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dc.contributor.authorFrühwirth, Rudolf
dc.contributor.authorStrandlie, Are
dc.date.accessioned2021-03-18T03:04:52Z
dc.date.available2021-03-18T03:04:52Z
dc.date.issued2021
dc.date.submitted2021-03-15T13:33:06Z
dc.identifierONIX_20210315_9783030657710_37
dc.identifierhttps://library.oapen.org/handle/20.500.12657/47321
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/64081
dc.description.abstractThis 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.
dc.languageEnglish
dc.relation.ispartofseriesParticle Acceleration and Detection
dc.rightsopen access
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PH Physics::PHP Particle and high-energy physicsen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PD Science: general issues::PDD Scientific standards, measurement etcen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognitionen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PH Physics::PHU Mathematical physicsen_US
dc.subject.otherParticle Acceleration and Detection, Beam Physics
dc.subject.otherMeasurement Science and Instrumentation
dc.subject.otherPattern Recognition
dc.subject.otherNumerical and Computational Physics, Simulation
dc.subject.otherAccelerator Physics
dc.subject.otherAutomated Pattern Recognition
dc.subject.otherTheoretical, Mathematical and Computational Physics
dc.subject.otherEvent reconstruction
dc.subject.otherTracking detectors in High Energy Physics
dc.subject.otherVertex reconstruction
dc.subject.otherClustering algorithms
dc.subject.otherExperimental High-Energy Physics
dc.subject.otherLHC
dc.subject.otherCalolimator for pattern recognition
dc.subject.otherVertex of particle collision
dc.subject.otherTriggering event and data analysis
dc.subject.otherOpen access
dc.subject.otherParticle & high-energy physics
dc.subject.otherScientific standards, measurement etc
dc.subject.otherMathematical physics
dc.titlePattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors
dc.typebook
oapen.identifier.doi10.1007/978-3-030-65771-0
oapen.relation.isPublishedBy9fa3421d-f917-4153-b9ab-fc337c396b5a
oapen.relation.isFundedBya39fc2ba-9538-4bcd-965c-6702ff320840
oapen.relation.isFundedBy26ae1657-c58f-4f1d-a392-585ee75c293e
oapen.relation.isbn9783030657710
oapen.collectionAustrian Science Fund (FWF)
oapen.pages203
oapen.grant.number[grantnumber unknown]
dc.relationisFundedBy26ae1657-c58f-4f1d-a392-585ee75c293e


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