0565793 - FZÚ 2023 RIV CH eng J - Journal Article
Aad, G. - Abbott, B. - Abbott, D.C. - Chudoba, Jiří - Hejbal, Jiří - Hladík, Ondřej - Jačka, Petr - Kepka, Oldřich - Kroll, Jiří - Kupčo, Alexander - Latoňová, Věra - Lokajíček, Miloš - Lysák, Roman - Marčišovský, Michal - Mikeštíková, Marcela - Němeček, Stanislav - Penc, Ondřej - Šícho, Petr - Staroba, Pavel - Svatoš, Michal - Taševský, Marek … Total 2914 authors
AtlFast3: The next generation of fast simulation in ATLAS.
Computing and Software for Big Science. Roč. 6, č. 1 (2022), č. článku 7. ISSN 2510-2036. E-ISSN 2510-2044
R&D Projects: GA MŠMT(CZ) LM2018104
Research Infrastructure: e-INFRA CZ - 90140
Institutional support: RVO:68378271
Keywords : GEANT * new particle * new interaction * CERN LHC Coll
OECD category: Particles and field physics
Method of publishing: Open access
DOI: https://doi.org/10.1007/s41781-021-00079-7

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with GEANT4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation -- the calorimeter shower simulation -- with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges and simulation needs of the ATLAS experiment.
Permanent Link: https://hdl.handle.net/11104/0339334