| 書目名稱 | Higgs Boson Decays into a Pair of Bottom Quarks |
| 副標題 | Observation with the |
| 編輯 | Cecilia Tosciri |
| 視頻video | http://file.papertrans.cn/427/426183/426183.mp4 |
| 概述 | Nominated as an outstanding PhD thesis by the University of Oxford, Oxford, United Kingdom.Describes in detail one of the most important searches in ATLAS to validate the Standard Model of particle ph |
| 叢書名稱 | Springer Theses |
| 圖書封面 |  |
| 描述 | The discovery in 2012 of the Higgs boson at the Large Hadron Collider (LHC) represents a milestone for the Standard Model (SM) of particle physics. Most of the SM Higgs production and decay rates have been measured at the LHC with increased precision. However, despite its experimental success, the SM is known to be only an effective manifestation of a more fundamental description of nature. The scientific research at the LHC is strongly focused on extending the SM by searching, directly or indirectly, for indications of New Physics. The extensive physics program requires increasingly advanced computational and algorithmic techniques. In the last decades, Machine Learning (ML) methods have made a prominent appearance in the field of particle physics, and promise to address many challenges faced by the LHC..This thesis presents the analysis that led to the observation of the SM Higgs boson decay into pairs of bottom quarks. The analysis exploits the production of a Higgs boson associated with a vector boson whose signatures enable efficient triggering and powerful background reduction. The main strategy to maximise the signal sensitivity is based on a multivariate approach. The analy |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | Higgs; LHC; Large Hadron Collider; ATLAS Experiment; Bbottom Quarks; Effective Field Theory; EFT; Simplifie |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-87938-9 |
| isbn_softcover | 978-3-030-87940-2 |
| isbn_ebook | 978-3-030-87938-9Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機版|小黑屋|
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