English

$\texttt{HEPfit}$: a Code for the Combination of Indirect and Direct Constraints on High Energy Physics Models

High Energy Physics - Phenomenology 2025-06-03 v2 High Energy Physics - Experiment

Abstract

HEPfit\texttt{HEPfit} is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to i)\textit{i)} fit the model parameters to a given set of experimental observables; ii)\textit{ii)} obtain predictions for observables. HEPfit\texttt{HEPfit} can be used either in Monte Carlo mode, to perform a Bayesian Markov Chain Monte Carlo analysis of a given model, or as a library, to obtain predictions of observables for a given point in the parameter space of the model, allowing HEPfit\texttt{HEPfit} to be used in any statistical framework. In the present version, around a thousand observables have been implemented in the Standard Model and in several new physics scenarios. In this paper, we describe the general structure of the code as well as models and observables implemented in the current release.

Keywords

Cite

@article{arxiv.1910.14012,
  title  = {$\texttt{HEPfit}$: a Code for the Combination of Indirect and Direct Constraints on High Energy Physics Models},
  author = {Jorge de Blas and Debtosh Chowdhury and Marco Ciuchini and Antonio M. Coutinho and Otto Eberhardt and Marco Fedele and Enrico Franco and Giovanni Grilli di Cortona and Victor Miralles and Satoshi Mishima and Ayan Paul and Ana Penuelas and Maurizio Pierini and Laura Reina and Luca Silvestrini and Mauro Valli and Ryoutaro Watanabe and Norimi Yokozaki},
  journal= {arXiv preprint arXiv:1910.14012},
  year   = {2025}
}

Comments

49 pages, 7 figures. Version accepted for publication