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研究生： 黃寘耕
Ji-Kong Huang
論文名稱： Study of the b-tagging Scale Factor using the tt ̅ Events from pp collisions at √s =13 TeV with the CMS Detector
指導教授： 余欣珊
Shin-Shan Eiko 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： 2017
畢業學年度： 105
語文別： 英文
論文頁數： 74
中文關鍵詞： 高能物理 、b夸克 、緊湊緲子線圈 、b標記演算法
相關次數： 點閱：8  下載：0 
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    • 源於b夸克所產生的粒子流(稱為b粒子流)，在新物理的研究與探索過程中扮演著不可或缺的角色。其出現於許多重要的物理過程中，分析家使用所謂的「b標記演算法」來辨識之。本研究所選用的樣本，富含 tt ̅ 粒子的半輕子衰變事件，接著比較模擬事件與所觀察到的數據中幾項與粒子運動有關的變數分布，並使用FTC方法估算b標記演算法的效率與誤判率。本研究所採用的數據，來自於2015年質子對的對撞，其對撞總能量為13TeV，總亮度為2.1 fb-1.

    The jets originated from b quark (b-jets) play a significant role in new physics researches. They show up in many important physical processes and we use the so-called b-tagging algorithm to identify them. This study select a sample enriched with tt ̅ semileptonically decayed events and compare various kinematic distributions in Monte Carlo simulation sample and the data, further use the FTC method to calculate the b-tagging scale factor and mis-tag rates. The data used in this study were recorded in 2015 from pp collisions at s = 13TeV and correspond to an integrated luminosity of 2.1 fb-1.

    Chapter 1 Introduction and Standard Model 1 1.1 Introduction 1 1.2 The Standard Model 1 1.2.1 Elementary fermions 2 1.2.2 Elementary bosons and fundamental forces 4 Chapter 2 The LHC and CMS detector 6 2.1 Large Hadron Collider 6 2.2 Compact Muon Solenoid 8 2.2.1 the coordinate system of CMS 9 2.2.2 The Silicon Tracker 9 2.2.3 The Electromagnetic Calorimeter 11 2.2.4 The Hadronic Calorimeter 13 2.2.5 The Magnet system 14 2.2.6 The Muon Chamber 14 2.3 The Trigger System 16 2.3.1 Level 1 Trigger 16 2.3.2 High Level Trigger 17 Chapter 3 Event Reconstruction 18 3.1 Physic Particles Reconstruction 18 3.1.1 Track reconstruction 19 3.1.2 Electron reconstruction 21 3.1.3 Muon reconstruction 23 3.1.4 Jet reconstruction 25 3.1.5 Reconstruction of missing transverse momentum 29 3.2 Primary vertex Reconstruction 29 Chapter 4 The b-tagging algorithm and the FTC Method 31 4.1 B-tagging algorithm 31 4.1.1 Track selection and secondary vertex reconstruction 32 4.1.2 The combined secondary vertex algorithm 35 4.2 performance of b-tagging algorithm 37 4.3 The flavor tag consistency method 39 Chapter 5 The Analysis and Results 41 5.1 The Monte Carlo simulation and data sample 41 5.1.1 The Monte Carlo sample 41 5.1.2 The data sample 45 5.2 tt semileptonic event selection 45 5.2.2 Jet selection 46 5.2.3 Event selection 47 5.3 data and MC comparison 49 5.4 Scale factor of B-tagging efficiency and mis-tag rate 56 5.5 Systematic uncertainties 58 5.5.1 Sources of systematic uncertainties on MC 58 5.5.2 Sources of systematic uncertainties on data 60 Chapter 6 Conclusion and outlook 61 6.1 Conclusion 61 6.2 Outlook 61 Bibliography 62

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