AtlFast3: The Next Generation of Fast Simulation in ATLAS

ATLAS Collaboration

doi:10.1007/s41781-021-00079-7

AtlFast3: The Next Generation of Fast Simulation in ATLAS

ATLAS Collaboration

Application and Research Center for Advanced Studies
Istanbul Aydin University
iThemba Labs
Department of Physics
University of South Africa
Cadi Ayyad University
Mohammed VI Polytechnic University
New York University Abu Dhabi
United Arab Emirates University
University of Sharjah
Universidad de La Serena
CERN
Aix-Marseille Université
University of Oklahoma
University of Massachusetts
University of Göttingen
Royal Holloway University of London
United States Department of Energy
Mohammed V University in Rabat
Tel Aviv University
Technion-Israel Institute of Technology
Argonne National Laboratory
Pontificia Universidad Católica de Chile
National Institute for Nuclear Physics
Abdus Salam International Centre for Theoretical Physics
King's College London
Johannes Gutenberg University Mainz
Université Savoie Mont Blanc
AGH University of Krakow
University of Toronto
Brandeis University
Northern Illinois University
Bogazici University
Istanbul University
University of Geneva
Rutherford Appleton Laboratory
University of California at Santa Cruz
Université Paris-Saclay
Institute for High Energy Physics
University of Pavia
Radboud University Nijmegen
Alexandru Ioan Cuza University of Iaşi
Laboratório de Instrumentação e Física Experimental de Partículas
University of Granada
IFT-UAM/CSIC
Joint Institute for Nuclear Research
McGill University
German Electron Synchrotron
University of Rome Tor Vergata
Weizmann Institute of Science
Kyoto University
Lund University
P.N. Lebedev Physical Institute of the Russian Academy of Sciences
Columbia University

Research output: Contribution to journal › Article › peer-review

81 Scopus citations

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.

Original language	English
Article number	7
Journal	Computing and Software for Big Science
Volume	6
Issue number	1
DOIs	https://doi.org/10.1007/s41781-021-00079-7
State	Published - Dec 2022

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10.1007/s41781-021-00079-7

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@article{69353a1280694a35bd0316162676b86e,

title = "AtlFast3: The Next Generation of Fast Simulation in ATLAS",

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.",

author = "\{ATLAS Collaboration\} and G. Aad and B. Abbott and Abbott, \{D. C.\} and Abud, \{A. Abed\} and K. Abeling and Abhayasinghe, \{D. K.\} and Abidi, \{S. H.\} and A. Aboulhorma and H. Abramowicz and H. Abreu and Y. Abulaiti and Hoffman, \{A. C.Abusleme\} and Acharya, \{B. S.\} and B. Achkar and L. Adam and Bourdarios, \{C. Adam\} and L. Adamczyk and L. Adamek and Addepalli, \{S. V.\} and J. Adelman and A. Adiguzel and S. Adorni and T. Adye and Affolder, \{A. A.\} and Y. Afik and C. Agapopoulou and Agaras, \{M. N.\} and J. Agarwala and A. Aggarwal and C. Agheorghiesei and Aguilar-Saavedra, \{J. A.\} and A. Ahmad and F. Ahmadov and Ahmed, \{W. S.\} and X. Ai and G. Aielli and I. Aizenberg and S. Akatsuka and M. Akbiyik and {\AA}kesson, \{T. P.A.\} and Akimov, \{A. V.\} and Khoury, \{K. Al\} and Alberghi, \{G. L.\} and H. Arnold and \{Da Via\}, C. and V. Dao and J. Hobbs and J. Jia and G. Piacquadio and D. Tsybychev",

note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.",

year = "2022",

month = dec,

doi = "10.1007/s41781-021-00079-7",

language = "English",

volume = "6",

journal = "Computing and Software for Big Science",

issn = "2510-2044",

number = "1",

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TY - JOUR

T1 - AtlFast3

T2 - The Next Generation of Fast Simulation in ATLAS

AU - ATLAS Collaboration

AU - Aad, G.

AU - Abbott, B.

AU - Abbott, D. C.

AU - Abud, A. Abed

AU - Abeling, K.

AU - Abhayasinghe, D. K.

AU - Abidi, S. H.

AU - Aboulhorma, A.

AU - Abramowicz, H.

AU - Abreu, H.

AU - Abulaiti, Y.

AU - Hoffman, A. C.Abusleme

AU - Acharya, B. S.

AU - Achkar, B.

AU - Adam, L.

AU - Bourdarios, C. Adam

AU - Adamczyk, L.

AU - Adamek, L.

AU - Addepalli, S. V.

AU - Adelman, J.

AU - Adiguzel, A.

AU - Adorni, S.

AU - Adye, T.

AU - Affolder, A. A.

AU - Afik, Y.

AU - Agapopoulou, C.

AU - Agaras, M. N.

AU - Agarwala, J.

AU - Aggarwal, A.

AU - Agheorghiesei, C.

AU - Aguilar-Saavedra, J. A.

AU - Ahmad, A.

AU - Ahmadov, F.

AU - Ahmed, W. S.

AU - Ai, X.

AU - Aielli, G.

AU - Aizenberg, I.

AU - Akatsuka, S.

AU - Akbiyik, M.

AU - Åkesson, T. P.A.

AU - Akimov, A. V.

AU - Khoury, K. Al

AU - Alberghi, G. L.

AU - Arnold, H.

AU - Da Via, C.

AU - Dao, V.

AU - Hobbs, J.

AU - Jia, J.

AU - Piacquadio, G.

AU - Tsybychev, D.

PY - 2022/12

Y1 - 2022/12

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85126227550

U2 - 10.1007/s41781-021-00079-7

DO - 10.1007/s41781-021-00079-7

M3 - Article

AN - SCOPUS:85126227550

SN - 2510-2044

VL - 6

JO - Computing and Software for Big Science

JF - Computing and Software for Big Science

IS - 1

M1 - 7

ER -

AtlFast3: The Next Generation of Fast Simulation in ATLAS

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