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Software Performance of the ATLAS Track Reconstruction for LHC Run 3

  • Faculty of Physics
  • University of Bucharest
  • iThemba Labs
  • Department of Physics
  • University of South Africa
  • University of Zululand
  • Cadi Ayyad University
  • New York University Abu Dhabi
  • Departamento de Física Teórica y del Cosmos
  • University of Granada
  • CERN
  • Aix-Marseille Université
  • University of Oklahoma
  • University of Göttingen
  • TU Dortmund University
  • United States Department of Energy
  • Mohammed V University in Rabat
  • Tel Aviv University
  • Technion-Israel Institute of Technology
  • New York University
  • National Institute for Nuclear Physics
  • Abdus Salam International Centre for Theoretical Physics
  • Stanford University
  • Université Savoie Mont Blanc
  • AGH University of Krakow
  • University of Toronto
  • Brandeis University
  • University of Manchester
  • Northern Illinois University
  • Istanbul University
  • Rutherford Appleton Laboratory
  • University of California at Santa Cruz
  • Institute for High Energy Physics
  • University of Pavia
  • Johannes Gutenberg University Mainz
  • Alexandru Ioan Cuza University of Iaşi
  • Ilia State University
  • McGill University
  • Royal Holloway University of London
  • University of Science and Technology of China
  • University of Rome Tor Vergata
  • University of Valencia
  • University of Hassan II Casablanca
  • Weizmann Institute of Science
  • Lund University
  • Waseda University
  • University of Bonn
  • Columbia University
  • University of Victoria BC
  • Université Grenoble Alpes
  • University of Edinburgh

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.

Original languageEnglish
Article number9
JournalComputing and Software for Big Science
Volume8
Issue number1
DOIs
StatePublished - Dec 2024

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