ATLAS Collaboration (Including: Becker, K., Facini, G., Harrison, P. F., Jones, E., Martin, T. A., Morgenstern, S., Murray, W. J., Roberts, B. A., Spangenberg, M. and Vladimirov, V. E.). (2022) AtlFast3 : the next generation of fast simulation in ATLAS. Computing and Software for Big Science, 6 (1). 7. doi:10.1007/s41781-021-00079-7 ISSN 2510-2044.

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Abstract

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. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.

Item Type:	Journal Article
Subjects:	Q Science > QC Physics
Divisions:	Faculty of Science, Engineering and Medicine > Science > Physics
Library of Congress Subject Headings (LCSH):	Particles (Nuclear physics) -- Instruments, Large Hadron Collider (France and Switzerland), Physics -- Data processing, Monte Carlo method, Particles (Nuclear physics) -- Mathematical models
Journal or Publication Title:	Computing and Software for Big Science
Publisher:	Springer International Publishing
ISSN:	2510-2044
Official Date:	December 2022
Dates:	Date Event December 2022 Published 11 March 2022 Available 17 December 2021 Accepted 7 September 2021 Submitted
Volume:	6
Number:	1
Number of Pages:	54
Article Number:	7
DOI:	10.1007/s41781-021-00079-7
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	26 April 2022
Date of first compliant Open Access:	27 April 2022
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Gosudarstvennyĭ komitet po nauke i tekhnologii︠a︡m http://viaf.org/viaf/154732294 UNSPECIFIED Conselho Nacional de Desenvolvimento Científico e Tecnológico http://dx.doi.org/10.13039/501100003593 UNSPECIFIED Fundação de Amparo à Pesquisa do Estado de São Paulo http://dx.doi.org/10.13039/501100001807 UNSPECIFIED [NSERC] Natural Sciences and Engineering Research Council of Canada http://dx.doi.org/10.13039/501100000038 UNSPECIFIED [NRC] National Research Council Canada http://dx.doi.org/10.13039/501100000046 UNSPECIFIED [CFI] Canada Foundation for Innovation http://dx.doi.org/10.13039/501100000196 UNSPECIFIED Agencia Nacional de Investigación y Desarrollo UNSPECIFIED UNSPECIFIED [CAS] Chinese Academy of Sciences http://dx.doi.org/10.13039/501100002367 UNSPECIFIED [MSTPRC] Ministry of Science and Technology of the People's Republic of China http://dx.doi.org/10.13039/501100002855 UNSPECIFIED [NSFC] National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809 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