Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors
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 fin...
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| Autors principals: | , |
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| Format: | Online |
| Idioma: | anglès |
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Springer Nature
2021
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| Accés en línia: | ONIX_20210315_9783030657710_37 |
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| _version_ | 1869528611330981888 |
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| author | Frühwirth, Rudolf Strandlie, Are |
| author_browse | Frühwirth, Rudolf Strandlie, Are |
| author_facet | Frühwirth, Rudolf Strandlie, Are |
| author_sort | Frühwirth, Rudolf |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-64081 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-640812025-03-23T17:17:04Z 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 thema EDItEUR::P Mathematics and Science::PH Physics::PHP Particle and high-energy physics thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDD Scientific standards, measurement etc thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition thema EDItEUR::P Mathematics and 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. 2021-03-18T03:04:52Z 2021-03-18T03:04:52Z 2021-03-15T13:33:06Z 2021 book ONIX_20210315_9783030657710_37 OCN: 1240210729 https://library.oapen.org/handle/20.500.12657/47321 9783030657710 https://directory.doabooks.org/handle/20.500.12854/64081 eng Particle Acceleration and Detection open access image/jpeg image/jpeg image/jpeg Attribution 4.0 International Attribution 4.0 International Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/47321/1/9783030657710.jpg https://library.oapen.org/bitstream/20.500.12657/47321/1/9783030657710.jpg https://library.oapen.org/bitstream/20.500.12657/47321/1/9783030657710.jpg Springer Nature 10.1007/978-3-030-65771-0 10.1007/978-3-030-65771-0 9fa3421d-f917-4153-b9ab-fc337c396b5a Austrian Science Fund 26ae1657-c58f-4f1d-a392-585ee75c293e 9783030657710 Austrian Science Fund (FWF) 203 [grantnumber unknown] open access |
| spellingShingle | 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 thema EDItEUR::P Mathematics and Science::PH Physics::PHP Particle and high-energy physics thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDD Scientific standards, measurement etc thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition thema EDItEUR::P Mathematics and Science::PH Physics::PHU Mathematical physics Frühwirth, Rudolf Strandlie, Are Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors |
| title | Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors |
| title_full | Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors |
| title_fullStr | Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors |
| title_full_unstemmed | Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors |
| title_short | Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors |
| title_sort | pattern recognition tracking and vertex reconstruction in particle detectors |
| topic | 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 thema EDItEUR::P Mathematics and Science::PH Physics::PHP Particle and high-energy physics thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDD Scientific standards, measurement etc thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition thema EDItEUR::P Mathematics and Science::PH Physics::PHU Mathematical physics |
| topic_facet | 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 thema EDItEUR::P Mathematics and Science::PH Physics::PHP Particle and high-energy physics thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDD Scientific standards, measurement etc thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition thema EDItEUR::P Mathematics and Science::PH Physics::PHU Mathematical physics |
| url | ONIX_20210315_9783030657710_37 |
| work_keys_str_mv | AT fruhwirthrudolf patternrecognitiontrackingandvertexreconstructioninparticledetectors AT strandlieare patternrecognitiontrackingandvertexreconstructioninparticledetectors |