The Search for Supersymmetry in Hadronic Final States Using Boosted Object Reconstruction (eBook)

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