c 2008 Alice Patricia Bridgeman - CDF - Fermilab

125 Pages·2008·1.38 MB·English

c 2008 Alice Patricia Bridgeman
°
MEASUREMENT OF THE tt DIFFERENTIAL CROSS SECTION, dσ/dM , IN
tt
pp COLLISIONS AT √s = 1.96 TEV
BY
ALICE PATRICIA BRIDGEMAN
B.A., The Johns Hopkins University, 2003
DISSERTATION
Submitted in partial fulfillment of the requirements
for the degree of Doctor of Philosophy in Physics
in the Graduate College of the
University of Illinois at Urbana-Champaign, 2008
Urbana, Illinois
Doctoral Committee:
Professor Mats Selen, Chair
Professor Tony Liss, Director of Research
Professor John Stack
Assistant Professor Brian DeMarco
Abstract
I present a measurement of the tt differential cross section, dσ/dM , in pp collisions at √s = 1.96
tt
TeV using 2.7 fb−1 of CDF II data. I find that dσ/dMtt is consistent with the Standard Model
expectation, as modeled by PYTHIA with CTEQ5L parton distribution functions. I set limits on the
ratio κ/M in the Randall-Sundrum model by looking for Kaluza Klein gravitons which decay to
Pl
top quarks. I find κ/M >0.16 at the 95% confidence level.
Pl
ii
Acknowledgments
The last five years have been at times exciting, frustrating, very sad and very happy for me. I can
saywithcertaintythatIwouldnothavecomethisfarwithouttheloveandsupportofmywonderful
parents,DennisandElizabethBridgeman. IrememberwhenIwasachildthefirstjobIwantedwas
that of an elephant-rider in the circus. Well, I turned out to be a physicist, but I know they would
have been there for me, helping me be the best elephant-rider in the world if that’s what I wanted
to become.
I also must thank the entire University of Illinois High Energy Group - my fellow grad students
and postdocs, past and present, and all of the professors. Of course my advisor, Tony Liss, deserves
top billing. He entrusted me to complete this analysis largely independently, which was a huge
challenge but also incredibly rewarding in the end. Of course, no one really does a high energy
physicsanalysisbythemselves. IreceivedincrediblehelpfromformerUofIpostdocAnyesTaffard.
Anyes does amazing work, in both quality and quantity, and I thank her for being an inspiration.
Tom Schwarz not only convinced me to do SVD unfolding, but also helped me get it working.
Tom also did the majority of the work on the background estimates which many people, including
me, use. I thank him for sharing and letting me graduate that much faster. Erik Brubaker was
extremely helpful for the last round of the analysis, it was really his insistence that things be done
right that caused the final result to improve as much as it did. I could not have made my beyond
theStandardModelMonteCarlosampleswithoutthehelpofthetopMonteCarlocoordinatorNate
Goldschmidt. Thankyou, Nate! KevinLannonandCharlesPlageralsohelpedmemanytimeswith
top code. And for those many other collaborators I did not mention, and the vast technical staff at
CDF and Fermilab, I thank you as well for your hard work - without you, I would have no data to
analyze.
I must also thank my fellow graduate students that I have become friends with over the years.
I will miss (or already do) Joe Gezo, Dan Vandervelde, Josh Sayre, Kevin Mantey, Alice Quisno,
JamesReedandtheotherassortedmembersoftheDoscrew. ImustalsothankEdRogers,whohas
beenmykindredspiritintheCDFgroupandhelpedmepassthequal. Youhaveallmadegraduate
school the best part of my now extremely long academic journey. Outside of physics I thank Jamie
Bond for being a great friend and running buddy. I thank James Patrick for getting me to Illinois
and past the prelim.
Finally I thank Kevin Inderhees for being with me through the very difficult process of finishing
a dissertation. Thank you for putting up with my attempts to solve all problems when I should be
sleeping and for my strange affinity for 80’s rock tunes while writing. I’m sorry I will not be with
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you in Urbana while you write your dissertation, but you will get through it and we can get Boris
the orange cat when you are done.
This work was supported in part by the United States Department of Energy under grant DE-
FG02-91ER40677.
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Table of Contents
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
Chapter 1 Introduction to Top Quark Physics . . . . . . . . . . . . . . . . . . . . 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 The Standard Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.1 Quantum Electrodynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.2 Quantum Chromodynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.3 The Weak Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 tt Production and Decay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.3.1 tt Production at the Tevatron . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.3.2 Top Decay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.4 The Top Quark in Physics Beyond the Standard Model . . . . . . . . . . . . . . . . 17
Chapter 2 The Fermilab Tevatron and the CDF II Detector . . . . . . . . . . . 20
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.2 The Tevatron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3 CDF II Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.1 Tracking Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3.2 Calorimetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3.3 Muon Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3.4 Luminosity Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.3.5 Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Chapter 3 Monte Carlo Models for Signal and Background . . . . . . . . . . . . 27
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2 Monte Carlo Event Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2.1 Signal Event Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.2 Background Event Generation . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3 CDF Detector Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Chapter 4 tt Event Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.2 Event Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.2.1 Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.2.2 Lepton Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.2.3 Track and Primary Vertex Reconstruction . . . . . . . . . . . . . . . . . . . . 34
4.2.4 Jet Reconstruction and Uncertainties. . . . . . . . . . . . . . . . . . . . . . . 34
4.2.5 Missing Transverse Energy Reconstruction. . . . . . . . . . . . . . . . . . . . 40
v
4.3 Heavy Flavor Tagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.4 tt Signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.4.1 Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.4.2 Reconstruction of tt Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.5 Data Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Chapter 5 Standard Model tt Backgrounds . . . . . . . . . . . . . . . . . . . . . . 46
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.2 Normalization of the Backgrounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.2.1 Electroweak and Monte Carlo Derived Backgrounds . . . . . . . . . . . . . . 48
5.2.2 tt in the Pretag W+jets Sample . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.2.3 Non-W Background Production. . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2.4 W+heavy flavor Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2.5 Mistag Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
5.2.6 Tagged Electroweak and non-W Backgrounds . . . . . . . . . . . . . . . . . . 50
5.3 Data Sample Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.4 M Distribution of the Backgrounds . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
tt
Chapter 6 A Review of Previous Results . . . . . . . . . . . . . . . . . . . . . . . 53
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6.2 Searches for Narrow Resonances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6.3 Search for Massive Gluons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Chapter 7 Analysis Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
7.2 Unfolding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
7.2.1 A Simple Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
7.2.2 The Need for Regularization . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
7.2.3 Regularized Unfolding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
7.2.4 Choosing the Regularization Parameter . . . . . . . . . . . . . . . . . . . . . 69
7.2.5 Algorithm Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
7.2.6 Implementing the Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
7.2.7 Unfolding the M Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . 70
tt
7.3 Calculating dσ/dM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
tt
Chapter 8 Systematic Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
8.2 Sources of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
8.3 Evaluating Systematic Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
8.4 Expected Sensitivity of the Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Chapter 9 Reducing the Systematic Uncertainties . . . . . . . . . . . . . . . . . . 80
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
9.2 Measurement of ∆ from the Dijet Invariant Mass Distribution . . . . . . . . . . 80
JES
9.3 Parameterizing the Response Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
9.4 Parameterizing the Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
9.5 Tests of Analysis Procedure with in-situ Jet Energy Scale Calibration . . . . . . . . 84
9.6 New Systematic Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
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Chapter 10 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
10.2 Kinematic Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
10.3 M Fit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
jj
10.4 Unfolding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
10.5 Differential Cross Section . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
10.6 Cross Checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Chapter 11 Consistency with the Standard Model and Limits on New Physics. 101
11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
11.2 Generation of RS Monte Carlo Events . . . . . . . . . . . . . . . . . . . . . . . . . . 101
11.3 Setting Limits with CL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
s
11.3.1 The Anderson-Darling Statistic . . . . . . . . . . . . . . . . . . . . . . . . . 103
11.3.2 Constructing the Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . 104
11.4 Limits on the Coupling of RS Gravitons to Top Quarks . . . . . . . . . . . . . . . . 105
Chapter 12 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Author’s Biography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
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List of Tables
1.1 The quarks and leptons of the Standard Model. [1, 2]. . . . . . . . . . . . . . . . . . 2
1.2 The gauge bosons of the Standard Model. . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Summary of representation of the first generation fermions under SU(2) and their
hypercharge. The same holds for the second and third generations. . . . . . . . . . . 9
3.1 Summary of Monte Carlo programs used to generate events for different classes of
background events. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.1 Possible final states of W+ and W tt daughters. The numbers are the percentage
−
of the decays with that final state. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.2 Summary of event selection used in this analysis. . . . . . . . . . . . . . . . . . . . . 31
4.3 Binning of M used in this analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
tt
4.4 Efficiencies of the various triggers used in this analysis. . . . . . . . . . . . . . . . . . 32
4.5 Requirements for electron identification. . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.6 Requirements for muon identification. . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.7 Acceptances for events with CEM, CMUP and CMX leptons which pass the event
selection. The bins are defined in Table 4.3. . . . . . . . . . . . . . . . . . . . . . . . 43
4.8 Eventselectionefficiencyforeventswhichpasstheeventselectionaccordingtolepton
type and M bin. The bins are defined in Table 4.3. . . . . . . . . . . . . . . . . . . 43
tt
4.9 The event counts after event selection according to lepton trigger type and jet bin.
The signal region is 4-jets, for a total of 650 events in 2.7 fb−1 of data. . . . . . . 45
≥
5.1 Cross sections used in calculation of Monte Carlo derived backgrounds. [33] . . . . . 48
5.2 Fraction of W+jets events with heavy flavor content (in percents), and the tagging
efficiency for the events. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.3 Predicted sample composition in each jet bin for 2.7 fb−1 of data. [36]. . . . . . . . 51
7.1 The mean and widths of the pull for the number of unfolded events in each bin, as
defined in Equation 7.48, for pseudo-experiments constructed with tt signal only. . . 73
7.2 Denominator in bins of Mtt, assuming 2.7 fb−1 of data. . . . . . . . . . . . . . . . . 74
7.3 The mean and widths of the pull for the number of unfolded events in each bin, as
defined in Equation 7.48, for pseudo-experiments constructed with both signal and
background events. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
8.1 Summary of systematic uncertainties on dσ/dM in each bin. All uncertainties are
tt
given as percentages. The bins are defined in Table 4.3. . . . . . . . . . . . . . . . . 78
8.2 Summary of total expected uncertainties. All uncertainties are given as percentages. 79
9.1 The mean and widths of the pull for the number of unfolded events in each bin, as
defined in Equation 7.48, at various ∆ points. . . . . . . . . . . . . . . . . . . . . 90
JES
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9.2 Summaryofsystematicuncertaintiesondσ/dM ineachbinfortheimprovedanalysis
tt
with ∆ fit. All uncertainties are given as percentages. The bins are defined in
JES
Table 4.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
9.3 Summary of total expected uncertainties. All uncertainties are given as percentages 92
9.4 Comparison of expected uncertainties for the baseline analysis with no ∆ fit and
JES
the improved analysis with the ∆ fit. All uncertainties are given as percentages
JES
and the total does not include the uncertainty due to the luminosity measurement. . 92
10.1 Measured dσ/dMtt in 2.7fb−1 of data. . . . . . . . . . . . . . . . . . . . . . . . . . . 98
10.2 Comparison of results in different sub-samples of the data. . . . . . . . . . . . . . . . 100
11.1 Cross Sections for RS gravitons at various κ/M points.. . . . . . . . . . . . . . . . 102
Pl
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