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Deep generative models for fast photon shower simulation in ATLAS
- 1.0616540 - FZÚ 2025 RIV CH eng J - Článek v odborném periodiku
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 … celkem 2858 autorů
Deep generative models for fast photon shower simulation in ATLAS.
Computing and Software for Big Science. Roč. 8, č. 1 (2024), č. článku 7. ISSN 2510-2036. E-ISSN 2510-2044
Výzkumná infrastruktura: CERN-CZ III - 90240
Institucionální podpora: RVO:68378271
Klíčová slova: ATLAS * photon: particle identification * network
Obor OECD: Particles and field physics
Způsob publikování: Open access
DOI: https://doi.org/10.1007/s41781-023-00106-9
The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.
Trvalý link: https://hdl.handle.net/11104/0363523Název souboru Staženo Velikost Komentář Verze Přístup 0616540.pdf 1 10 MB CC Licence Vydavatelský postprint povolen
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