Machine Learning for Muon Identifcation at LHCb

Particle identifcation is a key ingredient of most of LHCb results. Muon identifcation in particular is used at every stage of the LHCb trigger. The objective of the muon identifcation is to distinguish muons from charged hadrons under strict timing constraints. For this task, we use a state-of-the-...

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Detalles Bibliográficos
Autor principal: Kazeev, N
Lenguaje:eng
Publicado: 2020
Materias:
Computing and Computers
Detectors and Experimental Techniques
Particle Physics - Experiment
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/1525/1/012100
http://cds.cern.ch/record/2779640
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author Kazeev, N
author_facet Kazeev, N
author_sort Kazeev, N
collection CERN
description Particle identifcation is a key ingredient of most of LHCb results. Muon identifcation in particular is used at every stage of the LHCb trigger. The objective of the muon identifcation is to distinguish muons from charged hadrons under strict timing constraints. For this task, we use a state-of-the-art gradient boosting algorithm trained with real background-subtracted data. In this proceedings we present the algorithm along with the evaluation of its performance on signal and background rejection.
id cern-2779640
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2020
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spelling cern-27796402021-09-07T07:49:56Zdoi:10.1088/1742-6596/1525/1/012100http://cds.cern.ch/record/2779640engKazeev, NMachine Learning for Muon Identifcation at LHCbComputing and ComputersDetectors and Experimental TechniquesParticle Physics - ExperimentParticle identifcation is a key ingredient of most of LHCb results. Muon identifcation in particular is used at every stage of the LHCb trigger. The objective of the muon identifcation is to distinguish muons from charged hadrons under strict timing constraints. For this task, we use a state-of-the-art gradient boosting algorithm trained with real background-subtracted data. In this proceedings we present the algorithm along with the evaluation of its performance on signal and background rejection.oai:cds.cern.ch:27796402020
spellingShingle Computing and Computers
Detectors and Experimental Techniques
Particle Physics - Experiment
Kazeev, N
Machine Learning for Muon Identifcation at LHCb
title Machine Learning for Muon Identifcation at LHCb
title_full Machine Learning for Muon Identifcation at LHCb
title_fullStr Machine Learning for Muon Identifcation at LHCb
title_full_unstemmed Machine Learning for Muon Identifcation at LHCb
title_short Machine Learning for Muon Identifcation at LHCb
title_sort machine learning for muon identifcation at lhcb
topic Computing and Computers
Detectors and Experimental Techniques
Particle Physics - Experiment
url https://dx.doi.org/10.1088/1742-6596/1525/1/012100
http://cds.cern.ch/record/2779640
work_keys_str_mv AT kazeevn machinelearningformuonidentifcationatlhcb

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