Software Performance of the ATLAS Track Reconstruction for LHC Run 3
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
- Chair of Experimental Particle Physics
- Chair of Particle Physics
- Institute of Nuclear and Particle Physics
- Aix-Marseille Université
- University of Oklahoma
- University of Göttingen
- Dortmund University of Technology
- Mohammed V University in Rabat
- Tel Aviv University
- Technion-Israel Institute of Technology
- New York University
- Stanford University
- Laboratoire d'Annecy-le-Vieux de Physique des Particules LAPP
- AGH University of Science and Technology
- 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 (USTC)
- University of Rome Tor Vergata
- University of Valencia
- University of Hassan II Casablanca
- Weizmann Institute of Science
- TUD Dresden University of Technology
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.
Details
Original language | English |
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Article number | 9 |
Journal | Computing and Software for Big Science |
Volume | 8 |
Issue number | 1 |
Publication status | Published - Dec 2024 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0001-6480-6079/work/173049551 |
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ORCID | /0000-0003-0546-1634/work/173516667 |