EOS -- A Software for Flavor Physics Phenomenology
Abstract
EOS is an open-source software for a variety of computational tasks in flavor physics. Its use cases include theory predictions within and beyond the Standard Model of particle physics, Bayesian inference of theory parameters from experimental and theoretical likelihoods, and simulation of pseudo events for a number of signal processes. EOS ensures high-performance computations through a C++ back-end and ease of usability through a Python front-end. To achieve this flexibility, EOS enables the user to select from a variety of implementations of the relevant decay processes and hadronic matrix elements at run time. In this article, we describe the general structure of the software framework and provide basic examples. Further details and in-depth interactive examples are provided as part of the EOS online documentation.
Cite
@article{arxiv.2111.15428,
title = {EOS -- A Software for Flavor Physics Phenomenology},
author = {Danny van Dyk and Frederik Beaujean and Thomas Blake and Christoph Bobeth and Marzia Bordone and Katarina Dugic and Eike Eberhard and Nico Gubernari and Elena Graverini and Martin Jung and Ahmet Kokulu and Stephan Kürten and Domagoj Leljak and Philip Lüghausen and Stefan Meiser and Muslem Rahimi and Méril Reboud and Rafael Silva Coutinho and Javier Virto and K. Keri Vos},
journal= {arXiv preprint arXiv:2111.15428},
year = {2022}
}
Comments
32 pages, 8 figures, 4 ancillary Jupyter example notebooks