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Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report

Monte Carlo (MC) transport simulations often require a significant amount of computing resources due to the detailed physics simulations. There are various physics models and thousands of particles are transported through, in the particular case of this report, a complex geometry resembling the ALIC...

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Autor principal: Swain, Anthony
Lenguaje:eng
Publicado: 2023
Materias:
Acceso en línea:http://cds.cern.ch/record/2872075
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author Swain, Anthony
author_facet Swain, Anthony
author_sort Swain, Anthony
collection CERN
description Monte Carlo (MC) transport simulations often require a significant amount of computing resources due to the detailed physics simulations. There are various physics models and thousands of particles are transported through, in the particular case of this report, a complex geometry resembling the ALICE detector. This report outlines the development and use of automatic optimisation procedures using a geometric approach to reduce the number of relatively computationally heavy MC steps whilst removing a negligible number of hits in GEANT4. The approach was able to reduce the number of steps by roughly 8-9% whilst removing <1% of hits in any detector in the main barrel region of ALICE. Further study should be conducted, using the developed framework, to look at the absorber materials inside the detector. Alternative methods should be explored to optimise the region including the ZDC detectors.
id cern-2872075
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2023
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spelling cern-28720752023-09-22T21:46:05Zhttp://cds.cern.ch/record/2872075engSwain, AnthonyGeometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student ReportParticle Physics - ExperimentComputing and ComputersMonte Carlo (MC) transport simulations often require a significant amount of computing resources due to the detailed physics simulations. There are various physics models and thousands of particles are transported through, in the particular case of this report, a complex geometry resembling the ALICE detector. This report outlines the development and use of automatic optimisation procedures using a geometric approach to reduce the number of relatively computationally heavy MC steps whilst removing a negligible number of hits in GEANT4. The approach was able to reduce the number of steps by roughly 8-9% whilst removing <1% of hits in any detector in the main barrel region of ALICE. Further study should be conducted, using the developed framework, to look at the absorber materials inside the detector. Alternative methods should be explored to optimise the region including the ZDC detectors.CERN-STUDENTS-Note-2023-164oai:cds.cern.ch:28720752023-09-22
spellingShingle Particle Physics - Experiment
Computing and Computers
Swain, Anthony
Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report
title Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report
title_full Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report
title_fullStr Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report
title_full_unstemmed Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report
title_short Geometric Hyperparameter Optimisation of ALICE Monte Carlo Transport Simulations - Summer Student Report
title_sort geometric hyperparameter optimisation of alice monte carlo transport simulations - summer student report
topic Particle Physics - Experiment
Computing and Computers
url http://cds.cern.ch/record/2872075
work_keys_str_mv AT swainanthony geometrichyperparameteroptimisationofalicemontecarlotransportsimulationssummerstudentreport