https://doi.org/10.1051/epjconf/202024506017
Likelihood preservation and statistical reproduction of searches for new physics
1
University of Illinois at Urbana-Champaign, Urbana, IL, USA
2
CERN, Geneva, Switzerland
3
University of California Santa Cruz SCIPP, Santa Cruz, CA, USA
* e-mail: matthew.feickert@cern.ch
** e-mail: lukas.heinrich@cern.ch
*** e-mail: giordon.holtsberg.stark@cern.ch
Copyright 2020 CERN for the benefit of the ATLAS Collaboration. Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license.
Published online: 16 November 2020
Likelihoods associated with statistical fits in searches for new physics are beginning to be published by LHC experiments on HEPData. The first of these is the search for bottom-squark pair production by ATLAS. These likelihoods adhere to a specification first defined by the HistFactory p.d.f. template. This is per-se independent of its implementation in ROOT and it is useful to be able to run statistical analysis outside of the ROOT and RooStats/RooFit framework. We introduce a JSON schema that fully describes the HistFactory statistical model and is sufficient to reproduce key results from published ATLAS analyses. Using two independent implementations of the model, one in ROOT and one in pure Python, we reproduce the sbottom multi-b limits using the published likelihoods on HEPData underscoring the implementation independence and long-term viability of the archived data.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
