A STUDY OF ATMOSPHERIC NEUTRINOS
AT SUPER-KAMIOKANDEA DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THE
UNIVERSITY OF HAWAII IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
IN
PHYSICSDECEMBER 1997

By
John W. Flanagan

Dissertation Committee:
John G. Learned, Chair
Stephen L. Olsen
Sandip Pakvasa
L. Thomas Ramsey
Klaus Sattler

ii

We certify that we have read this dissertation and that, in our opinion, it is satisfactory in scope and quality as a dissertation for the degree of Doctor of Philosophy
in Physics.

DISSERTATION COMMITTEE|||||||||||||||||||||||||{
Chairperson|||||||||||||||||||||||||{|||||||||||||||||||||||||{|||||||||||||||||||||||||{|||||||||||||||||||||||||{

Acknowledgmentsiii

Support for this dissertation came from many sources, the rst of which is theauthor's advisor, John Learned, whose intuitition and creativity in the understanding of what is important in a physics analysis and how to get at it has been an
inspiration. In addition, he care for, and enthusiastically promotes, his students.
The author has also bene ted from the insight, support and patience of his otherthesis committee members: S. Pakvasa, S. Olsen, K. Sattler and T. Ramsey. In
addition, the author bene ted from discussions with S. Matsuno, and V. Stenger's
healthy dose of skepticism.
This dissertation and the experiment on which it is based is highly dependent
on the hard work and diligence of the many members of the Super-Kamiokande
collaboration. The construction, operation and analysis of data from this detector
has been, and continues to be, an enormous e ort involving the participation ofmany universities in the US, Japan, and Poland, and the list of people to whom theauthor is indebted is too large to exhaustively list, and the author must apologize
to anyone inadvertently omitted.
The leadership for the experiment has come from Y. Totsuka (U. Tokyo), and from
H. Sobel (UCI) and J. Stone (BU), who speak for the US institutions.
During the period of construction, B. Kropp of UCI was a forceful and caring
leader without whom it would be dicult to imagine the outer detector having been
completed on time. His dedication to the job and to his crew got us through a yearlong period of seemingly continuous crisis, without anybody getting hurt. He and
H. Sobel also gave the author and other non-UCI people on-site whatever material
support was needed to get the job done. J. Stone came through with assistance andsupport in time of diculties with the laser calibration hardware.
During analysis, the heads of the high-energy analysis groups deserve credit fororganizing the geographically spread-out members of the group: T. Kajita of theiv
onsite group, and E. Kearns and T. Haines of the o site group. E. Kearns has
been especially helpful to the author, having hosted the author at BU for a month
during analysis, and providing guidance through the preparation for the author's
rst public talk on the experiment. All other members of the o site high-energy
analysis group deserve special mention as well: M. Messier, B. Viren, K. Scholberg,
T. Barsczak, C. Mauger, W. Gajewski, D. Kielczewska, C.K. Jung, C. Yanagisawa,
E. Sharkey, M. Earl, A. Habig, and especially C. McGrew, who was responsible formost of the backbone of the reduction.
M. Nakahata of U. Tokyo has been a dedicated leader of the calibration group. Z.
Conner was a strong partner in the construction of the laser calibration system,as was R. Sanford, who along with W. Gajewski also spent a lot of time on thecalibration of the outer detector. M. Rosen provided expertise in laser optics. J.
George and L. Wai worked inhumanly long hours on the outer-detector DAQ. Manyothers should not be forgotten, among them J. Hsu Svoboda, whose e orts werecritical during construction, as were those of M. Vagins. R. Svoboda gave wise
advice on analysis matters, even if it wasn't always heeded. Mr. Shimoi of the
Kamioka Mining Company provided much practical assistance during construction.
J. Bruce took excellent care of many an administrative mess throughout the durationof the author's tenure on the experiment. A. Kibayashi helped the author out of atime jam as the defense deadline approached.
The author's parents, John and JoAnn, have always been there for the author,
even as has gradually migrated further and further across the planet from them.
Eventually, he will circle around
Finally, and most importantly, has been the loving support of Mika Masuzawa, who
as colleague, friend and wife has taught the author some of the most importantlessons that the author has learned. (Such as, it is wiser not to schedule a wedding
and thesis defense within one week of each other.) Her support and understanding
greatly aided the completion of this thesis.

vThis experiment is made possible with the cooperation and assistance of the Kamioka
Mining Company (Kamioka Kougyou K.K.). This work was supported in part by
the U.S. Department of Energy (DOE) and the Japanese Ministry of Education,
Science, Sports and Culture (Monbusho).

Abstractvi

Several measurements of atmospheric neutrino-induced events in the range  0:1
to  1 GeV have found a smaller than expected number of muon-neutrino-induced
events relative to the number of electron-neutrino-induced events detected. SuperKamiokande is a large-scale underground water-Cherenkov detector located in Gifu
prefecture, Japan, which began taking data in April 1996. The results of an analysis
of contained atmospheric-neutrino-induced events from 301.4 live days of detector
operation are presented, representing 18.5 kton-years of exposure. The ratio of
the number of single-ring muon-like events to the number of single-ring electronlike events is found to be lower than the same ratio predicted by monte carlo:,like)Data
R  ((,,like=e
like=e,like)MC = 0:64  0:04(stat)  0:06(syst) in the kinematic ranges usedby IMB (0:1 GeV/c < pe < 1:5 GeV/c and 0:3 GeV/c < p < 1:5 GeV/c), whilein the ranges used by Kamiokande (0:1 GeV/c < pe, 0:2 GeV/c < p and visibleenergy < 1:33 GeV), R = 0:65  0:04(stat)  0:06(syst). The results are discussed
in the framework of the two-neutrino oscillation scenarios  ,  ,  , sterile, and , e.

Contentsvii

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

iii

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vi

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

x

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

1.1 History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Atmospheric Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1  and e Separation . . . . . . . . . . . . . . . . . . . . . .
1.2.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . .
1.2.3 Observations (E  100 GeV ) . . . . . . . . . . . . . . . . .
1.2.4 Interpretation of Results . . . . . . . . . . . . . . . . . . . .
1.2.5 Atmospheric Neutrinos in Super-Kamiokande . . . . . . . .
1.2.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . .

1
3
5
5
9
11
14
14

2 Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.1 Super-Kamiokande detector . . . . . . . . . . . . . . . . . . . . . .
2.2 Data Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Detector Electronics . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3.1 Inner Detector . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4 Speci cations and Principles of Operations . . . . . . . . . . . . . .
2.4.1 ATM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.2 GONG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

16
21
22
22
23
23
25

viii
2.4.3 TRG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.4 LIME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5 Hitsum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5.1 Outer Detector . . . . . . . . . . . . . . . . . . . . . . . . .

26
27
29
29

3 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.1
3.2
3.3
3.4

PMT Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Time Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Charge Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . .
Laser Calibration Hardware . . . . . . . . . . . . . . . . . . . . . .
3.4.1 Laser and Optics . . . . . . . . . . . . . . . . . . . . . . . .
3.4.2 Optical Fibers . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.3 Inner Detector Fibers . . . . . . . . . . . . . . . . . . . . . .
3.4.4 Outer Detector Fibers . . . . . . . . . . . . . . . . . . . . .
3.4.5 Laser Calibration Operation . . . . . . . . . . . . . . . . . .

32
32
33
34
34
36
36
37
43

4 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.1 Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Event Classi cation . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.1 Single-ring Finding . . . . . . . . . . . . . . . . . . . . . . .
4.2.2 Muon Decay . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.3 Particle ID . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.4 Energy Determination . . . . . . . . . . . . . . . . . . . . .
4.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.1 Comparison of Analyses . . . . . . . . . . . . . . . . . . . .
4.4 Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45
49
49
52
58
59
62
78
78
90

ix

A Monte Carlo Cross-sections . . . . . . . . . . . . . . . . . . . . . . . 91
B The Super-Kamiokande Collaboration . . . . . . . . . . . . . . . . . 94
C Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

List of Tablesx

1.1 Summary of contained events from IMB-3 and Kamiokande. . . . .

8

4.1 Fitter errors on MC muons. . . . . . . . . . . . . . . . . . . . . . .
4.2 Fitter errors on MC electrons. . . . . . . . . . . . . . . . . . . . . .
4.3 Best- t results for oscllation scenarios. . . . . . . . . . . . . . . . .

47
48
81

List of Figures
2.1 Geometry of Cherenkov light from passage of relativistic charged
particle through the detector medium (water). . . . . . . . . . . .
2.2 Structure of detector, showing inner-detector cylinder surrounded byouter-detector shell. . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Super-Kamiokande tank in vertical section, showing the PMTs of theinner and outer detectors separated by a 55-cm \dead space." (Figure
not to scale.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4 Front (inner-detector) and Back (outer-detector) views of a typicalwall supermodule. . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5 Left: Data path between huts on tank top. Right: DAQ cards in
TKO crate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Inner Detector data acquisition hardware block diagram. Shown isthe data path within each of the 4 outer huts. Each online slave
computer (two per outer hut) reads out the hit information for one
eighth of the detector, passing the hit information to the event-builder
softtware in the central online host computer. . . . . . . . . . . . .
2.7 Outer Detector data acquisition hardware block diagram. Shown isthe data path within each of the 4 outer huts. The dual-port memories(DMPs) are read out in the Central Hut by the SUKANT online slave
computer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1
3.2
3.3
3.4
3.5

Laser Calibration DAQ . . . . . . . . . . . . . . . . . . . . . . . . .
Laser Calibration Optics . . . . . . . . . . . . . . . . . . . . . . . .
Laser Fiber Runs . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Laser Calibration OD Fiber Mounts . . . . . . . . . . . . . . . . . .
Laser ber di users . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi

17
18
19
20
21

22

31
38
39
40
41
42

4.1 Yastef vertex and direction errors on  1 GeV MC muons and electrons. 47
4.2 Distribution of fully-contained events within the ducial volume. . . 49
4.3 Example of an event classi ed as multi-ring. . . . . . . . . . . . . . 50

xii
4.4 Ringer values for data and monte carlo samples. Single-ring events
have a lower ringer value, and multi-ring events have a higher value.
4.5 Example of an event identi ed as muon-like. . . . . . . . . . . . . .
4.6 Example of an event classi ed as a decay-electron, following previous
muon event. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.7 Example of an entering muon which has stopped in the tank. Notethe presence of activity near the entry point in the outer detector,
in the upper-right hand corner, which is absent from fully-contained
events. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.8 Example of an event identi ed as electron-like. . . . . . . . . . . . .
4.9 ADPID lepton misidenti cation rates for quasi-elastic MC events
which pass the reduction cuts. . . . . . . . . . . . . . . . . . . . . .
4.10 DOCHIRA lepton misidenti cation rates for quasi-elastic MC events
which pass the reduction cuts. . . . . . . . . . . . . . . . . . . . . .
4.11 Visible energy of all events and those with mu decay. . . . . . . . .
4.12 Visible energy of single-ring events and those with mu decay. . . . .
4.13 Momentum of single-ring e-like events and those with a mu decay. .
4.14 Momentum of single-ring -like events and those with a mu decay. .
4.15 Adpid particle-ID distributions for data and MC, IMB cuts. . . . .
4.16 Adpid particle-ID distributions for data and MC, KAM cuts. . . . .
4.17 Dochira particle-ID distributions for data and MC, IMB cuts. . . .
4.18 Dochira particle-ID distributions for data and MC, KAM cuts. . . .
4.19 Distance along primary (yastef) track of decay (hayai) vertices forevents identi ed as muons with 500MeV < Evis < 5GeV . . . . . . .
4.20 Adpid PID distributions for data and MC, 1.5 GeV<Evis<5 GeV. .
4.21 Dochira PID distributions for data and MC, 1.5 GeV<Evis<5 GeV.
4.22 Fiducial volume distribution of all events and those with a mu decay.
4.23 Fiducial volume distribution of single-ring events and those with amu decay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.24 -like fraction vs zenith angle, 2-meter ducial cut. . . . . . . . . .

51
54
55

57
58
60
61
63
63
64
64
66
66
67
67
69
72
72
74
74
75

xiii
4.25 Muon-decay fraction vs zenith angle 2-meter ducial cut. . . . . .
4.26 -like fraction vs zenith angle 5-meter ducial cut. . . . . . . . . .
4.27 Muon-decay fraction vs zenith angle 5-meter ducial cut. . . . . .
4.28 -like fraction vs momentum. . . . . . . . . . . . . . . . . . . . . .
4.29 Muon-decay fraction vs momentum. . . . . . . . . . . . . . . . . . .
4.30 Asymmetry vs visible energy, data. . . . . . . . . . . . . . . . . . .
4.31 Asymmetry trajectory data. . . . . . . . . . . . . . . . . . . . . . .
4.32 Asymmetry vs visible energy, MC with no oscillations. . . . . . . .
4.33 Asymmetry trajectory MC with no oscillations. . . . . . . . . . . .
4.34 Asymmetry vs visible energy, MC with  !  osc. . . . . . . . . .
4.35 Asymmetry trajectory MC with  !  osc. . . . . . . . . . . . . .
4.36 Chi-squared, MC with  !  osc. . . . . . . . . . . . . . . . . . .
4.37 Asymmetry vs visible energy, MC with  ! Sterile osc. . . . . . .
4.38 Asymmetry trajectory MC with  ! Sterile osc. . . . . . . . . . .
4.39 Chi-squared, MC with  ! Sterile osc. . . . . . . . . . . . . . . . .
4.40 Asymmetry vs visible energy, MC with  ! e osc. . . . . . . . . .
4.41 Asymmetry trajectory MC with  ! e osc. . . . . . . . . . . . . .
4.42 Chi-squared, MC with  ! e osc. . . . . . . . . . . . . . . . . . .

75
76
76
77
77
82
82
83
83
84
84
85
86
86
87
88
88
89

A.1 IMBEast cross-sections. . . . . . . . . . . . . . . . . . . . . . . . .

93

Chapter 1
Introduction

1

1.1 History
The existence of a light, chargeless particle with spin 12 h was proposed in the early
1930s as a solution to the apparent lack of energy and angular momentun conservation seen in beta decays. Beta decay is characterized by the emission of an electronfrom a nucleus; using the particles known to exist in 1932, the proton, neutron andthe electron, the best model for beta decay available was:n ! p + e,
p ! n + e+i.e., the conversion of a neutron in the nucleus to a proton accompanied by theemission of an electron, or conversely the conversion of a proton to a neutron withthe emission of a positron. While this conserves charge, measurements of the energy
spectrum of the emitted electron or position (also denoted ) showed that not allof the momentum and energy released could be accounted for. In addition, sinceelectrons and protons have spin 21 , it is not possible to combine them to create thespin of the neutron, which is also 12 . But no other particles were observed in thesereactions.
Pauli proposed that a new, fourth particle must be carrying away some energy andangular momentum, unobserved.[1] Since the particle had not been detectable atthat point, it would have a very small cross-section. The observed electron energy
distribution, smoothly tapering o towards zero, suggested that it must be very lightor massless so that it could sometimes take away almost all of the released energy
while still conserving momentum. Conservation of angular momentum suggested

2that it have spin 12 . Conservation of charge implied that it was electrically neutral.
This particle was dubbed the neutrino by Fermi[2], who incorporated it into a newtheory of beta decay which introduced the weak nuclear force.
The revised beta-decay formula becomes:

n ! p + e, + e
p ! n + e+ + e
where the neutrino subscripts indicate that they are electron neutrinos and antineutrinos, though the presence of multiple neutrino avors (e, ,  ) wasn't knownat the time.
The neutrino itself was not directly observed until 1956 [3] by Reines and Cowan,
after preliminary experimental hints in 1953[4,5]. Using the Hanford nuclear reactor as a high- ux source, the neutrino byproducts from the ssion reactions weredetected by the use of a water and cadmium-chloride medium surrounded by liquid
scintillator. Incoming anti-electron neutrinos interact with protons in the liquid,
producing a positron and neutron:

e + p ! n + e+
The positron quickly annihilates with an electron to produce two 0.511 MeV gamma
rays, which were detected with photomultiplier tubes by observing the light fromelectromagnetic showers they produce in the surrounding liquid scintillator. Thisis followed a few microseconds later by the capture of the neutron on a cadmium
nucleus, leading to an excited nuclear state which subsequently releases a few MeV
worth of gamma radiation, which was again detected. This characteristic signatureof two time-separated signals was measured and compared with the detector on ando , permitting a conclusive detection.
Soon after this experiment, the existence of another type, or avor, of neutrino was
discovered at Brookhaven[6], the muon neutrino, which is produced in pion decay: + ! + + 3

, ! , + 
The muon neutrino and the electron neutrino are so labelled because they carry
lepton avor, a conserved quantity in interactions, with the number of [electrons +electron neutrinos] balancing on each side of an equation, as does the number of[muons + muon neutrinos]. The discovery of the tau lepton in 1975[7] implied thefurther existence of a tau neutrino.

1.2 Atmospheric Neutrinos
Atmospheric neutrinos are generated in cosmic ray interactions in the atmosphere:a cosmic ray (predominantly hydrogen and helium nuclei, plus small amounts ofheavier nuclei), interacts with a nucleus in the upper atmosphere and produces acascade of secondaries; the secondaries (typically pions and kaons) either interact
again or decay. The decay of pions generates muon neutrinos and muons, which canthen further decay into electrons, electron neutrinos and muon neutrinos.
For energies below a few GeV where most muons decay in ight in the atmosphere,some estimates of the relative uxes of muon and electron neutrinos can be madefrom this simple picture.[8] The rst is that the neutrino energy spectrum follows thepower-law primary spectrum. In such a cascade, the number of positively charged
secondaries is nearly equal to the number of negatively charged secondaries. Thus,
if we assume that all low-energy pions decay, + ! + + 
, ! , + and that their muon secondaries also decay,
+ ! e+ + e + 
, ! e, + e + 

4then because of the asymmetry of the  !  , which gives each of the two neutrinos
from muon decay about the same energy as the neutrino from the pion decay, thenin a given energy range:

e

 21

,




 21

,

and due to the excess of protons to neutrons in the incident cosmic rays,ee ,+ <1.

More detailed calculations have been made, accounting for nuclear abundances in
the atmosphere, muon energy loss and polarization, and the location of neutrino
measurement on the earth.[9,10, 11,12,13] For neutrinos below about 20 GeV, corrections to this picture need to be made to account for the e ect of the earth's
magnetic eld on charged particle trajectories, and on the e ects of the solar windon the ux of incoming cosmic rays.[13] At energies greater than a few GeV, muons
don't have much chance to decay before hitting the ground, which sharply reduces
the neutrino uxes further, especially the electron neutrino ux.
Atmospheric neutrino calculations have various uncertainties. Some of these, such as
the composition and ux of the primary cosmic rays, are common to all of the calculations. Other uncertainties, for example, the physics assumptions in the interaction
model, are not common to the di erent calculations. A comparison of di erent
atmospheric neutrino ux models nds that the di erences in overall neutrino ux
are large, up to 30%, due primarily to di erent models for pion production (20%)
and somewhat less due to di erent treatments of the geomagnetic e ects (10%).
However, the predicted relative rate of electron- and muon-neutrino interactions
varies by only 5%.[14]

5

1.2.1



and e Separation

The avor of the parent neutrino is determined by identifying the lepton typeproduced in the interaction. Two methods have been used to discriminate between
an electron- and muon-neutrino induced events: the rst is to observe the muon's
decay and the second is to examine in detail the nature of the particle tracks.
The rst, and conceptually the simplest method, is to record muon decays that occur
after the event in question. (Not all detectors have the ability to recognize the low
energy electrons from stopped muon decay.) If the muon decays can be recorded, thismethod can help distinguish between events with and without a muon. However,this method su ers from some de ciencies. Negative muons can be captured andtherefore be lost. In addition, a pion in an event can decay, producing a muon
whose delayed decay is then observed. Thus, neutral current events, due to either
electron- or muon-neutrinos that produce pions, can appear to be muon-neutrino
induced, making calculation of the expected fraction of muon decays complicated.
The second method is more ecient but also more complicated. This \patternrecognition" approach utilizes the di erence between an electron's showering track
and a muon's minimum ionizing track as these particles pass through the detector.
This method can also be fooled by pion production unless the detector has theability to identify and discard such events.
These two methods are largely independent measures.

1.2.2 Experimental Results
Atmospheric neutrinos were rst detected in underground detectors as early as
the late 1960s[15, 16]. These early experiments used horizontally separated setsof instrumented scintillator elements located in mine shafts to record the path ofmuons passing through the entire detector. Muon tracks reconstructed as being
within 40 deg of straight downward-going were assumed to be cosmic-ray muonsthat had penetrated from above; muon tracks closer than that to the horizontal, or6upward-going, were assumed to be the products of charged-current interactions ofatmospheric neutrinos in the earth surrounding the detector. Of course, some of thestraight downward-going events would also be due to neutrino interactions in therock, but they are indistinguishable from the background of penetrating cosmic-ray
muons. Upward-going muon event rates, which depend primarily on a detector's
muon energy threshold, are typically 0:3 , 0:4m,2yr,1.
In the 1980s, underground water-Cherenkov detectors were constructed for the purpose of searching for possible proton decay. These consisted of large tanks of water,
lined with photo-multiplier tubes which recorded the Cherenkov radiation producedby high-energy charged particles in the water. They sought to detect the decay
products of protons in the water, and were optimized for total event energies up to
and over the rest mass of the proton, 938 MeV. An important background to thissearch was the interaction of atmospheric neutrinos inside the detector.
Atmospheric electron- and muon-neutrinos of average energy  1 GeV , which interact within the detector volume, produce \contained" events. \Fully-contained"
events are those in which all visible products of the interaction stay in the detector,
while \partially-contained" events may exit the detector; in general, \contained"
is used to mean \fully-contained." Contained event rates, which depend on theenergy threshold and geomagnetic latitude of a detector, as well as solar activity,
are typically 0:5 kt,1 d,1.
While no evidence of proton decay was found, these detectors were able to study
the atmospheric neutrino \background." Large samples (> 100) of contained events
have been collected by two general types of detectors. The rates are consistent
with the expected interactions of atmospheric neutrinos. Because no conclusive
evidence for nucleon decay has yet been observed, these samples have been wholly
attributed to atmospheric neutrinos. The possibility that events from other sources
have been observed can not be excluded because of the large uncertainty (20%)in the prediction of the absolute rate of atmospheric neutrino-induced events, as
discussed above.

7
The ring-imaging water-Cherenkov detectors have the largest samples of atmospheric
neutrino-induced events. These detectors operate as total absorption calorimeters. Massive particles, such as  and , must be above Cherenkov threshold( 180 MeV=c) to be detected. Reliable discrimination between massive andshowering (e; ) particles is possible with sucient Cherenkov light collection(> 1 pe=MeV ). Particle direction is unambiguous but vertex resolution is relatively
poor ( 1 m).
Small samples of contained events are available from iron tracking calorimeters.
These neutrino detectors require volume-intensive instrumentation, limiting theirsize, but providing excellent spatial resolution ( 1 cm) and reconstruction ofparticle tracks. Particle types are inferred from their range and ionization yield.
A particle's direction is often not determined in these detectors.

Results from IMB The IMB-1 detector recorded 401 contained events during
an exposure of 3:77 kt , yr extending from September 1982 to June 1984. These

data provided an early measurement of the atmospheric neutrino spectrum andcomposition.[17] The fraction of events having an identi ed muon decay, whichindicates the content of muon neutrino-induced events in the sample, was 26%  3%.
Simulated data predicted 34%  1%. Separation of single- and multiple-ring eventsand identi cation of particle types in IMB-1 was not ecient enough to warrant amore sophisticated analysis of avor composition.
The IMB-3 detector began operation in May 1986 after an upgrade in sensitivity
to Cherenkov light. The added light collection allowed more ecient detection ofmuon decay, a lower trigger threshold, separation of single-ring and multiple-ring
events, and particle identi cation. By March 1991 an additional 935 contained
events were collected during a 7:7 kt , yr exposure. These data provided a more
precise measurement of the atmospheric neutrino spectrum and particle content.[18]The muon decay fraction of this sample was 37%  2%. Simulated data based on
an independent model of the atmospheric neutrino ux predicted 44%  1%. The
muon decay de ciency suggested in IMB-1 data persisted in IMB-3.

8
A more sensitive test of the neutrino avor composition in the atmospheric ux
di erentiated between non-showering and showering particles (in single ring events)using a \pattern recognition" method. These results con rmed an apparent de citof muon neutrinos interacting in the detector. The number of non-showering, single ring events, as a fraction of the total number of single ring events, in IMB-3
was 36%  2%(syst)  2%(stat). The prediction, based on simulated data, was
51%  5%(syst)  1%(stat). Again, a shortage of muon-neutrino induced events wasapparent.

Results from Kamiokande The Kamiokande detector collected 557 events ina 6.18 kt-yr exposure.[19] Although smaller than IMB, its resolution is better andits energy threshold lower due to a greater sensitivity to Cherenkov light. A subsetof these data were the rst to be analyzed using single ring event separation andparticle identi cation by pattern recognition. Similar de cits of muon decays and -induced events are observed in the Kamiokande data; they observed a fractional
rate of non-showering events of 49%  4% while they expected 61%. Table 1.1
compares the IMB-3 and Kamiokande data.[20,21,22,23]
Table 1.1: Summary of contained events from IMB-3 and Kamiokande.
IMB-3
IMB-3
Kam
Kam
# Evts. Frac. of Total # Evts. Frac. of Total
Obs. 1 Ring
507
{
310
{
MC 1 Ring
525
{
333
{
Obs.  decay
168
0.33
112
0.36
MC  decay
223
0.43
162
0.49
Obs/MC  decay{ 0.77  0.06
{ 0.73  0.07
Obs. e-like
325
0.64
159
0.51
MC e-like
257
0.49
128
0.38
Obs. -like
182
0.36
151
0.49
MC -like
268
0.51
205
0.62
Obs/MC -like{ 0.71  0.05
{ 0.79  0.06

9Frejus, NUSEX, Soudan-2 results Another type of neutrino detector is theiron-tracking type, characterized by tracking elements (typically streamer or drift
tubes) sandwiched between sheets of iron or steel. Three detectors of this type havereported measurements of contained atmospheric neutrino events: Frejus, NUSEX
and Soudan-2.

The Frejus detector, located in the Frejus highway tunnel between France and
Italy, collected 188 events.[24] All events with visible energy greater than 200 MeV
and an identi ed lepton are used to measure the ratio of charged current events
due to electron- and muon-neutrinos. Neutral current events are identi ed in thisanalysis. These data do not show a signi cant de cit of  -induced events. They
measured a fraction of muon-neutrino induced events, compared with the expected,of 1:0  0:15  0:08.[25] This analysis includes upward-going stopping and horizontal
muon events, but agrees with an earlier one based only on contained events.
The NUSEX detector, located under Mt. Blanc near the border of France, Italy
and Switzerland, consisted of 134 horizontal iron plates with plastic streamer tubes,
with a threshold energy of 200 MeV. They reported a ratio of muon-like events toelectron events of 0:960,:32
0:28 relative to expectation.[26]The Soudan 2 detector had published 42 single prong events.[27] The visible energy
threshold is lower than in Frejus and an anomalous (lower-than-expected) muonneutrino induced fraction is observed, though with limited statistics. New results[28]indicate a result that is between that of Frejus and those of IMB and Kamioka, withthe ratio-of-ratios being 0:75  0:19, thus accommodating either extreme.

1.2.3 Observations (E 

100

GeV

)

External events can be used to monitor the ux of atmospheric  at energies
typically 100 times higher than that of contained events. The direction of an upwardgoing muon is well correlated with that of its  parent. The distribution of zenith

10
angles, which peaks at the horizon due to the increased decay length in the atmosphere, is sensitive to possible distortions due to neutrino oscillations. The detectors
provide limited information on the energy spectrum of external events, thus limiting
the deduced information on the neutrino spectral shape. Large samples of external
events have been collected by four experiments. Two are the large ring-imaging
water C erenkov detectors mentioned above. Others are the Baksan scintillation
counter telescope and the MACRO detector.

High energy results from IMB The IMB detector recorded 617 upward-going
muon events during an exposure of 1444 m2 yr. This corresponds to a ux of
2:54  0:10(stat)  10,13cm,2 s,1 sr,1 above a muon energy threshold of  1:2 GeV .
The predicted value, is based on a hybrid of the Volkova and Lee and Koh ux
models, is 2:46  0:49(syst)  10,13cm,2 s,1 sr,1 .

Information about the neutrino energy spectrum is provided by measuring the fraction of upward-going muons that stop inside the detector. The measured stopping
fraction is 0:138  0:014(stat), while simulations predict 0:140  0:005(stat).

Kamiokande results on upward muons The Kamiokande collaboration reports

results based on 252 upward-going muon events, which were recorded during an exposure of 842 m2yr.[29] This corresponds to a ux of 2:040:13(stat)10,13cm,2 s,1 sr,1
above a muon energy threshold of 3:0 GeV . Predicted uxes are 1:92,2:2010,13cm,2 s,1 sr,1
depending of the ux model employed. Stopping muons have yet to be incorporated
in the Kamiokande analysis. The zenith angle distribution of upward-going muonsrecorded at Kamioka is compatible with the predictions from three ux models.
Insucient statistics prevents selection of one model over another.

Upward-Going Muons Observed in Baksan The scintillation telescope at

Baksan records upward-going muons above an energy threshold of 1 GeV . In 7.18
live years, the (17  17  13)m3 detector collected 421 events. This corresponds to11a ux of 2:77  0:13(stat)  0:09(syst)  10,13cm,2 s,1 sr,1.[30] The predicted ux is
2:45 , 2:75  10,13cm,2 s,1 sr,1 depending on the atmospheric neutrino ux model.

MACRO results on upward muons MACRO recorded 255 upcoming muon

events in 15 months of livetime, being found at the rate of 130 per year. Thee ective area averaged over the hemisphere is about 400 m2 , almost the same asfor IMB. A signi cant data sample was presented in a preliminary report at the
DPF meeting in August 1996 in Minneapolis,[31] showing an angular distributionthat is a bit low in the two bins nearest the nadir. The results seem to be in minor
disagreement with the older and larger samples from Baksan, IMB and Kamioka.

1.2.4 Interpretation of Results
As shown in the last section, the results from several independent measurements of
the atmospheric neutrino ux, spectrum, and composition are in good agreement.
However, low energy measurements disagree with the theoretical expectation for
the relative rate of muon-neutrino induced events. The expectations are based on
detailed predictions of the neutrino ux, neutrino interactions, and the response of
the detector(s) in question.
On the other hand, the absolute rate of high-energy (upward-going) muon-neutrino
induced events agrees with expectations, albeit with fairly large (primarily systematic) uncertainties. With less uncertainty, the rate of upward-going stopping muons
is about as predicted, suggesting that the shape of the high-energy muon-neutrino
spectrum is understood.
The apparent dearth of low-energy muon-neutrinos may have several di erent explanations. As a reminder, the predicted absolute rate of events of either neutrino
type is quite uncertain; thus, it has not been possible to determine if the muon-likeevents are missing or if there are too many electron-like events.

12

Theoretical uncertainties Many di erent ingredients go into the calculation of

the atmospheric neutrino rate in underground detectors: the energy spectrum andcomposition of the neutrino ux must be known, detailed account must be made forthe interaction of the neutrinos (including the absolute cross section, kinematics,
and modi cations to the interaction made by nuclei), and careful consideration of
the response of the detector to the interaction products. Each of these components comes with its own uncertainty. This section brie y describes the remaining
uncertainties.
As previously mentioned, the absolute ux of neutrinos is known only to about 20%.
However, the relative ux of electron- and muon-neutrinos is known much better.
The predicted fraction of muon-like events based on three di erent ux models does
not di er by more than about 2% and we use this to estimate the uncertainty inthe relative rate of muon-like events, due to the ux uncertainty.
The absolute value of the neutrino cross section in this energy range is somewhat
uncertain. The axial-vector form factor is known to about 10% and additional
uncertainty must be added to account for nuclear e ects. However, the uncertainty
in the relative electron- and muon-neutrino cross section is substantially less.
Finally a systematic error must be added to account for the uncertainty in the particle identi cation eciency. Fortunately, with detailed systematic checks performed
using cosmic-ray muons and muon-decay electrons, the uncertainty in the eciency
is only about 2%.
Therefore the estimated total systematic uncertainty in the fraction of muon-likeevents is about 5%. However, experimental tests are required to verify these results.

Possible new physics: neutrino oscillations One possible explanation of theapparent dearth of muon-type events is neutrino avor oscillations. Oscillations
between neighboring neutrino families is theoretically preferred. Muon-neutrino totau-neutrino oscillations will most e ectively rid the observed atmospheric neutrino
events of a muon-like component; however, e{ oscillations are also possible.

13
More convincing evidence for neutrino oscillations would be found in either theobserved neutrino energy spectrum (low energy neutrinos oscillate earlier) or in theirzenith angle distribution (downward-going neutrinos may not have had a chance tooscillate due to their short path length). muon-like events depends on either zenith
angle or energy.
Upward-going external muon-neutrino induced events (entering events with vertices
in the rock below) should show evidence for oscillations. Although at higher energies,
these neutrinos have all traveled great distances. Yet, the rate, and zenith-angle
and energy distribution of these events have been reported to be as expected frompredictions,[32,33]. Further research in this area is being carried out.

Possible new physics: proton decay It has been suggested[34] that the at-mospheric neutrino problem is not due to a de cit of muon-like events but to an
excess of low-energy electron-like events from proton decay. The analysis was basedon a selected neutrino ux calculation. Corrections were necessary to compare thiscalculation to the observed Kamiokande data. Although these corrections are notexact, the authors conclude that there are too many low-energy electron-like events(above the expected \background" from their corrected model) and these events arecompatible with p ! e+ with a lifetime of about 41031 years.

The most obvious criticism is that, using any of the more recent neutrino ux
calculations coupled to sophisticated detector simulations, analysis shows no such
low-energy excess. If protons do decay by the mode p ! e+ , several companion
modes (such as n ! e+ e, ) should have similar lifetimes; on the other hand, current
experimental lower limits for the lifetime for the companion modes are much longer
than the lifetime inferred above. Another criticism is that the anomaly seems toextend to too high an energy in Kamioka and IMB.

14

1.2.5 Atmospheric Neutrinos in Super-Kamiokande
Super-Kamiokande is a 50 kton water-Cherenkov detector. The sheer size of SuperKamiokande is very important for re ned measurements of the atmospheric neutrino ux and composition. The IMB detector recorded about 1 contained atmospheric neutrino event per day of operation whereas Super-Kamiokande records
about 7. Systematic uncertainties will eventually dominate the statistical uncertainty in Super-Kamiokande but the improved statistics allow the data to be cut
into di erent classes for systematic studies.
However, it is not only size that separates Super-Kamiokande from the earlier
generation of underground detectors. The pattern recognition method of particle
identi cation previously su ered from modest light collection (about 1 , 5 pe=MeV )and vertex resolution (about 1 m); for example, a mis t event vertex could turn amuon track into an apparent electron track and vice versa. Thus, the eciency
for correct particle identi cation in IMB-3 was slightly better than 90% and in
Kamiokande it is about 98%.

1.2.6 Conclusions
The underground measurements of the atmospheric neutrino spectrum and composition are in good agreement. The disagreement between these measurements andthe theoretical predictions is, however, statistically quite signi cant. The cause of
the disagreement must thus be either an unidenti ed systematic e ect in the ux
calculation, neutrino model, or detector simulation, or some new physics.
Investigation of systematic e ects (the neutrino model or detector simulation) requires controlled experiments. Such experiments include a charged particle beam
test, now concluded, and a future neutrino beam test. Both of these tests employ
a large water-Cherenkov detector at KEK. The beam test (E-261) indicated no
problem with the particle identi cation methods employed in IMB and Kamioka.
[35,36] Isolation of potential systematic problems with the neutrino ux calculations

15
will require, among other things, much more atmospheric neutrino data to search forenergy, zenith angle, or other e ects, that might indicate the nature of the problem.
The unambiguous con rmation that the atmospheric neutrino problem is actually
the result of some exciting new physics will require a vast increase in the size of theneutrino event sample. The most compelling explanation involving new physics isthat neutrino oscillations are causing the  's to disappear before they reach theunderground detectors.
Several complementary approaches are likely to be required to probe this possibility
completely. One approach uses the greater statistics in the neutrino sample, alongwith greatly improved resolutions and particle identi cation eciencies of SuperKamiokande to allow a detailed systematic search for possible energy or path-length
deviations that would indicate neutrino oscillations.
Another approach that will be used to attack this problem are accelerator based
long-baseline neutrino oscillation experiments. Because of the range of neutrino
masses implied by the atmospheric anomaly, such an experiment will require that theneutrino beam energy and path length satisfy EL  100 km=GeV . Such possibilities
have been investigated in proposals at FNAL, BNL and CERN for long-baseline
neutrino experiments. An  1 GeV neutrino beam from KEK (E-362) pointed at
Super-Kamiokande will ful ll this requirement with the added advantage of using
an existing, well understood, very large detector with excellent resolution.
Hints of an atmospheric neutrino problem were rst uncovered in data from the
IMB and Kamiokande detectors. The goal of the rst year of data-taking at SuperKamiokande has been to con rm the results, and acquire better statistics.

Chapter 2
Detector

16

2.1 Super-Kamiokande detector
Super-Kamiokande is a 50 kton water Cherenkov detector located in the Mozumi
mine of the Kamioka Mining Company in Gifu prefecture, Japan. It lies one kilometer below the peak of Mt. Ikeno, and is reached by a two-km long access tunnel. The
mine, a source of zinc, copper and silver ores until 1995, is now inactive and operates
chie y as a research site; in addition to Super-Kamiokande, the mine also houses
the predecessor experiment Kamiokande, the site of which is slated for conversion
to the KAM-LAND long-baseline reactor experiment. The water-equivalent depth
for cosmic rays is 2700 m.
Super-Kamiokande is a ring-imaging water-Cherenkov detector. Charged particles
moving through the water at relativistic speeds ( (= v=c) > c=n) emit a forward
cone of light with half angle given by:cos() = n1 ,which for water, with index of refraction n = 1:33, gives a Cherenkov angle of about
42 deg for  c. The light is emitted in a spectrum which, when folded throughthe transmission of water, ranges from 300 to 600 nm, and peaks at around 360 nm.
This light is detected by photomultiplier tubes, where the measured timing andintensity of the light at each tube is used to reconstruct the particle track. Figure
2.1 shows the geometry of the light relative to the charged particle track and thephotomultiplier tubes in the detector.
The detector comprises 11146 Hamamatsu R3600 50-cm diameter photomultipliertubes (PMTs), lining and viewing a cylindrical volume of ultra-pure water 16.9 m

17Vertex

Theta
Particle
Track

Figure 2.1: Geometry of Cherenkov light from passage of relativistic charged particle
through the detector medium (water).
in radius and 36.2 m high. An outer detector and shield of 2.5 m thickness of watercompletely surrounds the inner detector. The outer detector is instrumented by1885 Hamamatsu R1408 20-cm PMTs, and is used to reject incoming tracks fromcosmic rays and passively shield against radioactivity from the surrounding rock.
Figure 2.2 shows the relationship between the two main detector volumes.
The inner detector tubes are similar to those used in Kamiokande, redesigned for an
improved timing resolution of 2.5 ns at the 1 p.e. level. [37] The outer detector tubes
are the same tubes that were used in IMB, recycled. Attached to the equator ofeach outer-detector tube face is a \wave-shifter plate" which increases the collectioneciency by 60% over that of a bare tube. Figure 2.3 shows the tube mounting in
the detector in vertical cross-section.
The tubes are mounted in units of \super-modules," consisting of 12 inner-detector
tubes on the front side and 2 outer-detector tube/wave-shifter pairs on the back side.

18

Inner Detector

Outer Detector
Figure 2.2: Structure of detector, showing inner-detector cylinder surrounded byouter-detector shell.
The inner and outer tubes face away from each other to view their respective detector
volumes. The two detector regions are optically separated by a pair of opaque sheets
which enclose a dead region 55 cm in thickness. On the inner-detector side a black
plastic sheet is used to minimize re ections from an event back into the detector.
On the outer-detector side of the super-module, and lining the outer walls of thetank, is white re ective Tyvek sheeting in order to maximize the light-collectioneciency of the outer detector. The Tyvek which is mounted on the frame has a
black non-re ective backing, to absorb any light which makes its way into the dead

19

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Figure 2.3: Super-Kamiokande tank in vertical section, showing the PMTs of theinner and outer detectors separated by a 55-cm \dead space." (Figure not to scale.)space inside the super-module or is generated there by events passing through ororiginating in the dead space. Figure 2.4 shows the relative positions of the tubes ina supermodule. The wall of the detector is composed of towers of supermodules, 17high. There are 37.5 towers, Tower 28 being a half-width tower. The super-modules
on the top and bottom of the detector have a di erent framework, but the relative
tube positions are much the same.
The inner PMTs are read out with custom Analog Timing Modules (ATMs [38]),
which provide 1024 ns range at 0:25 ns resolution in time and 409:5 pC range at 0:1
pC ( 0:2 photoelectron) resolution in charge for each PMT. The outer PMTs are
instrumented with custom charge-to-time conversion modules, QTCs (built at BU),
which output timing pulses at a xed delay from the rising edge of the incoming
PMT pulse with a time-width proportional to the integrated charge of the PMT
pulse. These signals are then digitized with LeCroy 1877 TDCs with 16 s fullranges. The resulting resolutions are 0:5 ns in timing and 0:1 p.e. in charge. The

20

Side Super-Module

Front View

Back View

Figure 2.4: Front (inner-detector) and Back (outer-detector) views of a typical wall
supermodule.
time and charge calibration of the raw data for both inner and outer detectors isdone immediately oine and both analyses start with the same calibrated data.
The trigger is formed by the coincidence of PMT hits, at a threshold of 0:2 p.e.
in a coincidence window 200 ns wide. The trigger threshold is set at 5:5 MeV ofvisible energy, de ned as the energy of an electron which would produce the same
number of Cherenkov photons as the given event. (Note: after the rst year of datataking, a new \super-low trigger" was installed which permits data-taking down toa threshold of 4.5 MeV, though with lower eciency than that above 5.5 MeV.) The
noise rate in each tube is 3:6 kHz. The average attenuation length for Cerenkov
light is 68 m, varying 5% over the course of data-taking. The raw data are saved
at a total rate of 20 GB (one DLT tape) per day.

21

2.2 Data Flow
Data from the detector is read out via 10 \online slave" computers: 8 (named sukon1- sukon8) to read out the inner detector tubes, 1 (sukant) to read out the outerdetector tubes, and 1 (sukon9) to handle the trigger electronics. Data from the online
slaves is passed to the \online host" computer (sukonh), which assembles the data
into events and passes the events (in \online format") to a reformatting computer(sukrfm). This machine converts each event to oine format, and then transmits
it via ber optic link to the computer center outside the mine in the nearby townof Mozumi. There the data are further converted from raw hit counts to calibrated
T (ns) and Q (p.e.). The raw data are also archived to tape in Mozumi. Figure
2.5 shows the data- ow on the top of the tank; the online-host and reformatting
computers are located in the control room, in a tunnel o the top of the gure.
Control RoomHITSUM

Hut 1

ATMs (20)

GONG

Hut 4

Central
Hut
Hut 2

Hut 3

Tank-top data flow

TKO Crate (12 each Huts 1-4)

Figure 2.5: Left: Data path between huts on tank top. Right: DAQ cards in TKO
crate.
The calibrated data are distributed down two paths: one is a reduction chain operated by the onsite groups (consisting largely of members of Japanese institutions,22
but including participation from the University of Washington and SUNY Stony
Brook); the other is a tape archiving process operated by the US institutions forshipment back to SUNY Stony Brook in the US, where it undergoes a separate,
independent reduction from the onsite one for distribution to other institutions in
the US. The o site copy of the data also forms a backup for the onsite tape archive.

2.3 Detector Electronics
The inner and outer detectors, besides using di erent PMTs, also have di erent
read-out electronics. The hit information is merged inside the mine before beingtransmitted to the computer center in Mozumi.

2.3.1 Inner Detector
Figure 2.6 shows the data path for the inner detector. The speci c modules are
discussed below.
.................
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PMT
12

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ATM
Module.......
.......

SMP.......
........

.......
.......

20.......
.......
.......
.......

6

OnlineSlave

Online host.......
.......
........
.......

Figure 2.6: Inner Detector data acquisition hardware block diagram. Shown is thedata path within each of the 4 outer huts. Each online slave computer (two perouter hut) reads out the hit information for one eighth of the detector, passing thehit information to the event-builder softtware in the central online host computer.
This section presents a summary of the speci cations for the Super-Kamiokande
front-end electronics modules (ATM, GONG, TRG, LIME).

23

2.4 Speci cations and Principles of Operations
2.4.1 ATM
The ATM (Analog Timing Module) digitizes the charge and time information for
12 PMTs.[38] Each tube channel (0-11) is divided into two subchannels (A and B),
which alternate digitizing hit information from the PMT. There are 20 ATMs per
TKO crate in the Super-Kamiokande inner-detector DAQ.[39]ATM speci cations [38]: FIFO capacity: 1024 16-bit words.
 FIFO read-out format:
Word 0: [00][8-bit event #][0/1 (A/B)][0][4-bit chan #]Word 1: [01][00][12-bit TDC data (0-1023 ns, 0.25 ns/count)]
Word 2: [10][00][12-bit QDC data (0-409.5 pC, 0.1 pC/count)]
Word ..: Repeat for each hit received.
 Programmable modes:
OPERATE: Normal operation mode.
PEDESTAL: Used for TDC calibration. TDC gate width controlled by
GONG, instead of self-gating on a tube hit.
CAL: Used for QDC calibration. Takes input from CAL connector on frontpanel, instead of from tubes.
MEMTEST: Used to test FIFO memory.
 Other programmable options:{ Threshold (for all channels) programmable from 0 to -1.25V, in steps of
0.61 mV. (Threshold is applied after ampli cation; 0.1 p.e. corresponds
to minus 50-60 mV.)
{ Programmable 8-bit module ID.

24

ATM channel hit sequence
When a hit comes in from a PMT, the HIT one-shot (see Ref. [39], Figure 3-7) issues
a 900 ns gate. This goes into the \self-gate" logic, which starts the TAC charging
and opens a 400 ns acceptance gate on the QAC for whichever sub-channel (e.g.
A) is available on that tube channel. When the trigger signal reaches the ATM,the TAC stops charging, and analog-to-digital conversion for that sub-channel canbegin (but see below). However, no matter when the trigger comes in, the self-gatepart is dead for 900 ns from the start of the HIT signal from the one-shot. Once
that 900 ns is ended, the self-gate logic is ready to direct the next hit to the otherchannel (e.g. B). If a trigger does not come in within 1.1 s of the hit, the channel
initiates an auto-clear operation. 200 ns later, the sub-channel (A or B) can takeanother hit.
If both sub-channels A and B are occupied when a hit comes in, the hit cannot beprocessed and is lost.
The HIT signal for a tube channel always causes the channel to toggle between
taking data on sub-channel A or sub-channel B. (The sub-channel selection logic issimply a ip- op with its input connected to its output through an inverter, clocked
by the rising edge of the HIT signal. See Ref. [38]) Hence, if the selected subchannel for that particular hit is busy, the hit is lost, even if the other sub-channel
might be available to take the hit. However, this is a very rare occurrence, and thee ect on data-taking is negligible.

ATM hit conversion sequence
When a trigger comes in, all channels which had hits within 1.1 s before the trigger
get registered in the HITAD register. If the HITAD register is non-empty, conversionof all hit channels begins in the order of channel priority. (The channels, in orderof decreasing priority, are: 0A, 1A, ..., 11A, 0B, 1B, ..., 11B.) Conversion begins at
the rst hit channel in the priority list, and for each channel it consists of:

25
1. Writing the channel and event number to the FIFO.
2. Converting the TAC value, and writing it to the FIFO.
3. Converting the Q value, and writing it to the FIFO.
4. Resetting the channel, and clearing it from the HITAD register.
Conversion and writing to FIFO take 6 s per channel.
NOTE: Each trigger can lead to new hit channels being marked in the HITAD
register. The highest priority channel in the HITAD register always gets converted
next, so channels do not necessarily get converted on an event-by-event basis. For
example, if channel 4B is being converted for a particular event, and a new trigger
comes in with channel 0A being marked hit, then channel 0A will be be the next
channel to be converted after channel 4B, regardless of what other channels were hit
in the previous trigger. This means that hits from a single event will not necessarily
be contiguous in the ATM's FIFO.

Dead time
What is the dead-time for an individual tube? A hit for a particular tube is lost if:
 it comes within 900 ns of the previous hit from that tube (this is intentional,
to handle re ections); or the previous two hits had associated triggers, and neither channel A nor channel B for that tube has nished converting; or the previous hit had no associated trigger, but the hit before that did have a
trigger and has not yet nished converting (due to the sub-channel selection
mechanism described above); or it had no associated trigger (of course).

2.4.2 GONG
The GONG (GO/No Go) module is a TKO [40] module which handles triggeringand gate operation for all DAQ modules (ATMs) in the crate. There is one per

26
TKO crate. A summary of the features of the GONG module[41] designed forSuper-Kamiokande: Latches 16-bit event number from the TRG module (as di erential ECL via

ribbon cable).
{ Distributes lower 8 bits to ATMs (as TTL via ribbon cable).
{ Stores 16-bit event number internally, which gets read out when theATMs are read out.
{ Only retains the last event number { each new trigger overwrites theprevious event number.
 Distributes trigger signal from the front panel (either NIM via lemo, or differential ECL over the event- number ribbon cable { selectable by jumper
switch), to the ATMs over the TKO backplane.
 Can generate programmable delay (0-1500 ns, plus 50+ ns o set) for use incalibrating ATM TDCs.

2.4.3 TRG
The TRG (TRiGger) module generates event numbers, and distributes trigger signals to the GONGs. It has 8 inputs, each one of which can generate a trigger.
The TRG stores information about which of the input triggers (e.g., inner-detector
trigger(s), outer-detector trigger(s), calibration triggers) contributed to each event.
For each trigger input, a bit gets set in the Trigger ID byte. This Trigger ID byte
gets read out and stored with the event information by the DAQ software.
General behavior: Trigger res (sends TRIGGER OUT) about 30 ns after rst trigger input.
 Trigger ID is latched on second rising edge of 25 MHz clock after Trigger res.
( 50 ns after rst trigger input).

27

 Further trigger inputs between rst one and ID latch get lumped under rst

event number. Trigger inputs after that, and until Trigger CLEAR completes,
are lost.
{ There is about 120 ns minimum time between successive triggers (event
numbers).
{ This does not lead to dead-time, just merging of di erent events under
the same event number.
{ Trigger event number is incremented at the end of cycle, to be ready for
next time.
Two of the trigger inputs are reserved for dead-time monitoring. When the TRG isin dead-time monitoring mode, fake events are generated at the beginning and endof TRG dead-time (due to VETO assertion, e.g.) with one of the ID bits used tomark the beginning of dead-time, and the other to mark the end of dead-time.

2.4.4 LIMEThe LIME (LIMitEr) module monitors the event count, and regulates the readoutof the TKO crates by the SMP. Its primary function is to ensure that the ATMs areread out frequently enough that the ATM 8-bit event numbers can be reconstructed
properly into their corresponding 16-bit event numbers.
Every NAccept events ( settable via DIP switch ), an ACCEPT signal is sent to the
SMP. This initiates a read-out of the TKO crates. However: After every ACCEPT signal, there is a 120 s inhibitory period before thenext one can be sent. This ensures that, for normal data taking, the hits fora single event in one ATM are not spread over more than two data scans.
 No ACCEPT signal is sent while BUSY is asserted by the SMP.
While BUSY is asserted, the TRG is still permitted to continue ring, up until thenext modulo-NV eto event count. (NV eto , like NAccept, is settable via DIP switch.
NV eto must be larger than NAccept.) At the NV etoth event, VETO is sent from the
LIME to the TRG to halt data-taking.

28
The LIME maintains its own internal event counter, and does not see the eventnumber generated by TRG. This event counter is incremented every time the TRG
res. So the LIME's modulo-N event counter may not wrap around at the same
boundaries as real event numbers. However, the LIME has a \Clear" input forresetting the internal counters, which could be used to synchronize with the TRG
event counter, if needed.
For high-occupancy events, such as laser calibration events at high light levels, theATM FIFOs can over ow if NAccept is set higher than 28. (Each ATM FIFO has acapacity of 1024 words, or 341 hits, so it can hold 28 12-tube events.) To handle
such high-occupancy events, the LIME has a \Special Trigger" input which forcesan ACCEPT to be generated regardless of the state of the internal counters.

29

2.5 Hitsum
The ATM hitsum signal can best be represented by a trapezoidal pulse, with a risetime, de ned by 10% to 90% of the rising edge, measured to be 9.41.1 ns. The
pulse height was measured to be 14.41.3 ns, with a at-top duration of 151 ns. The
full width of the pulse at the base (measured from 10% o baseline at the leadingedge to 10% o baseline at the falling edge) is 200 ns.[42]2.5.1 Outer Detector
The outer detector forms a cylindrical shell around the inner detector. Separated
from the inner detector by an optically isolated dead zone 55 cm thick. It is
2.5 meters in thickness, passively shielding the inner detector from neutrons andgamma rays from the surronding rock. In addition, it is instrumented by 1885 20cm Hamamatsu R-1408 PMTs, which provide active detection of incoming cosmic
rays. The PMTs themselves, in fact, are recyled from the old IMB detector.
Figure 2.7 shows the data acquisition path from the OD PMTs to the central hut.
Each PMT is connected to a custom \paddle card," built at LSU, from which is
distributed high voltage and to which the analog signal from the PMT is passed.
This signal is then passed to a discriminator and charge-to-time converter (QTC)
module, built at BU. Each QTC channel self-triggers at a threshold set at 25 mV(about one-half p.e.), and integrates the charge of the PMT signal to produce adi erential-ECL pulse, the width of which is proportional to the integrated chargeof the PMT pulse. The leading edge of this pulse gives the time of the leading edgeof the PMT pulse (plus an o set).
A QTC channel also provide a HITSUM signal, 200 ns wide and 20 mV high per
hit. The individual hitsums from each channel in the outer detctor are summed ineach of the four outer huts, and then globally summed in the central hut and fed
as an input to the TRG module. If the OD trigger goes over triggering threshold(about 19 hits), it is held for 100 ns to see if the inner detector also generates a

30
trigger, because it is preferable for event reconstruction to have the event trigger
based on the inner-detector timing when there is inner-detector activity. Only if
no inner detector trigger is generated within the hold window is the outer detector
trigger released to generate an OD-only trigger. Otherwise, the two triggers are fed
together into the TRG, at the time of the inner-detector trigger, to provide tags
that both sections of the detector red.
The ECL pulse from each QTC is fed into an input of a LeCroy 1877 time-todigital converter (TDC). Five TDCs, with 96 input channels each, are located ineach Fastbus crate, one per outer hut. The TDCs record the rising and falling edgesof the QTC signals, and are read out by a Fastbus Smart Crate Controller, which
communicates with the OD DAQ online slave in (SUKANT) via VME-mounteddual-port memory modules in the central hut.
The TDCs are capable of storing up to 8 hits (16 edges) for each event, over a windowof up to 32 microseconds, providing a record covering a range both before and after
an inner-detector event of what was happening in the outer detector. The primary
aim of this expanded recording window is to catch \stealth muons," cosmic muons
which stop in the outer detector and then decay in the inner detector, generating a
Michelle electron which might otherwise be mistaken for a neutrino interaction in
the inner detector. The window for outer-detector data-taking was initially set at 16
microseconds before and 16 microseconds after the trigger time of an inner-detector
event. In September 1996 (starting with run 2800) this window was shortened to
10 microseconds before and 6 microseconds after the main event; in the event of ahigh-intensity hit on a tube, re ections on the PMT cable can lead to additional
hits being recorded in the TDC, which can over ow the 8-hit bu er in the TDC andlead to loss of the primary hit. While this does not a ect the ability to determinethat a cosmic muon has entered the detector (it is very clear that one entered fromthe number of hits in such a case!), the loss of in-time hits complicates the ability
to locate the entry cluster in the outer detector.
After the end of the outer-detector recording window, the outer detector becomesbusy for 2-5 microseconds (depending on the size of outer-detector data) digitizing

31
the hit information, and is unable to generate new OD triggers. During this digitization period, an \OD busy" bit is placed in the data stream so that the dead time
can be determined.
PMT....................
....
....
...
...
..
..
.
..
..
..
..
..
...
.....
....
....................

12.......
........
..
..........
.....
..........
........
......
..........
...
.........
..
...........
........
.
..........
..
..........
......
..........
....

PaddleCard.......
.....

4.......
.....
.......
.....
.......
....

QTC......
.......

2......
.......

TDC.....
......

5.....
......
.....
......
.....
......
.....
......

FSCC
DPM inCentralHut.....
......

Figure 2.7: Outer Detector data acquisition hardware block diagram. Shown is thedata path within each of the 4 outer huts. The dual-port memories (DMPs) areread out in the Central Hut by the SUKANT online slave computer.

Chapter 3
Calibration

32

The calibrations for the data fall into two classes:
1. Hardware calibration: converting raw digitized PMT counts to T (ns) and Q(p.e.).
2. Detector calibration: measuring the response of the detector in terms of number of measured p.e. per MeV deposited from each type of event.
The rst set of calibrations are carried out at intervals by members of the calibrationgroup, which supplies the same set of calibration constants to the data used by all
members of the collaboration. The second set of calibrations are carried out bymembers of the di erent analysis groups, with customized response functions developed for their particular needs, though with cross-checks against di erent energy
regimes as necessary.
This chapter describes the hardware calibration. Detector calibration is covered
under Chapter 4.

3.1 PMT Calibration
3.2 Time Calibration
The time slopes of the PMT readout electronics (ATMs and TDCs) are measured
independently of the PMTs. To measure the relative timing between each tube andthe trigger a nitrogen dye laser system is used (described in the next section). Light
from the laser is distributed to known points in the detector, from which the travel

33
time is calculated to generate a list of timing o sets based on each tube's response
to calibration pulses. In addition, each tube has a separate slewing correction thatmust be made for a given pulse-height; in general, the larger a pulse from a given
PMT is, the earlier it will go over the triggering threshold in the readout electronics.
This e ect is measured by varying the intensity of the laser pulse, which allows one
to make a \T-Q map" that describes the time o set correction one has to apply to agiven tube for a given measured charge from it. T-Q map runs are taken every few
months to provide updated slewing corrections for the inner detector. For the outerdetector, where precise tube-to-tube slewing corrections are not needed, an averageslewing correction that was measured soon after detector turn-on is used.

3.3 Charge Calibration
To calibrate raw charge (Q) readings into photoelectrons (p.e.) for each tube in the
inner detector, a xenon ash lamp is used as the light source. This source has much
pulse stability than the laser, which varies 10 , 20% from pulse to pulse and theintensity of which decreases over the long term as the ash cartridge wears out andthe dye bleaches.
The laser is used for Q calibration of the outer detector tubes. The method is thesame as that used in IMB[43]. Light pulses of varying intensity are used; at thelowest intensities, a tube will only detect less than one photon on average. The
occupancy (number of times a tube res per hundred laser pulses) of a tube at sucha low light level is used to calculate the average number of p.e. it receives using
Poisson statistics. This allows the single-p.e. response of the tube to be measured,from which the gain at higher light levels (100% occupancy) can be extrapolated.
At high enough light levels, typically around 50 p.e. for the outer detector tubes,
a tube begins to saturate. The gain for an outer detector tube is composed of alinear component, used for signals up to a measured saturation point, followed by aquadratic t beyond that point.

34
The pedestals, or zero-o sets, of the tubes is also measured. The inner detector
electronics have automatic pedestal measurements made every 30 minutes, which
are read out as special pedestal events in the data stream. Only one-eighth of theinner detector is put into pedestal mode at a time, in order maximize detector uptime for supernova detection. Pedestal mode events are not used as part of normal
data analysis. Outer detector pedestal measurements are made only occasionally,usually when there has been some change in the hardware.

3.4 Laser Calibration Hardware
3.4.1 Laser and Optics
An overview of the laser and optics section is shown in Figure 3.2. The basic scheme
is similar to that used in Kamiokande and IMB[43], with the addition of multiple
ber outputs to reach di erent parts of the detector.
The laser is a Laser Sciences, Inc. LSI V337-ND-S, which has an average pulse
energy of 300 J, and pulse width of 3-4 ns. It is a closed system nitrogen laser,
red by a TTL trigger. It provides a synch output from a photo-detector on theback of the ash tube which indicates the time of laser re to within about 1 ns, but
for greater precision we mounted a ber optic pickup to the back of the ashtube,
which goes to a fast (300 ps rise-time) PMT. This PMT, called \T.Mon." is used
to generate the detector trigger for timing calibrations.
The output of the nitrogen laser, with a wavelength of 337 nm, pumps a tunable dyelaser (0.3 nm bandwidth), which generates 384 nm output using Exalite 384 dye.
A logarithmically graded lter wheel is connected by ber to the output of the dye
module. and its output is fed into a two-way splitter.
The lter wheel for setting the light level is controlled by a stepper-motor controller
in a CAMAC crate. The slope of the lter wheel was measured with a PMT attached35
to the output of the wheel, and read out with a Caen C205 dual range chargeintegrating ADC (.25 pC on low range, 30 pC on high range). The slope is  270
steps per decade, with about a 1500-step range beginning at step 300 (the brightest
setting).
The ber from the lter wheel is fed into a 1:2 splitter and then to two opticalswitches. One switch is a 1:9 splitter, the other a 1:50. By convention, the channel
used for inner detector calibration is switch 1 channel 9. All 50 switches of the second
switch, and 2 of the channels on the rst switch, are connected to a set of opticalbers which are permanently mounted in the outer detector. This con guration
permits simultaneously ring two bers at once, which saves time and detector
down-time during outer-detector calibration runs. The switches are manufactured
by Dicon, and are normally operated via a CAMAC-mounted GPIB controller. They
can also be operated manually if desired, and have a separate \channel 0" (no bers
selected) position. The bers inside the switches contain a germanium dopant,which was found to uoresce in 337 nm light from the bare nitrogen laser without
dye module. (This is due to an absorption line at 330 nm.) This does not cause aproblem for ordinary calibrations at 384 nm, but in the event that it is desired tooperate the laser at 337 nm, the switches must be disconnected from the system.
The DAQ, shown in Figure 3.1, is CAMAC-based. The stepper-motor controller
and interface to the optical switches are not shown. The laser trigger, delayed by a
xed amount, is fed into the calibration input of the TRG module, generating events
which are tagged by the corresponding bit in the TRG-ID byte. Since laser triggers
can (very occasionally) be lost if they are preceeded within about 100 nanoseconds
by other triggers { and hence, the TRG-ID bit for the laser calibration might belost { other triggers are ordinarily disabled. It is possible to run without disabling
the other triggers; this triggering scheme permits the detector to continue operating
during calibration, though the non-calibration events during a calibration run has tobe set aside from normal analysis, to be used only if something interesting happens(e.g. a supernova) during the run.

36

3.4.2 Optical Fibers
Connected to the outputs of the switches are 53 optical bers of UV/Vis grade
fused silica with a 200 m diameter core. There is a 10 m fused silica cladding
and another 10 m protective layer. The bers are strenghtened with kevlar bers
running longitudinally, and encased in waterproof Hytrel tubing made by DuPont.
The bers for the bottom of the outer detector are 110 m long. All the rest (innerdetector, side outer detector, and top outer detector) are 72 m long.
The bers in the outer detector are tipped in a mixture of optical cement andtitanium dioxide, which helps di use the light. The bers in the inner detector also
have such a di using tip, but are additionally encased in UV plexiglas cylinders
which are lled with Ludox, a DuPont product which consists of 20 nm diametersilica spheres held in suspension, which provides very e ective di usion at UV
wavelengths. The same basic design was used in the IMB experiment. After themain detector construction was nished, but before tank- lling began, several \dry"runs were taken with a di erent di user ball design, which used re ecting mirrors
from an IMB design to bounce the light back and forth in the Ludox. A new laserball has been designed by Mark Rosen at UH, with improved isotropy over previous
models. The di erent designs are shown in Figure ??.
The top of the detector has several penetration holes built in. Twelve holes aroundthe circumference of the top of the tank and one hole near the middle of the top areused to feed the bers into the outer detector. These feedthroughs are gas-sealed
and semi-permanently mounted.

3.4.3 Inner Detector Fibers
The inner detector ber is stored on the tank top during normal data-taking, and is
fed through the central calibration hole only for laser calibration runs. The di user
at the end of the ber is clipped to the end of a steel wire when being lowered into
the tank to a measured depth.

37

3.4.4 Outer Detector Fibers
The bers for the top of the outer detector are fanned out from the single penetration
hole. The bers run along the top of the detector and are suspended by steel cables.
The side outer detector di users lie at two depths: one-quarter of the way down
the wall, and three-quarters of the way down the wall. There is a ring of 12 ber
mounts at each level going around the tank. This ensures that most tubes sees atleast two bers { this redundancy was necessary because it is very dicult to replace
the bers. Such an operation must wait until detector maintenance downtime. The
bottom outer detector bers run down the side of the detector in the veto region,
and are then distributed in the bottom OD to provide overlapping coverage for eachtube. They are mounted pointing upwards from a cable guide struts. The OD ber
mountings are shown in Figure 3.4.
14 bers are mounted in the bottom outer detector, 14 in the top, and 24 on theside walls for a total of 52 bers. The general layout is represented in Figure 3.3.

Laser Calibration DAQ
Programmable
Pulse generator

GPIB
Controller

StepperMotor
Controller

Readout

Out

ECL-NIM converter

TRG

EnableIn

Figure 3.1: Laser Calibration DAQ

Opticalswitches(2)

Filterwheel
steppermotor

Event-number bus(16 bit)Calibration
Trigger-enable
logic

Trigger
Laser
Fiber to back of laser flash tube

SignalTrigger monitor PMT

Discriminator

Gate

Delay

Generator

38

Laser and Optics
Inner
DetectorFiber
1:9 switch

SparesFigure 3.2: Laser Calibration Optics

Outer
Detector
Fibers (2)

Laser

Fast

Dye
mod.

Collimator

Variable

Fiber Attenuator

1:2 Splitter

1:50 switch

Outer
Detector
Fibers (50)

Monitor PMT

39

40

FIBERSINNER DETECTOR

OUTER DETECTOR
Figure 3.3: Laser Fiber Runs

41
Outer Detector Laser-ball Mounting
Top Outer Detector

Bottom Outer Detector
Fiber

4 cm

Stainless steel cables
Plexiglas sheet

Lucite block

Clamping bolts

Cable ties

Cable-tray post L-bracket

50 cm

Fiber
Side Outer Detector
Wall tyvek curtain
Fiber

Tank Wall
Tank structural bolt
Hose clamp(Stainless-steel)Back-board(Tyvek-wrapped
for reflectivity)
15 cm

Figure 3.4: Laser Calibration OD Fiber Mounts

42
Outer Detector

Inner Detector (Dry runs)
Fiber

Fiber

Glass (smooth surface)
TiO 2 / epoxy
diffuser
3mm
Mirrors

Ludox

Fiber
15 cm

Fiber

Glass (rough surface)
UV plexiglas
TiO 2 / epoxy
diffuserTiO 2 / epoxy
diffuser
Ludox

10 cm
Inner Detector (1996-1997)

Ludox

10 cm
Inner Detector (1997 - )Figure 3.5: Laser ber di users in use

43

3.4.5 Laser Calibration Operation
The lter wheel, optical switches and laser triggering are all controlled by a program
called \lasercal," which can be run in manual mode or accept a calibration schedulele. The 16-bit event number from the TRG is latched and read out from the
CAMAC crate in order to be able to assign the lter wheel and optical switch
settings to the corresponding event numbers. The output of the ltercal program is
a listing, for each laser event, of the latched event number and the lter and switch
settings.
The calibration events are retrieved oine and matched to the corresponding entries
in the ltercal log le for the determination of outer detector calibration constants.
The calibration constants are then used in the as part of the generation of thecollaboration-wide common data set. This provides a uniform set of calibration
constants for the various analysis groups in the collaboration. The calibration
constants are stored in les on the calibration reformatting computer, and they
are tagged with version numbers. These version numbers are used to associate thecorrect set of calibration constants with the data from di erent time periods. The
version numbers for both inner and outer detector constants get written into theevent header for later reference.
A series of outer detector gain measurements were made in the month after detector
turn-on. These measurements are extremely time-consuming { one hour per ber{ so the bers were in tandem, one ber on each side of the detector ring at thesame time.
Relative timing calibrations go much more quickly, since only one data set at one
light level is needed for each ber. Using a ltercal schedule to switch between bers,
a timing calibration completes in a little over an hour. Several timing calibrations
were taken in the rst few months of turn-on, as trigger hardware changes required.

Chapter 4
Analysis

44

For the rst year of data-taking, two separate sets of analysis groups formed toanalyze the high energy data from Super-Kamiokande, in order to detect possible
mistakes and provide a comparison of reduction and reconstruction techniques. One
group was the \onsite" group (led by ICRR), and the other group was the \o site"group, consisting of several institutions including BU, SUNY Stony Brook, UCI,
University of Warsaw, Los Alamos National Laboratory, and UH. The codes forboth data and Monte Carlo were completely independent, as was the determinationof the energy scale and systematic uncertainties. The common starting point foreach analysis was the raw data with electronics calibrations (ns and p.e.) applied.
In addition to the parallel onsite and o site high energy groups, there have also beenparallel low-energy groups, which study solar neutrinos and monitor for possiblesupernovae, and upward-going muon groups, which study muons that have been
generated in the rock below the detector by the interactions of atmospheric neutrinos
which have travelled through the earth from the other side. The high energy groups
engage in the study of tracks that originate within the detector from the interactionsof atmospheric neutrinos. They also search for signs of nucleon decay.
The collaboration decided that the the onsite and o site groups would graduallymerge after the rst year of data-taking. The high energy group has ocially alreadydone so, and so the \o site" reduction and analysis discussed below should beunderstood to be those of the \old-o site" group, as it is now called.

45

4.1 Reduction
Super-Kamiokande receives about 1 million event triggers per day. The greatest
number of triggers comes from very low-energy background sources such as radon,
gamma-rays from the surrounding rock and the glass of the PMTs, electronic noise,and solar neutrinos (about 30 per day). At the other end of the energy spectrum,
the events which take up the largest amount of space on tape are incoming cosmicray muons (about 3 per second), which have long track lengths and light up a large
number of tubes. Another source of high-energy noise events is \ ashers," tubes
which have begun to break down and occasionally emit light. Flashers can generate
light patterns which look like contained tracks; as soon as they are discovered they
are turned o , and several methods are employed to identify asher events in the
reduction.
The purpose of the of the o site high-energy data reduction code is to quickly lter
these events out to get a manageable subset of contained and partially-contained(exiting) event candidates. The philosophy of the early stages of reduction is to only
reject background candidates which are understood well enough that they can safely
be rejected, with the goal of saving every event of possible interest to the study of
atmospheric neutrinos, and also for the search for proton decay.
In the rst stage of the o site data reduction (\HIGHE1"), events are rst lteredfor obvious problems such as having no inner-detector or outer-detector data. The
majority of entering cosmic ray muons are removed by requiring that there be fewer
than 10 hits in the outer detector in a 200 ns window around the trigger time. A
rst pass at ltering out ashers is made by requiring that the the tube with themost charge must have less than 0:4 the total charge of the event. Events withfewer than 15 tubes in a 12 ns time-of- ight residuals window from anywhere in
the detector are rejected as noise, as are events with fewer than 100 p.e. in 20 ns
time-of- ight residuals window around a point- t vertex. Events falling within 100
microseconds of a previous event excluded from consideration as contained events,
but are kept and tagged as -decay electron candidates.

46
The output of HIGHE1 is about 80,000 events per day. This large number is mainly
due to the saving of one in every thousand events to form a minimum-bias sample.
The minimum-bias events are removed in the next stage of ltering, HIGHC2, which
is designed to restrict the data set to those events which are fully-contained.
In HIGHC2, a vertex point t is done based on timing residuals. A minimum of
150 photo-electrons must be collected in the inner detector within a 20 ns timingresiduals window from this vertex. A muon track t is applied, and events passing
the t with more than 2 outer-detector hits in a 50 ns window within 20 m of the
projected entry point are rejected as entering events. Events which have been foundfrom a separate analysis to have the repetitive patterns of speci c asher events areculled. The output of HIGHC2 is about 20 events per day.
In HIGHC3 a precise single-track event tter, \yastef" (originally developed for
IMB[44]) based on timing residuals and event geometry, is applied to the remaining
events. The vertex resolution of this tter is about 70 cm; Figure 4.1 shows vertex terrors, parallel t errors (along the track) and angular t errors for simulated muonand electron tracks of energy around 1 GeV. As can be seen, the error is primarily
parallel to the track, and depends on the event type; muon ts tend to get pulledforward along the track, and electron events tend to get pulled backward.
Tables 4.1 and 4.2 show angular resolutions (de ned as the point where 68% of theevents have a smaller angular deviation) and vertex deviation parallel to the track
for muons and electrons in ranges of visible energy from 50 to 5000 GeV. (Thevisible energy of an event is de ned as the energy of an electron which produces theequivalent amount of light in the detector.)
At the end of HIGHC3, events with yastef vertices less than 50 cm from the innerdetector PMT wall are removed. This leaves about 10 events per day.
In HIGHC4, a nal track tter is applied to events with greater than 15000 p.e., totest whether they might be entering muons. If the vertex of this t is within 1 mof the wall, the event is rejected. Otherwise, the results of the yastef t are used
to determine the position of the event. Events with a yastef vertex within 50 cm

47

400

Entries
Mean
RMS

300

1825
56.82
41.28

300

200

200

100

100

0

0

200

400

Entries
Mean
RMS

300

0

600

1825
51.47
44.62

200

100

100
0

80

200

60

1825
2.371
1.891

0

400

600

1876
-59.65
42.81

200

400

Entries
Mean
RMS

80

1876
2.160
1.730

60

40

40

20

20

0

200

1876
68.13
31.15

Entries
Mean
RMS

0
-200

400

Entries
Mean
RMS

0

300

200

0
-200

Entries
Mean
RMS

0

5

10

15

20

0

0

5

10

15

20

Figure 4.1: Yastef vertex and direction errors on  1 GeV MC muons and electrons.
Table 4.1: Fitter errors on MC muons.
Evis (MeV) Ang. Res. (deg.) Vertex creep (cm) RMS (cm)50-1003.6
14686
100-300
2.9
57
40
300-500
2.8
35
30
500-1000
2.6
4236
1000-1500
2.9
73
54
1500-3000
3.5
125
97
3000-5000
4.6
218
141

48
Table 4.2: Fitter errors on MC electrons.
Evis (MeV) Ang. Res. (deg.) Vertex creep (cm) RMS (cm)50-1007.1-82
55
100-300
5.5-82
47
300-500
3.7-68
45
500-1000
2.7-60
45
1000-1500
2.0
-55
39
1500-3000
1.7
-51
40
3000-5000
1.7
-32
46
of the wall are rejected. A nal asher test is also performed, to nd events withcharacteristically broad timing residuals distributions.
The nal sample is restricted to events 2 m from the PMT wall, corresponding to a
22.5 kton ducial mass. This results in 2707 fully contained events, including thoseoriginating from atmospheric neutrino interactions. Several visual event-scanningsessions were held thoughout the year to verify and tune the performance of the
reduction system. However, by the end of the data-taking period under discussion,
the percentage of background events found by scanning had been reduced to 0.2%.
The reduction is now fully automatic, a departure from previous experiments. The
remaining contamination is treated as a systematic error, and not removed.
Figure 4.2 shows the distribution of fully-contained events within the ducial volume,
2 meters from the inner optical barrier. The vertical scale is the Z-coordinate of theevent vertex, and the horizontal scale is the square of the horizontal distance of theevent vertex from the centerline of the detector; such a scale maps the cylindricalinterior of the detector into equal-volume bins. The distribution is smooth over thecylindrical volume.
The integrated livetime for this sample is calculated to be 301.4 days, or 18.5 ktonyrs. For comparison, Kamiokande and IMB each accumulated a little under halfthat amount over their entire lifetimes.

49

1500

1000

500

0

-500

-1000

-1500
0

250

500

750

1000

1250

1500

1750

2000
3
x 10

Figure 4.2: Distribution of fully-contained events within the ducial volume.

4.2 Event Classi cation
4.2.1 Single-ring Finding
An algorithm called \ringer" is used to select single-ring (quasi-elastic candidate)
events, based on the azimuthal distribution of light which falls behind the Cerenkov
cone of the track; events with azimuthal symmetry are considered single-ring, andthose with a higher asymmetry are considered multi-ring. The algorithm, developed
at BU, looks at the charge deposited in the tubes from 50 deg o the track direction
to 130 deg o the track direction, in a sliding window 40 deg wide. The tube charges
are corrected for tube coverage and water attenuation, and a 2 measure of the
maximum \imbalance" found is returned.
The single-ring and multi-ring results of these cuts agree with human scanners for
90% of the events, which is similar to the agreement level of two independent humanscanners. Based on Monte Carlo (M.C.) studies, the single-ring sample from this50
algorithm is estimated to contain 77% quasi-elastic interactions, 15% non-quasielastic charged-current interactions, and 8% neutral-current interactions.
Figure 4.3 shows an example of a multi-ring event which is rejected by this criterion.
Figure 4.4 shows the location of the cut on data and MC samples.

Figure 4.3: Example of an event classi ed as multi-ring.

51

600
500
400
300
200
100
0

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

7000
6000
5000
4000
3000
2000
1000
0

Figure 4.4: Ringer values for data and monte carlo samples. Single-ring events havea lower ringer value, and multi-ring events have a higher value.

52

4.2.2 Muon Decay
The identity of the incoming neutrino in a quasi-elastic charged-current interaction is determined from the type of lepton produced. Muon-(anti-)neutrinos giverise to (anti-)muons, and electron-(anti-)neutrinos give rise to electrons(positrons)
according to: + n ! , + p
 + p ! + + n
e + n ! e, + p
e + p ! e+ + n
The outgoing leptons can be identi ed in several ways. The easiest to use in a waterCherenkov detector are event topology and (in the case of muons) the detection offurther decay electrons:

+ ! e+ + e + 
, ! e, + e + 
The decay electrons are found in two ways: either as an extra track later in thesame event if they are generated within about 1 microsecond of the original muontrack, or else they can generate triggers and be found as \after-events" if they are
produced later than that. These events can be identi ed by their characteristically
low energies (up to 52 MeV), and by their timing relative to the previous event:the + lifetime is 2.19703  0.00004 -sec[45]; the , can be captured by a nucleus
before it decays, and so has a shortened measured lifetime in pure water of 1.7954
 0.0020 -sec.[46] The -decay search software is thus divided into two parts:\samedk" (developed at BU) and \afterdk" (developed at UH).
The samedk algorithm uses the vertex of the original muon to nd timing-residuals
peaks later in the same event. It works well for low-energy (sub-GeV) events, because
the muon tracklength at those energies is short (< 2 m) and the decay electron
vertex (if there is one) will not be far away. At higher energies the distance between

53
the muon and electron vertices increases, but the number of tubes \used up" by theoriginal event also increases as the event gets brighter; tubes which have been hit
already in an event are unavailable for recording further hits from any later track.
The afterdk algorithm uses a low-energy point- t, \hayai," developed at LSU for the
study of solar neutrinos. The details of its operation are given in Ref. [47]. The total
charge of all tubes within a 25 ns time-of- ight residuals window from the vertex,
corrected for water attenuation and tube coverage from the t vertex, is required to
be greater than 80 p.e., which corresponds to a lower-energy cut of about 10 MeV.
If the event is in the sub-GeV range, the hayai vertex is required to be found within
8 meters of the original event. (The vertex resolution of \hayai" is better than 1
meter for events over 10 MeV.) This requirement is waived for higher-energy events
where the muon tracklength is longer. After the discovery of a decay candidate,the candidate \after event" is cleared of all tubes within an 80 ns residuals window
centered around the hayai vertex, and the event is searched again for a new decay
candidate. Figures 4.5 and 4.6 show an example of a muon/after-decay pair.
It sometimes happens that a decay electron will appear late enough in a primary
event to generate a new trigger, and straddle the two events, with half its hits
in the rst event and half in the second. Such events are called \bye-bye" events(after the convention of T. Hayakawa of the onsite group), and they are found bycomparing the times when samedk and afterdk both nd a decay candidate. If thetwo candidates are within 100 ns of each other, a hayai t is applied to the samedk
event, and the event is awarded to the event with the better hayai goodness-of- t.
However, \bye-bye" events are rejected by a set of timing cuts designed to restrict
the attention to regions of relatively at eciency. The cleandk cuts are: 250800 nsec and 1.2-6 -sec. The light travel time across the detector from corner
to corner is 210 nsec, so decays within 250 nsec of the original event are foundwith low eciency and high background, since light from the original event is stilltraversing the detector. Events between 800 and 1200 nsec fall into the \bye-bye"region between events; not only is the software detection eciency lowered thereby the spreading of one track across two events, but there is also a detector trigger

54

Figure 4.5: Example of an event identi ed as muon-like.
ineciency in this region which grows with the size of the event. Finally, the time
cut at 6 microseconds is due to the rejection of all events with no outer-detector
data in the earliest stages of data reduction: for those runs which are subsequent to
the outer-detector data-taking window being shortened to end 6 microseconds after
than the primary event trigger (see Chapter 2), outer-detector data is missing forthe 2-3 microsecond digitization period following the 6-microsecond mark.
To study the relative eciencies of the detection of decay electrons between data andmonte carlo, cosmic ray muons which have stopped in the detector were studied. (See

55

Figure 4.6: Example of an event classi ed as a decay-electron, following previous
muon event.
Figure 4.7 for an example.) Such events have previously been studied at Kamiokande
where the charge ratio R(+=,) and polarization of stopping cosmic ray muons
were measured from a study of the resulting decay electrons. In that study, thecharge ratio was measured by tting the decay curve to a two-component lifetime
equation of the form:

N (t , (t + t)) = N+[1 , e(,t=+ ) ]e(,t=+ ) + N,[1 , e(,t=, ) ]e(,t=, ) ,56
where t is the binning width of the decay-curve histogram, N+ and N, are thetotal number of positive and negative muons, respectively, and + and , are the+ and e ective , lifetimes, respectively. From a sample of 1:6  105 muon-electron
event pairs, they determined the charge ratio R(+=,) for the muons stopping at
Kamiokande (400 m down the tunnel from Super-Kamiokande) to be 1:37  0:06
(stat) 0:01 (syst).[48]Stopping cosmic-ray muons are not saved in the o site high-energy reduction, so
a sample of 16,500 provided by Robert Svoboda of LSU and the o site low-energy
group was used as a test sample. These were t with the LSU muon tter \muboy,"which is described in Ref. [47], but which provides entry points and end pointsof stopping muon tracks to better than 1 meter resolution. Such a sample is notdirectly comparable to the contained event sample, having di erent vertex, endpoint and energy distributions, but it can be used to compare the relative detectioneciencies between the data and the monte carlo.
The muboy tracks were used to generate MC stopping muons for a comparison
sample. The charge ratio R(+=,) in the MC sample was set to 1:37, in accordancewith the Kamiokande measurement; a , capture in the MC is simulated by a fake\decay" of the , to two neutrinos, which e ectively makes it disappear in the event
simulation. There is no way to match the charges of the muons in the monte carlowith those in the data track-for-track, but this does not matter as long as the track
distribution does not depend on the sign of the muon { a dependence which there
is no reason to expect.
From these samples, the detection rate of decays is estimated to be 70% for +and 57% for ,. Contamination is less than 1%, as measured by the instances ofmultiple decay candidates for a single stopper. Detection eciencies between montecarlo and data agree within 3 %. This is taken as the systematic error on the relative
detection rate between data and monte carlo.

57

Figure 4.7: Example of an entering muon which has stopped in the tank. Note thepresence of activity near the entry point in the outer detector, in the upper-righthand corner, which is absent from fully-contained events.

58

4.2.3 Particle ID
Single-ring tracks are further classi ed into whether they are electron-like or muonlike based on the event topology. The biggest di erence between electron tracks andmuon tracks is that muon tracks tend to generate fairly clean and sharp Cherenkovcone patterns, while electrons tend to produce fuzzier distributions due to electromagnetic showers. Figures 4.8 and 4.5 show the characteristic light patterns forelectron and muon tracks.

Figure 4.8: Example of an event identi ed as electron-like.

59
An algorithm called \adpid" was developed at SUNY which measures the relative
amounts of Cherenkov light projected back onto the particle track before and after
the vertex to determine the amount of showering.[49] Adpid takes the light from theevent and projects it onto the track as though it had been emitted at the Cherenkov
angle. It then compares the di erence between the amount of light found 5 metersbehind the vertex to that found 5 meters in front of it to distinguish -like eventsfrom e-like ones. The misidenti cation rates for the quasielastic events in the MC
which pass the reduction cuts are shown in Figure 4.9. For those events in the range
100-1500 MeV, the misidenti cation rates for electrons and muons are 2.4% and1.8% respectively.
A secondary particle ID, \dochira," was developed at UH for comparison purposes.
It also uses the light pattern of the track, but applies a Kolmogorov-Smirno shape
test to the angular distribution which is compared against the results from a set ofmonte-carlo muons and electrons. The misidenti cation rates are shown in Figure
4.10. For those events in the range 100-1500 MeV, the misidenti cation rates forelectrons and muons are 5.5% and 4.4% respectively.
Adpid has better track discrimination especially at the bottom of the energy scale.
Dochira improves somewhat with energy, where Adpid gradually worsens, especiallyabove 5 GeV. However, by 10 GeV, contained leptons can be identi ed as electrons
simply by the fact that they are contained { muon tracks above that energy are
too long to be contained. Dochira agrees with adpid and 92 % of the time in the
sub-GeV data, and 93 % of the time in the monte carlo sample.

4.2.4 Energy Determination
The particle energy is reconstructed from the amount of light received at each tube,
corrected for its distance from the vertex of the event. This gives rst visible energy,
which as mentioned before is de ned to be the energy of an electron which would
generate the same amount of light as the given event, regardless of the actual particle

60

0.2
0.1
0

0

200

400

600

800

1000

1200

1400

0

200

400

600

800

1000

1200

1400

0.3
0.2
0.1
0

0.02
0.015
0.01
0.005
0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

0.15
0.1
0.05
0

Figure 4.9: ADPID lepton misidenti cation rates for quasi-elastic MC events whichpass the reduction cuts.

61

0.4
0.2
0

0.08
0.06
0.04
0.02
0

0.1
0.075
0.05
0.025
0

0

200

400

600

800

1000

1200

1400

0

200

400

600

800

1000

1200

1400

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

0.06
0.04
0.02
0

Figure 4.10: DOCHIRA lepton misidenti cation rates for quasi-elastic MC events
which pass the reduction cuts.

62type. From this, a particle momentum is assigned based on the identi ed particle
type.
The energy scale of the monte carlo is set at the low end by calibrations using acalifornium-nickel source: neutrons from decay of californium are thermalized bypassage through water and captured on nickel threads, leading to an excited nuclear
state which emits a 9 MeV gamma ray. At the upper end of the energy scale
stopping cosmic-ray muon tracks are used to set the energy scale > 1 GeV andabove. Periodic calibrations with these sources are used to track detector gain overthe course of the year, and to match water attenuation parameters in the montecarlo with that in the data. The energy calibration is checked by looking at datafrom a LINAC (which injects electrons up to 15 MeV directly into the detector
volume), muon-decay electrons and 0s produced
q by the neutrino interactions. Theenergy resolution is estimated to be 1:74%= E (GeV ) + 1:1%, with an estimated3:6% uncertainty in the energy scale.
The visible energy distributions for all events and for single ring events, data andsimulation, are shown in Figures 4.11 and 4.12, where all events and those witha muon decay tag are both indicated. Similarly, in Figures 4.13 and 4.14, arepresented momentum distributions of the single-ring e-like and -like events, dataand simulation, all events and those with muon decay tags.

4.3 Results
After assigning particle identi cation, events are selected with 0:1 GeV/c < pe < 1:5
GeV/c and 0:3 GeV/c < p < 1:5 GeV/c. This corresponds to the kinematic cuts
used in prior analyses by the IMB experiment.[21] This analysis chain has also been
performed with a minimum p of 0:2 GeV/c and a maximum visible energy of 1:33
GeV, corresponding to the Kamiokande kinematics cuts.[50] The nal data sampleof single-ring events, within the IMB momentum ranges, and with vertices in the22.5 kton ducial volume, consists of 727 e-like events and 537 -like events.

63

500

400

300

200

100

0

0

200

400

600

800

1000

1200

1400

Figure 4.11: Visible energy of all events and those with mu decay.

500

400

300

200

100

0

0

200

400

600

800

1000

1200

1400

Figure 4.12: Visible energy of single-ring events and those with mu decay.

64

180

160

140

120

100

80

60

40

20

0

0

200

400

600

800

1000

1200

1400

Figure 4.13: Momentum of single-ring e-like events and those with a mu decay.

225

200

175

150

125

100

75

50

25

0

0

200

400

600

800

1000

1200

1400

Figure 4.14: Momentum of single-ring -like events and those with a mu decay.

65
A sample of Monte Carlo events corresponding to 7.75 years worth of exposure was
generated, using the atmospheric  and e ux models of Agrawal, Barr, Gaisser,
Lipari and Stanev[13,12,51] and the pion-production model of Rein and Seghal.[52](See Appendix A) The M.C. events were processed through the same analysis chain
as the data. This results in 6518 e-like events (of which 5723 are CC events) and
7192 mu-like events (of which 7015 are charged-current events) for the IMB cuts.

66

100
80
60
40
20
0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

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0.8

1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

800
700
600
500
400
300
200
100
0

Figure 4.15: Adpid particle-ID distributions for data and MC, IMB cuts.

100
80
60
40
20
0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

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-1

-0.8

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-0.2

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0.2

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0.8

1

900
800
700
600
500
400
300
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100
0

Figure 4.16: Adpid particle-ID distributions for data and MC, KAM cuts.

67

70
60
50
40
30
20
10
0

-1

-0.8

-0.6

-0.4

-0.2

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-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

600
500
400
300
200
100
0

Figure 4.17: Dochira particle-ID distributions for data and MC, IMB cuts.

70
60
50
40
30
20
10
0

-1

-0.8

-0.6

-0.4

-0.2

0

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-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

700
600
500
400
300
200
100
0

Figure 4.18: Dochira particle-ID distributions for data and MC, KAM cuts.
The fraction of -like events in the data in this momentum range is 42:51:3(stat)%,while for for the monte carlo sample it is 53:5  0:4(stat)5(syst)%. This leads to,like)Data
a double ratio R = ((,,like=e
like=e,like)MC = 0:64  0:04(stat)  0:06(syst). In com-68
parison, IMB found 36  2(stat)5(syst)% versus 51  1(stat)5 (syst)%,[21], orR = 0:54  0:05  0:07.
In the range of momentum cuts, the fraction of events with at least one associateddecay is 29:8  1:3(stat)%, while from the monte carlo a fraction of 35:9  0:4(stat)0:3(syst)% is expected.
Applying cuts in the Kamiokande style, and calculating the double-ratio R thereby,,like)Data
it is found that R = ((,,like=e
like=e,like)MC = 0:65  0:04(stat)  0:06(syst). This is ingood agreement with the onsite analysis.[53]The above R values are derived using adpid. As a check, dochira is also applied.
From the greater cross-over, a few percent higher double ratio is expected fromdochira, and it is seen in R = 0:70  0:04  0:06 (IMB cuts) and R = 0:68  0:04  0:06
(KAM cuts).
8:8%1:1% of the e-like events (KAM cuts) have one or more decay signals comparedto the Monte Carlo prediction of 11:2%  0:4%  0:3%, where the error on the data
and the rst error on the Monte Carlo is statistical and the second error on the Monte
Carlo is the estimated error of the muon decay detection eciency. For -like events
we nd 56:6%  1:8% have one or more decays and 3:0%  0:6% have two or more
decays. This compares with the Monte Carlo predictions of 55:6%  0:5%  1:7%
and 3:3%  0:2%  0:1% respectively.
The vertex distributions of the primary events and of the decay candidates provide
information on the systematic errors due to tting errors and due to the ratio ofquasi-elastic to non-quasi-elastic events. For muon-like events with a suciently
large energy (> 500MeV ), it is possible to discriminate between decay candidates
produced at the endpoint of the muon track and those produced by pions decaying
near the vertex. Figure 4.19 shows the decay vertex projected along the track formuons above 500 MeV and below 5 GeV in both data and monte carlo samples. A
clear double-peaked distribution is seen: those vertices in the left peak are near the
event vertex (presumably due to pions), and those in the right peak are those at theend-point of the primary muon track.

69

16
14
12
10
8
6
4
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-500

0

500

1000

1500

2000

-500

0

500

1000

1500

2000

180
160
140
120
100
80
60
40
20
0

Figure 4.19: Distance along primary (yastef) track of decay (hayai) vertices forevents identi ed as muons with 500MeV < Evis < 5GeV .

70
From the overall shift in the location of the decay vertices relative to the primaryvertices, the yastef- tted vertex is found to be pulled about 10 cm forward in real
data compared to monte carlo events. This contributes 1% to the systematic in R
due to the e ective volume for muons changing relative to that for electrons: because
muons have longer track lengths than electrons in the detector, muons with vertices
near the edge of the ducial volume which are pointing inwards can be pulled in,while those pointing outwards cannot be pushed out as much as electrons and still
pass the reduction cuts.
From the ratio of the number of decay candidates in the left-hand peak to thosein the right-hand peak (each candidate being inversely weighted by the number ofdecays in each event), the agreement between data and monte carlo in the QE/nonQE ratio for events classi ed as muons is 0:7  3:1%. This leads to an estimate of
the systematic in R due to the QE/non-QE ratio in mu-like events of 3.2%.
From the di erence in the number of electron-like events with decays found, thesystematic error in R due to the ratio of quasi-elastic to non-quasi-elastic events
which are counted as electrons can be estimated to be 2.7%.
The total QE/non-QE ratio contribution to the systematic error in R is then taken
as 4.2%, taking the above two contributions in quadrature. (The contributions to
the muon side and to the electron side are through largely non-overlapping channels{ in particular, almost all of the neutral current events are counted as electrons in
the monte carlo.) This agrees with a separate theoretical estimation of 3% fromthe uncertainty in the quasi-elastic neutrino cross-section, and 2.6% from the non
quasi-elastic neutrino cross-sections, which taken in quadrature give 4.0%.
The total sources of systematic error in R are as follows: 1% from the absoluteenergy calibration, 1.5% from the conversion to muon momentum, 1% from ducial volume determination, 3.1% from single-ring selection, 3.5% from particle misidenti cation, less than 0.5% from cosmic ray muons and other non-neutrino related
backgrounds, 5% from the uncertainty in the calculation of the  =e ratio, 4.2%
from the uncertainty in the quasi-elastic/non-quasi-elastic cross-section ratio, 2%71from the statistical error in the Monte Carlo. These errors are added in quadrature
giving a total systematic error of 8.5%.
Looking at events above the sub-GeV range, the double-ratio for events in the range
1.33 GeV< Evis <5 GeV is 0:7030:11(stat)0:07(syst), where the total systematic
error, adjusting for reduced statistics, is taken as 9.5%.

72
20
17.5
15
12.5
10
7.5
5
2.5
0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

120
100
80
60
40
20
0

Figure 4.20: Adpid PID distributions for data and MC, 1.5 GeV<Evis<5 GeV.

12
10
8
6
4
2
0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

100
80
60
40
20
0

Figure 4.21: Dochira PID distributions for data and MC, 1.5 GeV<Evis<5 GeV.

73
In Figure 4.22 is presented the volume fraction versus numbers of events, for bothall events and those with a muon decay. In Figure 4.23, are the same quantities for
single ring events and those with a muon decay. The volume fraction plot shows datain successively larger concentric shells of equal volume, zero being the innermost.
This tests the data for systematic e ects which might be due to proximity to thedetector boundary.

74
225

200

175

150

125

100

75

50

25

0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Figure 4.22: Fiducial volume distribution of all events and those with a mu decay.

180

160

140

120

100

80

60

40

20

0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Figure 4.23: Fiducial volume distribution of single-ring events and those with a mu
decay.
The angular distribution of the -like fraction of the total events is illustrated in
Figures 4.24 and 4.26, for topologically identi ed events and those with muon decay

75tags, for both data and simulation. The direction cosine is +1 for downgoing and 1 for upcoming events. A trend towards more muon de cit in the lower hemisphereis visible.

0.5

0.4

0.3

0.2

0.1

0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Figure 4.24: -like fraction vs zenith angle, 2-meter ducial cut.
0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Figure 4.25: Muon-decay fraction vs zenith angle 2-meter ducial cut.

76

0.5

0.4

0.3

0.2

0.1

0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Figure 4.26: -like fraction vs zenith angle 5-meter ducial cut.

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Figure 4.27: Muon-decay fraction vs zenith angle 5-meter ducial cut.

77
Finally the muon-like and decay fractions plotted with respect to momentum arepresented in Figures 4.28 and 4.29.

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

0

200

400

600

800

1000

1200

1400

Figure 4.28: -like fraction vs momentum.

0.5

0.4

0.3

0.2

0.1

0

0

200

400

600

800

1000

1200

1400

Figure 4.29: Muon-decay fraction vs momentum.

78

4.3.1 Comparison of Analyses
The collaboration conducted two independent series of data reduction, event tting,and monte carlo simulation. Both analyses used the same data set calibrated
in terms of photoelectrons and time, proceeding with independent application of
conversions to energy (which involve interpretation of calibrations and such things
as corrections for water transparency, etc.) and all further selections, tting andinterpretations. The results are consistent with each other and with the previous
IMB and Kamiokande experiments, and con rm that the atmospheric neutrino
anomaly persists.

4.4 Interpretation
Since Kamiokande, IMB and other experiments reported anomalously low ratios ofmuon-like events to electron-like events 10 years ago, there have been a numberof models proposed to explain the phenomenon, ranging from contamination by
neutrons from the surrounding rock [54,55] to contamination by proton decay (ironic,
since atmospheric neutrinos were originally studied as background for proton-decay
searches). The rst of these objections was answered by Kamiokande, where they
showed that the pions produced by neutron interactions are identi able and notclustered near the walls as would be expected.[56] The second would imply that theanomalous ratio of ratios would not extend above the rest mass of the proton; themulti-GeV ratio is, however, still below expectation. A most serious possibility isthat of an error in the calculation of atmospheric neutrino uxes { this one cannot
easily be ruled out, despite the agreement between di erent ux models.
Assuming the ux model is right, one of the most persistent proposals, predating
any of the neutrino ux anomalies, is the possibility that if neutrinos have non-zero
mass, their avor (weak) eigenstates need not be the same as their mass eigenstates,
and hence they can oscillate from one type to another in ight. There are several
models in circulation, some of which will be discussed below, but the general scheme

79
can be represented by the simplest case of two- avor mixing, for example between
 and  , where the avor eigenstates are related to the mass eigenstates by:

0 1 0
10 1

cos
sin

@ A=@
A @ 2 A,,sin cos
3

where  is the mixing angle between the mass eigenstates and the weak eigenstates.
(This use of subscripts \2" and \3" for the mass eigenstates involved in  -
oscillations is conventional. Had it been e-, the corresponding mass subscripts
would have been \1" and \2.") The mass eigenstates propagate as:

0 1 0
10 1

E
0
A @ 2 A,i dtd @ 2 A = @ 2
3
0 E3
3

which leads to a  survival probability of:
223 L
P = 1 , sin2 (2)sin2( 1:27m
E ),where the neutrino energy E is in MeV, the distance travelled L is in meters, andthe m2 is measured in eV 2.
The notable features of this expression are that rst, the overall magnitude of theoscillations is set by sin2 2, and that second, the energy E at which oscillations
set in (for a given pathlength L) is determined by m2 . The case of sin2 2 = 1( = 45 deg) is referred to as \maximal mixing."
The above formalism can be generalized to three avors; this requires the use of two
mass-squared di erences (the third being determined by the rst two) and three
mixing angles. Here, only the two- avor models are considered.
In order to discriminate between competing models, two useful metrics from thedata are the \ratio-of-ratios" of relative ux rates of muon- and electron-like events,
and the directional asymmetries of each of these two types of event. The directional
asymmetries are de ned as:

A = DD+,UUAe = DDee,+UUee ,80where D is the number of downward-going muon-like events, U is the number of upward-going muon-like events, and likewise for the electron-like events.[57]\Downward-going" means cos < 0, where cos is the z-component of the momentum vector { not to be confused with the \cosmic ray" direction, which is the(opposite) direction from which the particle came.
Figure 4.30 shows the asymmetries plotted against the visible energy (electronequivalent energy) of the single-ring data from SuperKamiokande in 10 logarithmic
visible energy bins from 100 MeV to 5 GeV. The upper curve is A , while the lower
one is Ae. Figure 4.31 shows the same data as a trajectory in the A-Ae plane;arrows indicates the direction of increasing energy.
Figures 4.32 and 4.33 show these same quantities for the monte carlo events.
Following that are the asymmetries and asymetry trajectories. For those models
with adjustable parameters, the asymmetries shown are the results of 2 minimization in the asymmetries. The 2 function follows a formalism used in the AMY[58]and CELLO[59] experiments: a vector  of residuals a matrix V of errors is constructed, with the Vnnth diagonal element being the total 2 for each measurement,
and the o -diagonal element Vij being the common normalization error for the ith
and jth measurements. Then the minimized expression is2 = T V ,1.
Ten residuals measurements between data and monte carlo, one for each energy bin,
are taken in A and likewise in Ae for a total of twenty residuals elements. The o diagonal elements are taken as the estimated background, (0:2)2, and it is assumed
that the muon asymmetries are uncorrelated with the electron asymmetries. The
on-diagonal elements are taken as the sums of the squares of the statistical errors
in the data and monte carlo and the background. The detector is assumed to be
up-down symmetric. In addition, a set of ten residuals in the number of muonsnormalized to the number of electrons (R(=e)Data , R(=e)MC ) is t, using thenon-statistical part of the systematic errors as the o -diagonal elements.

81
Corrections were made in the oscillation probabilities for the e ects of matter on
the survival probabilities due to the di erent e ective potentials seen by di erent
avors as they pass through the earth. Using the parametrization of Akhmedov etal., this can be treated as a changing of the e ective oscillation amplitude sin(2)and m2 to values depending on the number densities of electrons in the matter (for , e) or neutrons (for  , sterile). The case of  , e does not require mattere ects. Sterile neutrinos, if they exist, will not interact with the matter and so will
have a di erent e ective potential than muon neutrinos.
Other than that, it is very similar to  , sterile , except that neutral-current events
are not oscillated away for muon neutrinos that become tau neutrinos, while they
are for sterile neutrinos, because the neutral current cross-sections are the same fortau neutrino and the muon neutrino (and the electron neutrino) but are zero forsterile neutrinos. Matter e ects are zero for  ,  .
The results are summarized in Table 4.3. For each model, the best- t (if the model
has adjustable parameters) 2=d:o:f is given for the 2 measured for the variationof the relevant parameters. The rst two colums show the 2 =d:o:f: and d.o.f. forthe t to the asymmetries, the second two columns show the same quantities for thet to the ratios, and the last two columns show the results for the combined t.
Table 4.3: Best- t resultsfor oscllation
scenarios.
2A;R
2A
2R
Model
dof dof
dof
dof dof dof
No oscillations 10 2.68 20 2.14 10 2.5 30
 ,  1
1.29 18 0.604 8 1.04 28
 , e 2
2.21 18 0.543 8 1.62 28
 , sterile 9
1.3 18 0.536 8 1.04 28
The best ts are for  ,  and  , sterile, which have nearly the same total 2 andbest t points (shown in Figs. 4.36 and 4.39), but with a slightly smaller allowed
region for  , sterile.
The best- t point for  , e is near that for the previous two cases, but the 2 ismuch worse, primarily due to the asymmetry. However, it is still better than the
no-oscillations case.

82

0.6

0.4

0.2

0

-0.2

-0.4

-0.6

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

Figure 4.30: Asymmetry vs visible energy, data.

0.6

0.4

0.2

0

-0.2

-0.4

-0.6
-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Figure 4.31: Asymmetry trajectory data.

83

0.6

0.4

0.2

0

-0.2

-0.4

-0.6

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

Figure 4.32: Asymmetry vs visible energy, MC with no oscillations.
0.6

0.4

0.2

0

-0.2

-0.4

-0.6
-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Figure 4.33: Asymmetry trajectory MC with no oscillations.

84

0.6

0.4

0.2

0

-0.2

-0.4

-0.6

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

Figure 4.34: Asymmetry vs visible energy, MC with  !  osc.
0.6

0.4

0.2

0

-0.2

-0.4

-0.6
-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Figure 4.35: Asymmetry trajectory MC with  !  osc.

85
0

-0.5

-1

-1.5

-2

-2.5

-3

-3.5

-4
0

0.2

0.4

0.6

0.8

1

Figure 4.36: Chi-squared, MC with  !  osc.

86

0.6

0.4

0.2

0

-0.2

-0.4

-0.6

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

Figure 4.37: Asymmetry vs visible energy, MC with  ! Sterile osc.
0.6

0.4

0.2

0

-0.2

-0.4

-0.6
-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Figure 4.38: Asymmetry trajectory MC with  ! Sterile osc.

87
0

-0.5

-1

-1.5

-2

-2.5

-3

-3.5

-4
0

0.2

0.4

0.6

0.8

1

Figure 4.39: Chi-squared, MC with  ! Sterile osc.

88

0.6

0.4

0.2

0

-0.2

-0.4

-0.6

2

2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

Figure 4.40: Asymmetry vs visible energy, MC with  ! e osc.
0.6

0.4

0.2

0

-0.2

-0.4

-0.6
-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Figure 4.41: Asymmetry trajectory MC with  ! e osc.

89
0

-0.5

-1

-1.5

-2

-2.5

-3

-3.5

-4
0

0.2

0.4

0.6

0.8

1

Figure 4.42: Chi-squared, MC with  ! e osc.

90

4.5 Conclusions
Super-Kamiokande went online at midnight, 1 April 1996, to start taking data on
atmospheric and solar neutrinos, search for signs of proton decay, and monitor for
supernova bursts. In its rst year of operation, it has caught up to the cumulative
livetime of its predecessor experiments, Kamiokande and IMB, and has been able tocon rm the continued existence of the anomalous atmospheric neutrino avor ratios
reported by those experiments. In addition, it is able to gather better statistics on
the angular distribution of events at energies > 1 GeV.
Soon, Super-Kamiokande will have enough data to more rmly indicate whether
neutrino oscillations remain a viable solution to the problem, and if so at what
set of parameters. In addition, it continues to take data on solar neutrinos, andwill soon become the far detector for the K2K long-baseline neutrino oscillations
experiment, which will aim  1 GeV neutrinos from the proton-synchrotron facility
at KEK, 250 km away.

Appendix A
Monte Carlo Cross-sections

91\It is not for children." { Wojciech Gajewski

IMB, like Super-Kamiokande, was divided into two analysis groups: East Coast andWest Coast. Each analysis group developed its own neutrino interaction model;
the Super-Kamiokande o site analysis group thus inherited two di erent simulation
programs, which have come to be known as \IMBEast," originally developed at the
University of Michigan[60], and \IMBWest," originally developed at UCI.[61]Both monte carlos use the atmospheric ux calculation of Agrawal, Barr, Gaisser,
Lipari and Stanev. [13,12,51] They also use common tracking code and detector model. The CERNLIB package GCALOR (version 1.03/08) is used for the
propagation of the interaction products; GCALOR uses CALOR to handle mosthadronic interactions, and calls on GEANT (version 3.16) to handle electromagnetic
interactions, and FLUKA to handle hadronic interactions above 10 GeV.
IMBEast uses the pion-production model of Rein and, Seghal[52], while IMBWest
uses one based on that of Fogli and Nardulli62. They agree with each other on pionproduction rates to within a few percent in the sub-GeV range. The two interactionmonte carlos have been modi ed somewhat to accommodate new values for the axial
mass and Fermi momentum.
The IMBEast monte carlo has undergone more extensive updates, in particular
to some of the pion-production cross-sections and its deep-inelastic cross-section
calculation, which which makes it preferable to IMBWest, especially in the multiGeV range. In fact the IMBWest neutrino spectrum cuts o at 5 GeV. IMBEast is
the MC used in the analysis.

92
The neutrino-free nucleon cross-sections used in IMBEast are shown in Figure A.1.
(Courtesy of Wojciech Gajewski.)

93

Figure A.1: IMBEast cross-sections.

Appendix B
The Super-Kamiokande
Collaboration
Institute for Cosmic Ray Research, University of Tokyo
Y. Fukuda, T. Hayakawa, K. Inoue, K. Ishihara, H. Ishino,
Y. Itow, T. Kajita, J. Kameda, S. Kasuga, Y. Koshio,
K. Martens, M. Miura, M. Nakahata, A. Okada, M. Oketa,
K. Okumura, M. Ota, N. Sakurai, M. Shiozawa, Y. Suzuki,
Y. Takeuchi, Y. Totsuka (spokesman)

National Laboratory for High Energy Physics (KEK)

J. Kanzaki, K. Nakamura, M. Sakuda, O. Sasaki, Y. Oyama

Bubble Chamber Physics Laboratory,Tohoku University

K. Fujita, A. Hasegawa, T. Hasegawa, S. Hatakeyama,
T. Iwamoto, T. Kinebuchi, M. Koga, T. Maruyama, H. Ogawa,
M. Onada M. Saito, A. Suzuki, F. Tsushima

Tokai University

M. Eto, M. Koshiba, M. Nemoto, K. Nishijima

Department of Physics, Osaka University

A. Kusano, Y. Nagashima, M. Takita, T. Yamaguchi,
M. Yoshida

Niigata University

T. Ishizuka, Y. Kitaguchi, H. Koga, K. Miyano, H. Okazawa,
M. Takahata

Department of Physics, Tokyo Institute of Technology
Y. Hayato, Y. Kanaya, K. Kaneyuki, Y. Watanabe

Gifu University
S. Tasaka

Miyagi University of Education
M. Mori

Department of Physics, Kobe University
S. Echigo, M. Kohama, A.T. Suzuki

Institute for Nuclear Study, University of Tokyo

K. Chikamatsu, E. Ichihara, T. Inagaki, K. Nishikawa,
A. Sakai94

95

Boston University

M. Earl, A. Habig, E. Kearns, S.B. Kim, M. Messier,
J.L. Stone, K. Scholberg, L.R. Sulak

Brookhaven National Laboratory
M. Goldhaber

University of California, Irvine

T. Barszczak, W. Gajewski, P.G. Halverson, J. Hsu,
L.R. Price, W.R. Kropp, F. Reines, H.W. Sobel

California State University, Dominguez Hills
K. Ganezer, W. Keig

George Mason University
R.W. Ellsworth

University of Hawaii

J. Flanagan, J.G. Learned, S. Matsuno, V. Stenger,
D. Takemori

Los Alamos National Laboratory
T.J. Haines

Louisiana State University

E. Blaufuss, R. Sanford, R. Svoboda, M.R. Vagins

University of Maryland

M.L. Chen, Z. Conner, J.A. Goodman, G. Sullivan

State University of New York, Stony Brook

J. Hill, C.K. Jung, C. Mauger, C. McGrew, B. Viren,
C. Yanagisawa

University of Warsaw
D. Kielczewska

University of Washington

J. George, A. Stachyra, L. Wai, J. Wilkes, K. YoungAppendix C
Author96

The author joined the Super-Kamiokande collaboration in the fall of 1993. The
Kamiokande and IMB collaborations, from which the core of the Super-Kamiokande
collaboration was formed, were at that time preparing to do a study of the particle
identi cation capabilities of water Cherenkov detectors [35,36], since that had beena point of controversy when those collaborations had published their measurementsof the atmospheric neutrino composition. To accomplish this a 1 kton \miniKamiokande" tank was built at the end of the K6 proton-synchrotron beamline
at the KEK National Accelerator Laboratory in Tsukuba, Japan. This provided a
set of particles of known type (electron, muon, pion) and energy (0.1 to 1 GeV),
with which the instrumentation and algorithms of Kamiokande and IMB could betested. The tank was rst instrumented with DAQ and PMTs of the type used in
Kamiokande, and then with the those of IMB. In the fall of 1993, the author inheritedfrom Gary McGrath (who had graduated in August) the task of resurrecting the laser
calibration system from IMB, and went to KEK in 1994 to install it and to work on
the construction, calibration, data-taking and decommissioning of the IMB part ofthe beam-test, which occupied most of the year. While there, he also made a detailed
study of the documentation for the DAQ system then in development for the SuperKamiokande inner detector, which provided a necessary basis of understanding forthe design of an outer-detector DAQ (by other US institutions), which could be
integrated with it.
In early 1995, he worked on the design of the laser calibration system for SuperKamiokande, which needed to be much more elaborate than those used in IMB
and Kamiokande. Because of the geometry and narrowness of the outer detector,
ultimately 52 separate optical bers needed to be run to various positions throughout

97
the outer detector volume, in addition to the one for the inner detector. IMB had
no outer detector and Kamiokande didn't calibrate theirs to the degree that wasneeded for Super-Kamiokande. (Kamiokande vetoed on the basis of a global hitsumof the outer-detector tubes. For Super-Kamiokande, a more detailed read-out was
desired in order to speed up the job of nding cosmic ray entry points, and in order
to be able to con rm whether suspected partially contained events really exited theinner-detector volume.) The job of procuring bers and making di user balls wasallocated to UM (Zoa Conner), while that of designing and procuring the rest of thesystem (laser, light distribution system, DAQ hardware and software) was allocatedto UH (the author).
In the spring of 1995, the author took up position at the mine in Kamioka, representing UH (and for the rst couple of months, the US) for the duration of preparation,
construction and most of the rst year of data-taking. The equipment installationand preparations for the it lasted a bit more than a year, until April 1996 when
the detector turned on. Besides working on the installation and testing of outerdetector photo-tubes, the author also worked on the installation of the laser bers to
all parts of the outer detector, the development, installation and testing of the laser,
optical switches, and laser calibration DAQ, various other mechanical and logisticalproblems, and the usual crises that come up in a construction project of that size.
During the tank- lling phase in January and February of 1996, the author even had
to make use of his scuba-diving license in order to x several mechanical problems
that had arisen underwater.
At the end of construction and the beginning of data-taking, besides working on
construction and calibration, the author wrote the code to convert the outer-detector
data from raw format to calibrated format, added several features to the event
display program (especially those concerned with monitoring the performance ofthe detector), xed the PMT location map for the outer detector, and worked on
characterizing and debugging the performance of the detector generally.
By the end of the summer of 1996, with the stabilization of the detector, the author
concentrated on the analysis of the data with the o site high-energy group, working

98
on mu-decay (afterdk), particle ID (dochira), early studies of the absolute energy
calibration, event-scanning, characterizing the di erences between the two o sitemonte carlos, and other data-quality studies. The author also wrote the rst draftsof the o site-analysis and detector sections of the high-energy group's sub-GeV
atmospheric neutrino paper. A track tter that he wrote became the basis for amuon tter developed for the upward-going muon analysis by Shigenobu Matsuno.
The author was born in Massachusetts in 1964, and grew up in Vermont. Afterattending high schools in Vermont, Massachusetts and Winchester, England, hemajored in Physics and Astronomy at Harvard University, where the topic of his
undergraduate thesis was the temperature distribution of the Perseus cluster ofgalaxies, under the tutelage of Dr. Christine Jones. After graduating in 1987, heworked as research assistant and then as programmer for the Extreme Ultraviolet
Explorer satellite at UC Berkeley, as part of the team developing the analysis suite
which generated skymaps and point-source uxes in real-time from the satellite
telemetry. In 1992, he began graduate studies at UH, and worked part-time on cablestress (snap-loading) simulations for the deployment of the DUMAND undersea
neutrino detector project under Dr. John Learned. (That project ultimately faced
too many technical diculties and was terminated, though they did leave a legacy ofsolutions to some of the great and unusual problems of deep-ocean experimentation,
which have been put to use by marine researchers in other elds.)
In the fall of 1997, the author married Mika Masuzawa, whom he had met while she
was working as a post-doc on Super-Kamiokande and who is now working for theaccelerator division at KEK. At the end of 1997 he will be joining her there on a
JSPS fellowship for two years.

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