Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialConference paper

Optimizing the throughput of the ATLAS Geant4 detector simulation

Benjamin J. Morgan, John Apostolakis, Marilena Bandieramonte, J. D. Chapman, Michael Duehrssen-Debling, Julien Esseiva, W. H. Hopkins, D. W. Kim, J. Schaarschmidt, C. Marcon, Nitika Nitika, Mihály Novák, M. A. Schmidt, E. Tcherniaev, Rui Zhang

EPJ Web of Conferences · 2025

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Summary

This technical paper documents physics and computational enhancements implemented in the ATLAS experiment's Geant4-based Monte Carlo detector simulation for Run 3 operations. The optimisations—spanning physics developments (range cuts, variance reduction techniques, Woodcock Tracking) and technical refinements (geometric optimisation, magnetic field switching, static linking, Link-Time Optimization)—collectively achieved a two-fold increase in simulation throughput relative to Run 2. The authors indicate further optimisation efforts remain under active development.

UK applicability

This paper is not applicable to UK farming systems, soil health, or nutritional research. It concerns particle physics infrastructure at an international research facility.

Key measures

Simulation throughput (factor increase); computational efficiency metrics; processing time per event

Outcomes reported

The study reported computational performance improvements to the ATLAS Geant4-based Monte Carlo detector simulation for Run 3 at CERN's Large Hadron Collider. Key outcome was a doubling of simulation throughput compared to Run 2 baseline configuration through physics and technical optimisations.

Theme
General food systems / other
Subject
Other / interdisciplinary
Study type
Research
Study design
Technical development report
Source type
Conference paper
Status
Published
System type
Other
DOI
10.1051/epjconf/202533701351
Catalogue ID
BFmokb3kqi-zdj5oa

Topic tags

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