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I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements

<!--HTML-->Detector simulation at the LHC is one of the most computing intensive activities. In these lectures we will show how physics requirements were met for the LHC experiments and extrapolate to future experiments (FCC-hh case). At the LHC, detectors are complex, very precise and ambiti...

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Autor principal: CAIRO, Valentina
Lenguaje:eng
Publicado: 2016
Materias:
Acceso en línea:http://cds.cern.ch/record/2135811
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author CAIRO, Valentina
author_facet CAIRO, Valentina
author_sort CAIRO, Valentina
collection CERN
description <!--HTML-->Detector simulation at the LHC is one of the most computing intensive activities. In these lectures we will show how physics requirements were met for the LHC experiments and extrapolate to future experiments (FCC-hh case). At the LHC, detectors are complex, very precise and ambitious: this implies modern modelisation tools for geometry and response. Events are busy and characterised by an unprecedented energy scale with hundreds of particles to be traced and high energy showers to be accurately simulated. Furthermore, high luminosities imply many events in a bunch crossing and many bunch crossings to be considered at the same time. In addition, backgrounds not directly correlated to bunch crossings have also to be taken into account. Solutions chosen for ATLAS (a mixture of detailed simulation and fast simulation/parameterisation) will be described and CPU and memory figures will be given. An extrapolation to the FCC-hh case will be tried by taking as example the calorimeter simulation.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2016
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spelling cern-21358112022-11-02T22:32:26Zhttp://cds.cern.ch/record/2135811engCAIRO, ValentinaI - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirementsinverted CERN School of Computing 2016inverted CSC<!--HTML-->Detector simulation at the LHC is one of the most computing intensive activities. In these lectures we will show how physics requirements were met for the LHC experiments and extrapolate to future experiments (FCC-hh case). At the LHC, detectors are complex, very precise and ambitious: this implies modern modelisation tools for geometry and response. Events are busy and characterised by an unprecedented energy scale with hundreds of particles to be traced and high energy showers to be accurately simulated. Furthermore, high luminosities imply many events in a bunch crossing and many bunch crossings to be considered at the same time. In addition, backgrounds not directly correlated to bunch crossings have also to be taken into account. Solutions chosen for ATLAS (a mixture of detailed simulation and fast simulation/parameterisation) will be described and CPU and memory figures will be given. An extrapolation to the FCC-hh case will be tried by taking as example the calorimeter simulation.oai:cds.cern.ch:21358112016
spellingShingle inverted CSC
CAIRO, Valentina
I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements
title I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements
title_full I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements
title_fullStr I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements
title_full_unstemmed I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements
title_short I - Detector Simulation for the LHC and beyond: how to match computing resources and physics requirements
title_sort i - detector simulation for the lhc and beyond: how to match computing resources and physics requirements
topic inverted CSC
url http://cds.cern.ch/record/2135811
work_keys_str_mv AT cairovalentina idetectorsimulationforthelhcandbeyondhowtomatchcomputingresourcesandphysicsrequirements
AT cairovalentina invertedcernschoolofcomputing2016