博碩士論文 105222028 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:10 、訪客IP:3.239.109.55
姓名 陳勁瑋(Ching-Wei Chen)  查詢紙本館藏   畢業系所 物理學系
論文名稱 從質子質子對撞在質量中心能量 13 兆電子 伏特利用緊湊渺子偵測器尋找重粒子衰變 到一對希格斯粒子於四個底夸克最終態
(Search for Heavy Resonances Decaying into a Pair of Higgs Bosons in the Four b quark Final State from pp Collisions at √s =13 TeV with the CMS Detector)
相關論文
★ 7 TeV 和2.76 TeV 質子對撞下,光子散射截面積的測量★ Search for Pair Production of t*-> t + photon : Estimation of Photon Purity and Study of the Top and W Mass Resolution
★ 以大型強子對撞機裡的緊湊渺子線圈偵測器尋找重夸克在半輕子頻道衰變成頂夸克和光子★ Search for Z′→Zh→llbb in pp Collisions at √s =8 TeV Using the CMS Detector at the LHC
★ Search for heavy resonances decaying into a Z boson and a Higgs boson in the 2l2b final state in pp collisions at √s = 13 TeV★ Study of the b-tagging Scale Factor using the tt ̅ Events from pp collisions at √s =13 TeV with the CMS Detector
★ 在大型強子對撞機的緊湊渺子線圈偵測器,使用13兆電子伏特的質子-質子對撞尋找會衰變到一對希格斯玻色子且最終狀態為四個底夸克的重共振態★ 在緊湊渺子線的質心對撞能量為 13 兆電子伏特的數據裡, 用字母法輔以突起搜尋之方法來尋找類 Z 玻色子衰變為 Z 玻色子及希格斯粒子在衰變為輕子與底垮克
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摘要(中) 論文將呈現尋找重粒子衰變到一對希格斯粒子於四個底夸克最終
態。分析基於大強子對撞機在質量中心能量 13 兆電子伏特利用緊湊
渺子偵測器在 2016 收集的數據,總亮度為 35.9??−1。希格斯粒子是
由正反底夸克對重建而成。希格斯噴流將由其質量、?21與底夸克標
記選定。95% 信心水準利用 CLs 計算生產截面乘以衰變分支上限
介於重粒子的質量從 1.2 兆電子伏特到 3 兆電子伏特低於 10 fb.
摘要(英) A search for heavy resonances decaying to a pair of Higgs bosons in the four b
quark final state is presented. The analysis is based on the data collected in 2016
with the CMS detector at LHC at center-of-mass energy √
s = 13 TeV, corresponding
to integrated luminosity of 35.9 f b−1
. The Higgs bosons are reconstructed
from high momentum b
¯b quark pairs. The mass variable, τ21 discriminator, and
double-b tagger are used for Higgs tagging. The signal regions are separated by
double-b tagger into two categories. A 95% upper limit on the production cross
section of σX × B(X → HH → b
¯bb¯b) is obtained from the combination of two
categories with a limit below 10 fb for mX from 1200 to 3000 GeV
關鍵字(中) ★ 大強子對撞機
★ 希格斯粒子
★ 緊湊 渺子偵測器
關鍵字(英) ★ LHC
★ CMS
★ heavy resonance
★ graviton
★ radion
★ di-Higgs
論文目次 1 Introduction and Theory Overview 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.1 Wraped Extra Dimension . . . . . . . . . . . . . . . . . . . 2
1.2.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Collider and Detector 7
2.1 Large Hadron Collider . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 The Compact Muon Solenoid Detector . . . . . . . . . . . . . . . . 7
2.2.1 Detector Kinematics . . . . . . . . . . . . . . . . . . . . . . 9
2.2.2 Magnet System . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2.3 Tracker Detector . . . . . . . . . . . . . . . . . . . . . . . . 10
Pixel Trackers . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Strip Trackers . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.4 Electromagnetic Calorimeter . . . . . . . . . . . . . . . . . 11
2.2.5 Hadron Calorimeter . . . . . . . . . . . . . . . . . . . . . . 12
2.2.6 Muon Detector . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 The trigger system . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3 Analysis Strategy 15
3.1 Data and Simulated Samples . . . . . . . . . . . . . . . . . . . . . 15
3.2 Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . 15
3.3 Event Reconstruction and Selection . . . . . . . . . . . . . . . . . . 17
3.3.1 Higgs Jet Reconstruction . . . . . . . . . . . . . . . . . . . . 19
3.3.2 Heavy Resonance Seletion . . . . . . . . . . . . . . . . . . . 21
3.3.3 Higgs Tagging Seletion . . . . . . . . . . . . . . . . . . . . . 22
3.4 Triggers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.5 Simulation Distribution . . . . . . . . . . . . . . . . . . . . . . . . 26
3.6 Data and Monte Carlo Comparison . . . . . . . . . . . . . . . . . . 28
4 Background Estimation 37
4.1 Bump Hunt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2 Alphabet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.3 Alphabet Assisted Bump Hunt . . . . . . . . . . . . . . . . . . . . 41
4.3.1 Signal model . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.3.2 Background model . . . . . . . . . . . . . . . . . . . . . . . 42
5 Systematic Uncertainty 45
5.1 Systematic Uncertainty on Signal Selection . . . . . . . . . . . . . 45
5.2 Summary table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
6 Final Result 53
6.1 Asymptotic CLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6.2 95% upper limit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Bibliography 57
A Optimization of the Selection 63
A.1 ∆η . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
A.2 Double-b Tagger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
A.3 Mass of AK8 Jet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
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指導教授 余欣珊(Shin-Shan Eiko Yu) 審核日期 2017-7-20
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