{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/eos-a-software-for-flavor-physics","title":"EOS -- A Software for Flavor Physics Phenomenology","arxiv_id":"2111.15428","date":"2021-11-30","proceeding":null,"authors":["Danny van Dyk","Frederik Beaujean","Thomas Blake","Christoph Bobeth","Marzia Bordone","Katarina Dugic","Eike Eberhard","Nico Gubernari","Elena Graverini","Martin Jung","Ahmet Kokulu","Stephan Kürten","Domagoj Leljak","Philip Lüghausen","Stefan Meiser","Muslem Rahimi","Méril Reboud","Rafael Silva Coutinho","Javier Virto","K. Keri Vos"],"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.","url_abs":"https://arxiv.org/abs/2111.15428v1","url_pdf":"https://arxiv.org/pdf/2111.15428v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"eos-a-software-for-flavor-physics","repo_url":"https://github.com/eos/eos","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}