Machine Learning for the LHCb Simulation

Most of the computing resources pledged to the LHCb experiment at CERN are necessary to the production of simulated samples used to predict resolution functions on the reconstructed quantities and the reconstruction and selection efficiency. Projecting the Simulation requests to the years following...

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Detalles Bibliográficos
Autor principal: Anderlini, Lucio
Lenguaje:eng
Publicado: 2021
Materias:
physics.ins-det
Detectors and Experimental Techniques
hep-ex
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2789455
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author Anderlini, Lucio
author_facet Anderlini, Lucio
author_sort Anderlini, Lucio
collection CERN
description Most of the computing resources pledged to the LHCb experiment at CERN are necessary to the production of simulated samples used to predict resolution functions on the reconstructed quantities and the reconstruction and selection efficiency. Projecting the Simulation requests to the years following the upcoming LHCb Upgrade, the relative computing resources would exceed the pledges by more than a factor of 2. In this contribution, I discuss how Machine Learning can help to speed up the Detector Simulation for the upcoming Runs of the LHCb experiment.
id cern-2789455
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27894552023-06-29T03:37:23Zhttp://cds.cern.ch/record/2789455engAnderlini, LucioMachine Learning for the LHCb Simulationphysics.ins-detDetectors and Experimental Techniqueshep-exParticle Physics - ExperimentMost of the computing resources pledged to the LHCb experiment at CERN are necessary to the production of simulated samples used to predict resolution functions on the reconstructed quantities and the reconstruction and selection efficiency. Projecting the Simulation requests to the years following the upcoming LHCb Upgrade, the relative computing resources would exceed the pledges by more than a factor of 2. In this contribution, I discuss how Machine Learning can help to speed up the Detector Simulation for the upcoming Runs of the LHCb experiment.arXiv:2110.07925oai:cds.cern.ch:27894552021-10-15
spellingShingle physics.ins-det
Detectors and Experimental Techniques
hep-ex
Particle Physics - Experiment
Anderlini, Lucio
Machine Learning for the LHCb Simulation
title Machine Learning for the LHCb Simulation
title_full Machine Learning for the LHCb Simulation
title_fullStr Machine Learning for the LHCb Simulation
title_full_unstemmed Machine Learning for the LHCb Simulation
title_short Machine Learning for the LHCb Simulation
title_sort machine learning for the lhcb simulation
topic physics.ins-det
Detectors and Experimental Techniques
hep-ex
Particle Physics - Experiment
url http://cds.cern.ch/record/2789455
work_keys_str_mv AT anderlinilucio machinelearningforthelhcbsimulation

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