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Publishing statistical models : Getting the most out of particle physics experiments

Cranmer, Kyle ; Kraml, Sabine ; Prosper, Harrison B. ; Bechtle, Philip ; Bernlochner, Florian U. ; Bloch, Itay M. ; Canonero, Enzo ; Chrzaszcz, Marcin ; Coccaro, Andrea and Conrad, Jan , et al. (2022) In SciPost Physics 12(1).
Abstract

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term... (More)

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
SciPost Physics
volume
12
issue
1
article number
037
publisher
SciPost
external identifiers
  • scopus:85124422901
ISSN
2542-4653
DOI
10.21468/SciPostPhys.12.1.037
language
English
LU publication?
yes
id
0e1f47cb-95bb-4267-8c93-2107beac0baf
date added to LUP
2023-01-19 15:57:29
date last changed
2024-04-18 18:14:26
@article{0e1f47cb-95bb-4267-8c93-2107beac0baf,
  abstract     = {{<p>The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.</p>}},
  author       = {{Cranmer, Kyle and Kraml, Sabine and Prosper, Harrison B. and Bechtle, Philip and Bernlochner, Florian U. and Bloch, Itay M. and Canonero, Enzo and Chrzaszcz, Marcin and Coccaro, Andrea and Conrad, Jan and Cowan, Glen and Feickert, Matthew and Iachellini, Nahuel F. and Fowlie, Andrew and Heinrich, Lukas and Held, Alexander and Kuhr, Thomas and Kvellestad, Anders and Madigan, Maeve and Mahmoudi, Farvah and Morå, Knut D. and Neubauer, Mark S. and Pierini, Maurizio and Rojo, Juan and Sekmen, Sezen and Silvestrini, Luca and Sanz, Veronica and Stark, Giordon and Torre, Riccardo and Thorne, Robert and Waltenberger, Wolfgang and Wardle, Nicholas and Wittbrodt, Jonas}},
  issn         = {{2542-4653}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{SciPost}},
  series       = {{SciPost Physics}},
  title        = {{Publishing statistical models : Getting the most out of particle physics experiments}},
  url          = {{http://dx.doi.org/10.21468/SciPostPhys.12.1.037}},
  doi          = {{10.21468/SciPostPhys.12.1.037}},
  volume       = {{12}},
  year         = {{2022}},
}