direction. However,
due to scattering of photons in the ice, the light is eventually distributed in all directions. On
a scale of 400 m by 800 m as shown in the gure, which is very large compared to the e ective
scattering length of the ice (24 m) the emission becomes approximately spherical.
One can see that the symmetry of the light distribution is shifted in the forward direction
by about one scattering length. The OMs are pointing downward in this simuation. A grid of
OMs has been marked in the gure with a horizontal spacing of 125 m and a vertical spacing of
17 m, corresponding to the IceCube baseline design.
Figure 39 shows the maximum number of photoelectrons to strike a downward-facing OM
77

Figure 39: Expected peak photocathode current or the maximum number of photoelectrons/ns from a
1 PeV cascade as seen by downward facing OMs.

78

per 10 ns bin for a 1 PeV shower. This gure can be used to derive the regions in which the
PMT will saturate. For events relevant for IceCube the saturation depends primarily on thephotocathode current. The gure gives the peak cathode current (in photoelectrons and ns). A
dynamic range of 150 pe/ns can be used.
Figures 40, 41 and 42 show how pulse shapes increase with distance from the OM for a
100 TeV, 1 PeV and 100 PeV cascade. Therefore the peak amplitude (max pe) drops lessstrongly than the integrated number of photoelectrons. As these plots clearly show, waveforms
will provide us with richly detailed information from which quantities such as cascade energy
and direction can be estimated. IceCube OMs will be linear up to at least 150 pe per 10 ns bin,which means that a 100 TeV (1 PeV) cascade can be recorded linearly from distances as close
as 30 m (50 m).

5.6.2  Event Signatures
Tau neutrinos can produce distinctive \double bang" and \lollipop" signatures in IceCube,as described earlier in section 5.5. Waveform information is particularly well matched to theextraction of these signatures. Although detailed reconstruction algorithms have not yet been
written, the following gures should make it clear that suÆciently energetic tau neutrinos canin principle be reconstructed and extracted from IceCube data.
Figure 43 shows the integrated number of photoelectrons from a double bang tau event of
about 10 PeV primary energy as seen by downward facing OMs. The decay length of the tau
lepton was 225 m. Figure 44 depicts the leading edge times of pulses from a tau lollipop event.
Note how the incoming tau leaves a small but clearly distinguishable set of early pulses prior toits decay in to a large cascade. Figure 45 shows the pulse shapes as a function of time generated
at various OMs for a double bang 10 PeV tau event. Note the distinctive double-peaked structure
in OMs at z = 125 m from the rst vertex: the rst peak is from the interaction of the  ; thesecond from the tau lepton decay. Figure 46 shows a tau event where the decay length of thetau was 300 m. At this distance, no single OM receives signi cant pulses from the two cascades,
but timing measurements still show quite clearly that two distinct cascades were detected. Notethat in gs. 43-46 the tau was generated travelling horizontally. That makes this analysis aconservative one because the horizontal orientation is the least favorable one for reconstructing
such events.

5.6.3 Summary
The studies of individual events gives insight in the variety of pulse shapes that are expected in
IceCube. The waveforms depend strongly on the following parameters: Energy: The integral of a given pulse shape depends strictly linearly on the energy of agiven event.

 Distance: The width of the pulse shape increases in an unambiguous way as a function of

position and orientation of the sensor with respect to the event. The distance of the event
79Figure 40: Pulse shapes generated by a 100 TeV cascade as observed by optical sensors in the positions
marked in g. 38. The amplitudes are given in photoelectrons per 10 ns interval, as seen by a 100 Msps
waveform digitizer.

80Figure 41: Pulse shapes generated by a 1 PeV cascade as observed by optical sensors in the positions
marked in g. 38. The amplitudes are given in photoelectrons per 10 ns interval, as seen by a 100 Msps
waveform digitizer.

81Figure 42: Pulse shapes generated by a 100 PeV cascade as observed by optical sensors in the positions

marked in g. 38. The amplitudes are given in photoelectrons per 10 ns interval, as seen by a 100 Msps
waveform digitizer. The pulses on strings 3 and 4 exceed the dynamic range of the photomultiplier. Onlyat larger distances there will be many sensors that are outside the region of saturation.

82

Figure 43: Top: Integrated number of photoelectrons from a tau event of about 10 PeV primary energy
as seen by downward facing OMs. Bottom: Same, but for upward facing OMs. The energy of the tau
was about 10 PeV and its decay length was 225 m.

83

Figure 44: Leading edge times of pulses from a tau \lollipop" event of about 10 PeV primary energy

as seen by downward facing OMs. The times are color-coded and shown as a function of  versus z .
Note that the earliest times (in yellow, cyan and green) are due to the minimum ionizing tau, and theremaining hits in the event at later times are due to the cascade from the tau decay.

84

Figure 45: Pulse shapes generated by a tau event of about 10 PeV primary energy, similar to that ing. 43. The amplitudes are given in photoelectrons per 10 ns interval. The tau decay length was 225 m.

85

Figure 46: Pulse shapes generated by a tau event of about 10 PeV primary energy, similar to that ing. 45, but the decay length of the tau lepton was 300 m. At this decay length, single OMs do not havedouble peaked pulse shapes as at 225 m, but it is still clear from the timing pro les that two cascades
occurred in the detector.

86

is the dominant parameter to determine the width of the pulse.

 Lepton avor: Muon tracks generated by , cascades as generated by e or neutral cur-rent interaction, and nally  interactions generated di erent waveforms. the complex
waveforms that can occur  event suggest that the waveform can play a substantial rolein the particle identi cation.

 Orientation: The pulse shape depends to some extent on the orientation of a cascade.
Reconstruction methods that exploit this rich information are yet to be developed. However,based on the above simulations, we conclude that the characteristics of the pulse shapes show astrong correlation with fundamental physical parameters. It should therefore be a goal to record
the pulse shapes with a precision suÆcient to extract the important features.
It should be noted that the sampling depth of 4 s can be exceeded in very rare cases(e.g., time pro les of tau events). Also, the dynamic range of existing large area PMTs will be
exceeded if either the energy of the event is very high or the PMT is very close to the event.
An increased dynamic range remains desirable. However, one should keep in mind that thedetection volume at larger distances from the event is very large in these cases. For example, incase of 100 PeV energy cascades or higher, the PMTs will be saturated up to distances of morethan 200 m. However there remains a very large shell of detector volume where hundreds of
PMT will sample waveforms. This will compensate to a large extent the limited signal quality
at closer distances.

5.7 Lower Energy Phenomena and Exotica
5.7.1 Muon Neutrinos from WIMP annihilation
If Weakly Interacting Massive Particles (WIMPs) make up the dark matter of the universe, theywould also populate the galactic halo of our own Galaxy. They would get captured by the Earthor the Sun where they would annihilate pairwise, producing high-energy muon neutrinos thatcan be searched for by neutrino telescopes. A favorite WIMP candidate is the lightest neutralino
which arises in the Minimal Supersymmetric Model (MSSM).
The typical energy of the neutrino-induced muons would be of the order of  25% of theneutralino mass. Since the muon threshold for IceCube is expected to be fairly high ( 100 GeV),
we expect IceCube to be sensitive mainly to neutralinos heavier than about 400 GeV.
In [121] the performance of IceCube was studied for two con gurations, a 9 string  9 string
pattern with 125 m string spacing and a detector consisting of eight sub-modules of 10 strings
each, with string spacing of 70 { 90 m within the sub-detectors (see g. 47).
The e ective area for WIMP detection depends on the WIMP mass as well as on the typicaldecay channel (\soft" channels from WIMP decays into many secondaries, \hard" channels fromdecays into a few secondaries only). Figure 48 shows e ective volumes and e ective areas for therectangular pattern (\standard" geometry, left) and the modular pattern (right), separately forneutrinos from the Sun and the center of the Earth, and for soft and hard spectra, respectively.
87

y (meters)y (meters)

600

Standard IceCube geometry

400

600
400

200

200

0

0

-200

-200

-400

-400

-600

-600

-400

-200

0

200

400

-600

600

IceCube geometry with submodules

-600

-400

-200

x (meters)

0

200

400

600

x (meters)

Figure 47: Con gurations studied in [121]882Aeff (m )2

Aeff (m )The standard geometry gives about 0.7 square kilometer area for both solar and terrestrial
WIMPs, provided the decay channels are preferentially hard. For soft channels, the area drops
down to less than 200 000 m2 for WIMP masses of 200 GeV. Compared to the standard geometry,the modular geometry gives somewhat worse results for hard decay channels and slightly better
results for soft channels.

10 6

10 5

10 6

10 5

Earth hard
Earth soft
Sun hard
Sun soft

10 4Standard IceCube geometryβ < 5 degrees
10 3
10

10

2

3

10
10
Neutralino mass (GeV)

Earth hard
Earth soft
Sun hard
Sun soft

10 4Modular IceCube geometryβ < 5 degrees
10 3
10

4

10

2

3

10
10
Neutralino mass (GeV)

4

Figure 48: E ective area after a 10-degree cut on the angle between the reconstructed muon and theangle of the source, for di erent annihilation places, annihilation channels and WIMP masses. Results
for the standard geometry to the left and for the modular geometry to the right.

Figure 49 shows the predicted muon rates from WIMPs annihilating in the Earth and the
Sun as a function of the WIMP mass. Shown are results for the standard con guration withsimple quality cuts after reconstruction. Each symbol in the plot corresponds to one particular
combination of MSSM parameters (with the WIMP mass being one of them). Lines indicate
the limits which could be achieved with IceCube after 5 years observation. Di erent symbols
mark MSSM versions which are currently ruled out by direct detection experiments, which could
be seen by direct detection experiments if the sensitivity is increased by a factor of ten, andwhich could not be seen by present direct detection experiments even after tenfold increase insensitivity, respectively. All values are normalized to 10 GeV threshold for reasons of comparison6 . It has been shown in [121] that IceCube could play a complementary role to future direct
detection experiments (like CRESST or GENIUS) for annihilation in the Earth, and even has
6

For certain directions the IceCube energy threshold indeed might be reduced below 20 GeV. If the track of thesecondary muon is close to the vertical and close to an individual string (say less than 7 m), PMT amplitudes
will be high, scattering e ects will be small, and consequently arrival time jitters will be small. Under these
conditions not only the muon energy can be determined with an accuracy of a few GeV from its track length,
but also the vertex cascade may be identi ed and its energy determined. Taken all strings together, one obtains
a detection volume of 10 Megatons at a threshold of 20 GeV.

89

a slight advantage over direct detection experiments for certain low-mass WIMP models andannihilation in the Sun.

5.7.2 Neutrino oscillations
With a 10 Megaton detector of 20 GeV threshold, IceCube may also play a role in con rming
the compelling indications that atmospheric neutrinos oscillate. Studies of systematics andbackgrounds have revealed that signi cant progress requires much smaller spacing of OMs alonga string than presently planned (namely 4-6 meters). For reduction of the threshold toward thehorizon also a considerably smaller string spacing would be necessary. Such specialized e ort
is only warranted if ongoing experiments fail to conclusively prove the oscillation hypothesis.
In that case one would consider to create a densely equipped region for detection of low-energy
contained events as one part of IceCube. This region would be nested in the full array whichacts as veto against through-going tracks. A possible solution would be to ll AMANDA-II
with additional strings with small OM spacing. Note that interpretation of the feeble angulardependent oscillation e ects at high neutrino energies require an extremely good understandingof the detector systematics.
In recent papers [122], the possibility is discussed to direct a neutrino beam to IceCube either a WBB beam or a beam from a neutrino factory. The short duty time of an accelerator
would allow to relax the cuts for background suppression since during the short spill times thedetector is nearly free of background. The aim would be to measure mixing angle 13 and thesign of m231, even though it is not possible to discriminate between charges. However, it has has
to be investigated how well discrimination between muon tracks and ccascades at low energies
would work.

5.7.3 MeV Neutrinos from Supernovae
Although the MeV-level energies of supernova neutrinos are far below the AMANDA/IceCube
trigger threshold, a supernova could be detected by observing higher counting rates of individual
PMTs over a time window of 5-10 s. The enhancement in rate of one PMT will be buried
in dark noise signals of that PMT. However, summing the signals from all PMTs over 10 s,
signi cant excesses can be observed. With background rates more than 10 times lower than
ocean experiments, AMANDA and IceCube have the potential to see a supernova and to generate
an alarm signal.
IceCube, with low-potassium glass spheres (40 K decays in the glass sphere are the main
source of external noise), might barely reach the the Large Magellanic Cloud.
AMANDA is oÆcially, and will actively be in the near future, a member of the Supernova
Early Warning System (SNEWS) [154]. The role of AMANDA will be to yield one of several
coincident alarm signals from di erent detectors like Super-K, LVD and SNO (Macro being shut
down in the mean time). On top of that, IceCube might participate in the goal to estimate thesupernova direction by triangulation [153].
Figure 50 shows the increase in counting rate as seen in AMANDA-II and IceCube. Given
90

-3

-1

Muon rate from the Earth (km yr )

10 7

th

E µ = 10 GeV
Standard IceCube Geometry

10 6
10 5
10 4
10 3
10 2

Soft

10

Hard

1
10
10
10
10

-1
-2

lim
σSI > σSI
lim
lim
σSI
> σSI > 0.1σSI
lim
0.1σSI
> σSI

-3
-4

-3

-1

Muon rate from the Sun (km yr )

10

10

2

3

10
10
Neutralino Mass (GeV)

10 7

th

10 6

Soft

10 5

Hard

10

4

E µ = 10 GeV
Standard IceCube Geometry

4

10 3
10 2
10
1
10
10
10
10

-1
-2

lim
σSI > σSI
lim
lim
σSI
> σSI > 0.1σSI
lim
0.1σSI
> σSI

-3
-4

10

10

2

3

10
10
Neutralino Mass (GeV)

4

Figure 49: The predicted muon rates from WIMPs annihilating in the Earth (left) and the Sun (right)

as a function of the WIMP mass. Each symbol in the plot corresponds to one particular combinationof MSSM parameters. Lines indicate the limits which could be achieved with IceCube after 5 years
observation. Di erent symbols mark MSSM versions which are currently ruled out by direct detection
experiments (dots), which can be seen by direct detection experiments if the sensitivity is increased by afactor of ten (+), and which could not be seen by present direct detection experiments even after tenfold
increase in sensitivity (), respectively.

91

a known template for time evolution of the pulse, the resulting accuracy in timing could be
14 ms for AMANDA-II and as good as 1-3 ms for IceCube. The resulting angular resolution
depends on the orientation of the triangulation grid with respect to the supernova. For thethree detectors Super-K, SNO and IceCube it would between typical values of 5 to 20 degrees.
Figure 51 shows the 2 -contours of reconstructed supernova direction for a randomly choosen
supernova event.
With dedicated detectors like Super-K, one can determine the neutrino direction from electron direction measurement in  e interaction with an accuracy of about 5Æ .

Figure 50: Simulated count rate data for a supernova at the center of the Galaxy, for AMANDA-II (left)
and IceCube (right). The lines correspond to the simulation input.

5.7.4 Relativistic magnetic monopoles
Several theories predict the existence of magnetic monopoles with a magnetic charge which
obeys the Dirac quantization rule g = n  e=(2 ) with n = 1; 2; 3; ::: and = 1=137. A magnetic
monopole with unit magnetic Dirac charge g = 137=2  e and a velocity close to 1 would emitCerenkovradiation along its path, exceeding that of a bare relativistic muon by a factor of
8300 for = 1. The value 8300 is obtained from (137=2)2 multiplied with n2r , with nr = 1:33
being the refractive index of water. This is a rather unique signature. Figure 52 shows the lightemission from a monopole as a function of . Note that due to the production of Æ electrons,the monopole produces light even below its own Cerenkov
threshold.
92

Figure 51: 2 -contours of reconstructed supernova direction for a randomly choosen supernova event.
It was assumed, that timing data from a detector at the South Pole are combined with data fromSuperKamiokande and SNO. In the left gure, a time resolution of 14 ms (AMANDA-II) was assumed,in the right gure, a time resolution of 3 ms (IceCube). The nominal supernova direction was cos  = 0:1,
 = 2:98. Note the twofold ambiguity which even for IceCube necessarily remains if only three sites
contribute.

93

10
10

6

monopoleδ5dn / dx , cm

-1

10

7

10
10
10
10

4

3

2

1

bare
muon
0

10
0.4

0.6

0.8

1.0

β

Figure 52: C erenkov light emission from magnetic monopoles in water (in photons per cm) as a functionof velocity. The curve labeled \Æ" represents the light produced by delta electrons which are generated
by the monopole below its Cerenkov
threshold.

94

Any early Universe phase transition occuring after in ation has the potential to populate theUniverse with a ux of magnetic monopoles. Observations of galactic magnetic elds, as well as
observations matched with models for extragalactical eld lead to the conlcusion that monopolesof masses below 1015 GeV can be accelerated in these elds to relativistic velocities [147]. Figure 53 summarizes the limits obtained until now. Note that these limits are below the so-called
Parker bound (1015 cm 2 s 1 sr 1 ). This bound is is derived from the very existence of galacticmagnetic elds which would be destroyed by a too high ux of magnetic monopoles.
A cube kilometer detector could improve the sensitivity of this search by about two ordersof magnitude compared to the present AMANDA limit. As mentioned above, the search could
be extended to down to velocities  0:5 by detecting the Æ electrons generated along themonopole path.

upper limit (cm-2 s-1 sr-1 )10 -14

Soudan
KGF

10 -15

10 -16

10 -17

Baikal

MACRO
Orito
Amanda

δe

lect

rons
IceCube10 -18
0.5

0.75

1.00

β =v/cFigure 53: Limits on the ux of relativistic monopoles achievable with IceCube compared to existing
limits.

5.7.5 Slowly moving, bright particles
The passage of a particle with a velocity signi cantly below c yields a very distinct time pattern.
Candidates for particles with a velocity < 0:1 c and with strong light emission are GUT
magnetic monopoles or nuclearities [120, 148]. GUT monopoles may induce protons decays.

Therefore one would expect Cerenkov
light signals generated by the nucleon decay products
along the path of the monopoles. For certain regions of the parameter space in monopole velocity
and catalysis cross section, these signals would cause sequential hits in individual PMTs withintime windows of 10 5 { 10 3 s.
Nuclearities (strange quark matter) should be aggregates of u, d and s quarks in equal
proportions, and of electrons, to ensure their electrical neutrality. They should be stable for95

all baryon numbers in the range between ordinary nuclei and neutron stars (A  1057 ). They
could have been produced in the primordial Universe or in violent astrophysical processes. Seefor recent reviews [148, 149].
The most relevant upper limits on the ux of these particles come from track etch experiments
or liquid scintillator experiments (both e.g. represented by MACRO). The Baikal experimenthas searched for enhanced counting rates over time intervals of 500 s and deduced upper limits
on the ux of GUT monopoles and strange quark matter [120]. The search technique relies on
detectors with a low counting rate. In the Baikal case a rate as low as 100 Hz is achieved by
local coincidences. With a counting rate per OM of 300 Hz (compared to typically 1 kHz for
AMANDA), also IceCube may look for corresponding phenomena.

5.8 IceCube Con guration Flexibility
The default IceCube con guration is optimized for the TeV{PeV neutrino energy region. In the
scenario where a potential signal is seen at PeV energies or above, but the IceCube array has not
yet been fully deployed, the IceCube design permits considerable exibility. String deployments
can be modi ed to increase subsequent interstring spacings, expanding the geometrical area
at little added nancial expense. Since muons at these energies are brighter, one crossing thearray would experience no \blind" corridors. Of course, performance at lower energies would
su er with increasing interstring spacing. Conversely, if a signal is detected at the lower end of
the TeV{PeV energy scale, the detector can be \back lled" using as-yet-undeployed DOMs toincrease the overall pixel density. This would enhance sensitivity to lower energy neutrinos.

5.9 Calibration of High-Level Detector Response Variables
Detector geometry, angular response, vertex resolution and energy response can be calibratedusing in situ light sources, IceTop-tagged or untagged downgoing cosmic-ray muons, and atmospheric neutrinos. Examples of in situ light sources include blue and UV LEDs, lasers buried in
the ice or placed on the surface and connected via optical ber to di using elements placed in
the ice, buried DC light sources, etc. Lower-level parameters like cable lengths will be calibrated
online by the DAQ system and can be veri ed by adapting some of the techniques described
below.

5.9.1 Geometry Calibration
IceCube simulations indicate that downgoing muons can be used to determine the relative positions of the OMs to an accuracy of less than 1 m, which is suÆcient for accurate reconstruction ofneutrino-induced muons and cascades. The algorithm entails using tted downgoing cosmic-ray
muon tracks and calculating the probability for a photon from the track to arrive at each of anumber of imaginary spatial grid points surrounding the putative OM position. Averaging overmany tracks, each set of grid points around each OM describes a paraboloid whose maximum
can be used to estimate the true OM position. Using these new position estimates for each OM
we can then repeat the entire procedure until the iterative procedure converges.
96

2

OM 700

1.5
1

OM Displaced in Y by 1.5 m

Y Shift [m]

0.5
0
-0.5
-1
-1.5
-2
0

1

2

3

4
5
Iteration

6

7

8

9

Figure 54: Calculated correct position of a single OM. The OM was intentionally displaced from its true
position by 1.5 m The procedure demonstrates that convergence occurs in three iterations.

97

2

8.278

10
Entries1∆X (m)

Constant
Mean
Sigma

0

/ 11
8.994
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0.2568

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680

700

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2

7.148

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/ 11
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2∆Y (m)OM Channel

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680

700

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740

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∆Z (m)OM Channel

Figure 55: Left plots: Intentional displacements of OMs (straight lines), all applied at the same time,

and their calibrated positions (dots connected by lines). Right plots: Calibrated OM positions relative
to original correct values. The left plots demonstrate that the calibration procedure can cope with string
displacements which are larger than what the IceCube drill is designed to deliver. The right plots showthat the resolution of the calibration is roughly 30 cm. The o set in Z is believed to be an artifact of
inaccuracies in the Monte Carlo parameterization of the photon arrival times.

98Tests using simulated data have shown that the procedure converges quickly enough that it
can be used to determine geometry positions of OMs almost immediately after deployment. A
plot showing the convergence of the procedure for a single OM, whose position was intentionallydisplaced from its correct position by 1.5 m, is shown in g. 54. Figure 55 shows how well theprocedure calibrates the correct OM positions after intentional three-dimensional displacementsof a string's position. This procedure will be a useful high-level test of the success of the
deployment at the full-string level, and will permit the running of subsequent calibrations which
require detector geometry as input. More computationally intensive re nements of the technique
can be used to ne-tune the positions for use by the online lters and downstream data analyses.
(Bright in situ light sources may also be useful for geometry calibrations, and indeed this is how
the AMANDA geometry has been calibrated. However, IceCube's larger interstring spacing may
limit the e ectiveness of this techinque.)

5.9.2 Calibration of Angular Response
Events simultaneously triggering IceTop and IceCube constitute a data sample which can beused to calibrate IceCube's angular response. A similar technique has been used successfully
by AMANDA with SPASE-2 triggers, where only a limited solid angle was available for study.
With substantially larger solid angle coverage, IceTop should enable IceCube to calibrate its
angular response more completely and accurately.
Over a smaller solid angle, IceTop can provide a tagged single muon beam for calibration of
IceCube response to single muons and their direction reconstruction. This will require a denser
subarray component, either in the center or perhaps also at one or more other locations on thesurface, that triggers at a much lower threshold for showers with energies of roughly 10 TeV
that are most likely to have only zero or one high energy muon capable of reaching IceCube.

5.9.3 Calibration of Vertex Resolution
The vertex resolution for cascades can be studied with pulsed in situ light sources located at
known positions in the ice. Varying the intensity of these sources provides a way to study
the vertex resolution as a function of energy. In AMANDA, sources have been determined to
produce light outputs equivalent to a cascade event with several hundred TeV of energy.

5.9.4 Energy Calibration
The IceCube energy response can be calibrated using a number of independent techniques.
Atmospheric neutrinos provide a test-beam with a known energy spectrum against which IceCube can be calibrated. Downgoing muons may also be of use here, although often such eventsare composed of mulitple muons. (This may be addressed by IceTop, as discussed below.)
Bremsstrahlung events from downgoing muons provide an energy calibration for cascades at thelower end of the energy scale, up to several hundred GeV. In situ light sources, preferably with
precisely controllable output intensities, o er a way to calibrate IceCube energy response tocascades at higher energies, up to roughly 500 TeV.
99

5.10 IceTop
The solid surface above IceCube allows the possibility of a surface air shower array that can beused for calibration (by providing a set of tagged muon bundles), for veto of certain backgrounds
generated by large air showers and for cosmic-ray studies. A square kilometer array of suitably
designed detectors on a 125 m grid has full eÆciency for air showers from 1015 eV to 1018 eV.
Thus it covers an important energy range from below the knee of the primary spectrum to anenergy where we may expect at least the beginning of a transition from galactic cosmic-rays tocosmic-rays of extragalactic origin.

5.10.1 Tagged Muon Bundles

Figure 56 summarizes the characteristics of IceTop events in IceCube. Bundles range from  10
muons at the top of IceCube from 1015 eV protons to  104 muons in the core of a shower
generated by an iron nucleus of 1018 eV. Most of the muons are concentrated in a core withtypical size less than the spacing between IceCube strings, and about half the muons in thebundle range out inside IceCube. The high energy events contain muons with suÆcient energy
to produce bursts of radiation in IceCube. There will be about 100 tagged air showers per daywith multi-TeV muons in IceCube. Since a muon that goes through IceCube deposits about
200 GeV or more of energy, one sees from the diagram that there will be of order ten thousand
tagged events per year in IceCube in which more than 100 TeV of energy is deposited by themuons. The ability to identify and measure such coincident events readily is a unique feature ofa deep neutrino detector under a solid overburden.
The surface detectors are modelled on the water Cerenkov
tanks pioneered by the Haverah
Park air shower experiment [89] and currently used in the Auger detector now under constructionin Argentina [155]. At the South Pole the water freezes, but the Cerenkov
light generated byrelativistic charged particles is essentially the same as in water. This has been veri ed by asmall test tank deployed inside the current South Pole Air Shower Experiment (SPASE) [156]during the 00/01 Antarctic season. Design and layout of the tanks is described in 6.9.
We have adapted Auger tank simulation tools and used them to simulate IceTop tanks inorder to simulate waveforms expected in showers with energies in the PeV{EeV energy range.
Figure 57 shows a sample IceTop waveform generated in this manner.
Most of the showers that trigger the detector will be near the threshold energy of approximately 200 TeV. Air showers with this energy typically contain 1 to 10 muons with suÆcientenergy to reach the deep detectors within a radius of 20-30 m of the shower trajectory. A fractionof these events will be used for calibration of the angular response and reconstruction algorithmsof IceCube, as mentioned above.

5.10.2 IceTop as a Veto
In addition to providing a sample of events for calibration and for study of air-shower-induced
backgrounds in IceCube, the surface array will act as a partial veto. All events generated byshowers with E > 1015 eV can be vetoed when the shower passes through the surface array. In
100Energy spectra of muon bundles in IceCube
10

4Nµ(>Eµ)per shower with E0

E0=10
10

3

10

2

101

1016

Rate per yr

1015
Burst regime

14

50

0

10-1

10

eV

1017

10
10

18

5000

Top
Bottomof IceCube

5

5*10

7

-2

10-3

10

5*10

>109

-4

10-1

100
101
Eµ (TeV at production)

102

Figure 56: Diagram showing the energy spectra of muon bundles in IceCube associated with air showers(proton primaries) that can be measured with IceTop. Each curve is labelled at the left by the primaryenergy of the associated shower and on the right by the number of events per logarithmic energy intervalthat strike the surface array within the solid angle determined by IceTop and IceCube. The surface
array is fully eÆcient for showers above 1015 eV. The arrows indicate muon energy at production in theatmosphere needed to reach the top and the bottom of IceCube. Muons above  3 TeV will tend to
produce bursts of radiation in IceCube.

101

Figure 57: The upper panel shows the waveform of the signal at 300 m from the shower core for a

proton-initiated shower of 100 PeV. The simulation is for an 8 in PMT at the center of the tank viewing
photons re ected from the bottom and sides of the ice tank. The lining of the cover is black. The
marks at the top of the gure indicate the arrival time at the top of the ice of muons (top set of marks),
electrons (middle set of marks) and -rays (bottom set of marks). The lower panel shows the the muon
contribution to the waveform. In both panels the amplitude is plotted as a function of time at the outputof the base of the PMT. Most of the delay is due to the drift time of electrons in the PMT.

102

addition, higher energy events, which are a potential source of background for neutrino-induced
cascades, can be vetoed even by showers passing a long distance outside the array. In particular,
showers with E > 1017 eV and cores a km outside the array will produce a minimal trigger near
the boundary of the array.

5.10.3 Cosmic-ray Physics
The IceCube-IceTop coincidence data will cover the energy range from below the knee of thecosmic-ray spectrum to > 1018 eV. Each event will contain a measure of the shower size at
the surface and a signal from the deep detector produced by muons with E > 300 GeV atproduction. At the high elevation of the South Pole, showers will be observed near maximum
so that shower size will give a relatively good measure of primary energy. The ratio of themuon-induced signal in IceCube as a function of primary energy (as determined by shower sizeat the surface) will give a new measure of primary composition over three orders of magnitude
in energy. In particular, if the knee is due to a steepening of the rigidity spectrum, a steepeningof the spectrum of protons around 3  1015 eV should be followed by a break in the spectrumof iron at 8  1016 eV.

103

6

Experimental Requirements

In this section we discuss the requirements on IceCube technologies dictated by science. The
most important requirements can be summarized as follows: time resolution of  5 ns rms,

 waveform digitization with  200 Msps ( rst 400 ns) and  33 Msps (thereafter), waveform sampling depth of 4 s, dynamic range of  200 PE/15 ns,
 dead time of  1%,
 gain variation of  2% per week, OM noise rate  500 Hz, overall permanent channel failure rate of < 5%.

While extensive simulations of the IceCube detector and its performance have been done,
ongoing studies of improved analysis techniques using the operating AMANDA-II detector may
still suggest changes in these requirements.

6.1 Time Resolution
From operation and Monte Carlo simulations of the AMANDA detector we have learned thatevent rates and angular resolution of atmospheric neutrinos, as well as the eÆciency for rejecting
the background of atmospheric muons, do not depend on the accuracy of time calibration (t0 )and on time resolution (t ) provided they do not exceed 10 ns. Deterioration of the detector
performance becomes apparent only above 15 ns because below this scale scattering in the bulk
ice is the dominant e ect. For the higher energy PeV{EeV neutrino signals in IceCube, therequirement may even be looser because the average distances over which photons are collected
are increased and so are the e ects of scattering. For electromagnetic showers, waveform digitization will be important, but a timing accuracy similar to the one required for muon tracks
should be adequate.
A resolution of  5 ns is a well-motivated requirement. Better resolution results in better
performance in rare cases. For instance, science requiring low thresholds, or the detection ofshort muon tracks very close to strings, may bene t from better time resolution because thee ect of scattering is suppressed. Examples are the detection of neutrinos from the annihilationof dark matter particles in the center of the Earth (producing short, nearly vertical muons) andthe detection of oscillating beams from an accelerator at a northern site. One may also be able
to argue for improved time resolution on the basis of better reconstruction of the direction ofelectromagnetic showers induced by electron-neutrinos, or to separate close showers from theproduction and decay of tau-neutrinos (double bang events). One should keep in mind that time
resolution is ultimately limited by the PMT at 1{2 ns for multi-PE signals.
1046.2 Waveforms
Experience with the AMANDA detector for observing electromagnetic showers and high-energy
showering muons has demonstrated the signi cant advantages of using the presently available\reduced" waveform information, like amplitude and time-over-threshold (TOT) rather thanamplitude alone. Light scattering results in strong signal dispersion over large distances. Thise ect dilutes information (namely the precise arrival time of the rst photon), but also adds
information: The length of the light signal recorded by a single PMT indicates the distance to thelight source. Therefore the combination of amplitude and time structure allows one to distinguishbetween close, dim light sources and distant, bright light sources. The reconstruction of distant
tracks and very large high energy showers will therefore require full waveform digitization. For
instance, simulations based on TOT alone have demonstrated very poor angular resolution forelectromagnetic showers.
Waveforms should be recorded at a rate of  200 Msps for the rst 400 ns in order to obtain
good timing and double pulse resolution. For longer times, a lower sampling rate of  33 Msps
is suÆcient to tease out structure due to secondary light pulses such as those due to double
bangs from  events.
The waveform sampling depth should be roughly 4 s, long enough to capture full waveform
information from most (but not all) double bang events.

6.3 Dynamic Range and Linearity
The basic requirement is a dynamic range of 200 PEs per 15 ns. The interval 15 ns represents
the typical time duration of a single PE pulse. This requirement is mostly driven by the reconstruction of energy and direction of very high-energy showers, typically 1 PeV. These produce
measurable light over times of several hundreds of nsec. The amplitude and the waveform of
the light pulses at the OM carry information on the position, the directionality and the energyof the shower. Figure 58 shows AMANDA-II PMT pulses from an in situ N2 laser pulse witha light output equivalent to a 1 PeV shower. The oscilloscope pulses shown are from OMs atthree distances between 45 and 167 m.
Because of scattering of the photons in the ice, the shape of the photon pulse broadens withincreasing distance from the point of emission. For example, at a distance of 60 m (about half
the string spacing in IceCube) a 1 PeV shower will generate a PMT pulse of 1000 (200) PEs
with a FWHM of 100 ns (150 ns) in forward (backward) direction of the shower. The example
illustrates the directionality information contained in these data. Such an event will be observedby hundreds of OMs up to distances of more than 250 m from the interaction. The maximum
current in this event reaches 12 PE/ns, or 180 PE/15 ns. Because of the greatly enhanced crosssection at 6.4 PeV (Glashow resonance), events at this energy may be preferentially observed,
despite a falling spectrum. For these events, the peak input signal is more than 1000 PE/15 ns(at a distance of 60 m).
The non-spherical shape of the initial light pattern can be exploited for good directionaland energy reconstruction. While the number of PMTs that saturate increases with higher
105

Figure 58: PMT signals from a 335 nm nitrogen laser signal simulating a 1 PeV shower (about 101 0
photons). The light is detected by AMANDA-II optical modules with ber-optic readout at distances ofapproximately 45 m (black trace), 115 m (red trace), and 167 m (cyan trace).

106

energies (10 PeV and higher), the total number of PMT that observe a signal grows by aneven larger number. Based on evaluations of simulated waveforms, we conclude that a dynamic
range of about 15 PE/ns would be suÆcient for an accurate reconstruction of the relevant event
parameters (energy, direction), even though OMs nearest the shower will saturate.
PMTs that are very close to the shower core will saturate at the maximum anode current
that a PMT is able to sustain. In the case of the Hamamatsu 10 in PMT, which is a prime
candidate for IceCube, the anode current is limited to 80 mA, which sets an upper limit on the
dynamic range in PE that depends on the gain. The operating conditions of IceCube suggest
a gain of  107 , corresponding to a theoretical peak of 500 PE/15 ns. It seems reasonable toexpect that the PMT can sustain anode currents of 200 PE per 15 ns for intervals of about100{200 ns. Recognizing the limitations on the dynamic range set by the PMT, and accepting
a saturation of the 10% of the OMs near the shower core, we set the physics requirement for the
dynamic range to 200 PE/15 nsec.

6.4 Absolute Amplitude Calibration and Stability
The absolute calibration of OMs should be known to better than 5%. The absolute calibrationand measurement of the angular acceptance of the instrument will be performed by observing
known signals from LEDs and from cosmic ray muon tracks. The measurement of shower pro lesrequires good calibration of individual OMs; see above. The dependence of the muon e ective
area of the operating AMANDA-B10 detector is close to, but less than linear.

6.5 Dead time
We aim for a deadtime for muon triggers as low as 1%, assuming a trigger rate of 100 Hz.
Actually, one might consider to lower certain thresholds of the hardware triggers, e.g. in order
to cover low energy tracks. This might increase the trigger rate and nally lead to a slightly
higher deadtime.

6.6 Sensitivity of optical modules
Maximum light collection is of highest importance. In particular, it helps to lower the detection
threshold for low energy muons and increases the detection sensitivity for supernovae. For highenergy muons or cascades, it might allow for an increase in the string spacing. Compared to
Amanda-II, the light collection will be improved by the use of PMTs with diameter 10 in or larger,
giving about 40% better light collection than the present 8 in PMTs. If a sound technologicalsolution is found, wavelength shifter coatings should be applied to the glass spheres. Present
results indicate that this may result in a 20{35% better light conversion.

6.7 Noise Rate and Noise Rate Stability
Ice is a very low noise medium; the noise is dominated by radioactivity introduced by the OM
itself. The noise rate in individual OMs is required to be less than 0.5 kHz (compared to typically107

1 kHz in the present AMANDA array). For that aim, glass spheres with very low radioactivity
content (< 0:05% potassium content) should be chosen. Rates for all OMs should be recorded
for optimal sensitivity and detector monitoring.
For the muon trigger, this level of noise is readily eliminated by the use of local coincidences(a pair of OMs that are adjacent or separated by no more than one OM report).
Supernova detection is based on the identi cation of rate excesses over a few seconds. It
is made possible by the low noise rates and becomes impossible if the rates are as high as
2 kHz. With 300 Hz noise rates, IceCube could monitor not only our own Galaxy, but also the
Magellanic cloud.
Rates have to be recorded every ms with 10 bit dynamic range, with the possibility to adjust
arti cial dead time between 0 and 1 ms in 10s steps.

6.8 Failure Rate
IceCube Monte Carlo studies have shown that the quality of muon and cascade reconstructions
are rather resilient to permanent channel failure rates as high as 10%. (A permanent channel
failure is one which cannot be repaired, e.g., a broken in-ice connector.) For muons, only thedi erence between the true and reconstructed space angle shows some degradation, but only byroughly 3%; for cascades there is essentially no degradation at all. These results can be extended
qualitatively to tau events as well.
The main impact of such failures would be to reduce the detector sensitivity. This reduction
is energy-dependent and is more pronounced at lower energies. For example, a 10% failure rate
results in the loss at trigger level of 40% of muons with energies between 400 and 500 GeV, but
only 5% of muons with energies between 8 and 10 TeV. Above about 30 TeV there is no loss. A
10% loss would therefore not dramatically a ect ultrahigh energy muon neutrino physics, but
it would adversely impact IceCube atmospheric muon neutrino physics, and the usefulness ofthese neutrinos as an IceCube calibration tool.
Under the reasonable assumption that sensitivity loss varies roughly linearly with the permanent failure rate, requiring the permanent channel failure rate to be below 5% reduces theimpact of such losses on atmospheric muon neutrino physics. At the same time, a 5% failure
rate is a realistic goal.

6.9 IceTop
The IceTop array should trigger at near the 90% level for air showers above 500 TeV, which
will require stations of roughly 7 m2 area located near the top of each string. The tanks shouldhave a dynamic range of  104 to cover the PeV{EeV energy range without saturation over thefull lateral extent of the showers. This will likely require using separate low gain and high gain
modules within each tank.
To reduce the background rate each station should consist of two tanks, each roughly 3.5 m2
in area. A local coincidence should be implemented between neighboring tanks to eliminate
single muon events as well as reduce the likelihood of triggering on random electron and photon
108hits not associated with larger air showers. The separation of these individual tanks should belarge enough to keep the number of local triggers to a level that can be handled by the DOM
communications, perhaps several meters.
A denser subarray within IceTop should consist of smaller tanks on the order of 1 m2 area
separated by 10 m so that they will have a much lower threshold near 10 TeV to trigger on
showers most likely to contain only one high energy muon. This subarray could be composedof the present SPASE array with an embedded standard IceTop station. The subarray should
record only a fraction of the data that triggers depending on what is needed for calibration andmost acceptable for the DAQ.
In addition, it is possible that we will decide to record as much of this low energy data as
DOM communications will allow, storing several days of data in a disk cache at the Pole. Thiscache should be accessed when interesting IceCube events come in over that same time, when
all low energy surface array data from a wide time window on each side of the interesting eventsshould be separated out and stored for later investigations.

109

7

Design and Description of IceCube

7.1 Overview
In the IceCube baseline design, 80 strings are regularly spaced by 125 m over an area of approximately one square kilometer, with OMs at depths of 1.4 to 2.4 km below the surface, as
shown in g. 59. In sections 5 and 6 the performance criteria and experimental requirements
for this device have been distilled from the scienti c goals. In addition to explicit technicalrequirements, however, the instrumental design concept must incorporate many additional factors such as system cost, software/hardware integration issues, engineering risks, lowest practicalpower dissipation, noise rejection, noise generation, thermal and physical shock, data ow, MeanTime Before Failure (MTBF) of components, production Quality Assurance (QA), deployment,
constraints on commissioning personnel, remote intervention capabilities, calibration, cost ofoperations, as well as disparate factors such as safety and educational values. The process of
optimization involving all these disparate issues has led to an innovative approach, with many
attractive features. Nevertheless, no exotic, high speed, brute force, or unproven elements areneeded in this concept.
There are three fundamental elements in this architecture, common to both IceCube and
IceTop: The Digital Optical Module (DOM), which captures the signals induced by physicalprocesses and preserves the information quality through immediate conversion to a digitalformat using an innovative ASIC, the Analog Transient Waveform Digitizer (ATWD); A Network, which connects the highly dispersed array of optical modules to the surface
data acquisition system (DAQ) and provides power to them;

 A Surface DAQ, which maintains a master clock time-base and provides all messaging,data ow, ltering, monitoring, calibration, and control functions. Many design features
have been realized in the AMANDA string 18, as discussed below.

The instrument design is based on a decentralized digital architecture [157]. The motivation
for this approach arises primarily from the need to acquire, from a km-scale instrument, quite
complex information in the presence of substantial backgrounds.
Roughly 1.5 kHz of downgoing cosmic ray muons penetrate the geometric volume of IceCube,
about six orders of magnitude more than muons induced by neutrinos. The Cerenkov
radiation
cones generate complex optical signals that are further complicated by scattering in the ice
before detection. Parent directionality is not uniquely determined by simple time di erences {a horizontal muon generates equal quantities of upgoing and downgoing light. In most cases,
neutrino-induced upgoing muons are distinguishable from backgrounds only with sophisticatedts using global space-time correlations.
Given the high background/signal ratio and event complexity, it would be imprudent to lterout the atmospheric muons with tight trigger logic at an early stage. In addition, the downgoing
muons o er an ever-present and copious calibration source, as well as a potential arena for the110

AMANDA-II

RunwayIceCube

South
Pole

SPASE

Figure 59: A top view of the IceCube detector, showing the locations of the 80 IceCube strings as wellas the AMANDA-II array, the SPASE array, the airplane runway and the South Pole.

111

detection of subtle astrophysical processes, or possibly even signatures of extreme energy release
events in the cosmos.
As noted in section 5, data and simulations show that, for both neutrino-induced and background events, the information content at the photomultiplier (PMT) ranges from single photons
arriving over a span of about 1 s to many hundreds (even thousands) of photons arriving within
15 ns. Extremely high-energy events may generate many thousands of photoelectrons in a continuum of complex patterns lasting several microseconds.
Figure 60 shows a fairly typical raw waveform obtained from a DOM operated in coincidence
mode to capture signals induced by a down-going muon. In this gure, the rst photon to be
detected appears in the ATWD record at about sample 20. Somewhat later, a larger numberof detected photons appears, possibly the result of a shower process at some distance from thedirect path of Cerenkov
light, or possibly the result of multiple muons passing nearby. Froma study of these waveforms it is clear that the arriving signals are frequently complex, in therange of 15% for muon-induced signals. Because of the optical scattering, all photons must be
included in the analysis to determine the nature of the event.
A measure of the parent muon neutrino energy comes primarily from the capability to record
very large energy losses producing electromagnetic showers along a muon trajectory. For electron
neutrinos, the showers occur in isolation, requiring for identi cation that no muon trajectoryis present. Tau neutrinos at extreme energies can produce two showers separated by a shortdistance. The earlier parts of the shower-induced waveforms vary most rapidly and reach thehighest amplitudes. The most useful information about shower direction is found here, imposing
challenging technical requirements.
Time measurement of these signals over the km-scale volume must be established and maintained with a resolution and accuracy of 5 ns. The capture of this highly variable complex
information requires high-speed (200 Msps), high dynamic range (14 bits) waveform recording. These technically challenging desiderata provide the impetus for an innovative instrument
design.
The architecture makes use of modern ideas that rely on time-stamps applied very early toeach datum. This approach reduces the amount of real-time circuitry to a remarkably small level
relative to traditional DAQ concepts. Correspondingly, data ow is built on conventional networking techniques using messages that may contain either data or control content. Advantagesof the architecture based on the DOM include: High dynamic range and signal purity since PMT signals are captured and digitizedin proximity and isolation.

 Low system power consumption due to an innovative custom ASIC, the Analog Transient Waveform Digitizer (ATWD).

 Fully automated remote commissioning and calibration procedures, minimizing

South Pole personnel, an extremely important consideration during South Pole modernization .
112

Figure 60: An observed waveform due to muon(s) passing near a DOM pair, operated in coincidence.
113 No low-level analog signal processing in the counting house o ers more predictablelarge-scale system behavior.

 Absence of optical bers in the system reduces system cost substantially, eliminates 
30 plane ights, simpli es and shortens deployment procedures, and maximizes reliability
since all connectivity is carried by copper wire pairs.

 Minimal real-time circuitry within the DAQ, made possible by time-stamped data
and message-based architecture.

 Network-based DAQ organization requires only one custom hardware design (theDOM Hub).

 Use of commercial o -the-shelf components reduces costs, shortens development
time, and enhances test facility realization.

 Year-round regular operation provided by robustness against noise at surface due todrilling and pole operations, even during commissioning of new strings.

 Operational exibility is provided by programmable logic and CPU located within
DOM, permitting changes stimulated by data or new ideas.

The discussion of the Instrument Design elaborated below will bene t from a brief descriptionof the performance obtained with a string of 41 Digital Optical Module (DOM) prototypes
deployed in January 2000 by the AMANDA Collaboration. These DOMs were intended to serve
two purposes:
1. Contribute to the regular AMANDA data stream by delivering real-time analog PMT
signals via optical bers to the AMANDA counting room. Because these signals appear
identical to the signals of other strings, string 18 contributes to the scienti c goals of
AMANDA without compromise.
2. Demonstrate the advantages and feasibility of a purely digital technical approach, in which
PMT signals are captured and digitized locally, within the optical module. The digital
data were transmitted to the surface using the twisted pair copper conductors that also
bring power and control signals to the DOMs.
Both of these purposes were achieved, despite challenging schedule and nancial constraints.
The DOM prototypes of AMANDA string 18 were designed, built, and deployed in about 14
months, and strong support throughout the collaboration during this period was essential for theultimate success of the e ort. Because schedule pressures were so severe, little attention could
be given to the issues of reliability and QA. Nevertheless, most of the DOMs of string 18 havedelivered extremely stable performance throughout the nearly two year period of operation. One
DOM board seems to have developed an internal problem; PMT HV can still be set so that thismodule continues to contribute to AMANDA data. Two PMT HV bases appear to have failed,114

indicating that re-engineering to enhance QA for this subsystem may be needed. There appears
to be an intermittent electrical connection in the main cable for another DOM. The remainderof the 41 DOMs have operated continuously with no glitches, crashes, or other indications of
instability.
During CY 2000, the DOMs were equipped with a simple surface DAQ that could control
PMT HV, set other operating parameters, and return housekeeping data and occasional waveforms to the surface. In January 2001, a subset of four DOMs was equipped with a more complete
surface DAQ based on single-channel Test-Boards, designed initially for commissioning of DOM
boards. With the four-channel Test-Board DAQ, time synchronization is possible, permitting
data from di erent DOMs to be correlated to a few nanoseconds, and even demonstrating thedetection of downgoing muons. Most of the technical results described in this section come froman analysis of data obtained with the Test-Board DAQ.
The successful operation of AMANDA string 18 has proven not only the feasibility of thedigital system architecture, it has also shown that the associated software is both straightforward
to design and stable in operation. Much of the software framework that has enabled thesetechnical results will serve as a springboard for subsequent IceCube e orts.
The block diagram of the Test-Board DAQ is shown in gure 61. For reference, the various
approaches used by AMANDA are described in section 7.5.

7.2 Digital Optical Module
The Digital Optical Module (DOM) is a self-contained data acquisition platform that is
capable of capturing and digitizing real-time PMT pulses, storing data internally, and, whenrequested, transmitting them to a surface data acquisition (DAQ) system. It contains its own
processor, memory, ash le system, and real-time operating system (RTOS). The DOM iscapable of scheduling background communications tasks while acquiring data from a local waveform digitizer. All calibration functions needed to interpret data for physical content may be
invoked under software control; some operate as scheduled tasks without interfering with dataacquisition, and others require dedicated control of state.
A Field-Programmable Gate Array (FPGA) is used to implement most low-level logical functions of the DOM, facilitating fully programmable and exible implementation of performancefeatures. The FPGA is programmed automatically from a con guration le that the CPU retrieves from ash memory in the DOM after power-up and self-boot has occurred. The FPGA
design and CPU programs can be replaced at will subsequent to deployment to enhance functionality. This capability has been exploited already in the AMANDA string 18 (DOMs only),using the satellite link to the south pole from the northern hemisphere.
The basic elements of the DOM are the optical sensor for Cerenkov
light, an electronic
circuit board for processing signals, a HV generator for the optical sensor, an optical beacon for
calibration purposes, and the glass pressure housing. The general physical layout of a generic
DOM is shown in g. 62.

115

Test DAQ Board Layout
Main Components Diagram
Deployed for Time Calibrations, 2001.

T.B.1

10 MHzPLL(3 Other Test Boards)(3 Other Test Boards)

PLL

GPS

T.B.2

PLL
(T.B.1)

16.8 MHz

PLL
T.B.3
33.6 MHz

8b

FPGA

PLL
T.B.4
16.8 MHz Clock Signals
to Multiple Components

TB Power
SupplyTwistedPair(to DOM)High Pass Filter
Low Pass Filter

80 V
DOM
Power
Supply5b

PLDCommunications

ADC

Controller
CPU

Communications

DAC(Single−Board
Linux
Computer)Communications

Disc.
PC−104
Relay
SwitchDAC

Figure 61: Block diagram of the \Test-Board" used in the AMANDA DOM string DAQ system.
116

Electrical Cable

PMT HV Power Supply PCB

PMT Anode signal cable

Pulse Xfmr

LED Flasher PCB

DOM PCBgel
8.0"

Photocathode

Photocathode

Schematic view of OM with Digital and Optical Analog Capability

Figure 62: Schematic pro le view of a generic Digital Optical Module, showing pressure sphere, optical

coupling gel, PMT, signal processing electronics board, LED asher board, PMT base, and electricalpenetrator.

117

7.2.1 Pressure Housing
The spherical glass pressure housings are standard, well-proven items of commerce, used innumerous oceanographic and maritime applications. For IceCube, the most important qualities
are mechanical reliability, cost, optical transmission, and potassium content. Commonly known
in the US as Benthospheres, a trade-name of Benthos, Inc., the dominant US supplier, these
simple devices have an excellent record for reliability. Over 700 of these, from both Billings
and Benthos, in various implementations and sizes, have been deployed in AMANDA without
evidence of a single implosive failure. To ensure reliability against implosion, care must be taken
not to chip either the surfaces of the hemispherical rims that form the equatorial ground-glassseal, or the holes that permit penetrators to carry signals and power across the boundary. Costs
for standard pressure-tested Benthospheres are modest, in the range of $350.
For IceCube, a 13 in diameter sphere is the optimum size. While larger spheres are available
that could a accommodate larger optical sensor, the costs for drilling larger diameter holes (withan appropriate margin of safety during deployment) rise very quickly, making larger sizes a poor
overall trade-o .
Because the Cerenkov
radiation mechanism produces the greatest intensity at ever-smaller
wavelengths, limited ultimately by self-absorption, it is of interest to push the optical transmission limit of the glass to a value below the quantum eÆciency limit of the PMT. For processing
and mechanical strength, the manufacturers use a borosilicate glass that limits transmission toabout 350 nm, well above the expected 220 nm limit for deep polar ice. It is conceivable thatan exterior surface layer of an appropriate wavelength shifter for the component shorter than
350 nm could increase the e ective light yield, and this is being explored.
The potassium content of the typical borosilicate glass includes a naturally occurring fractionof 40 K. The particle from the decay of this isotope produces Cerenkov
radiation at a level that
dominates the observed PMT noise rate, unless steps are taken to reduce the overall potassium
content of the glass. At the request of IceCube collaborators, manufacturers have been able toproduce glass with substantially lowered potassium content without compromise to important
processing, mechanical, or optical qualities. It is anticipated that IceCube optical modules will
display noise rates very close to those of isolated dark-adapted PMTs.

7.2.2 Optical Sensor

The optical sensor is a medium-size (10 inch diameter) hemispherical 10-stage photomultiplier tube (PMT), made by Hamamatsu. PMTs very similar to the intended device have been
deployed within AMANDA with generally excellent experience. These large PMTs o er surprisingly good time-resolution, as indicated by a transit-time-spread (TTS) for single photo-electron(SPE) pulses of about 2.5 ns rms. Despite their large photocathode area, these PMTs, in total
equilibrated darkness, generate only 300 Hz or less of spontaneous noise pulses at temperaturesless than 0Æ . Photocathode sensitivity extends well into the UV, limited by the optical transmission of the glass pressure sphere at 350 nm. For each detected photon, the PMT produces
SPE pulses that have characteristic rise (fall) times of 7 (11) ns.
118

Due to the stochastic nature of the electron multiplication process, SPE pulses display signi cant variations in pulse shape and amplitude. The measured pulse area distribution of DOM#1 (the deepest), acquired over a period of 10 days, is shown in g. 63. The histogram isformed by adding together consecutive ATWD samples for the pulses that rise above a digital
threshold, and subtracting a measured pedestal. This simple method works well enough if thediscriminator threshold that launches the ATWD is suÆciently low that nearly all SPE pulses
result in a trigger. It should be noted that a fair fraction of the PMTs in string 18 do not havesuch good peak to valley ratios, and the spectrum shown in g. 63 is better than most.

SPE Spectrum

Figure 63: Measured pulse area distribution of DOM #1 measured over a period of 10 days in CY 2001.

Most of the histogram is SPE noise pulses. The stochastic nature of the electron ampli cation processleads to a very broad distribution such that some SPE signals fall below threshold.

To de ne a measure of gain, the peak region of spectra such as that shown in g. 63 are119

t to a simple a Gaussian form. From the t parameters, an average gain can be extracted.
Repeated measurements taken over 180 days in CY 2000 have demonstrated that the combined
PMT + DOM signal processing electronics provide excellent gain stability. These results areshown in g. 64. Because PMT gains were set to optimize the optical signal paths, which
had wide variations, and because some PMTs displayed poor peak-to-valley ratios, high quality
ts could be obtained for less than half of the deployed ensemble of DOMs. The mean ofthe distribution,  2:8% per year corresponds to drifts of 0.05% per week, far below theexperimental requirement of 2% per week; none of this subset comes close to 2% per week.

Gain Drifts DOMs Percentage/Yr from ATWD

Figure 64: Measured distribution of a subset of DOM gains, recorded over a period of 250 days in CY
2000. The mean in this ensemble is less than 3% per year, with none approaching the experimental
requirement of 2%/week.

At a gain of 107 , a typical SPE pulse will have an amplitude of 8 mV into a 50
120

load.

Under these conditions, the signal displays some nonlinearity at around 2 V, reaching complete
saturation at 4 V. The e ective dynamic range under these conditions is approximately 500 PE.
The PMT maximum output current at the anode is limited by space charge e ects in the dynode
chain. As signal size increases, the space charge e ects appear rst at the last dynode, then at
the next to last, and so forth. Not only does the pulse amplitude display a non-linear relationshipto the input photon signal, but the pulse shape begins to stretch out considerably. The e ective
dynamic range may, in principle, be increased by lowering the PMT gain below 107 . At somepoint in the range of a few millivolts, intrinsic electronic noise will degrade performance at theSPE level.
With careful circuit design and layout, however, ultimate performance may exceed 500 PE
signi cantly. It seems feasible to utilize a dynode tap to obtain a signal that could extend the
dynamic range at least another order of magnitude beyond what can be practically achieved
from the anode signal. This general idea has been used in many past experiments, and should
be practical for IceCube. This possibility is being explored actively.

7.2.3 PMT HV Generator
The PMT HV generator, known familiarly as the PMT base, is a multi-stage voltage multiplier,or Cockroft-Walton circuit, with an oscillator running at a few tens of kHz. The base mustmeet a number of important requirements, in particular, high reliability, high stability and low
induced noise. A voltage multiplier has certain potential advantages since the voltage steps
are smaller than that of a single stage multiplier. If arranged correctly, the base will naturally
supply the most current to the dynode stages near the anode, where the pulse loading occurs.
This produces an attractive low power design. On the other hand, there are more parts, which
could a ect MTBF.
The IceCube PMT base will have two separate sections. One section, supplying the potential
di erence between the photocathode and the rst dynode, will be xed at a voltage near the
manufacturer's indicated maximum. This produces a uniform transit-time among the DOMs,
and produces the best peak-to-valley ratio for the SPE pulse-height spectrum. The second
section will be variable under software control, to obtain the desired 1  107 gain. Experience
with AMANDA string 18 shows that reliability is an issue, as two bases appear to have failed. All
HV designs involving semiconductors must be based on conservative design practices, since evenextremely rare discharge mechanisms can be fatal. Induced noise also appears to be present,
at least in the timing measurements, which give better results with the PMT HV o . The
re-engineering of the PMT base to improve reliability is recognized as an important task.

7.2.4 Optical Beacon
The string 18 DOMs are each equipped with six GaN LEDs, which emit predominantly in thenear-UV at 380 nm. The luminous intensity and the pulsing rate may be varied over a wide
range under software control. At their brightest, these beacons can be seen by OMs 200 m
distant. Due to their high intrinsic capacitance, LEDs are not easy to pulse at ns speeds; the121pulse width is 5 ns. The LEDs are broad angular emitters, spaced at 60Æ around a vertical axis,
and are canted over to produce a roughly hemispherical source. Some AMANDA analog OMs
have been equipped with similar optical beacon boards using GaN LEDs emitting at 450 nm;
these have also proved to be useful for test purposes. The PMT HV must be turned down at
the emitting DOM to avoid potentially harmful pulses.
The optical beacons can be used to knit together a highly over-constrained measure of relative
DOM positions within the array. They can also be used to study optical properties of the ice atthese wavelengths.

7.2.5 Signal Processing Circuitry
The block diagram of the DOM signal processing circuitry is shown in g. 65. The principal
logical and functional elements are:

 State control; Waveform capture and digitization;
 Local time generation;
 Local/master clock time transformation;
 Cable length measurement for timing o sets; Data ow;
 Local coincidence capability; Control and glue logic, provided by an FPGA; A low-power 32-bit ARM CPU for higher level operations; Power conversion and ltering; Monitoring and calibration;
 Message handling - send/receive .
State Control The DOM is operated as a slave in a master/slave relationship with the surface

DAQ. Upon power-up, it enters a wait state for an interval of a few seconds, to permit downloading of new rmware or software. If no messages are received before time-out, the DOM willboot from Flash memory and await commands. Normal operation of the DOM is dominated bya data-taking state.
In addition, a local-time calibration process is periodically invoked, so that the local DOM
time may be ultimately transformed to master clock time with nanosecond accuracy. The time
calibration process appears as separately scheduled thread, with no deleterious impact upon
122

Digital Optical Module
Main Components Diagram
First Prototype, Deployed 2000.

Toyocom
Oscillator(16.8 MHz)

Boot
Flash

PLL
(frequency
doubling)

Application
Flash

Digital Clock Signals
to Multiple Components

FAST
ADC

10b

Lookback

SRAM

CPU

SRAM
8b

ATWD

CPU

Delay Line

10b

SPE/MPE

Boot ROM

FPGA

Disc.

8b

DAC
Anode, First Dynode

PLD

PMT
Base
TwistedPair(to Surface)Communications

ADC
DAC

High Pass Filter
Low Pass Filter

Communications

DAC
Flashers

Power
SupplyCommunications

Disc.
DAC

Figure 65: Block diagram of the digital optical module signal processing circuitry.

123

the data-taking state. Other active threads are message receive/send and data transmission,
also invisible to the data-taking process. There are several calibration modes, such as running
optical beacons, cable length measurement, etc., during which normal data-taking is presumably
inactive.

Information Capture The DOM is equipped with innovative circuitry that is well-matchedto the PMT pulse characteristics and dynamic range. The capture of waveforms with 300 MHz
14 bit resolution is a daunting technical challenge if only conventional ash ADCs are considered.
Power dissipation for the ensemble of FADCs would be several watts, imposing an undesirable
operating condition; noise due to the large amount of digital activity and data ow presents aninhospitable engineering environment. Instead, the DOM concept takes advantage of the fact
that, most of the time, nothing is happening: t between pulses is more than 106 ns. Circuit
activity need occur only when pulses appear.
The waveform capture capability is realized through a custom Application Speci c Integrated Circuit (ASIC) designed at Lawrence Berkeley National Laboratory (LBNL), the Analog
Transient Waveform Digitizer (ATWD). The ATWD has four channels, each with 128 samples,that synchronously record di erent input waveforms. For IceCube, three of the channels willcapture the PMT signal presented at three di erent gain settings. This arrangement provides anelegant multi-range linear PMT signal capture method. With three channels operating at 15,
3, and 0.5 gains, the ATWD provides the rough equivalent of a 14 bit 200{800 MHz ADC.
Due to schedule pressures, the DOM prototypes in string 18 were equipped with only 10 and2 gain channels. The third channel was, instead, routed to an analog multiplexer that could
connect to various internal signals for diagnostic purposes.
The fourth ATWD channel in string 18 DOMs is permanently connected to the DOM internal
clock, to calibrate/monitor ATWD sampling speed. Experience with string 18 has shown that
the ATWD sample speed is extremely stable. In IceCube, the fourth channel will be connected
to an analog multiplexer to permit that channel to share more than one function. The ATWD
sampling speed needs to be calibrated and monitored, but only rarely after initial calibrations
are completed and the system is stable. As noted above, some other internal signals that havediagnostic value also need only infrequent interrogation. Most of the time, 99.9%, the fourthchannel is available to capture a dynode tap signal that could increase the PMT signal e ective
dynamic range by at least another order of magnitude. The goal is to reach at least 5000 PE,
a capability that will enhance the reconstruction of EHE events, should they occur within thevolume of IceCube.
The capture process is initiated by a \launch" signal derived from a discriminator connectedto the high-gain signal path. The capture process stores waveforms as analog voltages on fourinternal linear capacitor arrays. The sampling action is generated by an active delay line within
the ATWD, with \look-ahead" to create a sampling gate of width suÆcient to obtain adequate
settling on a capacitor before the gate switch opens, e ectively closing that sampling window.
With the ATWD, waveform capture occurs at sampling speeds that may be varied at willfrom 200 Msps to more than 1 Gsps, corresponding to capture intervals of 640{128 ns. It
124appears that capture at 300 MHz (3.3 ns/sample) is appropriate for our scienti c goals. The
higher speed capture is useful for characterizing PMT signal shape and other diagnostic purposes,
but is not needed to extract timing information from a typical waveform. A single DC current
controls the sampling speed. All channels within an ATWD sample synchronously, with aperture
variations between channels measured to be less than 10 ps.
The ATWD performance combination of GHz sampling and very low power dissipation,
100 mW is unmatched by any single commercial device for transient waveform capture. The
sampling action is controlled by an active delay line internal to the ATWD. No ultra-high speed
logic/clocks are needed in the DOM, a highly desirable engineering situation. The maximum
frequency in the string 18 DOMs is the local clock frequency, a very comfortable 33.6 MHz. For
IceCube, this frequency may be higher, but will likely not exceed 40 MHz.
Two ATWDs, arranged with alternate selection logic, permit capture of longer waveforms,
and also serve to reduce dead-time. For waveforms exceeding the ATWD capture interval,
sampling at a lower frequency is suÆcient to capture relevant information at later times. For
this purpose, The DOM is equipped with a 10-bit low-power FADC, operating at the DOM local
clock frequency. The PMT signal in this path is reshaped to match the lower sampling rate.
The ATWD has two distinct functions{transient waveform capture, and digitization of captured signal. These two functions are separately controlled, so that a captured signal subsequently judged uninteresting may be ignored. This feature minimizes dead-time, and also
facilitates a true local coincidence capability (see sec. 7.2.9) between neighboring DOMs, inwhich only time- and space-associated signals are digitized. The immediate conversion to adigital format preserves data quality during subsequent DAQ data ow processes.
For interesting events, waveform capture in the ATWD is followed by 10-bit simultaneousconversion of all 128 samples/channel by an internal common-ramp Wilkinson ADC. The internal
scalers count on both positive and negative clock transitions. At 33.6 MHz, complete digitization
requires about 15 s. Because of natural CMOS manufacturing variations that create o sets in
the internal comparators, there exists uctuations in the baseline, or pedestal, of the captured
waveform. These pedestal variations are in the range of 5{15 counts; they are quite stable andare easily subtracted away during data processing.
A single ATWD digitizing waveforms at the nominal noise trigger rate of 300 Hz, will introduce deadtime of 0.5%. To this, an additional deadtime of about 0.1% must be included
for readout of data via a 10-bit parallel bus. With two ATWDs operating in ping-pong mode,
deadtime due to random noise hits is less than 1  10 4 .
The ATWD is currently designed for a 1.2 m CMOS process with double polysilicon capacitors. This manufacturing process may not be available inde nitely, as new CMOS processes
with ever-smaller feature size and other characteristics supplant older ones. The ATWD should
be updated by not only choosing an appropriate one of these processes, but by increasing sample
depth to perhaps 256 instead of 128, and adding new features such as a built-in DAC to reduce
ADC pedestal o sets to an insigni cant level. For IceCube, no aggressive design steps would becontemplated, only those for which substantial experience already exists in other ASICs.

125

Local Time Generation Each PMT hit must be time-stamped such that correlated hits

throughout IceCube meet the relative timing accuracy requirement of 5 ns rms. This is accomplished within the DOM using a two-stage method that produces a coarse time-stamp and ane time-stamp, both in local time units. Once data reach the surface, the local time units aretransformed to master clock units, and ultimately linked to GPS.
Although timing accuracy and resolution are in the few nanosecond range, no high-speed
clocks are needed anywhere in the system for the time measurement process. The current string
18 DOM design maintains a 54-bit local clock running at the DOM 33.6 MHz clock frequency.
The 33.6 MHz is obtained by frequency-doubling a free-running Toyocom 16.8 MHz quartz
oscillator. For IceCube, as noted earlier, the local clock frequency may be higher.
This oscillator product displays exceptionally stable behavior: measured drifts (Allan variance) taken in the laboratory are typically Æ t  0:06 ns/s, i.e. Æf=f  60  10 12 , as shownby the histogram of 46 of 49 tested oscillators in g. 66. The three oscillators not included in
the histogram were markedly worse, but still within the manufacturer's speci cations. A test
program will select the best 90{95% of the devices. Each point in the histogram represents theanalysis of 720 measurements taken consecutively over an hour (5 s intervals). The samples inthis histogram were taken after a stabilization period of a few days, as it is well known thatquartz oscillators will display asymptotically better stability after an initial run-in to shake odust, relieve strain, etc. This extraordinary stability obviates the need (and perhaps even thepractical possibility!) for a phase-locked loop connecting the local and master clocks. Such shortterm stability is only an order of magnitude or so worse than that of high quality commercial
rubidium stabilized clocks. The cost of the Toyocom oscillator is $25.
The coarse time-stamp process begins as a PMT signal triggers the discriminator. The
discriminator pulse is then resynchronized to the next DOM clock transition edge. The resynchronized pulse provides the ATWD \launch" signal. In other words, the synchronous launchingof the ATWD causes the PMT signal to arrive within a one-cycle wide region of the ATWD
capture window. The clock value at the instant of ATWD launch is recorded in an appropriate
FPGA register. The \coarse time-stamp" is de ned as the clock value recorded in this register.
At 33.6 MHz, this coarse time-stamp provides a time quantization  of 29.76 ns (at 40 MHz, is 25 ns). Because the register is loaded by the same signal that launches the ATWD, theconnection between coarse-time stamp and ATWD launch is robust.
Clearly, the coarse time-stamp does not provide the desired 5 ns resolution. However, theleading edge of the PMT signal waveform within the ATWD record will occur somewhere within
this particular 29.76 ns interval. The \ ne time-stamp" is de ned as the waveform position
within the ATWD record. The measure of the ne time-stamp must be extracted from the
ATWD record by an algorithmic method. A simple extrapolation to baseline of the waveform
leading edge can serve as the measure of the ne time-stamp, although more sophisticatedmethods can be easily envisaged. Even with the small SPE signals, the contribution to timing
resolution due to all electronic noise sources and digitization is expected to be less than 1 ns rms,
smaller than the PMT transit time jitter of 2.5 ns rms.
For all this to work, the PMT signal must be delayed suÆciently such that the leading edgeof the signal always appears well after the ATWD sampling action has begun. An overall delay
126

15Best analysis result 46 of 49

Counts

10

5

0
0

50

100

150

200

Allan Variance in parts per trillion
Toyocom Model 909F 15.36 MHz oscillators.
Each data point represents one hour (720 pt) test

Figure 66: Histogram of measured Allen variance for 46 Toyocom oscillators, measured at 5 s intervals
relative to a good frequency standard. Some of the outliers above 100 ppt later stabilized to fall within
the trend.

127

of about 75 ns is needed to accommodate both the coarse time-stamp  random delay and the
propagation delay of the circuitry. In string 18 DOM prototypes, a coil of coaxial cable (50 ft)
was employed for this purpose, an e ective but bulky solution. For IceCube DOMs, a lumped
delay line may be chosen. These provide adequate performance and o er an attractively compact
solution; of course, reliability of this device (as well as all other parts) at low temperatures must
be demonstrated.
Our observations con rm that standard commercial GPS clocks are subject to much larger
short-term drifts than the Toyocom devices themselves. Figure 67 shows measured drifts of
one DOM local clock (in the ice) showing a 3.5 ns short-term variance between measurements
taken at 2.6 s intervals relative to GPS. In comparison, the Toyocom oscillators displayed about
50 times better stability than this during laboratory measurements taken relative to a goodfrequency standard (a Stanford Research Systems Loran system). Clearly, standard commercial
rubidium clocks, which typically o er Æf=f 2 x 10 12 per 100 s, are a much superior choicefor the master clock. The link from master clock to GPS can be easily made once per second
with standard hardware and software.

7.2.6 Local/Global Time Transformation
All DOM data, recorded in association with the free-running local clocks, must be transformed to
IceCube master clock units in order to reconstruct events. Because drift is negligibly small overa period of seconds, a simple linear transformation between local and master time is suÆcient.
This could be performed within the DOM or, more likely, at the surface within the DAQ. In
either case, this transformation requires continuously updated knowledge of local clock frequency
and phase, relative to the master clock. Because the Toyocom oscillators are so stable, thelocal/master clock calibration process needs to be invoked only a few times/min per DOM.
Consequently, this vital function requires only a tiny fraction of the network bandwidth.
The master clock units are linked to GPS time once per second in the online DAQ topermit the connection of IceCube events with other detectors, and oine comparison withpotentially interesting astrophysical occurrences. Interpolation within the one second interval
is expected to be better than 1 ns rms. Synchronization of event time with other laboratory
detectors, terrestrial or non-terrestrial, will require detailed accounting of delays throughout theas-installed IceCube DAQ and master clock system. The ultimate accuracy for inter-laboratory
timing cannot now be speci ed but may reasonably be expected to fall in the range of 10 ns.
The calibration process involves a periodic transmission to a DOM by the surface DAQ of
a simple bipolar time-mark signal, perhaps 5 s between edges, synchronized precisely to themaster clock. These time-mark signals, however sharply de ned at the moment of generation,
experience degradation while propagating down the twisted pair cables due to dispersion andattenuation. Propagation over 2{3 km of cable results in rise-times of roughly 1.8{2.4 s. These
values depend somewhat on the de nition of rise-time, since the 1/t asymptotic approach isvery slow. The propagation of signals such as step functions over cables such as these is very
well understood. In most respects, they can be modeled as delay lines with 10:1 ratio fordelay/rise-time. This is schematically illustrated in gure 68.
128

Clock Drift
2.6 sec intervals,

over 15 minutes

3.4 ns, rms

1-Frequency Ratio(DOM/GPS)
Figure 67: Measurement of Toyocom/GPS frequency ratio at 2.6 second intervals for 15 minutes. The

3.4 ns rms is the product of the distribution sigma value times the measurement interval,
10

9 x 2.6 seconds dominated by short term drifts in the GPS unit.

129

i.e., 1.3 x

DOM Time-Synchronization Method
Surface
Front-EndElectronics

GPS (UTC)∆t (delay)

Freerunningoscillator

ADC

DOM

Figure 68: Transmission of a bipolar time-mark signal synchronized to the master clock by the surface
DAQ to the DOM provides the connection between local and master clock time.

130

The challenge is to exploit the very stable behavior of the cables and clocks to extract atiming measure with a relative accuracy not exceeding 5 ns. The term \relative" is essential,
since an o set due to method, common to all DOMs within the required resolution, is irrelevant.
The other essential conceptual element is a simple relationship between voltage noise during
measurement and time resolution:Æ t = ÆV=(dV=dt)(5)
The dV/dt of signals arriving at the DOM fall in the range of  106 V/s. If voltage measurement
noise is on the order of 1 mV, then timing resolution will be in the range of 1 ns. Clearly,
environmental noise can signi cantly degrade time resolution, and must be controlled for this towork well. In the laboratory, using a simple discriminator and lter, resolutions less than 1 ns
are easily achieved. However, this simple approach contains an undesirable aw due to random
errors in device thresholds, which may be several millivolts. According to the above equation,
shifts of several nanoseconds may occur among an ensemble of DOMs because of unknown
threshold o sets. The threshold o sets can in principle be measured by pulse injection, but
questions linger as to validity of method due to concerns such as the integrative behavior of thediscriminator coupling pulse rise-time and width to e ective threshold.
On the other hand, it is completely straightforward to employ a conventional FADC andmeasure the entire waveform of interest, including baseline just before the pulse arrives. Digitalo sets from one FADC to another become irrelevant. Most noise sources are very e ectively
suppressed because the baseline is measured just before the pulse appears. Defective or distorted
waveforms, for whatever reason, may be recognized and rejected. A 10-bit FADC running at
the local clock frequency samples the leading edge and the immediately preceding baseline, as
well as subsequent features such as the zero-crossing point. About 16 samples of each feature ismore than suÆcient. Figure 69 shows the actual received waveform after  2 km of cable.
The measure of timing may be chosen in various ways by focussing on various parts (orperhaps all) of the waveform, with di ering systematic impact. The two most illustrative approaches focus on the leading edge or the zero-crossing point of the received bipolar time-markwaveform. Although dV/dt is higher for the zero-crossing point, this measure is prone to greater
error since the extrapolation to baseline is less immediate, and the instant of zero-crossing depends on circuit component values and on the risetime of the pulse, which depends on cable
length. The zero-crossing method, although o ering somewhat better precision for tracking oscillator frequency, is not as suitable for establishing the local-master time transformation, which
also includes phase. A leading-edge method is a simpler and more appropriate choice.
The presently used leading-edge algorithm simply extrapolates to baseline using a few samples above a threshold. Bene ts from using more sophisticated tting to the waveforms surely
exist, but remain to be explored. The leading edge measurement algorithm, in whatever form ittakes, must be sophisticated enough to avoid excursions into the very rst part of the waveform
during which the rst and second derivatives have the same sign, or it must permit a suÆciently
complex spline form that spans accurately the somewhat asymmetric point of in ection. In any
case, the results show that the desired time resolution can be obtained, even with the most
simple approach.
131

Time Tick ADC Waves at DOM

Figure 69: Time-mark waveforms measured at the digital optical module, after traveling through 2+kmof twisted pair.

132

The extrapolation-to-baseline algorithm de nes the instant that the waveform was received,in local DOM time units. At the surface, the moment of transmission is precisely de ned by themaster clock time distribution subsystem. Repeated measurements of this type serve to measure
the frequency and phase of the DOM local clock very accurately. The stability of the Toyocom
oscillators will permit, with bene cial e ect, ts that include measurements made over several
minutes.
Figure 70 presents the results obtained with DOMs deployed in the ice. This gure needssome explanation to extract the intrinsic resolutions of the DOM and Test-Board DAQ. Eachpoint in the one-way
p histograms is based on two consecutive measurements; the rms of eachmeasurement is 1/ 2 smaller. The di erences between up-going resolution (7.8 ns) and downgoing resolution (4.5 ns) is thought to be due to a noisier environment in the counting room
(where the Test-Board DAQ is located) than in the DOM. The round trip resolution involves
one up-going and one down-going measurement, and is observed to be approximately the sum of
the individual resolutions taken in quadrature. In the future, resolutions should be better, sincea GPS clock would not be used directly as a master clock, and steps would be taken to reduceor eliminate environmental noise in IceCube. The time resolution measured in the laboratory
using a Toyocom oscillator as reference was indeed signi cantly better, 3 ns rms, supporting
this hypothesis.
The measurement of the local clock phase, however, contains an O set due to the di ering
physical lengths of the twisted quads throughout the detector. The di ering physical lengths,
twists, and stretches introduce di erences in the propagation time for signals to pass from one
end of a cable to the other. The signal propagation time, or cable electrical length, can vary bya large amount, up to 5000 ns from the top of the IceCube string to the bottom.
The traditional way to measure cable electrical lengths is known as Time Domain Re ectometry (TDR). Simply put, the TDR method sends a short pulse into a cable and measures thetime between input and a return signal from the end of the cable; however, the TDR method
requires either an unterminated or a shorted end point to re ect electrical energy. Neither condition is permitted in our case, since the cable must serve as a fairly high-bandwidth network anddeliver power as well. In addition, the return pulse shape is very di erent due to dispersion andattenuation in the cable during the round trip, complicating the de nition of time measurement
at the level of accuracy that we require. More relevant than the electrical lengths themselves,
however, are the di erences in these electrical lengths. The cable electrical lengths must be
measured in a way that provides accurate relative values of the cable lengths. There is an easy
way to do this, known as the Reciprocal Active Pulsing (RAP) method (see next section) [158].
Since our approach is novel, we present in some detail how timing precision and accuracy of3{5 ns is obtained throughout a simple copper-based km-scale network. We emphasize thatevery critical functionality regarding time-base integrity has already been demonstrated in the
AMANDA string 18 DOM ensemble.

133

Time Resolution with Leading Edge

4.5 ns
7.8 ns7 ns

Figure 70: Time resolution results obtained
p with the digital optical modules currently deployed in the ice.
The resolutions displayed here are  2 larger than the individual resolutions because two consecutive
measurements are used to generate each point in the histograms. GPS clock drift, digitization noise, andenvironmental noise in the counting house dominate the resolutions.

134

DOM Time Synchronization
Offset Measurement

12SurfaceElectronicss

SurfaceElectronics

GPS (t1)

GPS (t2)

Tround-trip = t2 - t1

∆t (down)∆t (up)

Reciprocal
ActivePulsing

δt

ADC
DAC

DOM
For identical electronics: ∆t (down) = ∆t (up) = 1/2( Tround-trip-δt)

Figure 71: General concept of the RAP method for measurement of the electrical length of the twisted
quads.

135

7.2.7 Cable Electrical Length Measurement
The RAP method employs a timing strategy identical to the local/master clock time-base calibration, but adds symmetric round-trip measurement with identical bipolar time-mark pulsesthat are sent/received in both directions. The return pulse is separated by a known, programmable wait interval. The wait interval is chosen to allow the pulse energy in the cable todissipate, so that the rst pulse has a negligible impact on measurement of the second. By using
circuitry, rmware, and software identical to that used for local time calibration in both DOM
and Surface DAQ, the measurement of cable length provides high relative accuracy in cable
length measurements, even though the rise-times vary somewhat due to di ering cable lengths.
The RAP method may be used with either the DOM or the DAQ as the initiator of the rst
pulse; consistent results are obtained in either case. The RAP method is, of course, invoked bysoftware, with no need for manual intervention. The general idea is illustrated in g. 71.
The de nition of cable length is simply one half of the total delay between initiating pulse
and received responding pulse, minus one half of the wait interval. Although a common o set
exists in this method, taking the relative di erences among the ensemble of cable lengths reduces
this source of error to a negligible level.
Measurements of the deployed AMANDA string 18 cables were made from the northernhemisphere using the satellite link to the South Pole to download relevant code and commands.
The results, shown in g. 72, are completely consistent with expectations. The statistical error
bars, 1 ns, are much smaller than the points. The RAP process may be invoked repeatedly,
leading to a measurement value for each DOM with negligible statistical errors; it may also be
invoked automatically at periodic intervals, to monitor system stability, without interfering withnormal data acquisition.

7.2.8 Data Flow and Feature Extraction
The raw representation of a digitized waveform would include 128 10-bit samples and the 54-bit
time stamp, requiring at least 170 bytes in an unreduced format. Waveforms exceeding the
maximum digitization value of 1023 would initiate digitization of the next (lower) gain channel,
resulting in additional 1280 bits of data, etc. Without ltering or compression, a DOM with
300 Hz noise would generate 50 kB/s, or more, most of which is uninteresting noise hits withlong pedestals. Such a data rate would overtax the network capacity.
Feature extraction, local coincidence, and zero-suppression o er useful methods to reducethe bandwidth burden on the network. Feature extraction o ers a powerful means to reducetransmission rate since most of the hits, perhaps more than 95%, are simple SPE pulses. The
feature extraction process for SPE events reduces the waveform information to amplitude andtiming information only. After extraction, an SPE hit should require only 8 bytes to characterize,
including coarse and ne time-stamps. What is critical is that the algorithmic procedure thatmakes the determination whether a given waveform is an SPE or not be robust, since detailed
information is permanently lost after extraction. It seems reasonable to set the cut such thattypical SPE waveforms pass occasionally to the surface.
136

Cable Length (delays) Measurement

Figure 72: Measured electrical lengths of twisted quad cables in string 18 using the RAP method.
137

In any case, the bandwidth requirement for SPE waveforms will drop by a factor of 20 withfeature extraction. This leads to a data rate/DOM for SPE pulses of 2.3 kB/s, assuming a
300 Hz noise rate. Feature extraction is included in the baseline DOM capabilities because it
provides such a large data compression factor.
For multiple photoelectron events, the \non-SPE" waveforms, perhaps the full 170 bytes/eventare needed. Assuming 5% of the 300 Hz hit rate fall into this category, another 2.5 kB/s are
generated. While zero-suppression can reduce the unneeded pedestal data for this category, thefactor of reduction here may be only a factor of 2. Zero-suppression may also complicate event
formatting, and its role in DOM data transmission may not be prominent.

7.2.9 Local Coincidence
Conventional experimental design traditions bring all real-time signals to the counting-house,
within which various trigger logic arrays impose lters to retain only events of interest. For
IceCube, the architecture is quite di erent, and real-time functions play a limited role in the
DAQ. Information arrives at the \counting house" in the form of time-stamped data packets.
Since the vast majority of PMT pulses are noise hits, it is reasonable to ask what is the impact
of noise on system design and cost, and on physics.
The noise rates of the PMTs are interesting for scienti c purposes such as SN/GRB searches
and for diagnostic purposes such as PMT gain stability. However, the DOM noise rate isapproximately 100 times greater than the rate induced by high-energy particles. The question
naturally arises whether it is necessary to transmit all the noise pulses individually to the surface
DAQ. Unlike hits due to high energy particles, noise hits appear randomly, primarily as isolatedhits, with no correlation to neighboring or nearby DOMs. Isolated hits are de ned as thosehits falling within a loose timing window, 1 s, but separated by two or more unhit DOMs
between. In AMANDA, such isolated hits have been relentlessly \cleaned out" during an earlystage of analysis. From the standpoint of event tting, an isolated hit is more than 100 times
more likely to be noise than signal.
Given that 5% of the PMT hits are non-SPE events, and that feature extraction is inoperation for the remainder, the data rate per DOM is 5 kB/s, without local coincidence.
Evidence from string 18 suggests that 15% of the coincidence events are non-SPE in character.
The expected coincidence rate is 5 Hz, including random coincidences. At this rate, each
DOM would generate only 500 bytes/s, about one order of magnitude lower than withoutcoincidence. With local coincidence, data processing resources needed at the surface become
smaller by a comparable factor as well.
The question turns next to whether some simple local coincidence requirement, imposed in
the ice, selects essentially all interesting hits for transmission to surface. Early work on this
topic, including both analytical and Monte Carlo studies based on an IceCube-like geometry,but using an AMANDA-like trigger criterion, suggest that a local coincidence requirement does
eliminate a small fraction, 1{3%, of real events [159, 160, 161], depending on the tightness oftiming cuts. These isolated hits may add some useful information about energy, but likely addvery little to tracking precision.
138

It should be noted that event ltering in IceCube is likely to be quite di erent than thatof AMANDA. The digital system architecture permits much greater exibility in the design oflters, due to software implementation rather than hardware. Studies have not yet been madeto determine whether IceCube would or would not su er a loss of eÆciency, and hence whether
the instrument would be operated with some form of local coincidence. If the conclusion is yes,
local coincidence will be used, then isolated hits would not be present in the output data, except
as they contribute to the noise rate histograms for SN/GRB searches. In either case, the DOM
design will include the local coincidence capability. IceTop, discussed elsewhere, will employ
local coincidence operation to mitigate the uninteresting but copious ux of low-energy muonsat the surface. For IceCube, the use of local coincidence is an option that can be turned on oro .
Each DOM communicates with its nearest neighbors by means of a dedicated copper wire
pair about 20 m in length. This link is thus capable of propagating short pulses, 50 ns, withgood edge characteristics. The DOM is capable of sending and receiving these short signals ina full duplex mode. It is therefore straightforward to arrange logic within the FPGA such that
digitization occurs only when some coincidence requirement has been met. Once a DOM has
triggered an ATWD, it sends signals to each of its neighbors and also starts a count-down froma predetermined number of clock cycles. While the count-down is active, a DOM is receptive
to pulses from either or both of its neighbors. Should this occur, the DOM will digitize, store,
and subsequently transmit the time-stamped data to surface. Meanwhile, the neighboring DOM
will have started a count-down period to initiate a period of receptivity, even if it has not yet
been triggered. If the neighboring DOM had been triggered prior to receiving a pulse, it will
initiate digitization as well. This logic ensures that the local coincidence will capture events
independent of which DOM is hit rst.
In this way, a local coincidence requirement of programmable width has been implemented
in AMANDA string 18 and has worked awlessly. For the future, it is intended to augment
this capability such that a DOM which receives pulses from each of its neighbors during the
programmed interval, which itself has not yet been triggered, will transmit pulses back to bothso that they will initiate digitization. This will realize next-to-nearest neighbor coincidence.
A somewhat more sophisticated approach is also possible, in which a triggered DOM transmits a pulse to each of its neighbors, as before, but which is now a pulse of predetermined
length, say three clock cycles. A neighboring DOM that has not triggered will observe this pulse
and transmit it onward but with only two cycles in length; each untriggered DOM in this chain
will transmit the pulse onward, shortening it until it reaches zero length. In this manner, acorrelation length for the local coincidence requirement can be introduced that extends beyond
next-to-nearest neighbor. It remains to be determined whether such a scheme adds to physicalcontent.
The cost for implementation is fairly modest, as a minimal amount of circuitry is needed togenerate and receive these pulses, in any scenario. The penetrator must have six pins, rather
than two. The cable connecting DOMs is more complicated since it must support six wires.
However, by using a short cable to connect four DOMs to just one main cable breakout, asimpli cation has been achieved in the main cable construction; costs for the main cable are139

reduced signi cantly.
The PMT noise rate can be recorded properly by the DOM, and transmitted periodically tothe surface DAQ as time-ordered histograms, so that the supernova/GRB search capability isretained. Programmable dead-time for the histogramming scalers can be included to alleviatestatistical degradation due to after-pulsing; this requires only a small amount of FPGA logic
to implement. Assuming that the histogramming intervals for detection are 10 ms, the averagecount is only 3. Allocating 8-bit (maximum count: 255) scalers for the GRB/SN search adds
only 100 bytes/s, an insigni cant burden. These 10 ms, 8-bit, scalers are unlikely to over ow,
even for a very nearby SN.
In addition, however, the DOM can maintain a circular bu er of many seconds (even minutes,
if needed) depth, lled with the stream of coarse time-stamps, rounded o to 0.1 ms. This
provides a detailed record of any anomalous rate development, should a nearby SN occur. Theinterval of interest could be requested in the event that a global sum of the 10 ms data indicatesthe onset of a signi cant upward rate uctuation.

7.2.10 System Design Aspects
Control Logic An Altera 10K50 FPGA provides the glue logic between circuit elements andhandles all real-time activities, i.e., those operations for which nanosecond timing is required.
The FPGA handles the synchronized launch of the ATWD, loads data into memory, receives
messages from the surface and transmits the requested response message. The FPGA will be thesite for the SPE feature extraction process. For an FPGA implementation, algorithms involving
only integer arithmetic are desirable; this does not appear to impose a limitation for accuracy,
robustness or execution speed.

ARM CPU The string 18 DOM state is controlled by a low-power Cirrus logic 32-bit CPU

targeted toward the hand-held market. The choice of an ARM device was deliberate, in thereasonable hope that this general architecture would remain viable in the market-place at least
for the duration of the IceCube production phase. The particular CPU employed in AMANDA
string 18 is certain to be replaced by similar but more powerful devices on a yearly time-scale;nevertheless, software compatibility is expected to be high. A product from another vendor may
be chosen for IceCube.
The CPU runs a Real-Time Executive, a thin version of a Real-Time Operating System(RTOS). This facilitates interrupt response and message handling. The CPU boots from ash
memory upon power-up, and runs at 16.8 MHz in string 18. It o ers the rough performanceequivalent of a 31 MHz 486, with a power dissipation of only 50 mW. Higher level functions
requiring code unsuitable for FPGA implementation will be realized in the ARM CPU. Since
the string 18 DOMs were designed, new FPGA products that o er embedded ARM CPUs (hardor soft) have become available. Such integrated devices may provide an attractive simpli cation
through the elimination of one complex component.

140

Slow Control, Calibration, and Self-Test Features Each DOM is responsible for con-trolling critical data taking parameters. These include setting local PMT high voltage levels,
discriminator threshold levels, ATWD digitizer control voltages, and even selection and loading of appropriate FPGA programs. Since none of these operations is performed during actual
data acquisition, they are deemed part of the slow control system. All adjustments capable ofa ecting the quality and quantity of data produced by the DOM are controlled from within the
DOM itself. Therefore, all slow control requests, regardless of their origin (user interface, automated experiment control sequences, etc.) are nally serviced within the DOM and its resident
software.
Each DOM is also capable of carrying out extensive self-test sequences. In addition to
verifying correct operation of the digital platform and peripherals within the DOM, these programs can test analog electronics for the presence of increased noise, or spurious discriminatoror ATWD behavior. Upon initiation, these tests are carried out under the control of the local
DOM processor and results are reported back to surface electronics upon their completion.
One of the most important of these self-test features is uniqueness. Each DOM has its own
serial number, most likely and elegantly implemented via a preprogrammed serial memory chipon the PC board. Upon booting up, this identi cation number is transmitted to surface DAQ,
which can then verify that the channel number in the DAQ corresponds correctly to the deployed
sequence along the string. Thus, cockpit errors that can easily lead to reversed connections or
misplaced channels are instantly located.
There are many DOM parameters, measurable either with scheduled tasks in the DOM CPU,or via command messages from anywhere, that must be included in the calibration database.
The primary scheduled task is the local-master clock transformation calibration process. Other
tasks that should not require frequent activation are the ATWD capture speed calibration, the
ATWD trigger discriminator threshold scan, the PMT SPE pulse-height distribution/average,
and ATWD transfer characteristics such as sample pedestal values, gain and linearity. The
transit time of photoelectrons through the PMT can be measured using a built-in triggerable
weak light source (not the optical beacon board).

7.3 Network
The km-scale network supporting the signal detection elements must be robust, cost-e ective,
and transparent, in the sense that data quality and operational exibility are not compromised.
Despite the challenging technical requirements for data quality, a simple all-copper network cansuÆce.

7.3.1 Copper Links
All timing calibration, control, and communications signals between a given DOM and the surface DAQ are provided by one conventional twisted pair of 1 mm diameter copper conductors
insulated with PVC. The impedance is in the range of 100 . This pair also supplies power to theDOM. The resulting network is both cost-e ective and robust, since the number of connections
141

(i.e., two) needed for all functionality is minimal. The twisted pairs are assembled rst in double
pairs, as \twisted quads," and enclosed in a common sheath. The required number of twisted
quads are then wrapped around a Kevlar strength member and covered with a protective sleeve.
Breakouts of individual quads to facilitate connections to the DOMs are periodically introduced
at the appropriate positions.
Cable bulk and cost are reduced by planned operation of two DOMs per twisted pair. Thismeans that two neighboring DOMs are ganged together at depth, with a simple network at thejunction point to distribute power and transmit impedance-matched signals. DOM operation
employs alternate interrogation of each member of the DOM pair to obtain unambiguous anduncon icted data ow. The data rates per DOM are anticipated to be 5 kB/s. Even with
two DOMs/twisted pair, the bandwidth of the copper links is suÆcient to support easily the
expected traÆc level of 10 kB/s, or equivalently, 80 kbits/s. Fast base-band communication
over twisted pair links of 2{3 km can reach 400 kbits/s or signi cantly higher, depending on
protocol. Nevertheless, it should be noted that the margins here are only a factor of 4, andany action that would increase the PMT noise rate or data/hit will reduce the margin of safety
against network saturation, increasing the motivation to utilize the local coincidence feature.
Data transmission to the surface DAQ occurs by alternate interrogation of the DOMs sharing
a twisted pair. Di erential send/receive results in very low levels of cross-talk for these digital
signals, measured to be less than 1% using the deployed AMANDA string 18 cables. Deployment
operations are also simpli ed substantially, since only a single electrical connector needs to bemated and veri ed.
The use of an all-copper wire network eliminates the need for the optical bers that havebeen used in AMANDA. Optical bers are obviously capable of transporting analog information
at the bandwidth needed, but the copper network can meet this goal with digital transport of
information. In the rather unorthodox AMANDA mode of optical ber use, i.e., being frozen
in while supporting large vertical gravitational forces and freeze-in force gradients, failure ordegradation of signal was commonly observed, typically in the range of 5{15% of channels. Thispattern presents an unacceptable level of loss for an instrument of the scale of IceCube. The
actual causes of failure or degradation have remained a subject of speculation, since realistic
testing of ideas and possible remedies does not appear feasible. Combined with the goals to savecosts, eliminate dozens of plane ights, simplify and shorten deployment procedures, the historyof reliability problems generates ample motivation to develop an instrument design based on an
all-copper network.

7.3.2 Time-Base Distribution
While the all-copper network plausibly meets the goals of robustness and cost-e ectiveness, it
may seem less apparent that such a network could meet the goal of a distributed time base at
the few nanosecond level. As noted earlier, dispersion and attenuation lead to a substantial
degradation of pulse rise-time in copper links of this length ( 2s for 2.5 km). Nevertheless,the realization of local ) master clock time transformation with a relative accuracy of 3 ns overa km-scale array is remarkably straightforward, requiring only a tiny fraction of bandwidth and142minimal circuitry for this purpose. The exceptional stability of the DOM local oscillators facilitates this process. Preliminary results with the four DOMs in string 18 in AMANDA operated
by the Test-Board DAQ give values for time \synchronization" of 5 ns rms, in agreement withexpectations, and with clear prospects for further improvement by algorithmic modi cations.
The measurement and calibration of timing o sets introduced by di erences in twisted-paircable lengths has been performed automatically and remotely via satellite links by system operators in the Northern Hemisphere. No manual interventions by pole personnel are necessary at
any time for this purpose. The Reciprocal Active Pulse (RAP) technique exploits the capabilitiesof the DOM to measure o sets with a statistical precision of 1 ns as discussed in section 7.2.7.

7.4 Surface DAQ
7.4.1 Overview
The general concept for the surface system DAQ is shown in g. 73. The proposed DAQ design
revolves around three separate phases of event creation:
1. Within a string, the collection of hits into \string coincidence events."
2. The collection of string coincidences and the decision to form a global event trigger.
3. The gathering of hits on all strings which belong to global events, and the recording of thecomplete event information on disk and tape.
These tasks can be laid out in more detail by enumerating the messages that are exchangedon the various networks of the DAQ. The following items are also summarized in the gure.
Since 100BaseT networking is assumed, bandwidth requirements are shown to be comfortably
less than 8 MB/sec in each case.
One notable feature about this design is the prevalence of o -the-shelf computing and networking hardware from the earliest possible point in the data ow diagram. It should be further
noted that the focus is on commercial hardware and software found in the world of e-commerceand Web services industry as opposed to process control. Furthermore, there is a clear emphasison the use of commercial Ethernet networking protocols and hardware in place of more traditional bus-based architectures such as VME or CPCI. Both of these features are intentionaland represent our belief that, given both the expected data rates and the diÆcult maintenanceenvironment at the South Pole, these choices represent the best solutions for both system performance and stability. A corollary of the emphasis on o -the-shelf hardware products is thatmost of the e ort in DAQ is software.
The system consists of an interconnected set of hardware components and software tasks.
While this design does allow for a great deal of exibility in how these components are grouped
together and mapped onto various networks and processors, the overall system performance goals
dictate that certain aspects of this grouping are xed. In the following discussion, the distinction
between system software processes and actual CPUs within the system should be noted. For
143

F

2 - 5 Units

String Subsystem:
60 DOMs

DOM
Pair

DOM
HU

20 k /sec

pairs

0 Strings

N x 20 kB/sec

String A
100 aseT
StringProcessor

Total traffic: 0.6 M /sec
All Hits 0.6 MB/sec

Lookback Requests
String Coincidence
Messages - 170 kB/sec

5 CPUsFulfill Lookback Messages
0.6 MB/sec

Fulfill
Lookback
MessagesEventuilderEvent A
StringCoincidence
Messages

GlobalTrigger

100 aseT
Total traffic: 1.6 M /sec
Built events ~ 1 MB/sec(all event builders)

Event Triggers /Lookback Requests for
all Strings - 0.8 MB/sec

Online A
100 aseT
Satellite

Data
Handling
CPU Cluster

Total traffic: 1M /sec
Data Handling
Disk Cache

Tape

Figure 73: Conceptual illustration of DAQ system organization.
144

example, a complete string of optical modules is said to terminate in a single processor, called
the string processor.
For the purposes of system design, it has been important to decide that, since an opticalmodule string represents a logical grouping of data for triggering purposes, all data from one
string will always ow to a single processor and will not be distributed across multiple CPU's.
While, for the purposes of this document, it is easiest to discuss the string processing program as
executing on a single processor, namely the string processor, the system design does not requirethat each string be handled by a separate processor. It does, however, require that all datafrom all DOMs in a string are routed to a single system process that can deal with them in aneÆcient and complete manner.

7.4.2 DOM Hub
At the surface, the twisted pairs from DOM pairs on a string are connected to a DOM Hub.
Each twisted pair connected to the DOM Hub is de ned as a channel. It is appropriate to design
the Hub such that the number of channels per Hub is a factor of the number of DOM pairs on
a string, i.e. 30. For example, if the DOM Hub accommodates six channels, ve DOM Hubs
are needed to service an entire string. If the DOM Hub accommodates ten channels, then only
three DOM Hubs are needed (similarly, two DOM Hubs will suÆce if a Hub has 15 channels).
The functions of the DOM Hub include power distribution and control for each DOM pair,message control, data ow management from the DOMs, downloading of software, rmware,and operating parameters, and generation of time calibration signals. The DOM Hub design isderived from the single-channel Test-Board used to read out string 18, and is the only signi cantpiece of custom hardware awaiting realization. It is conceivable (and likely) that the design andlayout of the DOM Hub will accommodate more than six channels. In what follows, however,
we assume a conservative default of six channels per DOM Hub (12 DOMs).
The DOM Hub design is centered on an embedded processor that provides low level communications services between the surface and the DOM and provides high level communications
services (i.e. TCP/IP) to the string processor. The DOM Hub will consist of 1U rack-mounted
chassis with front-end electronics including FPGAs and FADCs for 12 DOMs, an embedded CPU
daughter card for processing and communications functions, and a power supply capable of providing power for all attached DOMs. The back panel of the chassis contains connectors for direct
attachment to DOM deployment cables, master clock distribution, and a standard 10/100BT
network connector. The embedded processor is a credit-card-sized 200 MHz StrongARM CPU
running Linux.
The DOM Hub will support TCP/IP protocol and will deliver data streams for each DOM tothe string processor using the standard socket programming model. Furthermore, the DOM Hub
will provide transparent web-based communications with individual DOMs so that maintenanceand minimal testing functions may be performed remotely without the need of the full dataacquisition system.
All real-time functions in the surface DAQ that depend on nanosecond-level timing are contained within the DOM Hub. Data transferred from the DOM Hub to downstream elements in145the surface DAQ are time-stamped messages; subsequent processing needs only to ensure adequate data ow. The latencies of network operation do not introduce synchronization problems.
The DOM Hub receives a carefully distributed 40 MHz master clock. This master clock
will be linked ultimately to GPS, providing a universal time reference to other GPS-linked data
sets to  40 ns. The DOM Hub maintains a register capable of assigning a unique time-stamp
for at least one day (44 bits). Although runs will likely not extend more than one day, it isstraightforward to track time perhaps for as much as a year (51 bits). Test functions will beincorporated to ensure that every DOM Hub has exactly the same master time. These test
functions will operate as separate, scheduled threads that will not interfere with normal dataacquisition.
Assuming a PMT noise rate of 300 Hz, 60 DOMs per string, a fraction of 5% of hits needing
full waveforms, 170 bytes per waveform and 8 bytes per non-waveform hit, one obtains a DOM
data rate of about 5 kb/s and 0.3 MB/s per string. Because these data ow rates are modest,the surface DAQ can be network-based rather than a more traditional crate/backplane/bus
implementation. Of course, with local coincidence, these rates would drop an order of magnitude
further.
Data from each DOM is requested periodically, at a rate of 10 Hz. This provides adequately
small latency for data streaming purposes, and maintains a reasonable transmission burst of 0.5{
1 kb/request. Each request for data includes the time-mark signal as the rst pulse. The DOM
will ignore most of these, using them only as frequently as local clock drift characteristics require.
DOM data packets with local time-stamps are locally bu ered in the DOM Hub. For eachstring, hits from DOMs connected to ve DOM Hubs are sent over a String LAN (one 100BaseT
network switch) to a String Processor (SP).

7.4.3 String Processor

Data bu ered in the DOM Hub is block-transferred periodically, 10 Hz, to the String Processor(SP). The SP is expected to be a standard PC CPU running a Linux OS. Here, data is converted
to master time units. The desired space-time correlations characteristic of physics, traditionallyde ned with real-time electronic trigger systems and called \triggers," are found in our casethrough software algorithms in the SP. Simulations have shown that only about 5% of available
CPU cycles of a 1 GHz PC are needed to perform typical coincidence algorithms for a 60-DOM
string.
Each String Processor is also connected to a global Event LAN. String coincidences arereported by each String Processor to the Global Event Trigger on the Event LAN. The Global
Event Trigger is envisioned as a single processor on the Event LAN, which is also connected toa set of processors that serve as Event Builders. Assuming a string coincidence rate of 60 Hz
per string, an average of 4 hits per coincidence event, and 60 DOMs per string, one obtains a
total data rate for all 80 strings of less than 0.2 MB/s for these messages.
When trigger conditions for a particular event type are ful lled, the global event trigger
informs the String Processor to tag all hits that occurred near enough in time to the global
trigger time. If one assumes a global aggregate trigger rate for all trigger types of 1 kHz,146

10 bytes per message, and 80 string processors, these \Look-back Requests" require an average
bandwidth of 0.8 MB/s.
The String Processor sends the data for the tagged hits to one of a set of Event Builder CPUs.
This also occurs over the Event LAN. Assuming 20 random noise hits per event, 12 muon hits
per event, and the above values for the average number of bytes per hit and for the global event
rate, one obtains an average bandwidth of 0.6 MB/s. This brings the total bandwidth usage on
the Event LAN to about 1.6 MB/s, well within the capabilities of 100BaseT switches.
It may turn out that the waveform data retrieval task for the look-back requests may be justas easily handled by sending all waveform data associated with the string coincidence trigger
messages, since the amount of data arriving at the SP is roughly the same as the look-backrequest traÆc. This software architecture would eliminate the look-back process, yielding adata ow diagram without loops at this level. In this scenario, however, the destination of
the waveform data needs to be considered carefully to ensure arrival at the appropriate Event
Builder target CPU.
The Event Builder CPUs send fully constructed events to a disk server over the Online LAN.
The disk server will write events to disk. Since the bulk of the event data is in the hits, thebandwidth on this network will be not signi cantly more than 0.6 MB/s. 1 MB/sec is a safe
number to assume, well within the 100BaseT limits. In addition to the Event Builder processors
and the disk server, the Online LAN also is connected to the processors that constitute theonline ltering and data archiving system. Events are still represented in master clock timeunits, but also have the associated GPS times linked to each.
This design is attractive, in part, due to its high degree of modularity and exibility. Thus
to create a minimal test stand for DOM production and quality control, one can simply workwith a single DOM Hub attached to one or more DOMs (or DOM pairs). Functionality for awhole string can be achieved by networking the DOM Hubs to an o -the-shelf String Processor
CPU and installing the requisite software. In an international collaboration where hardware
production, software development, testing and deployment will be carried out on multiple continents, this is a key advantage. Finally, with the proposed \network-heavy" scheme, IceCube
will bene t from a tremendous amount of community experience and publicly-available tools
for TCP and UDP-based networking, which far outstrips the resources available for bus-basedarchitectures such as VME or Compact PCI.

7.4.4 IceCube and IceTop System Integration
The DOM and its associated DOM Hub design will accommodate the technical requirementsof both IceTop and IceCube, with di erences con ned to rmware, software, and operating
conditions. Within the counting house, the di erences would be apparent only in the network
con guration.
Each IceCube string requires 15 quads for the 60 DOMs. Unlike IceCube, the IceTop DOMs
will not share a twisted quad with a neighboring DOM since the expected rates are higher thanthose of IceCube. The four IceTop DOMs thus require two quads, for a total number of 17 DOM
twisted quads/string. In addition, there will be ancillary devices added to the string, such as
147

pressure sensors used during deployment and freeze-back, so the expected total number of quads
will be at least 18 per string, perhaps more. The fraction of counting house resources neededfor IceTop is 15% relative to IceCube.

IceCube The 80 strings of IceCube will require 400 (240, 160) DOM Hubs in the counting

house under the assumptions that a DOM Hub has 6 (10, 15) channels (two DOMs per channelin IceCube) and is housed in 1U mechanics. The DOM Hubs and 80 (perhaps less) associatedString Processors will require something like 10 (6, 4) oor-to-ceiling racks. The space-savingthat would be obtained with the 10- or 15-channel version is substantial, and provides ample
motivation for high design density.

IceTop IceTop, described in detail elsewhere in this document, will consist of an ensemble offrozen water tanks situated just below the surface, and located near each of the 80 strings. Eachstring will have two tanks separated by a few meters to suppress single muon events, yielding
a total of 160 tanks. To extend the dynamic range, each tank will be viewed by two DOMs
operated at substantially di erent gain settings. This facilitates the capture of extremely highenergy air showers. The local coincidence requirement will be operational between the high-gain
DOMs in the two tanks. The coincidence requirement will reduce to an acceptable level therate induced by the relatively copious ux of uninteresting single muons penetrating the tankvolume.
With 160 tanks and two DOMs/tank, IceTop's 320 DOMs will bring 320 twisted pairs (in160 twisted quads) into the IceCube/IceTop counting house. These IceTop quads will plug into
54 (32, 22) DOM Hubs dedicated to IceTop, if the DOM Hub supports 6 (10, 15) channels.
The IceTop DOM Hubs will connect to a dedicated IceTop Global Trigger CPU and Event
Builder, with a LAN architecture analogous to IceCube. The output data stream will be linked
to IceCube by both master clock times and GPS time units for online and oine analysis.

7.4.5 Experiment and Con guration Control
The system design described in this document is based on a loosely-coupled collection of subsystems whose operations are, for the most part, decoupled. One advantage of such a design isthat it allows some independence in the design and implementation of individual sub-systems.
However, in order to co-ordinate these elements into a single, coherent system, some degree ofoverall control is required. This function is provided by the experiment control system.
The IceCube detector can, at any given moment, be described as being in one of several
operational states. These states serve as short, meaningful descriptions of just what operations
are being performed by the detector. By enumerating which operations are allowed in which
detector states, this state model also serve as a mechanism to control and co-ordinate operationsof separate detector sub-systems.

148

Scope of Experiment Control The detector, as a whole, can be though of as being in oneof the following states: \idle," \entering data-taking state," \running," \paused," \exiting datataking state," \calibrating" or in one of several \testing" states. Each of these states has certain
implications for the operations of each sub-system. For example, if the detector is taking data,
the DOM string control sub-system should not be able to alter PMT high voltage settings on an
active OM. Similarly, although it is permissible to alter individual settings for an inactive DOM(i.e. an DOM not included in the global trigger's list of active DOMs), it should not be possible
to initiate LED beacons on this particular DOM since resulting light would a ect data taking
activities. Therefore, all sub-systems refer to experiment control as the single indicator of thesystem's current aggregate operational state. Each sub-system is responsible for designing its
internal operations and states to be consistent with the overall detector behavior described byexperiment control's current state.

Common Component Control Model In addition to providing all sub-systems with aconsistent indication of the detector's overall state, experiment control must, in order to initiate
and control data taking, be able to request sub-systems to perform certain actions. Depending
on a particular sub-system's role in the detector's operation, these actions can be relatively
simple or fairly complex. For example, when beginning data taking, DOM string control will be
required to log current DOM parameter settings to a local database and change its state from
\idle" to \data taking." The fact that the DOM string control sub-system is in the \data taking"mode implies that it will be unresponsive to user requests to reset critical DOM parameters.
Other sub-systems may require more complex responses to experiment control commands.
To the extent that the complexity of these operations is only of concern to the sub-systemitself, the details of these operations should remain concealed within the sub-system's operation.
Each sub-system should be able to accept a high-level request from experiment control to moveinto a new state. Following this request, each sub-system will respond with its new state andstatus. Successful transitions of each sub-system into the appropriate state will lead experimentcontrol to indicate that the detector has taken on the desired nal state (e.g. \running"). The
failure of any sub-system to appropriately move to the desired target state will indicate a systemproblem and will cause experiment control to bring all sub-systems back to a consistent and safe
state.
It should be noted that with the loosely-coupled system described here, individual control
operations are best handled directly by those sub-systems involved. That is, commands andrequests for monitoring and status information will be processed by the sub-systems themselves,
not by some single intervening agent (e.g. experiment control). The advantage of such a designis that additions and alterations to sub-system controls and interfaces need only be implemented
in one place -the sub-system itself. They do not have to be further integrated into additional
supervisory programs or levels.
However, it should be pointed out that, with this implementation model, it is possible forthere to be a wide and confusing variety of user interfaces for each sub-system. Even withexperiment control properly playing its detector-wide coordinating role, it will be possible to149

implement sub-system user interfaces in many di erent and potentially awkward styles. A
certain degree of discipline in design and implementation of individual sub-system user interfaces
will be required in order to produce a consistent overall look and feel. Given the breadth offunctions requiring user interfaces and the necessity for e ective remote (albeit secure) access,the adoption of a web-based user interface model is preferred.

DAQ Con guration Database The DOM string control sub-system will be responsible forkeeping an accurate database of DOM-related parameters for each data taking session. While
this list of DOM parameters and operational settings is not yet complete, it is safe to assume
that, during any given data taking session, each DOM participating in the detector array will
have 50 to 100 parameters that describe its intended operation. These will include static ducial
information such as serial number, string and position location, rmware version number, etc. It
will also include per session information such as PMT high voltage, trigger threshold level, and,if some level of waveform capture is included in the DOM, parameters that describe operationof waveform capture and feature extraction algorithms.
This same database will also be used to control which DOMs are actually participating indata acquisition operations for detector array and, if required, insure that unused DOMs are
powered down and/or not contributing unwanted triggers to string processor trigger processors.
This same database will be used by the Global Trigger and Event Builder sub-system to control
operations of the String Trigger processor algorithm.

Component Discovery and Self Con guration The IceCube detector will be deployedover a period of several years. Furthermore, during the summer deployment season, opticalmodule strings will be deployed, tested and integrated at rates far in excess of that experienced
by the current collaboration. While the physical logistics for drilling, deploying and cabling
detector strings are critical to the success of this timetable, the speed with which the dataacquisition system can adapt and re-con gure to the addition or deletion of new optical module
strings will be of equal importance.
Each sub-system located at the South Pole must be aware of its environment and capable ofdetermining whether needed hardware and software components are available. This operation
can be performed automatically when individual sub-systems are started or can be the resultof an explicit re-con guration command. The most basic example of such an operation isenabling the experiment control sub-system to locate, via a set well-de ned network operations,and establish communications with all other operating sub-systems. A more complex, butconceptually similar, con guration operation enables the DOM string control sub-system todetermine which strings are present and which optical modules are in an operable state. This
resource discovery scheme can be extended to on-line sub-systems as well by enabling the lter
farm manager to discover which individual processors are available to participate in its operation.
If this technique is consistently applied across all sub-systems and is combined with accurate and complete documentation of the experiment cable plant, it becomes relatively simple toincorporate both additional DOM strings and computing resources as they are installed. The
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presence or absence of portions of the hardware and software system become apparent to operators as each sub-system reports its success or failure during a \con gure" operation. In addition
to speeding integration of new portions of the detector, this capability allows fast and e ective
resolution of complex system-wide equipment problems. This capability can also provide criticalequipment status information when recovering from an unscheduled power loss.
Just as it is critical to be able to automatically incorporate new DOM strings and computing
components as they are installed, it is also important to be able, under computer control, tomark portions of the system as o -line or \non-participating." The most obvious need for such afacility is during system debugging. It is often useful to remove elements from the system in order
to investigate their role in generating speci c error conditions. Unfortunately, it is not always
convenient or possible to electrically disconnect or power down suspected hardware or software
components. Some data acquisition problems may require this sort of system de-population forcorrect diagnosis and repair. If these problems occur during the winter season, the ability toremove some components from the system, via remote access, will be of great advantage.

7.4.6 Security Environment\Security" can cover a wide range of capabilities and protections. It is worth reviewing thecurrent use of the term in computing and communications systems. In current computing
usage, the term security is based on four principles: authentication, authorization, privacy, andnon-repudiation. Brie y, authentication involves the veri cation that a user has the identity
they claim to have, authorization veri es that a given user has the authorization or privilege
to perform a requested operation, privacy assures users that messages and data exchanged
with another user will be private to only those two parties, and non-repudiation stipulates thatrequests received from a user cannot be repudiated at a later date (e.g. electronic transfer offunds). Each of these principal functions can be implemented separately and each with varying
degrees of completeness. Furthermore, several di erent technologies can be used to achieve someor all of this functionality. While simple open password schemes are not considered to provide
any real level of security, suitable software mechanisms, such as DES, Kerberos, and PKI (Public
Key Infrastructure), exist and are readily available.
An exact statement of IceCube security requirements does not, as yet, exist. However, basedon past AMANDA experience and reasonable projections of IceCube operations, several needs
are obvious. Regardless of what network access level protections may be implemented upstream,such as screening of requestor IP addresses, it is important that all control commands be veri ed
and screened by a security service at the South Pole site. This service should provide, at aminimum, strong authentication and authorization functions. These would basically regulate
who would have access to data acquisition and on-line control and monitoring information andwhich speci c capabilities would be allowed on an individual basis. While privacy and nonrepudiation functions do not appear to have any role in experiment control and monitoringat present, any suitable security service will allow their implementation at a later date. In
discussing security in the context of experiment control, it is assumed that a certain level ofrobust security is provided by the underlying operating system and network environment. It is151assumed, for example that unauthorized access to system accounts has been eliminated and that
network routers and their control ports have been made suitably safe. The following discussion
centers on the application design decisions that will enhance this low-level security and protect
the resulting system from unauthorized or inadvertent use.
One mechanism used in designing secure control systems is to create a nite number of\roles" that users can take on when logged onto a system. These roles are typically descriptive
in nature (e.g. \operator," \implementers," \maintenance technician," \super-user"). Users
requesting access to the data acquisition or on-line sub-systems at the South Pole will present
their name, security credentials, and intended operational role to the security service. Afterauthenticating user identity, the security service determines whether a user is authorized to takeon the requested operational role. If these security checks are successful, the user then has all
the privileges associated with that operational role.
One of the advantages of this scheme is that it creates a clean partition between security services and system operations. Security mechanisms can be centralized into a single point of access.
Individual sub-systems are then able to treat all commands as having been issued by authenticated users acting in an authorized capacity (i.e. role). In addition to these implementationeÆciencies, this scheme also clari es overall system design and operation. Although commands
to sub-systems will carry the identity, as well as the acting role, of the requestor, the design
becomes one primarily driven by the requestor's role. The act of describing the set of all possibleuser operational roles implicitly describes all possible modes of system operation. For example, since each sub-system di erentiates between normal operations allowed by an \operator"
and those privileged commands reserved for \implementers," lists of permissible \operator" and\implementer" functions take on detector-wide meaning and signi cance. Furthermore, since,at the sub-system implementation level, every command must be checked against the role of therequestor, sub-system behavior becomes both well-organized, easily described and, hopefully,
documented.

7.4.7 DAQ Components
Slow Control The DOM string control sub-system will consist of a central control programand co-operating tasks executing on each string's dedicated control processor. Since the detector
will grow by the addition of DOMs organized as strings and since the only electrical and logicalpath for communicating with a particular OM is through its string processor and cable, thisdesign is a natural t for the detector's topology.
The central slow control program will be responsible for all user and experiment control
interface functions to the optical modules and will be responsible for all DOM-related interactions
with the detector con guration database. These database interactions will include queries of
DOMs currently active in the detector, setting and recording of internal DOM parameters fordata taking, and recording of individual DOM calibration information acquired during low level
calibration operations. Most DOM string control operations will be synchronous command ormonitoring requests.
At present, there are only a small number of possible states for the DOM string control sub152

system. These states should be suÆcient to indicate the following DOM string control activities:
o -line or idle, performing self-con guration and string discovery, performing one or more local
DOM calibration functions, on-line and able to accept operator commands, and on-line but only
accepting monitoring requests (as during normal data taking). Additional states can be added
as needs arise. It should be noted that these states, as well as those of other sub-systems, will
not correspond exactly to those of the experiment control program. They do, however, represent
a list of possible sub-system behaviors that are consistent with the overall detector operation.
The central control program will also be responsible for discovering via their associated string
processors, all DOMs presently in the detector. Once connected to the local area network, newly
added strings will be incorporated into the central control program through a single \recon gure"command. This same operation will allow strings temporarily removed from the detector for
purposes of test or electronics repair to be marked as \non participating strings" and theirrespective DOMs recorded as \o line."

String Data Handling Each DOM in a string produces a stream of hits and waveforms that,

via the String LAN, ultimately reaches the string processor. All operations surrounding datatransfer, sorting and interactions with other system components (e.g. the global trigger) are
the responsibility of the string data handling process. The rst phase of its operations centeron the delivery of string level hit information to the global trigger process. Upon reception ofdata from one or more DOMs, its initial task to sort this data into structures that allow quick,eÆcient determination of local coincidence during a sliding time window (typically 8 s). When
all coincidences for a given time period have been found, they are properly formatted and passed
on to the global trigger process.
The second phase begins when the global trigger process responds with a list of time intervalsof interest. It is then the string data handler's task to collect raw data from all DOMs for eachof the time intervals of interest and forward the resulting data set to the appropriate Event
Builder. In practice, these two phases will overlap and provision must be made to have several
such operations in progress at any one time.
There are only a small number of possible states for the string handler process. Thesestates should be suÆcient to indicate the following activities: o -line or idle, performing selfcon guration and DOM discovery, processing normal data triggers, paused due to operator
request or error condition, and performing string speci c tests. Additional states can be added
as needs arise.

Global Trigger As described above, the global trigger is responsible for generating lists in-dicating the occurrence of detector-wide events of interest. It consumes the list of hits asdetermined by the string data handling process in each string processor and emits a list of
UTC-based times that bracket hits considered to be possible events. The global trigger behavessynchronously with the aggregate collection of on-line string processors. That is, the global trigger waits until all string processors that are con gured and active to report their contributions
for a given time interval. Only when all string contributions are present, can the global trigger
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begin the process of determining what events might have occurred. Once this determination iscomplete, the Global Trigger selects an Event Builder for the current data sequence and passes
a list of UTC time intervals to both the selected Event Builder and all string handling processes.
During normal operation, all 80 string processors will remain synchronized within the reporting period speci ed when data taking was initiated. This period can range from as low as100 ms to perhaps a few seconds, without degradation of system performance or compromiseof data integrity. Several global triggers may be found within one reporting period. As describedabove, for each reporting period, ALL string processors must forward string-level local coincidences, or their absence, to the global trigger in order to initiate the global triggering process.
In the absence of such a report, the global trigger will re-synchronize all string processors andforward, to the Event Builder an indication of what reporting periods were discarded. Persistent
failure of a string processor program or CPU will cause the global trigger manager to enter a
non-operating error state. Experiment control will detect, during periodic system scans, thisstate change and force an abnormal end of run sequence for all data acquisition sub-systems.
Co-ordination activities and generation of global triggers are performed by a single global trigger process executing on a dedicated processor. Since this activity requires the exchange ofmultiple messages between this process and each string's data handling process during eachreporting period, high speed, low latency network connections between these processors is ofgreat importance.
There are only a small number of possible states for the global trigger sub-system. Thesestates should be suÆcient to indicate the following activities: o -line or idle, performing selfcon guration and string processor discovery, processing normal data triggers, paused due tooperator request or error condition, and performing global trigger speci c tests. Additional states
can be added as needs arise. As with other sub-systems, it should be noted that these statesneed not correspond exactly to those of the experiment control program. They do, however,represent a list of possible sub-system behaviors that are consistent with the overall detector
operation.

Event Builder The I/O requirements for IceCube are not very demanding, opening up many
possible approaches to event building. We opt for a simple yet exible approach based oncommercial hardware. Its main elements are a farm of the order of ve \event worker" PCs connected via a switched ethernet network and a control PC that manages the farm and distributes
the work. This asynchronous approach o ers a redundant, fault-tolerant, reliable and scalable
solution that should work with minimal maintenance e ort. The amount of CPU time neededfor event building has not yet been studied in detail but is estimated not to be the de ning
factor for the size of the farm. The number of PCs is rather determined by the requirement of
redundancy. To exploit the CPU capacity, several tasks will be incorporated in addition. We
currently envision the following set of tasks: Asynchronous merging of data from 80 string-wise sources (event building);
 Low level monitoring, data consistency checks and online calibration;154

 Feature extraction from digitized pulse shapes.
A special control PC is used to control event building by selecting speci c event worker PCs
that are ready to accept data, usually in a round-robin way. In addition it will be used forcon guration, system and data supervision and will host a graphical user interface. If a PC has
crashed, the load is taken over by the other PCs in a dynamic way and the PC is question is
automatically rebooted. All event working PCs 's have identical functionality. Their number iscompletely scalable and can be adjusted according to needs. The bu ered string-wise data willbe "pushed" to an idle event worker PCs roughly every 10{100 s. The Control PC also provides
a list of links to data belonging to the same trigger time stamp. In this way only pointers aremodi ed and the PCs are running in an \I/O-free" mode. The data are actually only moved in
the last step before writing the data to disk. Such a farm can be built based on today's standard
networking equipment.

7.4.8 Calibration Operations
Calibrations serve a crucial and central role in the operation of the IceCube detector. They
must, to the greatest extent possible, be automated. The present digital design allows calibrations to be carried out without any physical intervention to the data acquisition system. Thatis, all calibrations can be performed without disconnecting cables or physically re-con guring
DOM electrical data paths. However, while this is a necessary condition for fully automated,
unattended calibration operations, it is not a suÆcient one. Further design and detailed descriptions of operational sequences are still required for automated operations to become a reality.
While the following framework should allow such operations to take place, further discussions
are needed in order to insure their successful operations within the current design.

DAQ Calibration Operations The primary calibration operation carried out within the
DAQ system is that of synchronizing time bases for all DOMs with the GPS clock. This operation
will take place automatically once every 5 to 10 seconds. The actual nanosecond-level signaling
operations are performed by the DOM Hub and DOMs themselves. The DAQ's only role isin enabling such operations and supervising the dissemination of the calculated clock o setsfor each DOM to both the DAQ con guration data base and, through an as yet unspeci ed
mechanism, the Online system. The primary DAQ component involved at the supervisory levelis the string processor. Since all data leaving the string processor is corrected to UTC, this is
the rational point at which to control and implement needed time base corrections. All othercalibration IceCube calibration operations are based on analysis of data collected by a carefully
con gured, but normally operating DAQ. Therefore, these calibration operations fall outside thescope and capability of the DAQ and are, more properly, Online functions.

Online Calibration Operations In addition to the time base synchronization calibration

performed by the DAQ system, additional calibration operations are required for successful
detector operation. These include, but are not limited to, determination of individual PMT
155high voltage settings, determination of proper PMT trigger thresholds and measurement ofcable delays for all DOMs. As noted above, all of these calibration tasks are based on speci cdata analysis applied to the detector data stream. Therefore, these calibration operations areprimarily operating in the Online domain. In fact, they can all be considered to be part of a
special subset of normal data taking operations. It should be noted that some of these Online
calibration operations will produce data required for correct operations within the DAQ system.
In these cases, mechanisms must be in place for inserting these calibration values into the DAQ
con guration data base.
In practice, these operations can be automated and orchestrated by the main supervisory
program, experiment control. Experiment control can select a particular DAQ con gurationand instruct DAQ to begin operations. It can then select a particular Online con guration andinstruct Online to begin operation. With a suitable level of exibility at the experiment control
level, fairly complex sequences of calibrations can be carried out in an automated manner.

7.4.9 DAQ and Online Monitoring
Operations and Error Logging The design described in this document partitions systembehavior into a number of low-level tasks and assigns them to individual sub-systems. Furthermore, these sub-systems are organized together through a single experiment control sub-systemthat is able to orchestrate their operations into a single co-ordinated activity. While such adesign has been proven to be both exible and reliable, when problems do occur, the relatively\loose" connection between subsystems can make proper diagnosis diÆcult. A well-designed
operations log is a key tool in allowing rapid discovery and correction of individual sub-systemproblems.
All sub-systems will be able to log messages to a single, system wide operations log. Eachmessage will be tagged with the name of the sub-system as well as the time of entry. Eachmessage will also include numerical and text elds to describe error conditions as well as global
state information such as experiment control run number and state. While there will be provision
for one or more free form text areas, the format will include mandatory xed format elds tofacilitate automated searching in one of several modes. At a minimum, the log will be searchable
by sub-system, time and global run number. In practice, this operations log may be built on
existing open-source or commercial database technology.

DAQ and Operations Monitoring It is anticipated that, at least for purposes of detector

and data acquisition system monitoring, there will be a number of groups interested in having
independent and uncoordinated access to one or more software sub-systems at the South Pole.
As described earlier, design distinctions between monitoring requests and control commands willallow the use of robust, commercial-grade web server programs for a large portion of these userinteractions. Routing requests for monitoring data through a web server concentrates most of
the interactive data ow through a well-debugged program that acts as a bu er between o site data requests and data acquisition and on-line sub-system programs. Unfortunately, thismechanism is still subject to periodic and occasionally unscheduled communications outages
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between the northern hemisphere and the South Pole. Given the wide distribution of local timezones within the IceCube collaboration, this can create limited or, at a minimum, inconvenient
access to monitoring data.
With the interposition of a northern hemisphere server/cache gateway system, much of thedata acquisition and on-line sub-system monitoring data can be made available to collaboration
members at their home institutions during reasonable day-time hours. This gateway system
would be con gured to refresh its cache from sources at the south pole during times of expected
communications availability and serve these monitoring data les in response to browser andclient requests. During times of communications blackout between the south pole and northernhemisphere, collaboration members would be able to direct their browsers and client programs
to the gateway system and obtain current, within 24 hr, detector and sub-system status. Furthermore, if it were deemed necessary to restrict general collaboration access to South Polesystems, this architecture would provide a straight forward mechanism for distributing detector
monitoring information. Thus, up-to-date detector and data acquisition system performancedata is made available collaboration-wide on a best-e ort basis.
Portions of the monitoring and operational information will be needed for correct interpretation of data during later analysis. This can include current and cumulative trigger rates for all
trigger types as well as Event Builder statistics and gross DOM data rates on a string by stringbasis. There must be a mechanism for identifying and passing monitoring data from the DAQ
system to the Online system. This may consist of a separate data stream, or even the periodic
inclusion of monitoring data in normal data streams.

Online Components The Online system is essentially a carefully organized portion of theOine environment that has been targeted for execution at the data acquisition site under thecontrol of the experiment control sub system. It has three primary responsibilities. First, it is
the sole component responsible for copying the DAQ event stream from the shared disk system,
located on the Online LAN, to both archive storage (i.e. tape) and, via satellite, to the northernhemisphere. As such, it is capable of reformatting and repackaging data from the Event Builder
into those forms best consumed by oine analysis tasks. Secondly, it provides the frameworkand control mechanisms for executing any online lter operations used to analyze, reduce orreject data from any of the data streams emitted by event builders. And thirdly, as describedabove, the Online system contains lters and or programs that perform all calibration functions
beyond those of DOM time base synchronization performed by the DAQ system

7.4.10 DAQ Computing Environment
COTS Hardware and Software Components There has been a real e ort, during thedesign of both the DAQ and Online systems, to maximize the potential for using commercial,o the shelf (COTS) hardware and software components. At a minimum, this includes use ofopen source operating systems (namely, Linux), standards-based network and communications
software and PC-based computing platforms. Of course, we feel it also should allow for thepurchase of standards-based components as required. This can, for example, include purchase157

of PC clusters that have well engineered cooling and maintenance features or disk systems thathave extensive space management and diagnostic software packages.

String LAN Components As noted earlier, each string terminates in its own private net-

work. In practice, this network consists of a set of DOM Hubs and a single processor connected
to an o -the-shelf switched Ethernet hub. This design nicely encapsulates the entire string behind each string processor, which serves as the complete interface to the string. Based on system
performance, we may choose to have two or more strings share the same string processor. If so,
we need only increase the number of Ethernet attachments required for the commercial switchedhub.

String, Global Trigger, and Event Builder Processors Depending upon the degree towhich multiple OM strings can be accommodated on a single string LAN and processor, the
IceCube DAQ, when fully implemented, may have on the order of 50 to 100 processors. By
any measure, this is a substantial number of systems to house and maintain. When designinga system with such a large number of processors, several factors besides basic unit processor
cost must be considered, such as operation in a low humidity and low pressure environment
with an occasionally unreliable power source. Many vendors have addressed the ancillary issues
involved in con guring, operating, and maintaining large clusters of PC-based Linux systemsmost notably for use in the e-commerce industry. For these markets, vendors have addressedsuch issues as increased packing density (e.g. one processor per 1U rack space), improved
ventilation and temperature monitoring, improved, tool-free, modular repair capabilities, andnetwork-based remote diagnosis and control of individual processors. These systems typicallyhave a full, but limited set of disk, communications, and PCI resources. In determining thefunctionality and interconnections needed to implement both the DAQ and Online systems,
care has been taken to stay within the physical and logical constraints presented by these PC
cluster implementations.

Event LAN The data rates presently anticipated indicate that the communications network

used to connect all OM string processors with the single global trigger processor and multiple
Event Builder processors can be adequately serviced by conventional data network (100BT or
Gigabit Ethernet). As with the String LANs, this network is well bounded and only requires alocal switch-based infrastructure.
If these data rate projections grow beyond the capabilities of either 100BT or Gigabit Ethernet technologies, alternate, o -the-shelf solutions can be inserted into this architecture withoutmajor perturbations to the system design. In particular, we have investigated the Myricom
switched fabric inter-processor network as a potential solution.

Storage Systems and Online LAN As with network infrastructure, storage systems rep-resent an area where system data rates dictate the technical solution. The primary storage
facility shown in this design is that which provides the exible data bu er between the DAQ
158

and Online system partitions. This system design e ectively increases performance by providing
parallel computing resources for those paths with the highest data throughput rates. At thejuncture of the DAQ and Online systems, this implies a shared network-based storage systemwith multiple access paths to both Event Builder and online processors. The current aggregate
data rates indicate that a 100BT based commercial SAN (Storage Area Network) system willmeet the necessary storage and throughput requirements. As with the selection of processors,storage system selection should not be based solely on hardware costs. Most modern commercial
systems include system level features such as automatic mirroring, local automated backup andremote fault diagnosis and con guration tools. These facilities should receive high considerationin vendor and system selection.
As with the Event Builder LAN, the technical solutions are sensitive to the ultimate data
rates expected within the system. If the current projected data rates prove inadequate, consideration will be given to their e ect on the I/O bandwidth requirements of the shared disk
system. Alternate solutions with substantially higher throughput rates do exist - most notably
ber channel based SAN arrays. Since these storage systems use individual PCI interfaces anda separate switched fabric interconnect for all disk related data, the costs - as well as the data
throughput - increase dramatically.

7.5 AMANDA Data Transmission Techniques
For historical reference, we present here the data transmission techniques used in the past by the
AMANDA detector. The present AMANDA II detector has been deployed over several seasons,with a stepwise implementation of detectors with improved data transmission techniques. An
array of four strings (AMANDA-B4) was installed in 1995/96, with the OMs connected to thesurface by an electrical coaxial cable that transmits both the HV and the analog anode signal;
see g. 74, left. PMTs are operated at a gain of 109 to drive the pulses over 2 km of coaxial
cable without in-situ ampli cation. Hamamatsu R5912-2 PMTs with 14 dynodes are used toachieve the high gain; they require positive high voltage (HV) at the anode. The signal at thesurface is picked up via a DC blocking high-pass lter. The time-o set t0 is measured by sendinga laser-generated light pulse through an optical ber from the surface to a di user ball close
to the OM. The anode signal is considerably attenuated and dispersed by the 2 km cable, withtypical time over threshold of 550 ns and rise time of 180 ns. A correction for the amplitudedependent o set of the time when the signal exceeds a xed threshold (time slewing correction)
is applied o -line, resulting in a time jitter of roughly 5 ns. Coaxial cables have been replacedby twisted-pair cables for the 216 OMs deployed on six strings (strings 5-10) in 1996/97. Bothattenuation and dispersion were signi cantly reduced compared to coaxial cables. The rise timedecreased from 180 ns to 100 ns. Some test-OMs were instrumented to transmit analog opticalsignals through the laser calibration bers.
In 1997/98 the array was expanded by 3 test strings (strings 11-13) that used optical bers on
all OMs, both for calibration and for analog transmission of the PMT pulses. The main goal wasto evaluate this technology under realistic conditions and to compare various optical bers andoptical connectors. Electrical transmission was installed as a backup. The PMTs were operated
159

at a gain near 109 . Figure 74 shows the functionality of these OMs. The ber transmitting thecalibration signal from the surface penetrates the OM. The light is directed to the di user ball
via an optical splitter. The PMT anode current is converted into an infrared signal by an LED
operating at 1300 nm, which is transmitted to the surface where it arrives essentially without
dispersion. Optical bers, connectors and penetrators are more vulnerable to the high pressureswhen the hole refreezes than their electrical counterparts. For electrical connectors, the losses
were close to 10% for string 1-4 but, after using penetrators with an appropriate shape, thisvalue was reduced to 3% for strings 5-10. The failures of the optical connections have been, andstill are, about 10%, although half of these operate satisfactorily with attenuated amplitudes.
The advantages of the optical analog transmission compared to the electrical analog techniqueare: High bandwidth (rise time of 5 ns);
 Good double pulse resolution;
 Higher dynamic range due to lower HV;
 No correction for amplitude-dependent time slewing needed and, therefore, easier calibration;

 No pickup of electromagnetic noise, no cross-talk; Operation during drilling operations is possible.
The analog ber optic signal transmission became the default technology for the expansion
to AMANDA II.
Experience with AMANDA II has shown that before establishing analog ber optical transmission as an adequate technology for IceCube, the following improvements are required: 1)
the light transmitter, whether LED or laser diode, has to be operated with an independent andadjustable bias current, and local electronics in the OM must provide that function, and 2) ahigher current-to-light conversion factor must be achieved. This resulted in the dAOM (digitally controlled Analog Optical Module) concept. An alternate technical approach is the DOM(Digital Optical Module), which represents a departure from traditional AMANDA techniques
because the digitization of the PMT signal is performed under ice. The right part of g. 74 gives
a functional description of both. Both technologies were deployed and tested with the 1999/00
completion of AMANDA II.
The dAOM concept is depicted as second from right. A DC/DC converter in the OM
converts the 60V-supply voltage to the low voltage required to operate a microprocessor andother integrated circuits. The HV is generated by a Cockcroft-Walton generator, which is
implemented in the PMT base. Voltages between the cathode and the rst dynode, and between
the rst dynode and the anode, can be set separately. Slow control and reply signals areexchanged over the electrical cable. Also, an electrical analog signal is transmitted as a backup
to prevent a complete loss of signal in case of damage to the optical ber.
160

100 ns

100 ns

HV

60 ns

HV

control

control

+

t0

t0

60 V

+

t0

100 V

synchropulseslocal
coinc.

electrical
opticalFigure 74: AMANDA OMs (from left to right): electrical signal transmission, passive optical signaltransmission, active optical signal transmission (dAOM) and digital signal transmission (DOM).

161

Rightmost, the DOM is shown, which makes use of the same HV generator as the dAOM.
The waveforms are digitized in the OM and transmitted to the surface via the electrical cable.
Determination of the t0 o set and the synchronization between clocks at the surface and the
OM are done using the electrical cable. There is no need for a ber cable, which results ina savings of approximately $1.8k hardware costs per channel; other signi cant but less directsavings, such as 30 fewer plane ights, deployment simpli cations, etc., are also realized.
In the 1999/2000 season six strings (strings 14-19) with 42 (41) OMs each were deployed. Of
the 251 OMs, 189 use an improved passive, analog optical transmission system (with electricalback-up). The PMT anode current that drives the LEDs is now ampli ed in the OM by atransformer circuit. The HV is supplied from the surface. The rest of the OMs use DC/DC
conversion inside the OM. Twenty-three OMs were of the dAOM type, with 10 using LED transmitters and 13 using Laser Diode (LD) transmitters. Forty-one modules are of the DOM type.
The DOM modules have been equipped with LEDs and ber optic read-out for implementationin the AMANDA II DAQ. Both the dAOM and the DOM are operated at considerably lower
voltages than the standard analog OMs. They did not show any signi cant gain loss during theyear 2000.

162

8

Data Handling

Data from the IceCube sensors will be selected, reconstructed, ltered and analyzed to achieve
the scienti c goals of the project. The software used in this endeavor extends from rmware
deep in the ice, through the DAQ, to the Data Handling, and nally into the analysis. In thissection, we describe the Data Handling software and associated computing hardware.
The location of IceCube at the South Pole places special demands on what would otherwise
be a straightforward software system. First, the Data Handling software must provide robust,
fast and accurate ltering of the data in an essentially online environment. This is because
IceCube's high data rate from downgoing muons results in a large data volume in spite of a small
individual event size, and the satellite bandwidth for uploading data to the northern hemisphereis much too small to permit full raw data transfers. Second, the harsh environment of the South
Pole and its inaccessibility for about nearly 3/4 of the year mean that \winter-overs" must be
employed to maintain the detector. Since winter-overs will often not have expertise in all aspectsof the detector, the interfaces used to control and monitor the Data Handling system at the Pole
must be simple, user friendly, and battle-tested, and the associated computing hardware systems
must be reliable and fault-tolerant. Third, in the absence of a centralized laboratory facility, andsince the collaboration cannot meet as frequently as one might wish, it is crucial that interfaces
between various subsystems are very well de ned to allow for independent software development.
In sec. 8.1 we describe the general features of a Data Handling software system for the
IceCube detector, and demonstrate that these features are available in existing software packages,
or require no special techniques to custom build. Oine data ow is covered in sec. 8.2. The
various streams into which we divide the data are discussed in sec. 8.3, and the way it is organizedin sec. 8.4. Data latency requirements are described in sec. 8.5, and sec. 8.6 gives an outline of
the schedule for implementation of the Data Handling system.

8.1 System Elements
IceCube data is similar to that of other high-energy and astrophysics experiments. In particular,
the concept of uncorrelated triggered events allows us to reuse many of the tools and concepts
of other projects. More generally, the IceCube data handling system can be built with current
technology. The main elements of the Data Handling system are: software management;
 system engineering; development environment;
 analysis framework; database; visualization;163 development interface; integration at the Pole; hardware; data distribution.
These elements are discussed in the following subsections.

8.1.1 Software Management
The complexity of IceCube software and the dispersed nature of the IceCube collaborationstrongly suggest the use of standard software management practices to organize communication,
manpower, money, and project reviews. Industry software project management practices will
be followed to implement the IceCube software.
Project-wide software management has several broad areas including oversight of: the DAQ real-time system, the Data Handling framework and database tools, the development of simulation, trigger and lter algorithms.
A common development environment and software architecture will be most eÆcient for both
implementation and long-term maintenance.
Interfaces will be de ned between subsystems and testing procedures established. Software
professionals will be employed to build the database and network programs. Physicists will
likely implement many of the procedures. To ensure robust operation, software consultants will
be involved at every stage{the design phase, a construction or development phase, and nallya maintenance phase{and perform regular reviews of the code. The data will be stored formany years, and the analysis is anticipated to continue for up to 15 years. Long-term software
maintenance must be considered.

8.1.2 System Engineering
System engineering involves identifying the most logical set of subsystems and specifying completely all interfaces between them. In broad strokes this de nes the structure of the software
project. Subsystem speci cation will then occur in parallel by people with appropriate software
skills. The speci cations will be reviewed to ensure overall system integrity.
A uni ed architecture minimizes the number of people needed for development and more
importantly, long term maintenance. The main cost of architecture is in the initial stage ofsystem engineering. Common interfaces will be used by all subsystems. Single implementations
are easier to maintain and more exible to replacement. In long-term projects, exible application program interfaces (APIs) can be re-implemented as commercial products become old andbetter options become available.
1648.1.3 Development Environment
A development environment is used to support the software development. Design tools, debuggers, etc. are needed in all stages of software development. In addition, both code anddocumentation need to be added, removed, and modi ed in an organized fashion by all developers. It is especially important for developers in di erent subsystems to be able to discuss themeaning of the speci cation and modify it as needed in a rational system. To save in overhead
a common development environment will be used to implement IceCube software.
Design packages such as Rational Rose [162] or SourceForge [163] provide visual modelingtools which are useful for creating a blueprint of the software architecture, a critical rst step inthe design of a complex software system. We will evaluate such tools to determine which, if any,might suit our needs. If we opt for a tool that the collaboration is not familiar with, it will be
important to provide training in its use. The freeware GNU debugger GDB, the GNU compilers
for FORTRAN, C and C++, the source code manager CVS and the release management anddistribution system based on RPMs are all standard in the physics community, currently in
use in AMANDA, and meet our requirements for ease of use and e ectiveness. Tracking anddistribution of important design and technical documents can be accomplished with existing
packages, such as the commercial EDMS system used at CERN [164].

8.1.4 Analysis Framework
The framework is used to de ne how users interact with pieces of data. It is a set of rules andmethods for selecting data, applying algorithms and adding new information to the dataset.
Several frameworks are under consideration including the CERN packages Gaudi, LHC++ andRoot [165]. Importantly, these packages will be supported over the lifetime of IceCube.
Implementation of the framework for IceCube will include a exible API to event, calibrationand monitor data. Time correlation of these types of data will also be provided by the framework.
For example, this allows an analyzer to correlate measurements of the South Pole environment
with physics data. Data objects are stored in memory so that all algorithms act on the samedata. The input data is protected from corruption by making copies of it as deemed necessary.
The framework also supports an arbitrary number of modular algorithms through a standard
API. Algorithms may add or remove data from the data stream. A standard set of options ismade available to select needed operational modes.
A users manual including documentation to the APIs is provided to ensure optimal user
access to the data. Except for visualization components, all components support execution via
batch mode.

8.1.5 Database
Organizational elements in the data sample are supported by one or several databases. Calibration, le/stream organization, and possibly event data are organized using database tools.
The calibration and monitoring database contains all the information needed for reconstruction, simulation and analysis (like geometry, PMT gain, and OM status) but also slow control
165

information, hardware con guration, trigger status, and an electronic logbook. This databaserequires and is optimized for fast access through APIs by the software on the basis of the event
time stamp. Quantities needed, for instance to de ne an OM status and calibration, are de ned
by a starting time and a validity time range. Its size, which depends on system stability and ourchosen time granularity, is small enough to work on local copies regularly distributed to slavenodes. Access to the master copy is, of course, write-restricted. Multiple calibrations can be
performed and checked with possibility for rollback.
A similar approach has been successfully developed and implemented for AMANDA-II using
MySQL. Relational databases are well-suited for this kind of conditional (temporal) database.
Many database managers using SQL exist and are well-tested. Commercial products like Oracle
provide in addition a high level of security, advanced developing and managing tools and permit
object-oriented interfaces to user software.
The le/stream organization database contains the complex data sample/stream organization. The large number of chunks into which data are sliced requires a database (most probably
relational) to speed up random access of events. Placing the full sample of events in a large
database is under consideration. For this kind of application, object oriented database management systems (ODBMS) like Objectivity are probably best suited and are used by large
HEP experiments in the US (Babar) and Europe (the current choice of all LHC experiments at
CERN). However, one must keep in mind that IceCube has a large number of events of small
size and a simple event and detector structure. As a consequence, requirements are quite different from those needed for accelerator/general purpose detectors. ANTARES, which is quite
similar to IceCube, uses Oracle, a relational database management system (RDBMS), insteadof Objectivity. Yet another possible option is one of the object-relational database management
systems (ORDBMS), like Oracle 9i.
The strong points of the ODBMS approach are: the database mirrors the structure of eventsand objects in the software, links and relations between objects are easier to modify, a lot oftools have already been developed by the HEP community, the user does not need to know
where the data are physically located, and physics is done by event tagging instead of the usual
miniDST/Ntuple strategy. On the other hand, there are also strong drawbacks to an approachthat relies heavily on network performance and introduces large overheads which do not scalewith the database size. Large-scale realistic tests are necessary to check that for IceCube where
simple, well-tested solutions exist for event handling, this kind of ODBMS solution would confera true bene t.
The database is designed so that it can be interfaced to and used for online, oine andMonte Carlo reconstruction and analysis. In any case, the physical organization of the database(internal tables, physical location on disk/tape) is designed to optimize data access. Graphicaluser interfaces and histogramming facilities to display and study database contents are provided. An adapter layer of software is used to plug the database into the analysis framework.
Improvements in commercial databases and the support of a few carefully chosen le formats
are expected to result in several database implementations and adapters. The framework anduser interface are isolated from changes in the details of the database implementation via theadapters.
166

Benchmark tests were performed (using Linux on a 700 MHz PII and using TrueUnix on
a 500 MHz Alpha) using a simple relational data base manager like MySQL with a 300 MB conditional (temporal) data base (corresponding to about six years of IceCube calibration/monitoring).
Mean access time, based on a user key like \instant of validity" ranged from 0.5 to 5 ms for
random search on randomly generated data depending on the cache state, demonstrating thefeasibility of this approach. If it is decided that the full event sample is also stored in a database,the size of the sample may reach many terabytes (even after selection of a given physics stream).
Even if careful organization of the data structure can keep the space overhead small, time overhead and data transfer time can become very large. Since database managers like Objectivity
do not scale simply with the size of the data sample, large scale tests have to be performed
before adopting such a solution.
Projected sizes of the individual database components are as follows: Calibration: 4800 OMs  200 bytes  5 calibration types  5 times/year: 25 Mbytes/year.
 Monitoring: About 10 of AMANDA's 700 OMs change status each day. Extrapolating
to IceCube with 4800 OMs, conservatively assuming that OM stability does not improve,
about 50 will change status each day. Assuming a status change is described by 60 bytes:
2 MB/year.

 Slow control, con guration, trigger status: 1MB/year.
 Electronic logbook: 10 MB/year.
 File handling management: 200 bytes to describe le  160 les  360 days: 11 MB/year.
8.1.6 Visualization
Software tools will be provided to display the data in several forms:

 Dump events to screen in text format.
 Plot statistical distributions (PAW style).
 3-D event visualization.
 Monitor plots showing trends in time.
8.1.7 Development Interfaces
Collaborators are anticipated to interact with the software at some level either as algorithm/ lter
developers or as users of the visualization packages. Developer physicists will have access to user
manuals and local experts to aid in their work. Visualization packages will have user manuals,
and commercial products will be used whenever possible to minimize the amount of specialized
knowledge needed to work with the data.
167

8.1.8 Integration at Pole
Operation of the detector at the pole requires all processes be directed by an experimental control
process. The online lters, trigger, disk, tape and satellite bandwidth need to be implemented
within this system. Embedding the framework modules and data access (not necessarily natively)
into the South Pole system is crucial to the smooth operation of the detector.

8.1.9 Hardware
Computers and storage are needed both at the Pole and in the northern hemisphere. A clusterof roughly 50 CPUs (with 1 GHz processors) is needed to satisfy the peak demand for quick
turnaround post-deployment calibrations, and the steady-state demand for reconstructing andltering 1.5 kHz of events. This cluster provides suÆcient peak processing power to keep pacewith deployments, and allows an ample 33 ms/event of processing to reduce the data by afactor of 30 down to 50 Hz. Several additional machines are needed at the Pole for satellite
transfer, tape backup and disk cleanup. Four terabytes of disk is needed at the Pole for storageof thirty days' worth of raw les. A total of 500 tapes (at 100 GB/tape) is needed to store
the full raw data sample each year, and 50 additional tapes for backing up the ltered data.
In the northern hemisphere, the ltered and raw data are stored for > 15 years at 2 TB/year
and 50 TB/year, respectively. A disk archive of 60 TB will be needed to cache 15 years' worth
of ltered and simulated data. Several clusters totaling 300 CPUs (with 1 GHz processors)
are needed to support the oine analysis. This cluster is used for data reorganization for thearchive long-term access, additional reconstructions and lters, and simulations of backgroundand signals.
The data from the Digital Optical Modules (DOMs) is transferred to standard 100BaseT
network hardware once reaching the surface. From this point on requirements for computing,networking, and storage can be met by commercial hardware. The design of data ow in the
hardware is modular, allowing for scalability and maximizing robustness. It is possible to makeestimates of upper limits on data ow rates, and it is found that presently available commercial
hardware will be adequate.
Once the data signals from the OMs are being transferred to a standard network, a cascading
design of switches with redundant paths will be used. At 10 Tb/day transfer rate current 1 Gb
Ethernet has orders of magnitude higher capacity than what we anticipate IceCube will requireon average (tested using the NFS protocol).
The operating conditions at the South Pole dictate that certain measures are taken to ensure
performance equal to a more standard working environment. The IceCube system is operated on
UPS (Uninteruptable Power Supply) systems. This protects against transient power anomalies,
and provides a grace period for controlled system shutdown if a power outage lasts longer thana user-speci ed period of time. Due to the high altitude at the South Pole, the e ectivenessof air cooling systems is reduced. Most computer components are not speci ed to operate at
this altitude. Also the very dry environment results in large static build up. Experience has
shown that by using more aggressive cooling systems, careful anti-static handling techniques,
168and routine discharging by numerous grounding strips, the same level of performance can beachieved as in a normal working environment.
Because of the physical isolation of South Pole for almost 3/4 of the year, and the limited
personnel available during this period, the standardization of hardware with the support contractor to NSF is essential to obtaining the maximum level of mutual technical support, andeÆciency in stocking spare components. This attitude has already been adopted by AMANDA
and has been shown to provide many advantages not only to the science project, but South Polesupport crew.

Storage The choices for large data storage are expanding rapidly with options such as Snaple servers, IDE RAID, FireWire disks arrays, and the more traditional SCSI RAID disk arrays.
The system most suitable for IceCube is the SCSI RAID array. This system provides adequate
storage size, reliability, and transfer speeds. A major advantage is that the main components, the
SCSI disks, are standard throughout the whole systems. With the introduction of the Ultra 160
72 GB disks, arrays of 8 disks giving an overall size of 500 GB (access rates greater than 10 MB
per sec through an NFS mount), or 4 days of uncompressed raw data. Two such arrays would
be adequate for storage of raw and ltered data. Arrays such as these are highly reliable with
hot swappable disks and power supplies resulting in operation being continuous even throughhardware failures. Another advantage of using SCSI is that the tape drives have access to thedata on the same bus, resulting in very high data transfer rates. Similar units are used as caches
along the data ow chain to guard against data loss if the data ow is interrupted. All Data
Handling hardware, including CPU, disk and tapedrives, ts into three standard-size racks.
Due to the unreliable nature of the satellites available for use at the South Pole, all ltereddata is backed up on tape in the unlikely event that this data will need to be physically transferred
north. Also, to guard against the possibility that a future technique requires re- ltering, tapecopies of the raw data are made. Currently available tape technology such as SDLT (Quantum
SDLT, 110 GB raw data at 22 MB/sec) is adequate for the maximum expected data rate of
130 GB per day. Using an array of 4 tape drives gives roughly one week between operator
interventions. The ltered data and raw data are stored on separate tapes.

CPU Cluster Once built events are on disk storage they need to be ltered. This requires

large amounts of CPU power and a means of controlling the priority of the ltering and otherimportant tasks. This is a problem that the High Performance Computing community has
been addressing for many years and a number of batching and load equalization systems areavailable. A system that is widely used, and which suits this situation well, is PBS (Portable
Batch System). This is a very exible system with a very large user base. It will give priority
control over jobs, as tasks such as post-deployment calibrations and monitoring are given highpriority, and ensures optimal use of the CPU resources. A large cluster such as this is accessed
via one control node, with the rest of the system being easily expanded as required by the
expansion of the detector, and or the use of more advanced ltering techniques. Very powerful,compact and inexpensive clusters are now available using dual CPU 1U rack mount machines.
169

The long period over which IceCube is installed and operated means the consequences oftechnology advances need to be considered. Such advances in the past have resulted in increased
system performance at reduced cost, and size. More recently there has been a strong focus on
increased energy eÆciency and robustness. Thus, all future advances in technology work in thefavor of IceCube, and restraints imposed by current hardware speci cation will only be relaxed
and limited resources such as power and space will not be greater than what is estimatednow. By standardizing on speci c vendors early, upgrading hardware will be feasible and asstraightforward as possible.

Hardware Monitoring Monitoring of the performance of the detector can be divided into

two sections, the hardware health, and the state of physical characteristics of each device. The
hardware layout of the detector is very modular, with only a few basic units being used. The
characteristics of these basic units depends on their function. Disk storage has characteristics
such as total storage used and available, and rate of change. The performance of networking
devices can be measured by connectivity and response times. CPU nodes have characteristics
of both a storage and a network device.
Modern hardware has the ability to monitor the physical health of a device, usually througha system monitoring bus. The Linux OS has software written to access this information, making
it possible to quickly monitor CPU loads, temperatures, cooling systems, and power supply
voltages. Other devices such as network switches use messaging protocols such as the traditional
UNIX syslog system to make this information available.
As with other monitor information, the hardware status information will be entered into thedata stream. A hardware monitoring process, as part of the overall monitoring package for thedetector, will extract these packets of monitoring information from the data stream and display
them in a graphical manner. Many such graphical systems already exist with features such as
visual highlighting of system states and problems. During the hours of network connectivity
to the South Pole, users will be able to examine the state of the detector as a function oftime. This information will be regularly synchronized with a server which is always available fordetailed examination both at the Pole and elsewhere. On-site users will be immediately noti edof problems through an email pager system.
With the implementation of IceCube being over a period of years, it will be possible to test
performance estimates of the system as it is scaled up. This will allow for adjustments andcorrections before full operational mode is reached.

8.1.10 Data Distribution
Filtered data is transferred via satellite to a single location in the northern hemisphere. From
there it is automaticaly copied via the internet to a designated IceCube institution in the US,
where one or more backup copies are made and a standard set of data quality checks are
performed. Checks are made to ensure that all the data from the Pole has been transferredcompletely and correctly, e.g., through use of checksums. Further tests investigate the qualityof the data itself. Some of these tests are exactly the same as those performed at the Pole170

to further check the integrity of the ltered data transfer. Other more detailed tests are also
performed (these tests have not yet been de ned).
The data is then copied via the internet to a few designated distribution centers in the US
and Europe and additional tape backup copies are made. Ultimately, all the ltered data, at
2 TB/yr, reside on disk at each institution (or at centralized facilities shared by a small groupof institutions).
The tapes of raw data are shipped north from the Pole at the beginning of each season toa location where at least one full copy is made. Each copy is stored at a di erent locations in
Europe or the US for added safety.

8.2 Oine Data Flow
The DAQ system depicted in g. 73 deposits data of several di erent origins into a disk cacheat the South Pole. Triggered events with a size of about 1.0 kB are collected at roughly 1.5 kHz
and are intermingled with monitor and calibration data. Triggered events are dominated bydowngoing atmospheric muons. These gures can be used to estimate the total data from thedetector: 130 GB/day or 50 TB/year. Since the satellite bandwidth is 12 GB/day, we must
reduce the data volume by roughly an order of magnitude at the Pole. This reduction will
be accomplished with specialized lters. The hardware required to implement these lters is
described in sec. 8.1.9. In addition to the ltered data, we will also send monitor data andcalibration data over the satellite. A sketch of the Data Handling system is provided in g. 75.
Note that during the six-string rst year, all raw data will be delivered to the northernhemisphere over the satellite for analysis and lter development, and taping at the Pole will
only be used for data backup. The required bandwidth is estimated from the fraction of strings
relative to the full IceCube detector and the estimated IceCube un ltered raw data rate: 6=80 
130 ' 10 GB/day. (AMANDA-II will also require satellite bandwidth of about 2 GB/day; thetotal required bandwidth remains below 12 GB/day.) Transferring the entire un ltered raw data
the rst year gives the software developers additional time to develop a coherent system, and inparticular to develop the robust online lters which will be required in all subsequent years.
A pre- lter raw data cache will hold 2 days' data so that correlations with GRBs and otherexternal triggers can be studied. The post- lter cache needs to hold at least a week of data tohandle failed transfers and satellite down times smoothly. We will avoid continuously saturating
the bandwidth every day to further ensure that the transfer process can catch up with thedata taking in a reasonable amount of time. Prioritizing data for transfer may be useful during
recovery period.
After transfer, the ltered data will be cached for the inde nite future in a mass archive.
Expected data size is 2 TB/year plus a comparable amount of simulated data. Additional
processing will be provided as necessary to support the analysis working groups' access needs
and use of the data. The CPU requirements for IceCube simulations are estimated from thedesire to simulate a reasonable fraction of the background (e.g., 20%), and from an estimated
1 s/event IceCube simulation time. Table 11 lists bandwidth, CPU and diskspace requirements
for IceCube. Data which is not transferred over the satellite will take over a year to receive171Process
event builder
Pole lter
online calibration
satellite transfer
simulationoine processing

approx. output 1-GHz CPU
bandwidth
requirements
1.0 MB/s
1
50 kB/s45
25 MB/yr5
12 GB/day
1
n/a
300< 50 kB/s
50

Cache (cache type)30-day raw (FIFO)
30-day ltered (FIFO)
ltered data archive (permanent)
simulated data archive (permanent)

cache size
4 TB
330 GB
2 TB/year
2 TB/year

Table 11: Bandwidth, cache and CPU requirements for IceCube data handling. Note that theonline calibration uses 5 CPUs only for the deployment period.

172

CPU Cluster
for Calib. & Filtering~50GHz of CPU

130 GB/day

String Processors

Raw Data
Tape Backup

Raw Data
Cache
4 TB

Event Builder

DataBase

SystemControl
11 GB/dayMonitoring
Interface

FMCG
Data
330GB

Satellite
TX Control
FMCG: Filter, Monitor,
Calibration, GRB

Trigger

Non-continuous fastsatellite and slow 24/7
Iridium access

FMGC Data
Tape Backup

SN, GRB, Ext. Trigger

Figure 75: Diagram of the IceCube Data Handling system at the Pole. Arrows indicate direction ofprimary data ow, with data ow volume as indicated. The raw data is cached for lter processing andto permit extraction of raw data coincident with GRB (and other external) triggers. External triggers
may arrive at any time if Iridium access is available. Raw data is permanently recorded to tape. Filter,monitor, GRB and calibration (FMGC) data are bu ered to a small disk cache and transferred via
satellite link to the northern hemisphere. With Iridium access, monitor data can also be uploaded to thenorthern hemisphere. FMGC data is also backed up to tape at the Pole. (See g. 73 for a diagram of
the upstream DAQ system.)173

from the Pole, archive and lter. Since it is highly desirable and certainly feasible to perform
ltering at the Pole, we are concentrating our e orts on such a system. There are several bene ts
which accrue from this decision. First, the data analysis can begin essentially right after data istaken, more than a year sooner than otherwise. Second, priority is placed on looking at the data
immediately so that problems are detected and xed promptly. Finally, we are concentrating oure orts on a single system from the start. To avoid having to re lter this data, it is imperative that
this system works reliably. Note that the scenario in which ltering occurs only in the northernhemisphere has its own serious downside beyond its inherently longer latency: computing needs
grow overwhelmingly large if we demand reasonably fast ltering turnaround times.
Tapes are used at the Pole to backup ltered data in order to deal with possible long-term
satellite outages. Tapes are also used at the Pole to make copies of all the un ltered raw data.
All data written to tape is checksummed to help ensure data integrity.
In the northern hemisphere, the computing constraints are similar to those for any large
computing project. Data samples of about 2 TB/yr are archived in a mass storage system foraccess. Distributed data needs to t on user's facilities at their home institutions. Processing
power needs to be somewhat centralized for big projects and otherwise distributed for accessibility to the analysis. Expensive software tools or licenses need to be purchased in such a waythat all collaborating institutions can participate fully in the data analysis.

8.3 Data Model
The signal data will be separated with good eÆciency from the downgoing muons using just a
few selection criteria. These criteria are desiged to include overlaps between the ltered data
sets to ensure that no valid data is lost. Table 12 lists a set of tagged data samples that are to be
extracted at high eÆciency from the downgoing muon background and the approximate satellite
bandwidth required for each one. A short description of these samples follows in order to givecorrespondence between the data samples and the analysis topics. The purpose of describing
the samples is not to solidify their description, but rather to indicate the level of background
reduction we believe is necessary for this data model to work. Final available satellite bandwidth
will not be known precisely for some time, and event size and event rate can only be estimatedat this stage, but table 12 is suÆciently accurate to guide design work.

8.3.1 High Multiplicity
The IceCube trigger system will probably include some sort of majority trigger in which somenumber N of time-coincident hits re the trigger. For some M > N , the trigger rate is suÆciently
low to t within the satellite budget. This sample is otherwise un ltered. It supports the search
for new physics at the highest energies accessible to IceCube. The other physics samples are
devoted to the lower-energy analyses.

174

Data Samples
Full Raw
High Multiplicity
Upgoing Tracks
Cascade/tau
GRB downgoing Muons
IcetopSupernova
Prescaled Raw Data
MonitorCalibration (from in situ light sources)
Full-sky Summary Histograms
Total

Required Tape
Bandwidth (GB/day)
130
4.0
1.5
3.0
1.0
2
0.1
0.5
0.1
0.1
0.5
130 + 13 = 143

Required Satellite
Bandwidth (GB/day)
4.0
1.5
3.0
1.0
0.1
0.1
0.5
0.1
0.1
0.5
11

Table 12: Summary of IceCube Data Samples designed to support the science goals. The two rightcolumns indicate the tape and satellite bandwidths budgeted to each sample at this very preliminary
stage.

8.3.2 Upgoing Tracks
Upgoing tracks are typically muons originating from neutrino interactions in or below the instrumented volume. Upgoing tracks can be selected by zenith angle after a quick reconstruction.
Tracks may be triggered via either a global multiplicity trigger or a string multiplicity trigger.
Candidate upgoing muon tracks need further requirements imposed, such as a minimum
path length that is greater than the string spacing, and a zenith angle > 80Æ . The \line t"
angular resolution for short tracks is not good enough to reduce the misreconstructed backgroundsuÆciently. However, recent improvements in the speed of the likelihood reconstruction makeit possible to include it in the Pole Filter. With a resolution online of roughly 2 degrees,
misreconstructed background is eliminated much more eÆciently. A similar cut on AMANDA
data reduces the data by a factor of 100: (130 GB=day)=100 results in < 1:5 GB/day.
Events triggered by a string multiplicity trigger select nearly vertical tracks at lower energy
than the previous selection. Additional selection criteria are a veto on activity elsewhere in thedetector and timing pro les near the speed of light.

8.3.3 Cascades/Taus
Cascades are the result of electron-neutrino interactions and neutrino neutral-current interactions. IceCube triggers on them using some type of multiplicity trigger. Evidence that the events
contain a core of light due to the large number of charged particles in the shower is required toseparate them from the downgoing muons. Cascade energies need to be suÆcient to light up
several strings for analysis purposes.
175

Cuts on the spatial extent of the charged core may be used provided tau detection eÆciency
remains high. The high energy cascades, one of which is displayed in g. 24, are of suÆcientenergy to be included in the high multiplicity sample. This sample is dedicated to the lowerenergy cascade analysis.

8.3.4 GRB Downgoing Muons
To study Southern Hemisphere GRBs, one needs to keep all downgoing muons for a 10 min
period around the GRB time. At the South Pole it takes a day or two to receive the GRB
trigger times from other experiments, so the raw data needs to be cached for a minimum of
2 days. One external GRB trigger per day and saving 10 min of raw IceCube centered aroundthe external trigger time corresponds to 1 GB/day required bandwidth out of the Pole.
It will be some time before another satellite is launched to provide these data as frequently
as once per day. The next generation experiment may have a higher GRB noti cation rate. For
the rst few years, therefore, we expect the IceCube GRB bandwidth requirements to be muchless than 1 GB/day.
A recent paper by Waxmann suggests that once every 40 years a supernova is close enoughto produce about 100 muons in IceCube shortly after the event. Presumably this event would
be very bright and we could search for it in the same way that we search for GRB.

8.3.5 Icetop
The IceTop array detects high energy cosmic ray shower events. These events typically havehigh multiplicity and are expected to include waveforms. Their estimated raw data rate is
1{2 GB/day, reduced to 0.1 GB/day after ltering.

8.3.6 Supernova
Supernova are expected to produce a large number of low energy neutrinos. The experimental
signal is an increase in all the PMTs of about 100 photons over a 10 s period. This analysis
requires us to record the PMT noise rates in 10 s bins for the duration of the experiment. This
adds up to about 0.1 GB/day.

8.3.7 Prescaled Raw Data
A minimum bias sample of prescaled downgoing muons can be used for geometry and timing
calibrations, to monitor detector stability, and as a test of background rejection algorithms usedin other analyses. Taking this data at 4 Hz yields a data sample of 0.5 GB/day.

8.3.8 Monitor
Monitor data is used to measure the quality of the data and verify the stability of the detector
over the lifetime of the experiment. Types of monitor data that we considered are: trigger, lter,
176

and reconstruction rates, temperature sensors, DOM RAP jitter, PMT gain, risetime, peak-tovalley, occupancies and noise rates, network activities, system deadtime, building power, UPS
status, local weather conditions, and station parameters such as satellite status, drilling, andairplane landings. Measuring the DAQ related quantities once every 10 min seemed suÆcientand contributes about 1.5 MB/day for each item monitored on 4800 PMTs. The 1 GB/day
bandwidth allows us to measure 600 such quantities. Many quantities are recorded much lessoften, and some have fewer than 4800 channels.
There is no reason to limit the monitor data to activities at the Pole. The software is also
designed to include monitor data from any post-processing lters as well. We will build on the
AMANDA experience to implement a web-based monitoring interface and electronic logbook
for IceCube.

8.3.9 Calibration
This sample consists of data from in situ light sources. This kind of data is triggered event
data, although several di erent triggers may contribute. Triggering either from the light pulse
or with coincident hits is possible. Our other calibration source is downgoing muons which will
be available in the prescaled raw data.
Other calibrations, such as PMT gain and eÆciency, may be generated in real time in the
DOM rmware, and as such will already exist in the data stream. These calibrations need to
be extracted and analyzed oine.
From various sources, calibration constants are compiled and stored for use by the reconstruction. Since constants may be modi ed as the analysis improves, a database implementationis the obvious preferred choice with version numbers to keep track of what has been done.

8.3.10 Full-Sky Summary HistogramsHigh energy photons are predicted to send showers deep into the ice, triggering the IceCube
detector. Since this analysis requires sifting through every downgoing muon that triggers thedetector, it would be too cumbersome to achieve without a prede ned histogramming of the data.
Full-sky summary histograms are therefore created every few minutes, resulting in 0.5 GB/day.
From these histograms energetic point sources in the Southern Hemisphere may be discovered.

8.3.11 Un ltered Raw
After the rst year, all un ltered raw data is written to tape at the Pole, hand-carried out of
the Pole at station re-opening each November, copied and stored in at least two locations in thenorthern hemisphere. The limitations on the use of the raw data are described in sec. 8.4.

8.4 Data Sample Organization
Several tagged samples will be bundled into one \physics" stream. The physics stream includes
the monitor, high multiplicity, upgoing tracks and cascade/tau data. They are distinguished177

from one another by virtue of, for example, a set of bits in each data record's header. An actual
data event, for example, may have both the bits corresponding to the high multiplicity andcascade/tau tags set. Monitor information has the monitor bit set, etc. It is a requirementthat data from one of the above streams can be time-correlated with data from any other of theabove streams. One possible way to implement this is to have all the data time-ordered andresident in one le, but other implementations are certainly possible. Time slicing may provevaluable as well. In this scenario, the data are sliced into chunks representing a short lengthof time (something like 10 s or 10 min). A database can then catalog the chunks, speeding up
random access to the events.
Several obvious advantages accrue from this \bundled data" scenario:

 Monitor data is available at analysis time from within the same program used to analyze
data, so one can imagine plotting not only (say) zenith angle of selected events, but also
noise rates measured at roughly the same time the event occurred in the detector.

 There are not multiple types of les which need to be transferred from pole; the system issimpler overall.

 Prescaled raw data is also available at analysis time, making background estimation andmonitoring detector performance with downgoing muons easier.

The size of the les is dominated by tagged physics events, so the additional data volume of themonitor data, prescaled raw data, etc. does not substantially increase overall le size.
An important point here is that we are saving the full raw data stream. In the six-string
rst year, the raw data are transferred over satellite for analysis and lter checkout. After thatit grows too large for the satellite bandwidth, and we plan to copy it at the Pole onto tape.
The estimated size of this sample is 50 TB/yr. The tapes are mainly envisioned as an insurance
policy and we are only allocating resources for their archiving and no additional resources fortheir use. If a collaborator comes up with a compelling new analysis idea which requires data
not present in the various ltered data sets, the rst step will be to develop a new lter andinstall it at the Pole. In this way, current data is used to validate the new idea. After the newidea passes this test, the collaboration may decide to obtain the signi cant additional resources
needed to re lter all the raw tapes.

8.5 Latency
Latency is de ned as the time between when an event is triggered and when it arrives on an
analyzer's disk. Data from the main analysis tags (high multiplicity, upgoing track, cascade/tau)should have a 1-2 week latency, which includes possible further processing/ ltering in the north.
Monitor data should have a latency of less than 24 hrs. Supernova data should have as close tozero latency as possible. One way to implement a very short latency time is to use the Iridium
system (if it remains available). Data volumes for supernova triggers are small enough to makethis feasible. IceCube can then be a full- edged participant in SNEWS, the Supernova Early
Warning System [48].
178Possible uses of 24/7 low-bandwidth coverage beyond SNEWS include IceCube monitor data.
This would have the clear advantage of allowing us to keep close track of detector performance,
including during times when the winter-overs would be sleeping. This coverage would also bevery handy for small system maintenance tasks and for sending alarms to to the winterovers.
Obviously, the South Pole becomes much less remote with this kind of coverage.
After the rst six-string year, the full raw data has a latency of at least a year, corresponding
to the movement of tapes from the Pole to the north. For IceCube design purposes, the latencyof this data sample should be considered in nite since the resources needed to use it are not in
the current budget.
Another latency issue arises due to calibration constants (e.g., geometry) which will beneeded by the Pole lters. We envision three categories of constants:

 initial constants: Within 2 days of deployment, crude constants should be available for theoperation of the string. An example of this would be OM locations from drill logs.

 on-line constants: Within a week or two of deployment, the results of in situ light sourcesand downgoing muons need to be included for stable data taking.

 oine constants: As the analysis requires, constants need to be included in the database.
Multiple sets can be supported with the use of version numbers.

8.6 Schedule
IceCube construction will take a number of years. A simpli ed rst-light data model is usedconsisting of only a multiplicity stream, calibration and monitor data. The multi-sample modes
and full online ltering machinery are realized in the second year of operation as more strings
are deployed and the un ltered raw data rate outstrips the available satellite bandwidth.
Software subsystem development must be prioritized, so that the rst year's data is handled
without having to deviate dramatically from the overall system design. We need to develop
much of the infrastructure in the rst year. De ning APIs completely enables us to produce
needed subsystems without recoding later.

8.7 Summary
The IceCube Data Handling software system, though far from trivial, can be constructed using
existing software tools and methods, and it can be realized using existing commercial hardware.
To fully design and implement a reliable and robust system in time to analyze the data from the
rst six IceCube strings will require a substantial software design e ort which is best managed
by professional software engineers with experience in large scale projects like IceCube.

179

9

Data Analysis

9.1 Introduction
The main goal of the IceCube data analysis organization is to bring analyses to publication as
quickly as possible while maintaining the highest possible scienti c standards. To achieve thisgoal, the organization strives to ensure the infrastructure needed for analysis is provided andmaintained, to use analysis manpower resources in an eÆcient and fair manner, and to overseeand streamline a rigorous internal analysis review process. Analysis infrastructure includes thethree broad areas of detector calibration and data quality, signal and background simulation,and event reconstruction, and three working groups are formed to oversee these areas. Analysis infrastructure also includes computational resources, and large and small computer clusters
are employed for data distribution, analysis and simulation purposes. Analysis manpower isorganized into ve separate working groups, each of which contains several separate but related
analyses, so that ideas and methods can be shared easily among similar analyses. An Analysis Coordinator oversees the activities of all the working groups. The internal review process
is managed by the Analysis Coordinator who, in consultation with the Collaboration Board,
appoints a small committee responsible for bringing an analysis from the rst draft stage to
publication readiness and collaboration-wide approval.

9.2 Analysis Infrastructure
The analysis infrastructure is designed, constructed and maintained by three working groups,
each led by its own Working Group Coordinator (WGC). The coordinators are responsible for
ensuring that his/her group's responsibilities are ful lled and for maintaining communications
with one another and with the Analysis Coordinator. These working groups are as follows: The detector calibration and data quality working group; The simulation working group; The event reconstruction working group.
Given the vital importance of these tasks, both for performing viable analyses and for engendering a deep understanding of the IceCube detector, the associated workload is shared across thecollaboration, and each institution is obliged to contribute manpower to one or more of thesegroups.

9.2.1 Calibration Analysis and Data Quality Working GroupThe responsibility of this group is to collect, validate and install all detector-related constantsneeded for data analysis, and to continuously measure and help maintain data quality. This
work includes, for example, the generation of detector geometry constants, measurement of ice
parameters, and studies of detector response using in situ light sources, followed by installationof the resulting constants into the database. This work also includes the measurement and180analysis of quantities which track and improve data quality, such as the number of hot or deadPMTs, PMT noise rates, possible drifts in various online calibrations, and checks of overall data
quality using downgoing muons.
Much of the output of this group is in the form of entries to the database. This database,described in sec. 8.1.5, is accessed by both the reconstruction and the simulation codes, and thisgroup provides the appropriate software to make such access straightforward.

9.2.2 Simulation Working GroupThe simulation working group is responsible for writing, supporting and documenting all required
simulation programs. The group develops the software which simulates the response of thedetector to charged particles emitting Cerenkov
light, including but not limited to the simulationof ice parameters, photons passing through the ice, the PMT response, the DOM electronics,
and the trigger. The simulation package is compared to data whenever possible to ensure that
it is as close an approximation to reality as possible. This group also provides Monte Carlogenerators for the basic science topics covered by the Physics Working Groups (see below).

9.2.3 Reconstruction Working GroupThe reconstruction working group is responsible for writing, supporting and documenting thereconstruction programs for single muon tracks, multimuons, cascades, taus, contained eventsand the energy reconstruction. The reconstruction programs are created within the software
framework provided by the Data Handling group.

9.3 Computing Infrastructure
Computing resources are needed for data distribution, data analysis and simulation. Two copiesof all ltered data reside on disk in two post- lter clusters, one in the US and the other inEurope. This data amounts to roughly 2 TB/yr. In addition to the servers needed to control
these disk caches, permitting ready access to all members of the collaboration, each cache also
has an associated 50 GHz of CPU to perform additional ltering and/or reconstruction tasks.
This cluster is built up in stages to match the rate at which data is acquired and to minimize
the total expense.
Each FTE in data analysis is provided with a small \local" computing cluster (on the orderof four machines with ample disk space and some peripherals, replaced every three years) for
use in analyzing data. These clusters reside at each user's home institution, and are probably
ganged together when multiple FTEs in data analysis are at the same institution.
Acquisition of a large cluster for simulating IceCube and IceTop data is also planned. The
cluster also lters and caches this data. The nominal goal is to keep pace with the actual data
rate. Assuming roughly 0.5 s/event/GHz-CPU for generation and simulation, this translates toa need for 800 GHz CPU power for the full detector. As with the post- lter cluster, this cluster
is also built up in stages.
181

9.4 Physics Analysis
There are ve physics data analysis working groups focussing on the scienti c topics listed below.
The divisions between the di erent working groups are not absolute and it will almost certainly
be necessary to have collaboration between di erent groups. Each of these working groups
is led by a Working Group Coordinator (WGC). The WGC is responsible for organizing theanalysis work within his/her group, for scheduling and leading regular intra-group discussions,for overseeing the internal review of analyses, and for communicating regularly with the Analysis
Coordinator.

 Physics Working Group 1{ Atmospheric muons{ Icetop
This group develops the tools and the lters for analyzing muons coming from cosmicray interactions in the atmosphere. The use of the IceTop detector is very important forgeometry and eÆciency calibration of the IceCube detector. In addition IceTop is used asa veto detector for downgoing atmospheric muons. The group also does general air shower
physics analyses.

 Physics Working Group 2{ Atmospheric neutrinos{ Neutrino oscillations{ WIMPs
This group analyzes the low energy charged-current muon neutrino interactions, including
the atmospheric neutrinos, neutrino oscillations, and neutrinos from WIMP annihilationsin the Sun and the Earth.

 Physics Working Group 3{ High energy muon neutrinos (di use)
{ High energy muon neutrinos (point sources){ GRB muon neutrinos{ Relativistic monopoles
This group concentrates on analyzing the high energy charged-current muon neutrino
interactions inside and outside the detector. It searches for high energy neutrinos fromdi use sources, point sources, GRBs and relativistic monopoles.

 Physics Working Group 4{ Isolated cascades
182

{ Electron neutrinos{ GRB electron neutrinos{ NC events{ Tau neutrinos
This group analyzes high energy cascade events which could be due to electron neutrino
interactions, neutral current neutrino interactions or tau neutrino interactions.

 Physics Working Group 5{ Supernova{ Seasonal muon rate variations
This working group analyzes the Supernova data and Seasonal muon rate variations.
Certain general rules are followed to reduce experimenter bias in the analysis of data. Manpower permitting, analyses are done in parallel and independently by two or more groups. The
collaboration may decide to insist that a particularly important analysis be done in this manner.
Each analysis uses only a fraction of the available data to tune selection criteria, and only looks
at the full data set when all selection criteria have been nalized. Certain analyses should also
be \blind" such that the analyzer cannot tune selection criteria to enhance known source directions or times. For example, in a point source search one could alter reconstructed directions ina deterministic but hidden way, and only after the analysis is nalized are the true directions
used.
The Analysis Coordinator presents a report at each collaboration meeting giving an overview
of the status of each working group and its analysis work. Working Group Coordinators may
also be requested to give reports depending on the circumstances.

9.5 Internal Review Procedure
9.5.1 Introduction
Analysis results produced in the di erent working groups should be approved for submission
to refereed journals and presentation at conferences with a minimum of administrative delays,
while at the same time rigorously checked to ensure the highest possible quality. The Analysis
Coordinator has the primary responsibility for this important task.

9.5.2 Procedure
The rst venue in which a data analysis is discussed is within the appropriate Working Group.
This discussion is led by the WGC, and eventually results in the production of a document
detailing all aspects of the analysis. The level of detail should be such as to enable anyone in
the collaboration to repeat the analysis, with all systematic studies described and presented in183detail. All documentation produced in the Working Groups is made available to everyone in thecollaboration.
For parallel analyses where disagreement arises, or in other instances of disagreement, the
WGC attempts to resolve the issue. If the WGC cannot, the Analysis Coordinator tries to doso. Ultimately, the Collaboration Board may be asked to intervene.
The next step is production of a rst draft for publication. At this point, the Analysis
Coordinator appoints a paper committee. This committee consists of a small number of collaborators, preferably including some from outside the Working Group in question, to conduct theinternal review of the analysis and to shepherd it from rst draft to publication readiness. The
Analysis Coordinator also appoints one or more primary authors if there is no obvious person
for the task.
Once the paper committee is satis ed with the quality of the analysis and paper draft, thedraft is submitted to the collaboration for criticism and, eventually, approval for submission to arefereed journal. Final approval for submission to a refereed journal is given by the Collaboration
Board.

9.6 Prerequisites and Schedule
IceCube data analysis obviously requires ltered data, which depends on numerous aspects ofthe data handling machinery to be in place, and on geometry and other low level constants
placed into a functioning database. The analysis framework software must be functioning. The
post- lter clusters must be operating. The simulation framework and generation software must
be capable of simulating background and signal events, and the simulation cluster must be
operating. Basic monitoring information is required to permit veri cation of data quality. The
data analysis management structure should be in place.
Initial analysis e orts will focus on verifying overall detector performance in order to demonstrate clearly that IceCube is a functioning neutrino telescope. With this in mind, analysis of
atmospheric muons, especially in conjunction with IceTop, and analyses of atmospheric electron
and muon neutrinos, would all be a high priority.
Subsequent e ort will focus on those analysis topics that do not require substantial numbersof strings to get started, such as searches for WIMPs, monopoles, supernovae, and extremely
high energy cascades. Analysis topics relying on more strings, like searches for ultrahigh energymuons and cascades from point sources and di use sources, searches for ultrahigh energy tau
neutrino interactions, and IceTop composition studies would follow.

184

10

Drilling, Deployment and Logistics

10.1 Drilling10.1.1 Introduction
For decades glaciologists have used hot water drilling for rapid access to the inner workings ofglaciers. Though both hardware and energy intensive, hot water drilling provides the fastest andmost eÆcient way to access the deep ice. Water is also the ideal drilling uid for the IceCube
application. It is readily available, the hole is self-healing since the ice returns to essentiallyits original condition after the deployment of the detectors, and its optical properties meet theexperimental requirements. Importantly, this technique is the only drilling method capable ofmeeting the hole straightness requirement. Finally, components used to operate the system arestandard, reliable, and readily available from industrial outlets.
IceCube holes will be drilled with the Enhanced Hot Water Drill (EHWD). The EHWD
represents an evolution of the AMANDA drill, which was a research tool, to a production drill
capable of drilling 16 holes per season with 60 cm diameter to a depth of 2450 m. We have useddata gathered from drilling 23 holes for the AMANDA project to depths varying from 1000 to
2400 m to design a drill enabling us to drill and instrument a hole every 3.5 days.
Conceptually, hot-water drilling is as simple as it sounds. Water is pumped at high pressure
through a heating system and heated to near boiling temperature. The water is then forced
through a drill nozzle that directs a high-velocity stream of hot water against the ice in the hole,melting it. The drill is steered by gravity.
Hot-water drilling is energy intensive because of the large amount of energy associated with
the ice-to-water phase change. This distinguishes hot-water drilling from the more energyeÆcient, but much slower ice-coring method.
A hole with a 60 cm diameter and, for instance, a 1 m depth has a volume of 78 gallons.
With South Pole ice at -40Æ C, an equal volume of 100Æ C water is required to melt this volumeof ice. To achieve this in one minute, or drill at a rate of 1 m/min, requires 2 MW of heat. Afteraccounting for heat losses to the ice surrounding the hole, we conclude that a 5 MW system isrequired to drill at an average rate of 1.5 m per minute. With this rate the EWHD can deliver
IceCube holes to 2400 m depth in 40 hours with 7000 gallons of fuel. This can be seen as follows: One gallon of fuel can produce enough heat to produce about 80 gals of hot water at100Æ C. When burner eÆciencies of 80% and the eÆciency of conversion to electrical power
are included, this the number reduces to 50 gal of water per gallon of fuel.

 A 2450 m deep hole contains 190,000 gallons of water. To melt this amount of ice at 50
gallons of water per gallon of fuel requires about 4000 gallons of fuel. Since the overalleÆciency of the drilling process is 35% (half of the heat escapes into the surrounding ice
without melting it), we calculate that a hole will require 7000 gallons of fuel to drill. The
drilling time is 40 hours.
185

The relevant drilling parameters are pressure, ow and temperature. The heat delivered is the
product of ow and temperature. For constant pressures this ow varies as (hose diameter)8=3
and therefore this important parameter drives the performance of the EHWD system.
The conclusions presented above are buttressed by the wealth of data acquired with experimental AMANDA drills.
While hot-water drilling is conceptually simple, meeting the power requirements for safeand reliable drilling operations can be quite challenging. Drilling holes at the rate proposed to2400 m depth requires the design, construction and operation of a major industrial complex ina hostile environment. We list below the salient features of a hot-water drill system meeting ourrequirements.

10.1.2 Evolution of AMANDA Drills
Initially, the AMANDA drill was designed to provide holes to 1000 m depth for the deploymentof 10 in bathyspheres and the 1.5 in diameter cable connecting them to the surface. This
was accomplished with 1 MW of heat delivered through the largest commercial synthetic hoseavailable (1.25 in). Drilling time was about 70 hr using 4500 gallons of fuel per hole.
The current AMANDA drill was designed to drill to 2000 m. It requires three hose reels
to hold hose reaching this depth. The heat input to this drill was increased to 2 MW. Whiledrilling in the upper portion of the hole with only one reel of hose connected into the system,high ow rates and rapid drilling rates were achieved. Even though the ice is about 25Æ C warmer
near the bottom of the hole, the ow rate decreases signi cantly due to friction with the hosewall. With reduced ow rate, most of the heat is lost through the hose wall before reaching thedrill head. Thus, in the lower part of the hole, drilling is very slow as a result of the delivery of
low-pressure cool water to the drill nozzle. To drill eÆciently, the heat delivery to the drill headat 2450-m depth should be comparable to the heat delivered by the drill at the top of the hole.
Three holes were drilled to 2450 m with substantially increased fuel consumption and drilling
times. Drilling to 2400 m required 120 hours and 13,000 gallons of fuel, demonstrating that thedrill had reached a practical limit. In summary, the current AMANDA drill system is capableof drilling only four of these holes per season at these fuel consumption rates and would require
150 hours of drilling time per hole. The current drill also requires several weeks to build-up andbuild-down each season, limiting actual drilling to about six weeks per season.

10.1.3 Performance Criteria and Design of the EHWD
Requiring that the heat input achieved with the AMANDA drill is doubled and a constantwater ow is maintained through the entire drilling process, both of which are possible onlywith a single-reel design, one can extrapolate from drill data collected during the rst 1000 m
of AMANDA drilling. This extrapolation indicates that drilling to a depth of 2400 m canbe achieved in 40 hrs while consuming about 7000 gallons of fuel per hole, corresponding toa savings of about 400,000 gallons of fuel for IceCube's planned 80 holes. Note that faster
drilling is inherently more eÆcient because less time is spent warming surrounding ice. This186

extrapolation matches our earlier estimate based on the thermodynamics of the problem.
To deliver the required heat without increasing pressure, the hose size must be increased from
1.5 in to 2.5 in diameter. The hose must be mounted on a single large hose reel to eliminate
the 8 hr hose reel changes currently required for each hole during drilling and drill extraction.
The drill components are housed in mobile drilling structures that can be quickly towed into
place and integrated, so that the drill build-up and build-down time must be reduced to a totalof about three weeks, permitting the drilling of 16 holes during an approximately 75 day eld
season.
To improve fuel consumption we need to drill the holes quickly, particularly in cold ice. Thisrequires more heat at the drill nozzle. The amount of heat delivered to the drill nozzle is afunction of the hose diameter (given the desire to avoid hose pressures greater than 1000 psi).
The velocity of the water in the hose must be kept above 10 ft/s to avoid losing too much heatthrough the hose wall.
The discussion of the requirements above shows that, relative to the present AMANDA drill
system, the general design criteria of the EHWD are: Higher eÆciency
 Higher heat generating capacity
 Greater heat delivery capability
Additional design criteria are set by the need to: Drill 16 holes per season (IceCube proposal requirement) Reduce fuel consumption to 7000 gallons or less per hole
Other objectives are:

 Increase eÆciency to minimize fuel consumption
 Increased reliability Decrease the work load for the drill crew Decrease the time to set up and take the drill apart Improve mobility to cover the square kilometer array Maintain a high degree of safety
To achieve a drill design that meets these requirements, each major subsystem must be
designed accordingly. The major subsystems of the drill are:

 Power Generation Subsystem
 Preheating Subsystem187 Main Heating Subsystem
 High-Pressure Pumps Subsystem Heat Delivery Subsystem
 Drill Head
The ways in which these drill subsystems will meet the various eÆciency, speed, and heating
generation and delivery requirements are detailed below.

Power Generation Subsystem EÆciency: Two eÆcient (12 kWh per gallon of JP-8) 400 kW generators (one on line,

one in standby) will provide all electric power for the drill during drilling and deployment
operations; two 60 kW generators will provide all electrical power during non-drilling
operations. By comparison, the AMANDA generators produce only about 7 kWh per
gallon of fuel. Thus, the new generators are about 54% higher in eÆciency. Waste heatrecovery for supplementing preheating plant and Rodriguez well heat requirements areincluded in the design. Waste heat recovery is expected to save eight gallons of fuel perhour.

 Faster Build-up and Build-Down: The generators will be sled-mounted and will havefuel, water and electrical quick-connects for rapid integration during build-up and reducedbuild-down time.

 Greater heat generating capability: Waste heat recovery will recover about eight gallons
of JP-8 equivalent per hour of drill time.

 Greater heat delivery capability: not directly applicable. However, the main generators are

sized to provide the additional power required to electrically drive two new high-pressure
pumps added to the high-pressure pumps subsystem, as well as replace the two diesel
drives on the two current AMANDA high-pressure pumps. This more than doubles thegenerator output requirements of AMANDA.

Preheating Subsystem EÆciency: The Preheating plant provides about 25% of the total heat generation of thedrill. Waste-heat recovery heat will supplement the heat generated by high eÆciency (80%)
fuel- red heaters.

 Faster Build-Up and Build-Down: The Preheating subsystem will be located in sledmounted Mobile Drilling Structures having fuel, water and electrical quick-connects for
rapid integration during build-up and reduced build-down time.
188 Greater heat generating capability: The Preheating Plant will provide enough heat generating capability to increase the 200 gallons/min return and makeup water from nearfreezing to approximately 70Æ F. This is approximately double the AMANDA capability.

 Heat Delivery: The pumping capacity of circulator and transfer pumps will move about
twice as much water per minute as in the AMANDA drill. About 200 gallons/min of 70Æ F
water will be supplied to the suction side of the high-pressure pumps.

Main Heating Subsystem EÆciency: The design requirement is 80% minimum. Reusable AMANDA heaters will be
refurbished as necessary to achieve this design eÆciency.

 Faster Build-Up and Build-Down: The Main Heating subsystem will be located in foursled-mounted Mobile Drilling Structures having fuel, water and electrical quick-connects
for rapid integration during build-up and reduced build-down time.
 Greater heat generating capability: The EHWD must heat 200 gallons of 70ÆF water to190Æ F per minute, twice as much as the AMANDA drill. The EHWD has twice as manyheaters as AMANDA's main heating plant.

 Heat delivery: The inlet and outlet plumbing has been increased from 1.5 in to 2.5 in toaccommodate the increased ow.

High Pressure Pumps Subsystem EÆciency:The high-pressure pumps are the same as AMANDA's, but four will be required

instead of two for AMANDA. However, the ineÆcient diesel drives (about 7 kWh per gallonof fuel) will be replaced with electric drives. Since the new generators will deliver about
12 kWh per gallon of fuel and assuming an electric drive eÆciency of 90%, the eÆciency
is expected to improve by about 54%.

 Faster Build-Up and Build-Down: The High-Pressure Pumps subsystem will be located ina sled-mounted Mobile Drilling Structure having water and electrical quick-connects for
rapid integration during build-up and reduced build-down time.

 Heat delivery: The number of pumps will be doubled and the inlet and outlet plumbing
must be increased from 1.5 in to 2.5 in to accommodate the increased ow.

Heat Delivery Subsystem The Heat Delivery Subsystem includes the high-pressure hoseand the hose reel.

 EÆciency: The hose is increased from 1.5 in inside diameter to 2.5 in to accommodate theincreased ow and decrease the heat loss through the hose wall.
189

 Faster Build-Up and Build-Down: a single hose reel will hold the hose between the drill

head and hose reel (about 10,000 ft) instead of three for AMANDA. This reduces thenumber of sled-mounted components by two.

 Heat delivery: The hose is increased from 1.5 in to 2.5 in to accommodate the increasedow.

Drill Head

 Faster Build-Up and Build-Down: housing to be constructed of aluminum for lighter weightand easier handling.

 Heat delivery: The nozzle size is increased to accommodate the increased ow.
10.2 Deployment
10.2.1 Overview
The installation of optical modules (OMs) in the ice is referred to as string deployment. In awider sense the string deployment includes the preparation of the string hardware at the South
Pole and the termination of the string in the IceCube counting house. Once the borehole ofapproximately 50 cm diameter is drilled (melted) into the ice, the drill is removed from the holeand the site is available for the string deployment. From that moment on, the water column of2400 m depth begins to refreeze. The refreeze process is complete after about 5 days. However,already after about 24 hrs the diameter of the water column shrinks to a diameter comparable
to the size of the OMs. The OMs must reach their nal position before the water column
becomes too narrow. Figure 76 shows an image taken with a TV camera, which was deployedwith an AMANDA string. The glass sphere shown in the gure was deployed for demonstration
purposes only. Its diameter was 10 in, which is less than the 13 in spheres used for the OMs.
Nonetheless, it can be seen that in this case the water column was much larger than needed, andtherefore that more fuel was used to drill the hole than necessary. An engineering project called
Smart Drill is underway to optimize the drilling by maintaining an adequate hole diameter while
minimizing fuel consumption.
The deployment coordinator must decide how much time is needed for the deployment.
The drill team must provide a hole that meets certain requirements. These requirements andthe protocol of the hand-over are discussed later. Once the hole is released for deployment
the countdown starts. After this moment the time constraints for the string deployments are
absolute and unforgiving. In the worst case scenario a string can get stuck in the ice at a shallow
depth where it is of little or no scienti c value.

10.2.2 AMANDA Experience
AMANDA deployed a total of 23 strings to depths between 1000 and 2350 m. The chronology
of deployments is listed in table 13. The importance of the experience and expertise obtained in
190

Figure 76: Video image taken during deployment of string 13.

Year
MissionStrings OMs/string Depth (m) Duration (h)93/94 AMANDA-A
4
20
1000
13-18
95/96 AMANDA-B4
4
20
2000
15
96/97 AMANDA-B10
6
36
1950
12-15
97/98 AMANDA-II
3
42
2350
18-21
99/00 AMANDA-II
6
42
2020
10-15
Table 13: Chronology of AMANDA string deployments.

191

Figure 77: Installation of an OM.
ve AMANDA expeditions with string deployments cannot be overestimated for future IceCube
deployments. The rst deployments of strings to a depth of 1000 m were of an exploratory nature.
Over time, the number of OMs per string increased from 20 to 42. In addition, the complexityof the OMs themselves increased. Optical modules on strings 11 to 19 of AMANDA-II use bothelectrical cable and optical bers for signal transmission. For the DOM string (string 18) a more
complex connectorization scheme was used. A total of 3 winches were operated simultaneously
for all AMANDA-II deployments. During the 99/00 eld season the installation time was as
little as 8 min per OM, despite the enhanced complexity. In fact, the overall deployment time
for the strings remained approximately constant for all strings while the number of OMs per
string and OM complexity increased. This was accomplished due to a steady improvement in
the deployment procedure.

10.2.3 AMANDA Deployment
The basic components of a string are the main cable and the OMs. The OMs are attached to thecable for the rst time at the South Pole. There are no test installations prior to the shipmentof these components to the South Pole, so precise speci cation and quality assurance proceduresof all components are critical for a successful deployment.
Figures 77-79 illustrate the important components of the deployment sequence. Three people
work on the actual installation of the OM on the main cable. In total, a minimum of 7 people areneeded for a deployment. For each OM the tension on the main cable is temporarily transferredto the tower winch cable. Then the OM is integrated in the main cable and the tension istransferred back to the main cable. The OM is now integrated into the main cable.
192

Figure 78: An OM ready to be lowered into the drill hole.

193

Figure 79: An OM being lowered into the drill hole.

194

depth [mwe]String 16 - deployment
OM deployment

drop

2000

Average OM deployment: 12 min/OM

1750

Average drop speed: 13 m/min

1999
2000

1500

1250

500

250

0

0

M

M

/O

in

shift change

TV camera down the hole

750

17 m/min

New Year’s celebration

1000

2

4

/O

in

8m

8m

6

8

10

12

time [hours]
Figure 80: Deployment of AMANDA string 16. The depth, as measured by a pressure sensor, is plottedversus time. For this string the OM installation time was less than 10 hrs. The drop takes about 2 hrs.

195

Figure 80 shows the progress of the deployment with time. A pressure sensor mounted tothe bottom of the string monitors the depth of the string. The drill hole is lled with water up
to a level of about 50 m below the snow surface. The pressure begins to increase strongly after
the sensor reaches the water level. The pressure sensor is the primary measure of the absolutedepth of the string. Other measures are cable marks and possibly a secondary pressure sensor.
Each stop corresponds to the installation of on OM. The deployment reached speeds of 8 min
per OM. Once all OMs are installed the pressure corresponds to about 350 m water equivalentpressure (the length of the instrumented portion of the string minus 50 m at the top). Now the\drop" begins. The string is lowered to its target depth at a speed of approximately 15 m/min.

10.2.4 IceCube Deployment Overview
A diagram of the full IceCube deployment setup, depicting the counting house, the surface cable,an IceTop detector module and the down-hole cable, is shown in g. 81.
The mechanical installation of the OM is illustrated in g. 82. The OMs are attached to themain cable below and above as shown. A chain with a shortening clutch allows adjusting thelength to a precision of 1 in. This design is identical to that used on AMANDA strings 14 to 19
and is well understood.
Each OM is connected electrically to the cable via twisted quad cable breakouts at every
fourth OM position as shown in g. 83. Each twisted quad cable consists of 2 twisted pairs.
Each twisted pair provides 2 OMs with power and communication from the surface. Figure 84
illustrates how 4 OMs are connected to the main cable. The OMs are spaced by 17 m. Thus,
there will be a breakout of a quad cable every 68 m. A wiring harness will be used as an interface
between the twisted quad breakout on the main cable and the OM.

10.2.5 IceCube String Deployment Procedure
The requirement to deploy 16 strings with 60 OMs each in a single season, particularly in view ofSouth Pole population constraints, requires a further improvement of the deployment operation.
During the AMANDA deployments, the shortest time between the start of two subsequent
deployments was 120 hr. For IceCube the average deployment cycle time will be 84 hr for aperiod of about 60 days, excluding 5 days of down time. The increase in the eÆciency is possibleby optimizing every single element of the deployment procedures, in particular in the pre- andpost-deployment activities.
The digital signal transmission based on the design of the DOM allows a signi cant change
and simpli cation of the deployment procedure of IceCube strings. No optical ber cables will
be required. Thirty twisted pair cables will provide power and signal transmission for 60 OMs.
The absence of optical bers reduces the cargo by about 9000 lb per string, and simpli es test
procedures prior to and during the deployment. (During deployments of AMANDA strings 1113, problems were encountered when the breakouts of ber cables and electrical cables did notmatch up. These phasing problems were one of the reasons why the deployment times were196

IceCube
Counting
House

IceTopSurface cable:from Counting Hosestring position.
Includes IceTop OM.
Length specific for each string.

Connector
1350 mString:Fixed Length*: 2420 m

2400 mFigure 81: Schematic view of the string, the surface cable and an IceTop detector.

197

1)

180 cm3)

2)

Diameter of "string"

Figure 82: Mechanical integration of OM into the main cable.
198

ICECUBE CABLE: BREAKOUT SCHEMATICS(NOT TO SCALE)

Albrecht Karle
Dec. 13, 2000
Breakout schematics

Breakout on every fourth
OM position: 4, 8, 12, ... counting from top.
Cable Stop
down
0.9 m

No Breakout

0.9 m
Cable Stopupspacing to next
cable stop: 17 m

Cable Stop
down
0.9 m

No Breakout

0.9 m
Cable Stopupspacing to next
cable stop: 17 m

Cable Stop
down
0.9 m
Breakout
Cable Stop
up

0.9 m

0.6 m

Figure 83: Breakout schematics on main cable. Pre-installed cable stops are used to mount the OMs.
A twisted quad is broken out at every fourth OM position.

199

Wiring Harness
2 pin, male

Main cable
Twisted pair cablefor power andcommunication

6 pin connector
Twisted pair cablefor local
coincidence

feedthrough fortriple twisted pair

6 pin connector
opticalmodule6 pin connector

4 pin
Breakout
main cable

Splitter box,
pressure resistant
10,000 psi-60 C
size of PCB: TBD(est.: 3x10 cm2)

6 pin connector

2 pin, female

Figure 84: A group of four OMs is operated through a single twisted quad.

200

particularly high for strings 11-13. The phasing problems were solved in the 99/00 campaign.
The deployment with a single cable, of course, means such phasing problems cannot occur.)
The phases of string deployment are as follows:
1. Install weights (600 lb);
2. Install 60 OMs;
3. Lower string to its target position at 2403 m.
Several pressure sensors on the string are used to monitor the correct motion of the string.
Communications and power to the pressure sensors and to the newly connected OM is provided
through a slip ring mounted at the cable winch. The actual payout of cable will be measured
at the surface. The measured payout at the surface and the pressure increase at the bottom of
the string will be monitored for consistency. The correct electrical connection of each OM isveri ed at time of installation. A short electronic test sequence of no more than a few minutes
is performed at this time. Additional communication tests to the recently installed OMs cancontinue for a few more minutes.

10.2.6 IceCube Indoor Deployment
The shelter at the deployment site is very important for high quality OM installation at a rateof 2 strings per week. In the past, these shelters consisted of simple wind shields or a tent
structure. Figures 85 and 86 show the dome structure that was used for AMANDA string 14-19
deployments.
For IceCube a heated building (see gs. 87{90) coupled to the drilling apparatus will be
used as a deployment facility. This approach will improve the work conditions for the deployers
substantially. All deployers work indoors. The electronics control room is inside this building
but separated by a wall with large windows. The building is large enough to bring all or at least
most of the OMs inside prior to the deployment. A furnace will replace noisy bullet heaters
and eliminate exhaust near the work site. The ceiling may be partially transparent to takeadvantage of solar power and light. This building will also serve as a drilling shelter during thedrill operation.

201

Figure 85: Setting up a shelter for AMANDA deployments. The setup time of 3 hours is too long for
IceCube.

202

Figure 86: Completed shelter used for AMANDA deployments. This is type of shelter is not adequate
for IceCube.

203

Figure 87: Floor plan of the tower operations structure (TOS). The building is used for drilling anddeployment. The heated building provides power and network access.

204

Figure 88: Roof plan of the tower operations structure (TOS).
205

Figure 89: Side view of the TOS. The tower is at the top of the building to allow optimal conditions at
the drill hole.

206

Figure 90: The sheave is detachable from the main structure for transportation purposes.
207

Diameter43.0 cm
Depth
2410 mLifespan of 1st hole per season 32:00 hr
Lifespan of subsequent holes
29:30 hrTable 14: Requirements which the drill hole must meet at the time of handover to the deployment
team.
Deployment phase

Allocated Time (hr)Nominal Contingency Total
Preparation
1:00
1:00 2:00
Weights, pressure sensor
0:40
0:20 1:00
OM installation
14:00
6:00 20:00
Drop
2:30
2:00 4:30
Finish and secure string
1:00
1:00 2:00
Total
19:10
10:20 29:30
Table 15: Breakdown of deployment phases and allocated times.

10.2.7 IceCube Drill Hole Requirements
The drill hole needs to be of a minimum diameter and depth for at least the time required for thestring deployment. The minimal diameter is determined by the size of the OM (36 cm, including
the harness) plus the cable (4 cm). The tolerances on the OM size are 0.8 cm. The tolerance
on the cable diameter is 0.7 cm. We add an additional 1.5 cm for tapes and cable ties. The
maximum diameter of the string is 43.0 cm. The drill hole requirements are listed in table 14.
The speci ed duration contains contingency time for the deployment operation. The nominal
total deployment time is estimated to 19 hr. This allows for more than 10 hr of contingency.
The nominal depth is 2403 m. We allocate 7 m of contingency.
The deployment operation begins when the drill hole is accessible for the deployers. At thistime the drill and the downhole pump have been removed from the hole. In addition it is requiredthat the area behind the tower be accessible to position the winch with the IceCube cable. Oncethese conditions are met the hole is handed over from the drilling to the deployment command.
A breakdown of the di erent phases of the string deployment operation and the estimated timefor each phase is given in table 15. Contingency times are based on experience and possible
failure mechanisms. Possible failure scenarios include power, winch control, winch drive, tower
winch, computer and unexpected situations.

208

Release hole N
for deployment

Release hole N+1
for deployment

Transfer of mobile equipment(Hose winch, other winches,building, tower,...)
Drilling of hole N+1
0h

12h

24h

36h

48h

60h

72h

84h
Time

Deploymentof string N

Receive holefrom drillingteam

OM testing,deployment preparation,
Move string deployment room,
checkout at counting house
IceTop deployment, etc.

Deploymentof string N+1

Figure 91: Time schedule of a single drilling and deployment sequence. The projected time for a single
cycle is 84 hours.

Figure 91 gives an overview of the major operations during a single drilling and deployment
cycle of 84 hr, and g. 92 shows a schematic view of arrangement of drilling and deployment
infrastructure in the course of drilling ve holes.

10.2.8 Quality Assurance
Optical modules and associated components are all tested at various stages leading up to andincluding deployment. Tests which are done at McMurdo and the South Pole are described
below.

McMurdo Test Stand All OMs undergo a detailed test procedure and burn-in operation

before they are shipped to the South Pole. OM tests concern the integrity of the hardware after
the transportation. Most OMs will be shipped by vessel. They arrive in January in McMurdo
and stay there until about October of the same year. From here they are sent by air to theSouth Pole. The infrastructure at McMurdo permits extensive testing of OMs there. Therefore,
only a very brief test sequence will be required at the Pole. (The details of the tests will be
described elsewhere.) It is a fundamental concept of the test procedures that they do not require
unpacking the OMs from the shipping crates. The crates are therefore light-tight. It is planned
to wire the OMs inside the crate to a patch panel, which is accessible from the outside.
Only in the rst season (FY04) will all OMs be shipped by air to McMurdo. In the following
seasons an increasing fraction of OMs will be shipped by vessel. This requires that up to 1000
209

Drilling and Deployment Field Camp
Surface cables to strings

IceTopIceTopIceTopIceTop
3

2

1
OM

OM

DC

IceTop
4

5

DC

TOS

TOS

String 1 in operationwater return

deployment
winch 1TOW

Hose winch

deployment
winch 2

Time: 0Hole 1: String in operation
Hole 2: Deployment in progress
Hole 3: Drilling in preparation
Hole 4: Firn hole drilled
Hole 5: Firn hole drilled

StringCablesDrill
control
Center(DCC)

OMs

Central
Deployment
Lab
(CDL)

“Base Camp:
Centraldrilling structures(6 units for heaters,
pumps, Rodrigues
Well,...)

Figure 92: A schematic view of the drilling and deployment infrastructure with ve drill holes is given.

210

OMs be stored in McMurdo, and hence a similar number need to be tested there each season.
This is done with a DAQ system with 500 channels to test the all the OMs in two batches. The
duration of the tests is 2{3 months. The DAQ hardware can be shipped to the pole with thelast batch of OMs in the last year of string deployments and used for the main DAQ.

South Pole Test Stand The deployment infrastructure at the pole can be divided in three
categories:

1. The central deployment lab;
2. The string deployment room;
3. A room allocated for deployment support in the IceCube counting house.
All OMs are delivered to the central deployment lab. Here they undergo a nal test sequenceof not more than 60 min per OM. Again, the OMs are tested in the crates. The crates must be
light-tight such that the OM can be powered up and noise pulses and cosmic-rays observed.
A test DAQ is available to operate up to 100 OMs at a time. The test DAQ is very similar tosystems used at various locations during the OM production and shipping. The tests are shortin duration, ranging from 10 min to not more than 60 min. The tests are pass/fail and executedin software. OMs that fail the Q/A procedure are rejected for deployment and sent back. Only
minor mechanical problems are xed at the South Pole. OMs that show electronic problems are
not opened for repair at the Pole, instead they are sent back to McMurdo.
About 60 OMs will be tested at a time. Fifteen twisted quad cables (or 30 twisted pairs) need
to be connected to the crates waiting for tests. The time to wire up all the crates is estimated tobe 1{2 hr. While the test runs no longer than one hour, the time for debugging and evaluation
may take several hours. In total we allocate 24 hr of labor per string at the central deploymentlab.
After this test the OMs are powered o and the crates are opened for the rst time since
shipment from the northern hemisphere. The content of the crates is checked for completenessof all mechanical components. At this time the pressure inside the OMs is checked to makesure there are no leaks. Once the OMs are certi ed the crates will be marked and sent the next
deployment site.
Once the OMs are certi ed for deployment they can be moved to the string deployment
site. Sixty OMs plus about eight spares are loaded into the deployment room and partially
unpacked. During the deployment a nal continuity and communications test is performed.
This test requires at most a few minutes and can be performed in parallel with the mechanicalinstallation. The OMs are connected in groups of four. Once connected the deployment DAQ
veri es the continuity and runs some basic electronic and communications tests.

10.2.9 Practice Deployments
Experience has shown that the rst string deployment in each season is particularly challenging
due to lack of experience of most of the team members. Two strategies are planned to optimize
211

Year
FY04 FY05 FY06 FY07 FY08 FY09
baseline schedule
6
12
16
16
16
14
possible range
3-6
8-14 15-17 15-18 15-18 14-18
Table 16: Schedule for string deployments. The numbers indicate the how many strings are to be
deployed in each season in the baseline schedule and the possible range in the number of strings deployedeach year, as described in the text.

the performance during the rst deployment. A pre-deployment workshop of about two weeks
is planned and budgeted for all deployers. This is an opportunity to familiarize the team withthe procedure and the instruments used. Unexpected situations can be discussed. Particularresponsibilities can be de ned. A test stand will be available to practice the actual OM installation. The full deployment team must be at the South Pole two weeks prior to the rst
deployment to begin with the preparations, test procedures, and the setup of the instruments
and labs. A practice hole of about 50 m depth together with the full deployment infrastructure(tower, string deployment shelter, etc.) will allow deployers to practice the deployment on thesite. A subset of the deployment team needs to arrive at least three weeks prior to the rst
IceCube deployment to prepare the new infrastructure.

10.2.10 Surface Cable Installation
Deployment Sequence and Cable Plan Table 16 shows the deployment sequence during

the IceCube construction period, and g. 93 illustrates this sequence. The baseline schedulecalls for six strings to be installed in FY04, followed by 12 in FY05, then 16 for FY06{FY08
and nally 14 strings in FY09. In FY04, the chief goal is to achieve an end-to-end test of all
detector systems, a goal which is best achieved with a minimum of three strings, as indicatedby the rst number in the \possible range" row in Table 16. Similarly, in subsequent years the
rst number represents the minimum number of strings to be deployed, and the second number
the maximum, subject to the constraint that the sum over all years equals 80. Experience
gained in earlier years may permit even larger numbers of strings to be deployed in later years
than indicated in the table. For any year in which the number of strings deployed exceeds thebaseline schedule, there are production, logistics, and schedule implications which have not yet
been addressed. It is possible that an accelerated schedule, using contingency funds in earlier
years, will result in an overall savings to the project.
The addition of 12 strings in FY05 will embed the AMANDA array in IceCube strings.
The SPASE-2 array will be embedded only in FY09. A few SPASE-2 stations will have to be
relocated then, assuming that it is still in full operation. Trenches are used to bury the cables
at depths which will keep them secure for  15 yr.

Cable Trenches The separation of the main cable in a surface cable and an in-ice cable allows

for a very exible cable management. The surface cables will be laid and trenched independent
212

ICECUBE: CABLE PLAN

IceCube layout
Grid
north
100 m

FY06:16

FY05:12
Old

Pole

Sta

tion

line

(lin

AMANDA-B

eo

f de

ath

)

AMANDA-II

Runway

FY04:6

FY07:16SPASE-2

FY08:16

FY09:14

South
Pole

Dome

Figure 93: The deployment sequence.
213

of the exact timing of the drilling and deployment. In this design, the surface cable will betrenched before the drilling starts. Ideally the surface cable is already wired up in the counting
house by the time the string is deployed. As soon as the string is deployed it will be connectedto the surface cable and the string will be operated from the counting house hours after the
deployment is completed. Another advantage is that the valuable time during November will be
used to do the cable trenching. There is no need to wait for the strings to be deployed rst. The
cables will be trenched starting from the counting house. This avoids the pile-up of excess cable
in its vicinity. The small amount of excess cable, a few tens of meters, will be buried together
with the IceTop tank in the snow. This is where the connection between the in-ice cable andthe surface cable will be located. Cable trenching is done by the NSF contractor.

10.3 Logistics
10.3.1 Introduction
A South Pole Experimental Deployment is a highly detailed operation requiring the e ortsof many groups at the NSF and the Support Contractor as well as detailed planning of theexperimental group. This planning starts with the Operational Research Worksheet (ORW)
which describes the full long-term requirements of the experiment. It is supplemented eachyear with the Support Information Package (SIP), and later with direct meetings between theexperimenters, the NSF, and the Support Contractors so that all can agree on the exact level of
eld-support the experimenters can plan on being delivered by the NSF and the Contractor.

10.3.2 Documentation
The ORW is submitted along with the experimental proposal to the NSF, and it is reviewed
by the contractor to assess whether the experimental proposal can be adequately supported tomeet the needs of the experimenters. This document serves to outline the annual support anexperiment will require during the entire lifetime of the experiment.
The type of information required for both the ORW and SIP is listed below.

 PI and co-PI Contacts
 Project Description: Locations and Scienti c Opjectives
 Personnel: Proposed time period at the pole and speci c job-tasking, medical/dental
examinations and clearances. Travel arrangements.

 Safety Environment and Health Issues: Ice coring, use of heavy equipment, placement ofprobes. use of radioactive materials, hazardous waste, etc.

 Cargo: A complete listing of all of the cargo items one expects to ship.
 Construction and Fabrication Required Computers and Communications: Connectivity, system maintenance, on-site support214

 Laboratory/Observatory Requirements
 Aircraft Support
 Vehicle Support
 Global Positioning (GPS) Support
Experience with AMANDA has shown us that the best way to keep the NSF and Contractor
up to date concerning South Pole population levels and personnel medical/dental and travel status is to maintain a Deployment WWW-page. Both personnel and cargo movement information
is presented in spreadsheet formats (presently using EXCEL). These formatted personnel andcargo spread-sheets are also forwarded electronically to the contractor.

10.3.3 Personnel and Taskings
South Pole population levels are highly restricted, mainly due to station size limitations. In thepast AMANDA has been forced to cap its population to about 12-15 people at any time. The
eld-season generally runs from November 1st to about February 15th each year. This 15 week
period is generally divided into 3-4 project periods of 4-5 weeks duration. This generally matcheswith the period of time that people spend on the pole so that in any season we may have as
many as 35-45 people working at the pole during some period. Generally a task will involve 3-4
people and we generally schedule in 3-4 parallel tasks at any one period. This generally meansthat anywhere from 12-15 speci c tasks invoving 3-4 people for 3-5 weeks will get done during
a eld-season
The labor hours required for the deployment of a single string and the associated IceTop
detector is given in table 17. The total population required to perform these tasks follows fromthe labor required per string. Almost 40% of the deployment time is required for the actual
string deployment operation.
The basic string deployment operation requires 7 people during the core deployment operation. 24 hours are allocated for the deployment operation. This is almost 5 hours more than thenominal deployment time to ensure the readiness of the team at the time of the hand-over from
drilling. Including the IceTop deployment, we plan on a total population of 16 people during
times of full capacity string deployments. Three people are allocated for the IceTop deployment.
The IceTop deployment personnel requirements are the most diÆcult to estimate due to lack ofexperience.
As shown in table 18, the projected population reaches a maximum of 44 in all years. The
drilling population is higher in the rst year, due to the drill construction. The AMANDAand SPASE population is higher in the rst 4 weeks of FY04. The \Science" population is the
personnel required for the installations of the electronics and software in the counting houseand in the B2 science lab. This group will commission and operate the detector during thesummer. As soon as the deployment operation is phased down by the end of January, the science
population is increased to accelerate the commissioning of the last strings and to increase thee orts on data handling operations.
215

Operation
Time allocated (h)Cable drag52
Deployment (24*7)
168
Site. Preparation
16
Cable unpack and prep
20
OM Testing24
Documentation
10
PTS prep
15
Logistical and other support
20
IceTop
84
General assistance20
Total: String
429
Total: Week
858
Number of 54 hour shifts/week
15.9
Table 17: Labor hours required for a single string.

Person days: Total/season
Year
FY 04 FY 05 FY 06 - 09
Drilling
1509 1308
1307
Deployment
796 1334
1316
Science
676
905
1032
A-II/S-2
611
392
238
Sum
3592 3939
3893

Population during deployment periods:(Maximum/day)
FY 04 FY 05
FY 06 - 09
18
15
15
15
16
16
8
10
11
3
3
2
44
44
44

Table 18: Population required for the scal years FY04 to FY09. The population is broken downin drilling personnel, deployment personnel, science personnel for IceCube and science personnel
for the subsystems AMANDA-II and SPASE-2. The total number of person days during a South
Pole summer is given on the left. On the right the number of people is given during the periodsof highest population.

216

Item
Weight (lb) Volume (ft3 )Cable
10560a
307a
60 OM
3300b
270b
c
Mechanical400
4cWeights
600c
6cc
IceTop unit
1200
120c
Total: single string
16060
7070
Total: 16 strings
25690
11310
Table 19: Breakdown of weights and cubes per string and total for a single string and 16 strings.
(Quantities come from RK quotes (a), Ho man (b) and Karle (c).)

10.3.4 Medical/Dental Examinations
All personnel deploying to the South Pole have to pass a medical and dental examination. Thiscan be complicated and time consuming so the process is started in the May-June time period.
The contractor sends out the medical/dental packets and they also view the results of the tests
and make the decision if a South Pole candidate is medically quali ed. Di erences in Europeanand American dental standards have caused problems in the past. Medical quali cation is aprecondition to Antarctic travel.

10.3.5 Airline Travel
All U.S. experimenters have their airline tickets purchased by the contractor. These tickets
provide travel between their university location and Christchurch, New Zealand. Foreign participants have to provide transportation at their own costs to Christchurch. At that point all
participants are provided transportation at no cost to them, from Christchurch to Antarctica.
The experimenters are expected to pay for their lodging and food from their research contracts. Once in Antarctica there are no costs, since both food and lodging is provided.

10.3.6 Weights and Cubes
The main elements of a string are the cable and the OMs. Smaller mechanical components
are needed for the installation of the sensors. Weights are used at the bottom to keep thestring under tension. The weights and cubes for each string are listed in table 19. We groupthe cargo in three categories: Cables, OMs, and miscellaneous, where miscellaneous stands formechanical components, the weights and for the IceTop tank for each string. The followingcargo movements are required:
1. All incoming cargo is delivered to the central deployment lab as it arrives.

217

2. The equipment used for each string is transported to the exact location near the deployment site of a given string. The equipment is requested at the deployment site before thedrilling starts. This will be approximately 48 hours before the deployment begins.
3. Remaining packing materials are transferred to South Pole waste management.

10.3.7 Cargo Transport
Estimates of total mass and volume of material (\weights and cubes") required by IceCube over
its lifetime are given in the tables below. There are three ways that cargo can get to the South
Pole site, by \vessel," \Comm-Air" and \Kilo-Air."The vessel is the cheapest means of transport, but requires the most advance planning. Cargo
leaves Port Hueneme, CA by vessel on about December 15 and arrives in McMurdo, Antarctica
about 6 weeks later on January 25. The cargo is then own in C-130 Hercules aircraft to thepole or it winters in McMurdo and is is own at the beginning of the next season. Either way
the cargo is only available for use at the pole the following season. The vessel requires that
equipment be ready one year before it will be needed at the pole.
Kilo-Air is the most common way to ship items. Under this plan, items are shipped fromPort Hueneme to Christchurch NZ by vessel about September 15. From Christchurch they areown down to McMurdo, and then from McMurdo to the pole. This means that cargo usually
has to be ready about 60-70 days before it is needed at South Pole.
Comm-Air is the fastest and most expensive way to ship cargo to the pole and it requires
NSF approval. Items travel from Port Hueneme to Christchurch by commercial air-cargo. From
Christchurch to Antarctica they travel the same way as Kilo-Air.
All Antarctic cargo orginating in the U.S. is shipped from the NSF facility in Port Hueneme,
CA. Cargo originating in Europe is generally shipped to the NSF facility in Christchurch, NZ.
During the course of the IceCube deployment it is expected that about 1300K lbs of detector
components and 650K lbs of drilling equipment will be shipped to the South Pole via vessel. We
also plan to ship about 100K lbs of detector components and 100K lbs of drilling equipment via
Kilo-Air.
The tables 20 10.3.7 10.3.7 10.3.7 10.3.7 list the cargo to be shipped by the various means
listed above. In these tables, \ROS" stands for \Required On Site" and \N" is the current
year's string count minus one. The cargo is given in two categories that describe the mode oftransportation: Kilo-Air and Vessel. The cargo is broken down further in 3 categories of string
equipment: Optical Modules (OM), Cables, Miscellaneous.

218

FY Strings Weight (lbs) Cubes (ft3 ) ROS
04
6+1
23100
1890 12-13-03+N5 days
05
6
19800
1620 11-20-04+N3 days
06
4
13200
1080 11-16-05+N3 days
07
0
0
0 0
08
0
0
0 0
09
0
0
0 0
Table 20: Optical Modules to be shipped by \Kilo Air."FY Weight (lbs) Cubes (ft3 )
ROS
04
4000
1890 12-15-03
05
6000
1620 12-15-04
06
40001080 12-15-05
07
4000
0 12-15-06
08
1000
0 12-15-07
09
1000
0 12-15-08
Table 21: Miscellaneous hardware to be shipped by \Kilo Air."FY Strings Weight (lbs) Cubes (ft3 ) ROS
04
00
0 12-13-03+N5 days
05
6+2
26,4002160 11-20-04+N3 days
06
12+2
46,2003780 11-16-05+N3 days
07
16+1
56,1004590 11-16-06+N3 days
08
16+1
56,1004590 11-16-07+N3 days
09
14
46,2003780 11-16-08+N3 days
Table 22: Optical modules to be shipped by vessel.
FY Strings Weight (lbs) Cubes (ft3 ) ROS
04
6
13200
720 12-13-03+N5 days
05
12+2
30800
1680 11-20-04+N3 days
06
16+2
39600
2160 11-16-05+N3 days
07
16+1
37400
2040 11-16-05+N3 days
08
16+1
37400
2040 11-16-05+N3 days
09
14
30800
1680 11-16-05+N3 days
Table 23: Miscellaneous hardware to be shipped by vessel.
219

FY Strings Weight (lbs) Cubes (ft3 ) ROS
04
663,3501842 12-13-03
05
12
126,700
3685 11-20-04+N3 days
06
16
168,900
4913 11-16-05+N3 days
07
16
168,900
4913 11-16-05+N3 days
08
16
168,900
4913 11-16-05+N3 days
09
14
147,800
4299 11-16-05+N3 days
Table 24: Cables to be shipped by vessel.

220

11

Quality Assurance

The IceCube project oÆce will implement a quality plan meeting the requirements of ANSI/ISO/ASQC
Q9001-2000 (ISO 9000). The UW Space Science and Engineering Center (SSEC) is in the process of implementing a Quality Management System (QMS) meeting the requirements of ISO
9000 and eventual registration.
The IceCube Quality Plan will de ne the overall project policy, the processes to be controlled
and how they interact, and the procedures to be used. The plan will include, but not be limited
to, addressing the following areas:
1. The overall scope of the Quality Plan, the standards (ISO 9000, etc.) it is designed tomeet, and the management commitment to the plan. Exclusions, if any, will be listed. The
plan will make it clear how each element of the program is a ected by the quality plan,
who is responsible, how each requirement is to be met, and how we verify the e ectivenessof the plan.
2. Control of documents: who approves, how released and distributed, lists of documents,change procedures, how users are assured they have the latest documentation, and how
obsolete documentation is removed from the system. The document control system will
use on-line databases with web access to simplify the process, reduce paper handling andthe time and e ort needed to make changes, and make the latest information available toall project elements without delay.
3. Control of customer and supplier documentation: How such documentation is received,
logged, and stored. The process for assuring such documentation is the latest and correct
version is also described.
4. Procurement controls: how requirements are passed to suppliers and collaborators, what
information and documentation is required, how material is veri ed upon receipt, what
records are generated and kept. The nature of the quality requirements that are to passed
on to suppliers and collaborators will be described.
5. How the quality system is planned, maintained, improved, and veri ed. Management
review process, internal audits, corrective and preventive actions will be included andwill follow the ISO 9000 standard model. The essence of the system is to make ourprocesses clear and understandable so they can be reliably executed. The processes must besuÆciently clear and veri able so that de ciencies can be readily identi ed and corrected,
ideally before problems arise.
6. The quality organization: who is responsible for what. Internal communication processes,
management roles and responsibilities, the nature of the management reviews, internal
audits, and how these processes are carried out.

221

7. Awareness and training, certi cation, assuring personnel have the appropriate skills andexperience, the records required for these elements, the process for verifying the e ectiveness of training, and how de ciencies are corrected.
8. Design and development process: inputs and outputs, design reviews, design documents
required by phase, the purpose of the reviews, who is involved, the speci c items needed
for the review, the process for documenting review actions and closeout, the points of the
project where reviews are required, major and minor reviews (formal and informal)
9. Reliabilility guidelines: assembly standards, parts program (standards, testing, screening),
parts derating guidelines, traceability requirements, vendor documentation, receiving inspection, certi cations, parts documentation and how tied to assembled items. Spares
logistics and parts guidelines relating to spares.
10. Manufacturing planning: How manufacturing and assembly processes are planned, controlled, and veri ed. How in-process material is identi ed and what records are kept. This
includes the traceability documentation (parts lists, lot numbers, serial numbers, etc.),
how inspections are handled, by whom, the process for documenting non-conformances,
how the documentation and actual hardware are processed, test procedures, how test data
is kept, and what happens to the nal records after the item is complete.
11. Veri cation: Inspection and tests: standards, records, test procedures, integration processes, calibration of test equipment and associated records, integration logbooks, record
retention, con guration identi cation lists, and test procedures.
12. Non-conformance control: Identi cation of non-conforming articles, disposition processes,
rework, repair, MRB, and associated records. How repairs are planned and documented,
rework vs repair and how each are handled, Who determines what levels of disposition of
non conforming articles and why.
13. Service, eld support, logistics: spares, records of failures and malfunctions, con guration
management, con guration records, maintaining con guration records of items deployed,
maintaining spares and support for deployed items and items subject to con guration
control that are changed.
14. Internal audit plans and procedures, management reviews, schedules, personnel, training
for audits, audit follow up
15. Analysis of data for determining status and trends of product quality, customer satisfaction, supplier performance, areas needing attention for continual improvement and/or
corrective and preventive action and how this all relates to the management review process.
The details of the plan will resemble plans appropriate for spacecraft instrumentation because
IceCube must operate reliably in a remote and harsh environment, is a large and complex system,
222

once deployed cannot be returned for repair, and represents a major investment. The quality plan
must therefore be rigorous and fully integrated in the management and development process.
The ISO 9000 standard is process based using a \plan, do, check, act" model. The plan
begins with identi cation of the processes necessary to control quality. The de nition and documentation of those processes are done to the extent required to achieve the desired results.
The QMS emphasizes the process of continuous improvement via internal audits, corrective andpreventive action, and management review. The system is based on the heritage of assurance
programs meeting NASA requirements for spacecraft instrument development projects which
SSEC has implemented within a university based research and development organization. The
quality aspects of the project are designed and built-in from the beginning, rather than \testedin" after the fact. This approach makes quality assurance part of the management and engineering process thereby increasing eÆciency, improving results, and minimizing errors.
The key documents de ning the IceCube Quality Plan are:
1. American National Standard ANSI/ISO/ASA Q9001-2000 (and referenced documents).
These de ne the standards we are intending to meet.
2. The SSEC Quality Management System (QMS) Plan (in development). This describes
the UW-Madison SSEC Quality Management System policies and procedures.
3. The IceCube Quality Plan. This plan will detail the quality plan for the IceCube project.
The application of the SSEC QMS for this project and any special needs of IceCube will
be described in this document
4. Supporting Procedures, Speci cations, and Instructions. Some of these will be created forthe project, others will documents used by other projects.

223

12

Relationship of AMANDA and IceCube

The AMANDA-II detector will continue to take data during the construction phase of IceCube.
During and after this period, members of the AMANDA-II (and IceCube) collaborations will be
writing theses and publications based on analyses of AMANDA-II data. Since some membersof the AMANDA-II collaboration are not members of IceCube, AMANDA-II will continue to
produce an independent data stream. Also, since AMANDA-II needs to digitize its PMT signals
within a few microseconds, it must be running and triggering independent of IceCube.
During the 2001/2002 and 2002/2003 seasons the AMANDA-II detector will be upgradedwith waveform recording of its channels with optical readout. The DAQ system will in thesame period be upgraded in order to increase data capacity and reduce dead time. No signi cant further upgrades of AMANDA-II are foreseen after the 2002/2003 season. Thereafter, theAMANDA-II detector will mainly need maintenance and calibration, and as such it will takedata with minimal investment in personnel.
The AMANDA-II detector will be surrounded by IceCube strings (see g. 59), permitting thetwo detectors to be run in coincidence. As the number of deployed IceCube strings increases, datataken from a combination of the two detectors will provide a useful testing ground for IceCube
software, an important calibration tool for IceCube, and accelerate the ability of IceCube to
produce scienti c results.
Coincident triggering of AMANDA-II and IceCube is feasible at several levels. One could
treat AMANDA-II and IceCube as completely independent entities at trigger level and write out
the triggered data in two independent output streams. Selecting coincidence events can thenbe done oine, or in the IceCube event builder, using each detector's GPS timestamps. This
scheme is simple, but it has the (perhaps unimportant) drawback that it will miss parts of those
events which are below trigger threshold in one detector but not the other. It will also misscoincident events which are below threshold in both detectors.
It is possible to correlate events earlier in the data stream. The global trigger in the IceCube
DAQ system receives hit information via ethernet and the global trigger software runs on astandard computer (see Sec. 7 for details). By sending similar information from AMANDA-II to
the IceCube global trigger, a search for correlations between the two detector systems can easily
be done, without the need for any new hardware. The timestamps for AMANDA-II hits would
have to be corrected by the measured signal delays due to the down-hole optical bers, but thiscan be accomplished with a straightforward look-up table in the global trigger software.
The information that both detectors have correlated hits can be sent to both systems andagged in their respective data structures. This will make oine analysis easier. It is also
possible to write out a data stream with fully combined data information from AMANDA-II
and IceCube.
The information coming from AMANDA-II will di er in format and content from IceCube
data (with the partial exception of the DOMs in AMANDA-II string 18). The channels in
AMANDA-II which have only electrical read out will have no waveform information, only time,
TOT and ADC information. The AMANDA-II channels with optical readout will have waveform
information, but with di erent sampling frequency than that of IceCube. Data format trans224

lation and the ability of the IceCube oine analysis software to handle disparate information
content are therefore required.
The tasks outlined above require some IceCube software e ort, but that e ort should not be
substantial in the context of a well-designed IceCube software system. Further e ort to maintainand calibrate AMANDA-II is also needed, and will be part of the winter-over responsibilities,
with oversight and calibration analysis work done by IceCube and AMANDA-II physicists.
Overall, the e ort to integrate AMANDA-II and IceCube is not large, and the returns on thee ort will substantially outweigh the investment.

225

References[1] M. Nagano et al. J. Phys. G10 (1984) 1295.
[2] Yu. A. Fomin et al., Proc. 22nd Int. Cosmic Ray Conf. (Dublin) vol. 2 (1991) 85.
[3] M. Takeda et al., Phys. Rev. Lett. 81 (1998) 1163.
[4] M.A. Lawrence, R.J.O. Reid & A.A. Watson, J. Phys. G17 (1991) 733.
[5] M.I. Pravdin et al., Proc. 26th Int. Cosmic Ray Conf. (Salt Lake City, 1999) vol. 3, p. 292.
[6] D.J. Bird et al., Astrophys. J. 424 (1994) 491.
[7] D.J. Bird et al., Phys. Rev. Letters 71 (1993) 3401.
[8] E. Waxman & J. Bahcall, Phys. Rev. D 59 (1999) 023002.
[9] J. Bahcall & E. Waxman, Phys. Rev. D 64 (2001) 023002.
[10] G.R. Farrar & T. Piran, Phys. Rev. Letters 84 (2000) 3527.
[11] K. Griesen, Phys. Rev. Lett. 16 (1966) 748; G.T. Zatsepin and V.A. Kuzmin, JETPh Lett.
4 (1966) 78.
[12] A. Achterberg in High Energy Gamma-Ray Astronomy, (A.I.P. Conf. Proc. 558, ed. Felix
A. Aharonian & Heinz J. Volk, 2000) 392.
[13] J. Bednarz & M. Ostrowski, Phys. Rev. Letters 80 (1998) 3911.
[14] J.G. Kirk, A.W. Guthmann, Y.A. Gallant & A. Achterberg, Ap.J. 542 (2000) 235.
[15] T. K. Gaisser, in Observing Ultra-high energy Cosmic Rays from Space and Earth (A.I.P.
Conf. Proc. 566, ed. Humberto Salazar, Luis Villase~nor & Arnulfo Zepeda, Metepec, Puebla,
Mexico, August 9-12, 2000), p. 238.
[16] R. Gandhi, C. Quigg, M.H. Reno & I. Sarcevic, Astropart. Phys. 5 (1996) 81.
[17] T.K. Gaisser, astro-ph/9707283.
[18] Mannheim, Protheroe & Rachen, astro-ph/9812398; J.P. Rachen, R.J. Protheroe & K.
Mannheim, astro-ph/9908031.
[19] J. Learned & K. Mannheim, Ann. Revs. Nuclear and Particle Physics.
[20] C. Schuster, M. Pohl & R. Schlickeiser, submitted to Astronomy and Astrophysics.
[21] M. Pohl & R. Schlickeiser, Astron. & Astrophys. 354 (2000) 395.
226

[22] F.A. Aharonian et al., Astron. Astrophys. 349 (1999) 11.
[23] F.W. Samuelson et al., Ap.J. 501 (1998) L17.
[24] A. Djannati-Atai et al. Astron. Astrophys. 350 (1999) 17.
[25] Eli Waxman & John Bahcall, Phys. Rev. Letters 78 (1997) 2292.
[26] J. Rachen & P. Meszaros, Phys. Rev. D58 (1998) 123005.
[27] P. Meszaros & E. Waxman, astro-ph/0103275.
[28] A.K. Konopelko, J.G. Kirk, F.W. Stecker & A. Mastichiadis, Ap.J. 518 (1999) L13.
[29] W. Bednarek & R.J. Protheroe, Phys. Rev. Letters 79 (1997) 2616.
[30] R.J. Protheroe and T. Stanev, Phys. Rev. Lett. 77, 3708 (1996) and Erratum 78, 3420
(1997).
[31] G. Gelmini and A. Kusenko, Phys. Rev. Lett. 84, 1378 (2000).
[32] M. Birkel and S. Sarkar, Astropart. Phys. 9, 297 (1998).
[33] T. Weiler, Astropart. Phys. 11, 303 (1999); D. Fargion, B. Mele and A. Salis,
Astrophys. J. 517, 725 (1999).
[34] D. Cline and F.W. Stecker, contributed to OWL/AW Neutrino Workshop on Observing
Ultrahigh Energy Neutrinos, Los Angeles, California, Nov. 1999, astro-ph/0003459.
[35] V. Berezinsky, M. Kachelrei and A. Vilenkin, Phys. Rev. Lett. 79, 4302 (1997).
[36] J. Alvarez-Mu~niz and F. Halzen, Phys. Rev. D 63, 037302 (2001).
[37] F.W. Stecker et al., Phys. Rev. Lett., 66, 2697 (1991).
[38] J. Alvarez-Mu~niz and F. Halzen, First International Workshop on Radio Detection of HighEnergy Particles (RADHEP 2000), Los Angeles, California, astro-ph/0102106[39] Super-Kamiokande Collaboration, Y. Fukuda et al., Phys. Rev. Lett. 81 (1998) 1562.
[40] Sudbury Neutrino Observatory (SNO) Collaboration, Q.R. Ahmad et al., submitted toPhys. Rev. Lett. (nucl-ex/0106015).
[41] J.G. Learned and S. Pakvasa, Astrop. Phys. 3 (1995) pp 267-274.
[42] F. Halzen & D. Saltzberg, Phys. Rev. Letters 81 (1998) 4305.
[43] H. Athar, G. Parente & E. Zas, Phys. Rev. D62 (2000) 093010.
[44] A.P. Szabo & R.J. Protheroe, Astropart. Phys. 2 (1994) 375.
227

[45] J. Edsjo, WIMP searches with IceCube, Amanda Internal report, Jan.7, 2000.
[46] J. Bahcall and P. Meszaros, hep-ph/0004019.
[47] AMANDA supernova search paper, A. Bouchta et al.
[48] see K.Scholberg, Nucl.Phys.Proc.Suppl. 91 (2000) 331-337.
[49] A. Loeb and E. Waxman, astro-ph/0007049.
[50] T.K. Gaisser, F. Halzen, T. Stanev, Phys. Rep. 258 (1995) 173.
[51] F.W. Stecker, O.C. de Jager, Astron. Astrophys. 334, L85 (1998).
[52] E.N. Parker, Astrophys. J. 160 (1970) 383.
[53] E. Andres et al. (AMANDA Collaboration), Astropart. Phys. 13 (2000) 1{20.
[54] E. Andres et al. (The AMANDA Collaboration), Nature 410 (2001) 441.
[55] Bai et al., Proceedings of 27th Int. Conf. on Cosmic Rays, Hamburg 2001.
[56] T. R. DeYoung, Observation of atmospheric neutrinos with AMANDA, Dissertation, University of Wisconsin-Madison, April 2001
[57] Ch. Wiebusch, Muon Reconstruction with AMANDA, DESY-PROC 1999-01, July 1999
[58] G. C. Hill, proceedings of the XXXVIth Recontres de Moriond, Electroweak Interactions
and Uni ed Theories, March 2001.
[59] V. Agrawal, T. Gaisser, P. Lipari, and T. Stanev, Phys. Rev. D53 (1996) 1314.
[60] Nellen, L., Mannheim, K., & Biermann, P.L. Neutrino Production through Hadronic Cascades in AGN Accretion Disks. Phys. Rev. D47, 5270-5274 (1993).
[61] W. Bednarek and R. J. Protheroe, Mon. Not. Roy. Astro. Soc. 287(1997) 560.
[62] S. Colafrancesco, and P. Blasi, Astropart. Physics 9 (1998) 219[63] Stecker, F.W. & Salamon, M.H. High-Energy Neutrinos from Quasars. Space Sci. Rev. 75,
341-355 (1996).
[64] T.K. Gaisser, R.J. Protheroe, and T. Stanev, Ap. J. 492 (1998) 219.
[65] E. Andres et al. (The AMANDA Collaboration), Proceedings of Neutrino 2000 Conference,
Sudbury, e-print: astro-ph/0009242.
[66] Bolesta J.W. et al., Proc. 25-th ICRC, Durban South Africa, 7:29 (1997)[67] Porrata et al., Proc. 25-th ICRC, Durban South Africa, 7:9 (1997)228

[68] Rhode W. et al. (Frejus-Coll.), AstroPart. Phys. 4:217 (1996)[69] Protheroe RJ, astro-ph/9809144 (1998)[70] C.Spiering, Nucl.Phys.Proc.Suppl. 91 (2000) 445-452.
[71] Balkanov,V.A. et al., Astropart. Phys. 14, 61-67 (2000). See also http://wwwzeuthen.desy.de/baikal/baikalhome.html.
[72] Nucl.Phys.Proc.Suppl. 87 (2000) 436-438. See also http://antares.in2p3.fr/.
[73] G.V.Domogatsky (for BAIKAL Collaboration), Nucl. Phys. Proc. Suppl. 91 (2000) 438-444.
[74] See http://www.nestor.org.gr/.
[75] Zh.-A. Dzhilkibaev (for BAIKAL Collaboration), these proceedings, Int. Conf. on Neutrino
Telesopes, Venice, 2001, astro-ph/0105269.
[76] Waxman, E. & Bahcall, J.N. High-Energy Neutrinos from Cosmological Gamma Ray Burst
Fireballs. Phys. Rev. Lett. 78, 2292-2295 (1997).
[77] Waxman, E. & Bahcall, J.N. High Energy Neutrinos from Astrophysical Sources: An Upper
Bound. Phys. Rev. D59, 023002 (1999).
[78] E. Waxman and J.N. Bahcall, Phys. Rev. Lett. 78, 2292 (1997).
[79] AMANDA Collaboration (Bai et al.), Sep 2000. 7pp. Contrib. to the proc. of 3rd Int.
Workshop on the Identi cation of Dark Matter (IDM2000), York, England, 18-22 Sep 2000.
e-Print: astro-ph/0012285[80] Paper in preparation.
[81] Ahrens et al. (AMANDA collaboration), Search for Supernova Neutrino Bursts with the
AMANDA detector, accepted for publication, AstroParticle Physics, April 2001.
[82] http://www-zeuthen.desy.de/nuastro/publications/others/proposal.shtml[83] http://www.ssec.wisc.edu/a3ri/icecube/proposal/[84] http://www-zeuthen.desy.de/nuastro/[85] The Origin of Cosmic Rays, V.L. Ginzburg & S.I. Syrovatskii (Pergamon Press, 1964).
[86] M. Nagano et al. J. Phys. G10 (1984) 1295.
[87] Yu. A. Fomin et al., Proc. 22nd Int. Cosmic Ray Conf. (Dublin) vol. 2 (1991) 85.
[88] M. Takeda et al., Phys. Rev. Lett. 81 (1998) 1163.
229

[89] M.A. Lawrence, R.J.O. Reid & A.A. Watson, J. Phys. G17 (1991) 733.
[90] M.I. Pravdin et al., Proc. 26th Int. Cosmic Ray Conf. (Salt Lake City, 1999) vol. 3, p. 292.
[91] D.J. Bird et al., Astrophys. J. 424 (1994) 491.
[92] E.G. Berezhko & H.J. Volk, Astroparticle Phys. 7 (1997) 183.
[93] T.K. Gaisser, F. Halzen, T. Stanev, Phys. Rep. 258 (1995) 173.
[94] E. Waxman & J. Bahcall, Phys. Rev. D 59 (1999) 023002.
[95] P.Lipari, Astropart. Phys. 1 (1993) 195-227.
[96] G.R. Farrar & T. Piran, Phys. Rev. Letters 84 (2000) 3527.
[97] T. K. Gaisser, to be published in Proceedings of the International Workshop on Observing
Ultra-high energy Cosmic Rays from Space and Earth (Metepec, Puebla, Mexico, August
9-12, 2000), astro-ph/0011525.
[98] T.K. Gaisser, Talk given at the OECD Megascience Forum Workshop, Taormina, Sicily,
22/23 May, 1997, astro-ph/9707283.
[99] Mannheim, Protheroe & Rachen, Phys.Rev. D63 (2001) 023003, astro-ph/9812398; J.P.
Rachen, R.J. Protheroe & K. Mannheim, Comment presented at the 19th Texas Symposium, Paris, December 1998, astro-ph/9908031.
[100] J. Alvarez-Mu~niz and F. Halzen, Phys. Rev. D 63, 037302 (2001).
[101] L.V. Volkova, Yad. Fiz. 31, 1510 (1980) [Sov. J. Nucl. Phys. 31, 784 (1980)].
(1999).
[102] D. Cline and F.W. Stecker, science white paper from UCLA Workshop on High Energy
Neutrino Astrophysics, astro-ph/0003459.
[103] R.J. Protheroe and T. Stanev, Phys. Rev. Lett. 77, 3708 (1996) and Erratum 78, 3420
(1997).
[104] G. Gelmini and A. Kusenko, Phys. Rev. Lett. 84, 1378 (2000).
[105] The Detection of Faint Light in Deep Underwater Neutrino Telescopes, C. Wiebusch, Ph.D.
Thesis, PITHA 95/37, RWTH Aachen, Dec. 1995.
[106] M. Birkel and S. Sarkar, Astropart. Phys. 9, 297 (1998).
[107] Supernova Neutrino-Burst Detection with the AMANDA Detector, to be published.
[108] F. Halzen, J.E. Jacobsen: Possibility that High Energy Neutrinos Telescopes could detect
Supernovae, Phys. Rev. D49, 1758 (1994).
230

[109] K. Scholberg, SNEWS: the Supernova Early Warning System, Conference proceedings
paper of the 3rd Amaldi Conference on Gravitational Waves, astro-ph/9911359.
[110] Christian Weinheimer and Lutz Kopke, AMANDA internal note 20000203.
[111] Marc Hellwig et al., AMANDA internal note 20010301.
[112] T. Neunho er for the AMANDA Collaboration, contributed paper to ICRC 2001.
[113] P. Bauleo et al., UV-enhancement of photomultiplier response, a study of wavelength
shifters for the AMANDA/IceCube detector, August 99.
[114] J.F. Beacom and P. Vogel, Phys. Rev. D60, 33007 (1999).
[115] T. Weiler, Astropart. Phys. 11, 303 (1999); D. Fargion, B. Mele and A. Salis,
Astrophys. J. 517, 725 (1999).
[116] V. Berezinsky, M. Kachelrei and A. Vilenkin, Phys. Rev. Lett. 79, 4302 (1997).
[117] F.W. Stecker et al., Phys. Rev. Lett., 66, 2697 (1991).
[118] J.G. Learned and S. Pakvasa, Astrop. Phys. 3 (1995) pp 267-274.
[119] H. Athar, G. Parente and E. Zas, in preparation.
[120] I.Belolaptikov et al., Astropart.Phys. 7 (1997) 263.
[121] J.Edsjo, WIMP searches with IceCube, Amanda Internal report, Jan.7, 2000.
[122] K.Dick et al., Nucl.Phys. B588 (2000) 101-109 and Nucl.Phys. B598 (2001) 543-553.
[123] J.G.Learned, K.Mannheim, High Energy Neutrino Astrophysics, Ann.Rev.Nucl.Phys.
(2000).
[124] M.Leuthold, Proc.Simulation and Analysis Methods for Large Neutrino Telescopes, DESY
Zeuthen, 1998, DESY-PROC-1999-01 (ed. C.Spiering), 484.
[125] M.Leuthold, IceCube Performance Studies, Amanda Internal Report, Nov.1999.
[126] J.Krabi, C.Spiering et al., preprint PHE 91-03, Zeuthen 1991.
[127] E. Waxman & J. Bahcall, Phys. Rev. Lett. 78 (1997) 2292.
[128] E. Waxman & J. Bahcall, Phys. Rev. D 59 (1999) 023002.
[129] C.Hettlage and K.Mannheim, to appear in the Proceedings of the XXIst Moriond Workshop Very High Energy Phenomena in the Universe, Les Arcs, France, January 20-27 2001,
astro-ph/0103499
231

[130] T.Gaisser, to be published in Proceedings of the International Workshop on Observing
Ultra-high energy Cosmic Rays from Space and Earth (Metepec, Puebla, Mexico, August
9-12, 2000), astro-ph/0011525.
[131] P. L. Biermann et al., Nucl. Phys. Proc. Suppl. 87 (2000) 417, astro-ph/0008063[132] G.C. Hill, K. Rawlins, Amanda Internal Report[133] G.C. Hill Astropart. Phys. 6 (1997) 215.
[134] G.C. Hill. PhD thesis, University of Adelaide (1996)[135] G.C. Hill &. K. Rawlins Presentation at NSF Hartill Icecube Review, June 2000
[136] A.Hillas et al., Astrophys.J. 503, 744.
[137] T.Weekes, to be included in proceedings of the International Symposium on High Energy
Gamma-Ray Astronomy, Heidelberg, June 2000, astrop-ph/0010431.
[138] K.Wang et al., A survey of the Northern sky for TeV point sources, astro-ph/0103353[139] M.Leuthold, C.Spiering, H.Wissing, Amanda Internal Report.
[140] G.Feldman, J.Cousins, Phys.Rev. D57 (1998) 3873.
[141] S.Barwick, HENAP meeting (Venice, Feb. 2001), Amanda collaboration meeting in March
2001.
[142] S.Hundertmark, Amanda collaboration meeting in Oct. 2000.
[143] P.Meszaros and E.Waxman, astro-ph/0103275.
[144] D.Guetta, Review talk, to appear in the Proc. of the XXIst Rencontres de Moriond "VeryHigh Energy Phenomena in the Universe", Les Arcs, France, Jan. 20-27 (2001), astroph/0104045.
[145] C.Schuster, M.Pohl, R.Schlickeiser, Neutrinos from AGN as diagnostic tool, submitted toA&A[146] E.Waxman, submitted to PRL, astro-ph/0102317.
[147] T.Weiler, submitted to Astro. Part. Phys, astro-ph/0001233.
[148] D.Bakari et al., hep-ex/0004019.
[149] G.Giacomelli and L.Patrizii, Lecture at the Fifth School on Non-Accelerator Particle Astrophysics, Trieste, 29 June - 10 July 1998, hep-ex/0002032.
[150] E.Andres et al., Astropart.Phys.13 (2000) 1.
232

[151] see report on neutrino analysis on Zeuthen IceCube webpage.
[152] C.Spiering, Nucl.Phys.Proc.Suppl. 91 (2000) 445-452.
[153] L.Kopke and C.Weinheimer, Amanda Internal report.
[154] K.Scholberg, Nucl.Phys.Proc.Suppl. 91 (2000) 331-337.
[155] Pierre Auger Observatory, see http://www.auger.org/.
[156] J.E. Dickinson et al., NIM A440 (2000) 95.
[157] D. Nygren et al., Digital Optical Module & System Design for a km-Scale Neutrino Detector in Ice, LBNL INPA Internal Report, March 20, 1998.
[158] R. G. Stokstad, RAP - A Method for Absolute Time Calibration of a Large Array basedon a digital Optical Module System, LBNL-43200, October 9, 1998.
[159] R. G. Stokstad, Consequences of a Local Coincidence for a Large Array in Ice, LBNL41476, May 1998.
[160] J. Jacobsen and R. G. Stokstad, Consequences of a Local Coincidence for a Large Arrayin Ice II: Local Coincidences in AMANDA B-10 1997 Data, LBNL INPA Internal Report,
October 9, 1998.
[161] J. Jacobsen and R. G. Stokstad, Consequences of a Local Coincidence for a Large Arrayin Ice III: Monte Carlo Simulations, LBNL INPA Internal Report, October 24, 1998.
[162] See http://www.rational.com/products/rose for details about the Rational Rosemodel-driven software development system.
[163] See http://www.sf.net for details about the Sourceforge software development system.
[164] See http://cedar.web.cern.ch/CEDAR/ for details about the EDMS document handlingsystem.
[165] For Gaudi documentation, see http://proj-gaudi.web.cern.ch/proj-gaudi.

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