AtlFast3: The Next Generation of Fast Simulation in ATLAS
Authors
Camelia, EA
Amelung, C
Amrouche, CS
Publication Date
2022-12Journal Title
Computing and Software for Big Science
ISSN
2510-2036
Publisher
Springer Science and Business Media LLC
Volume
6
Issue
1
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Aad, G., Abbott, B., Abbott, D., Abud, A., Abeling, K., Abhayasinghe, D., Abidi, S., et al. (2022). AtlFast3: The Next Generation of Fast Simulation in ATLAS. Computing and Software for Big Science, 6 (1) https://doi.org/10.1007/s41781-021-00079-7
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 a new ability to model substructure within jets,
AtlFast3 is designed to be used to simulate large numbers of events for a wide
range of physics processes.
Keywords
Original Article, Innovation in HEP software and computing for the challenges of the next decade
Identifiers
s41781-021-00079-7, 79
External DOI: https://doi.org/10.1007/s41781-021-00079-7
This record's URL: https://www.repository.cam.ac.uk/handle/1810/335574
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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