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標題: | 研究 2018 Test Beam 中 HGCAL (高粒度量能器)能量重建之能力表現 CMS HGCAL prototype EM Energy Reconstruction Performance in a 2018 Test Beam |
作者: | Jyun-Wei Su 蘇俊瑋 |
指導教授: | 裴斯達(Stathes Paganis) |
關鍵字: | 粒子物理,高能物理,量能器,偵測器,能量重建, Particle physics,High energy physics,Calorimeter,Detector,Energy reconstruction, |
出版年 : | 2020 |
學位: | 碩士 |
摘要: | 世界上最大且能量最高的粒子加速器-大強子對撞機(LHC),正準備進入「高亮度」(High Luminosity)的時代。在下一個階段的運行過程中,LHC會產生10倍於前階段的累積亮度(integrated luminosity),其中的偵測器將會面臨兩個重大挑戰:輻射損傷以及碰撞點產生的事件數上升導致對單一事件的分析產生困難。高粒度量能器(HGCAL)作為緊湊渺子線圈實驗(CMS)的其中一項升級,高粒度量能器將會取代現有量能器兩端電磁量能器及強子量能器的部分。電磁量能器與大部分的強子量能器會採用0.5∼1平方公分大小的矽感應器,矽感應器精確的時間測量能力可以幫助分辨出短時間內產生的大量事件。本論文將以2018的粒子測試資料為主,研究2018模組的非均一性(non-uniformity)以及資料與蒙地卡羅模擬(Monte Carlo)之間是否存在差異性(非均一性)。本論文中我們測得在真實數據中的固定項(constant term)為0.82±0.14%而隨機項(stochastic term)為22.59±0.72%;而Monte Carlo中則分別為0.86±0.01%及22.91±0.07%。由此我們可以推論出真實數據和Monte Carlo有高度的一致性。我們也在真實數據和Monte Carlo中分別看到0.89±0.08%和0.61±0.05%的非均一性,兩者存在約0.65±0.06%的差異性。 The LHC, which is the largest and highest energy particle accelerator in the world, is preparing to step into the new era of high luminosity.The LHC will generate 10 times more integrated luminosity than now. Thus, the detectors in the LHC are going to face two big challenges: the radiation damage and the difficulty in analysis causes by event pileup. The High-Granularity Calorimeter technology is one of many upgrades of the CMS in phase-2 upgrading program, it will replace the existing endcap calorimeters, including the electromagnetic and hadronic sections. The EM calorimeters and a large proportion of hadronic calorimeter will use silicon sensors of 0.5∼1cm^2 which have high accuracy of timing capacity that is helpful to pile up rejection.This thesis is based on the test beam data in 2018. The main interest for the future HGCAL operation at LHC is in maintaining a low C-term below 1%. Energy non-uniformity effects impact directly the C-term and the information provided in this Thesis gives a first glimpse on the magnitude of these effects. In this thesis we found a constant term and stochastic term of 0.82±0.14%, 22.59±0.72% for data and 0.86±0.01%, 22.91±0.07% for Monte-Carlo (MC) respectively. The MC is in a good agreement with data. We also found a non-uniformity 0.89±0.08% for data and 0.61±0.05% for MC, which corresponds to a 0.65±0.06% mismatch between data and MC. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8138 |
DOI: | 10.6342/NTU202003921 |
全文授權: | 同意授權(全球公開) |
顯示於系所單位: | 物理學系 |
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U0001-1808202006262000.pdf | 29.9 MB | Adobe PDF | 檢視/開啟 |
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