找尋具有長生命週期新粒子的物理模型所預測的暗物質

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研究生：	陳冠宇 Kuan-Yu Chen
論文名稱：	找尋具有長生命週期新粒子的物理模型所預測的暗物質 Search for dark matter predicted by an extended model with long-lived particles
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：	2023
畢業學年度：	111
語文別：	英文
論文頁數：	90
中文關鍵詞：	長生命週期新粒子、暗物質、緊湊渺子線圈、大型強子對撞機
外文關鍵詞：	long-lived particles, displaced jet
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本篇論文的研究主題為尋找具有長生命週期新粒子的物理模型所預測
的暗物質。在此模型中，一對正反夸克交互作用會產生一個𝑍波色子與 𝑍'波色子，𝑍波色子會衰變成一對正反電子，而 𝑍'波色子會產生一對具有生命週期的新粒子𝛸2，𝛸2會各自衰變成暗物質𝛸1與一對d夸克，並在偵測器中被偵測為displaced噴流。本分析所使用的資料來自大型強子對撞機緊湊緲子線圈偵測器所收集的質子-質子對撞實驗，其質心能量為13TeV，且積分光度為35.9𝑓𝑏−1，為2016 Run II 蒙地卡羅事件。本研究首先利用三維軌跡變數研究不同質量點與生命週期對於噴流變量𝛼3𝐷 的影響，進而進行最佳化的變量篩選，最後使用假訊息率的方法進行背景物理的量測與預估。

A search for dark matter produced in association with mono-Z(ee), predicted by an extended theoretical model. In this model, a pair of interacting quarks produce a Z boson and a Z' boson. The Z boson decays into a pair of electrons channel, while the Z' boson produces a pair of new particles X2 with a lifetime. Each X2 further decays to a stable dark matter \chi_1 and a pair of d quarks are detected as displaced AK4 jets in the detector. The analysis data used in this study were collected from proton-proton collision experiments conducted vat center-of-mass energy √s = 13 TeV, corresponding to an integrated luminosity of 35.9 fb-1, using the CMS detector, specifically the 2016 Run II Monte Carlo events. This study first explores the effects of different mass points and lifetimes on the jet variable alpha_{3D} using three-dimensional track variables, then optimization of the variable selection and using a fake rate method to measure and estimate the background physics.

Introduction and Motivation 1
1 The Standard Model . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 Dark Matter and Dark Matter search at LHC . . . . . . . . . . . . 3
3 Long-lived particles . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
4 MC Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
4.1 Signal MC samples . . . . . . . . . . . . . . . . . . . . . . . 9
4.2 Background MC samples . . . . . . . . . . . . . . . . . . . 9
Experimental Setup 11
1 The Large Hadron Collider . . . . . . . . . . . . . . . . . . . . . . 11
2 The High Luminosity LHC . . . . . . . . . . . . . . . . . . . . . . . 11
3 Compact Muon Solenoid . . . . . . . . . . . . . . . . . . . . . . . . 11
3.1 Magnetic system . . . . . . . . . . . . . . . . . . . . . . . . 13
3.2 Tracker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Silicon Pixels Detector . . . . . . . . . . . . . . . . . . . . . 15
Silicon Strips Detector . . . . . . . . . . . . . . . . . . . . . 16
3.3 Calorimeter . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Electromagnetic Calorimeter . . . . . . . . . . . . . . . . . 18
Hadron Calorimeter . . . . . . . . . . . . . . . . . . . . . . 18
3.4 Muon Detectors . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.5 Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Physics object selection 25
1 Leptonic Selections . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
1.1 Electrons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
1.2 Muons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
1.3 Taus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2 AK4 Jets Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . 28
3 Tracks selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4 Missing transverse momentum . . . . . . . . . . . . . . . . . . . . 32
Displaced Jets variables Reconstruction 35
Background Study 39
1 Signal Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2 Overview of optimization . . . . . . . . . . . . . . . . . . . . . . . 40
2.1 Punzi significance . . . . . . . . . . . . . . . . . . . . . . . 40
2.2 MET cut optimization . . . . . . . . . . . . . . . . . . . . . 40
2.3 Dispaced variable cut optimization . . . . . . . . . . . . . 43
χ3D cut optimization and signal region cut for α3D . . . . . 43
3 Event Selections Summary . . . . . . . . . . . . . . . . . . . . . . . 45
4 Background Estimation . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.1 Fake Rate Method . . . . . . . . . . . . . . . . . . . . . . . 47
4.2 Closure test in MC . . . . . . . . . . . . . . . . . . . . . . . 49
Conclusion and Outlook 53
Appendix 55
1 Original Tracks for Track Variables . . . . . . . . . . . . . . . . . . 55
2 Analysis decision in Dispaced variable cut optimization . . . . . . 56
2.1 The reason for abandoning the use of displaced cut3 . . . 56
2.2 Compare α3D in different background processes . . . . . . 57
3 Additional research on background study . . . . . . . . . . . . . . 57
3.1 Compare α3D in different flavor in Top process . . . . . . . 57
3.2 Detailed study on fake rate . . . . . . . . . . . . . . . . . . 59
Comparison of fake rates between Top to eµ and Top to ee
process . . . . . . . . . . . . . . . . . . . . . . . . 59
Detailed comparison between the fake rate measurement
in Drell-Yan and Top to eµ process . . . . . . . . 59
3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Bibliography 63
                                

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