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Titlebook: Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors; Rudolf Frühwirth,Are Strandlie Book‘‘‘‘‘‘‘‘ 2021 The Editor

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書目名稱Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors
編輯Rudolf Frühwirth,Are Strandlie
視頻videohttp://file.papertrans.cn/743/742687/742687.mp4
概述Points to existing re-usable software.Provides numerous examples from running and planned experiments.Includes a comprehensive and up-to-date list of references for self-study.Features state-of-the ar
叢書名稱Particle Acceleration and Detection
圖書封面Titlebook: Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors;  Rudolf Frühwirth,Are Strandlie Book‘‘‘‘‘‘‘‘ 2021 The Editor
描述.This open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments.? ??.
出版日期Book‘‘‘‘‘‘‘‘ 2021
關(guān)鍵詞Event reconstruction; Tracking detectors in High Energy Physics; Vertex reconstruction; Clustering algo
版次1
doihttps://doi.org/10.1007/978-3-030-65771-0
isbn_softcover978-3-030-65773-4
isbn_ebook978-3-030-65771-0Series ISSN 1611-1052 Series E-ISSN 2365-0877
issn_series 1611-1052
copyrightThe Editor(s) (if applicable) and The Author(s) 2021
The information of publication is updating

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