CITATION.cff

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cff-version: 1.2.0
title: 'EOS: A Software for Flavor Physics Phenomenology'
message: >-
  If you use EOS in your publication, we ask you to cite the following publication(s):
type: software
authors:
  - name: The EOS Authors Collaboration
  - given-names: Danny
    family-names: van Dyk
  - name: and others
identifiers:
  - type: doi
    value: 10.1140/epjc/s10052-022-10177-4
repository-code: 'https://github.com/eos/eos'
url: 'https://eoshep.org'
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.
license: GPL-2.0-only