Publishing statistical models: Getting the most out of particle physics experiments
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.
Cite
@article{arxiv.2109.04981,
title = {Publishing statistical models: Getting the most out of particle physics experiments},
author = {Kyle Cranmer and Sabine Kraml and Harrison B. Prosper and Philip Bechtle and Florian U. Bernlochner and Itay M. Bloch and Enzo Canonero and Marcin Chrzaszcz and Andrea Coccaro and Jan Conrad and Glen Cowan and Matthew Feickert and Nahuel Ferreiro Iachellini and Andrew Fowlie and Lukas Heinrich and Alexander Held and Thomas Kuhr and Anders Kvellestad and Maeve Madigan and Farvah Mahmoudi and Knut Dundas Morå and Mark S. Neubauer and Maurizio Pierini and Juan Rojo and Sezen Sekmen and Luca Silvestrini and Veronica Sanz and Giordon Stark and Riccardo Torre and Robert Thorne and Wolfgang Waltenberger and Nicholas Wardle and Jonas Wittbrodt},
journal= {arXiv preprint arXiv:2109.04981},
year = {2022}
}
Comments
60 pages, 15 figures