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Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events

  • ATLAS Collaboration
  • University of Lisbon
  • CERN
  • Aix-Marseille Université
  • University of Oklahoma
  • University of Massachusetts
  • University of Göttingen
  • Royal Holloway University of London
  • United States Department of Energy
  • University of Copenhagen
  • University of Sussex
  • Tel Aviv University
  • Technion-Israel Institute of Technology
  • Argonne National Laboratory
  • Pontificia Universidad Católica de Chile
  • National Institute for Nuclear Physics
  • Abdus Salam International Centre for Theoretical Physics
  • King's College London
  • Johannes Gutenberg University Mainz
  • Université Savoie Mont Blanc
  • AGH University of Krakow
  • University of Toronto
  • Northern Illinois University
  • Bogazici University
  • Istanbul University
  • University of Geneva
  • Rutherford Appleton Laboratory
  • University of California at Santa Cruz
  • Université Paris-Saclay
  • Université Clermont Auvergne
  • Radboud University Nijmegen
  • Alexandru Ioan Cuza University of Iaşi
  • Laboratório de Instrumentação e Física Experimental de Partículas
  • University of Granada
  • IFT-UAM/CSIC
  • Joint Institute for Nuclear Research
  • McGill University
  • German Electron Synchrotron
  • University of Rome Tor Vergata
  • Kyoto University
  • Lund University
  • P.N. Lebedev Physical Institute of the Russian Academy of Sciences
  • Columbia University
  • University of Bologna
  • University of Victoria BC

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.

Original languageEnglish
Article number3
JournalComputing and Software for Big Science
Volume6
Issue number1
DOIs
StatePublished - Dec 2022

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