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Event generators for high-energy physics experiments

Campbell, J.M. ; Bierlich, C. LU ; Chakraborty, S. LU orcid ; Frederix, R. LU orcid ; Gellersen, L. LU ; Kirchgaeßer, M.M. ; Lönnblad, L. LU orcid ; Prestel, S. LU ; Reuschle, C. LU orcid and Sjöstrand, T. LU orcid , et al. (2024) In SciPost Physics 16(5).
Abstract
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced,... (More)
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments. Copyright J. M. Campbell et al. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
SciPost Physics
volume
16
issue
5
article number
130
publisher
SciPost
external identifiers
  • scopus:85196098534
ISSN
2542-4653
DOI
10.21468/SCIPOSTPHYS.16.5.130
language
English
LU publication?
yes
id
39836387-25b4-4088-8717-5b52c82d0d13
date added to LUP
2024-08-30 11:40:40
date last changed
2024-08-30 11:41:14
@article{39836387-25b4-4088-8717-5b52c82d0d13,
  abstract     = {{We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments. Copyright J. M. Campbell et al.}},
  author       = {{Campbell, J.M. and Bierlich, C. and Chakraborty, S. and Frederix, R. and Gellersen, L. and Kirchgaeßer, M.M. and Lönnblad, L. and Prestel, S. and Reuschle, C. and Sjöstrand, T. and Zapp, K.}},
  issn         = {{2542-4653}},
  language     = {{eng}},
  number       = {{5}},
  publisher    = {{SciPost}},
  series       = {{SciPost Physics}},
  title        = {{Event generators for high-energy physics experiments}},
  url          = {{http://dx.doi.org/10.21468/SCIPOSTPHYS.16.5.130}},
  doi          = {{10.21468/SCIPOSTPHYS.16.5.130}},
  volume       = {{16}},
  year         = {{2024}},
}