Back to Search Start Over

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

Authors :
Cranmer, Kyle
Kraml, Sabine
Prosper, Harrison B.
Bechtle, Philip
Bernlochner, Florian U.
Bloch, Itay M.
Canonero, Enzo
Chrzaszcz, Marcin
Coccaro, Andrea
Conrad, Jan
Cowan, Glen
Feickert, Matthew
Iachellini, Nahuel Ferreiro
Fowlie, Andrew
Heinrich, Lukas
Held, Alexander
Kuhr, Thomas
Kvellestad, Anders
Madigan, Maeve
Mahmoudi, Farvah
MorĂ¥, Knut Dundas
Neubauer, Mark S.
Pierini, Maurizio
Rojo, Juan
Sekmen, Sezen
Silvestrini, Luca
Sanz, Veronica
Stark, Giordon
Torre, Riccardo
Thorne, Robert
Waltenberger, Wolfgang
Wardle, Nicholas
Wittbrodt, Jonas
Source :
SciPost Phys. 12, 037 (2022)
Publication Year :
2021

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 impact of experimental results.<br />Comment: 60 pages, 15 figures

Details

Database :
arXiv
Journal :
SciPost Phys. 12, 037 (2022)
Publication Type :
Report
Accession number :
edsarx.2109.04981
Document Type :
Working Paper
Full Text :
https://doi.org/10.21468/SciPostPhys.12.1.037