Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events (2024)

ATLAS Collaboration (2022). Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events. Computing and Software for Big Science, 6(1), Article 3. https://doi.org/10.1007/s41781-021-00062-2

ATLAS Collaboration. / Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events. In: Computing and Software for Big Science. 2022 ; Vol. 6, No. 1.

@article{9ddc895cb957419ca449e76c9c8b82fe,

title = "Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events",

abstract = "The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.",

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 AbouZeid, {O. S.} and Abraham, {N. L.} 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 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 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 S. Akatsuka and M. Akbiyik and {\AA}kesson, {T. P.A.} and E. Akilli and Akimov, {A. V.} and Khoury, {K. Al} and Alberghi, {G. L.} and J. Albert and Verzini, {M. J.Alconada} and S. Alderweireldt and M. Aleksa and Aleksandrov, {I. N.} and C. Alexa and T. Alexopoulos and Connell, {S. H.}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1007/s41781-021-00062-2",

language = "English",

volume = "6",

journal = "Computing and Software for Big Science",

issn = "2510-2044",

publisher = "Springer Nature",

number = "1",

}

ATLAS Collaboration 2022, 'Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events', Computing and Software for Big Science, vol. 6, no. 1, 3. https://doi.org/10.1007/s41781-021-00062-2

Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events. / ATLAS Collaboration.
In: Computing and Software for Big Science, Vol. 6, No. 1, 3, 12.2022.

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

TY - JOUR

T1 - Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events

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 - AbouZeid, O. S.

AU - Abraham, N. L.

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 - 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 - 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 - Akatsuka, S.

AU - Akbiyik, M.

AU - Åkesson, T. P.A.

AU - Akilli, E.

AU - Akimov, A. V.

AU - Khoury, K. Al

AU - Alberghi, G. L.

AU - Albert, J.

AU - Verzini, M. J.Alconada

AU - Alderweireldt, S.

AU - Aleksa, M.

AU - Aleksandrov, I. N.

AU - Alexa, C.

AU - Alexopoulos, T.

AU - Connell, S. H.

N1 - Publisher Copyright:© 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.

AB - The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.

UR - http://www.scopus.com/inward/record.url?scp=85124276335&partnerID=8YFLogxK

U2 - 10.1007/s41781-021-00062-2

DO - 10.1007/s41781-021-00062-2

M3 - Article

AN - SCOPUS:85124276335

SN - 2510-2044

VL - 6

JO - Computing and Software for Big Science

JF - Computing and Software for Big Science

IS - 1

M1 - 3

ER -

ATLAS Collaboration. Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events. Computing and Software for Big Science. 2022 Dec;6(1):3. doi: 10.1007/s41781-021-00062-2