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oapen-20.500.12657-473212021-03-17T02:09:33Z Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors Frühwirth, Rudolf Strandlie, Are Particle Acceleration and Detection, Beam Physics Measurement Science and Instrumentation Pattern Recognition Numerical and Computational Physics, Simulation Accelerator Physics Automated Pattern Recognition Theoretical, Mathematical and Computational Physics Event reconstruction Tracking detectors in High Energy Physics Vertex reconstruction Clustering algorithms Experimental High-Energy Physics LHC Calolimator for pattern recognition Vertex of particle collision Triggering event and data analysis Open access Particle & high-energy physics Scientific standards, measurement etc Mathematical physics bic Book Industry Communication::P Mathematics & science::PH Physics::PHP Particle & high-energy physics bic Book Industry Communication::P Mathematics & science::PD Science: general issues::PDD Scientific standards::PDDM Mensuration & systems of measurement bic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition bic Book Industry Communication::P Mathematics & science::PH Physics::PHU Mathematical physics 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. 2021-03-15T13:33:06Z 2021-03-15T13:33:06Z 2021 book ONIX_20210315_9783030657710_37 9783030657710 https://library.oapen.org/handle/20.500.12657/47321 eng Particle Acceleration and Detection application/pdf Attribution 4.0 International 9783030657710.jpg https://www.springer.com/9783030657710 Springer Nature 10.1007/978-3-030-65771-0 10.1007/978-3-030-65771-0 6c6992af-b843-4f46-859c-f6e9998e40d5 26ae1657-c58f-4f1d-a392-585ee75c293e 9783030657710 Austrian Science Fund (FWF) 203 [grantnumber unknown] Austrian Science Fund Fonds zur Förderung der Wissenschaftlichen Forschung open access
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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.
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