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The Search for Supersymmetry in Hadronic Final States Using Boosted Object Reconstruction
Giordon Stark
Verlag Springer-Verlag, 2020
ISBN 9783030345488 , 263 Seiten
Format PDF, OL
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The Search for Supersymmetry in Hadronic Final States Using Boosted Object Reconstruction
Supervisor's Foreword
7
Acknowledgments
8
Contents
11
1 Introduction
15
2 Standard Model (and Beyond!)
17
2.1 The Standard Model
18
2.1.1 Spontaneous Symmetry Breaking
21
2.1.2 Quantum Electrodynamics (QED)
23
2.1.3 Quantum Chromodynamics (QCD)
27
2.1.4 Parton Distribution Function
31
2.1.5 Top Quark Decays
33
2.2 Beyond the Standard Model
34
2.2.1 Supersymmetry
35
2.2.2 Searching for New Physics Using Simplified Models
39
3 The Large Hadron Collider and the ATLAS Detector
41
3.1 Overview
41
3.2 LHC Upgrades
43
3.3 Operation of the LHC in Run 2
43
3.3.1 Pile-Up at the LHC
46
3.4 ATLAS Overview
48
3.5 ATLAS Geometry
49
3.6 Tracking in the Inner Detector
51
3.7 Calorimetry and the Calorimeter System
54
3.8 Muons and the Muon Spectrometer
59
4 Trigger and Data Acquisition
61
4.1 Overview
61
4.2 The TDAQ Subsystems
63
4.2.1 Level-1 Trigger
63
4.2.1.1 Level-1 Calorimeter Trigger
63
4.2.1.2 Level-1 Muon Trigger
65
4.2.2 HLT
66
4.2.2.1 FTK
66
4.3 Trigger Menu
66
4.4 Data and Simulated Event Samples
67
4.5 ATLAS Trigger System Phase-I Upgrade
69
4.5.1 The Global Feature Extractor Module
71
4.5.2 Slow Control and Monitoring of gFEX
75
4.5.3 Trigger-Aware Analysis Software
79
5 Event Reconstruction
80
5.1 Jets
80
5.1.1 Jet Algorithms
82
5.1.2 Jet Calibrations
86
5.1.2.1 Topocluster Calibration
87
5.1.3 Jet Energy Calibration
88
5.1.3.1 Jet Origin Correction
88
5.1.3.2 Pile-Up Correction
89
5.1.3.3 MC-Based Correction
89
5.1.3.4 Global Sequential Calibration
91
5.1.3.5 In-Situ Calibration
92
5.1.4 Uncertainties
94
5.1.5 Jet Kinematics
95
5.2 Flavor Tagging of Jets
96
5.2.1 Impact Parameter Tagging Algorithms
98
5.2.2 Secondary Vertex Finding Algorithm
98
5.2.3 Decay Chain Multi-Vertex Algorithm
100
5.2.4 Multivariate Algorithm
100
5.3 Muons
103
5.4 Electrons and Photons
105
5.5 Taus
106
5.6 Missing Transverse Momentum
106
6 Boosted Object Reconstruction
109
6.1 Size of Boosted Jets
109
6.2 Objects
111
6.2.1 Small-Radius Jets
112
6.2.2 b-Tagged Jets
113
6.2.3 Leptons
114
6.2.4 Overlap Removal
115
6.2.5 Large-Radius Jets
116
6.2.6 Missing Transverse Momentum
117
7 Search for Massive Supersymmetry at 13TeV
118
7.1 Searching for New Physics: A Counting Experiment
118
7.1.1 Signal Models
118
7.2 Kinematic Variables and Event Selection
120
7.2.1 Kinematic Variables
120
7.2.1.1 Object Multiplicity
120
7.2.1.2 Effective Mass
120
7.2.1.3 Transverse Mass
121
7.2.1.4 Total Jet Mass
121
7.2.1.5 Multijet Suppression
122
7.2.2 Event Selection
122
7.2.2.1 Good Runs
123
7.2.2.2 Tile, LAr, and SCT
124
7.2.2.3 Trigger
124
7.2.2.4 Jet Cleaning
125
7.2.2.5 Muon Cleaning
125
7.3 Preselection Comparisons of Data/MC
126
7.4 Optimizations
127
7.4.1 Analysis Strategy and Background Treatment
130
7.4.2 Optimization Strategy
131
7.4.3 Gtt-0L Optimization
131
7.4.3.1 Signal Regions
134
7.4.3.2 Control Regions
134
7.4.3.3 Validation Regions
134
7.4.3.4 Background Composition
135
7.4.3.5 N-1 Plots
136
7.4.4 Gtt-1L Optimization
136
7.4.4.1 Signal Regions
137
7.4.4.2 Control Regions
139
7.4.4.3 Validation Regions
142
7.4.4.4 Background Composition
143
7.4.4.5 N-1 Plots
143
7.5 Region Definitions for Cut-and-Count Analysis
144
7.6 Semi Data-Driven tbart Normalization
148
7.7 Systematic Uncertainties
149
7.7.1 Experimental Systematic Uncertainties
151
7.7.2 Theoretical Systematic Uncertainties on Background
151
7.7.3 Systematic Uncertainties on the Signal
155
7.7.4 Other Systematic Uncertainties
155
8 Results
156
8.1 General Likelihood
156
8.2 Background-Only Fit
158
8.2.1 Validation
158
8.2.2 Unblinding
159
8.3 Limits
160
8.4 Signal Acceptances and Experimental Efficiencies
165
9 Upgrade Studies
167
9.1 Motivating gFEX
168
9.2 gFEX Algorithms
170
9.2.1 The Reconstruction Algorithm
170
9.2.2 The Offline-Trigger Object Pairing Algorithm
170
9.2.3 Event Displays
171
9.3 Efficiency of Triggers
171
9.4 gFEX Studies
177
9.4.1 Pile-Up Energy Density Calculations
177
9.4.2 Pile-Up Mitigation Studies
181
9.4.2.1 Efficiency of Pile-Up Mitigation Techniques
184
9.4.3 Substructure Studies
186
10 Conclusion
190
A Optimizing Optimizations
192
A.1 Major Dependencies
192
A.2 Top-Level
193
A.2.1 Parameters
193
B xAODAnaHelpers
194
B.1 Background
194
C Ironman: Slow-Control and Monitoring
196
C.1 IPBus
196
C.2 Ironman
196
C.2.1 Server
197
C.2.2 Hardware
199
C.2.3 Jarvis, the Client
200
C.2.4 Internal Communications
200
C.3 Technical Details
201
C.3.1 Dependencies
201
C.4 Code Examples
201
C.4.1 Parse and Build IPBus Packets
201
C.4.2 Implementing IPBus
202
C.4.3 Implementing Jarvis
203
C.5 Implementing Callback Chain
203
D N-1 Plots
205
D.1 0-Lepton
205
D.2 1-Lepton
205
E ttbar Heavy-Flavor Classification/Flavor Contamination
212
E.1 0-Lepton Composition
212
E.2 1-Lepton Composition
212
F Sample List
223
F.1 tbart +Jets
224
F.1.1 Nominal
224
F.1.2 Systematic Samples
224
F.2 Single-Top Samples
225
F.3 tbart +X (X=W,Z,WW,H,tbart)
225
F.4 W+Jets
226
F.5 Z+Jets
228
F.6 Gtt Signal (Off-Shell)
230
F.7 Gtt Signal (On-Shell)
233
F.8 Gbb Signal
237
G Model-Dependent Limits by Region
241
H HEPData Plots
243
Glossary
247
Glossary
247
Bibliography
251
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