在與希格斯玻色子有關聯的暗物質搜索中去測量深度雙底夸克標記校正因子的誤判率

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研究生：	菲莎 Fasya Khuzaimah
論文名稱：	在與希格斯玻色子有關聯的暗物質搜索中去測量深度雙底夸克標記校正因子的誤判率 Measurement of Mistagging Scale Factor of the Deep Double b-Tagger in the Search for Dark Matter in Association with a Higgs Boson
指導教授：	余欣珊 Shin-Shan Yu
口試委員:
學位類別：	碩士 Master
系所名稱：	理學院 - 物理學系 Department of Physics
論文出版年：	2021
畢業學年度：	109
語文別：	英文
論文頁數：	101
中文關鍵詞：	暗物質、希格斯玻色子、夸克、緊湊緲子線圈、大型強子對撞機、誤判率
外文關鍵詞：	Dark matter, Higgs Boson, Quark, Compact Muon Solenoid, Large Hadron Collider, Mistagging scale factor
相關次數：	點閱：7 下載：0
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超過26％的宇宙總能量密度來自暗物質的貢獻。然而，暗物質的性質仍是未知的並且無法用當前理論解釋。藉由來自緊湊緲子線圈質心能量為13兆電子伏特且41.5 fb^-1 總亮度的質子-質子碰撞數據，搜索暗物質與一個會衰減成一對底夸克的希格斯玻色子生成的成果將會被呈現。信號事件被標記為巨大的遺失橫向動量且正對著一對底夸克。然而，許多背景事件可以模仿真實信號並通過信號甄選。藉由比較模擬跟真實數據中背景事件通過底夸克標記甄選的比例，可以測量來自被判定為信號事件的背景事件的機率的校正因子。以此計算統計和系統不確定度的校正因子。

More than 26% of the total energy density of the universe is composed of dark matter (DM). However, the properties of DM are still unknown and cannot be explained with the present information. A search for the DM produced in the presence of a Higgs boson decaying into a pair of bottom quarks is performed using proton-proton collision data collected at a center-of-mass energy of 13 TeV by CMS corresponding to an integrated luminosity of 41.5 fb^-1. The signal events are identified as a large missing transverse momentum recoiling against a pair of bottom quarks. However, many backgrounds can mimic this real signal and pass the signal selection. A scale factor of the possibility in detecting background events as signal events is measured by comparing the efficiency of background events passing b-tagging selection in the data and the simulation. Both statistical and systematic uncertainties on the scale factors are obtained.

Introduction and Theory Overview 1
1 IntroductionandMotivation...................... 1
2 Theory .................................. 3
2.1 StandardModelParticles ................... 3
2.2 2HDMPlusPseudoscalaraExtensions . . . . . . . . . . . 4
2.2.1 TwoHiggsDoubletsModel ............ 5
2.2.2 Type-IITwoHiggsDoubletsModel........ 7
2.2.3 Type-II2HDM+a................... 9
2.2.4 Alignment/DecouplingLimit........... 10
2.2.5 HeavyPseudoscalarA ............... 10
2.2.6 LightPseudoscalara ................ 12
Experimental Apparatus: the LHC and the CMS Detector 15
1 LargeHadronCollider ......................... 15
2 CompactMuonSolenoid........................ 16
2.1 CMSCoordinateSystem.................... 16
2.2 SuperconductingMagnetSystem............... 17
2.3 InnerTrackingDetector .................... 18
2.3.1 PixelTracker ..................... 19
2.3.2 SiliconStripTracker................. 21
2.4 ElectromagneticCalorimeter ................. 23
2.5 HadronCalorimeter ...................... 24
2.6 MuonDetector ......................... 25
2.7 TriggerSystem ......................... 27
2.7.1 Level1TriggerSystem ............... 28
2.7.2 HighLevelTriggerSystem............. 28
Event Reconstruction 31
1 PrimaryVertexReconstruction .................... 31
2 Particle-FlowAlgorithm ........................ 32
3 PileupReconstruction ......................... 33
3.1 PUPPIAlgorithm........................ 33
3.2 CHSAlgorithm......................... 35
4 pTmiss Reconstruction............................ 35
5 JetsReconstructionandHiggsTagging. . . . . . . . . . . . . . . . 36
6 LeptonIdentification .......................... 38
7 EventSelection ............................. 39
Analysis Strategy 41
1 DataSetsandMonteCarloSamples ................. 42
1.1 DataSets............................. 42
1.2 MonteCarloSamples ..................... 42
2 Selection ................................. 43
2.1 DeepDoubleb-Tagger..................... 43
2.2 SignalSelection......................... 45
3 DataandMonteCarloComparison.................. 46
4 BackgroundEstimation......................... 48
Results, Systematic Uncertainty, and Discussion 53
1 Mistagging Scale Factor of the Deep Double b-Tagger . . . . . . . 53
2 SystematicUncertainty......................... 55
2.1 IntegratedLuminosity..................... 55
2.2 The Cross Sections of the Monte Carlo Samples . . . . . . 55
3 FinalResultsandDiscussion...................... 57
Conclusion and Outlook 63
1 Conclusion................................ 63
2 Outlook.................................. 63
Bibliography 65
A 73
A.1 DeepDoubleb-TaggerOptimization................. 73
                                

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