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EOS -- A Software for Flavor Physics Phenomenology

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arxiv 2111.15428 v1 pith:WLNTZPS3 submitted 2021-11-30 hep-ph hep-ex

EOS -- A Software for Flavor Physics Phenomenology

Danny van Dyk , Frederik Beaujean , Thomas Blake , Christoph Bobeth , Marzia Bordone , Katarina Dugic , Eike Eberhard , Nico Gubernari
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Elena Graverini Martin Jung Ahmet Kokulu Stephan K\"urten Domagoj Leljak Philip L\"ughausen Stefan Meiser Muslem Rahimi M\'eril Reboud Rafael Silva Coutinho Javier Virto K. Keri Vos
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classification hep-ph hep-ex
keywords physicssoftwareexamplesflavorprocessestheoryvarietyachieve
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 4 Pith papers

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    Lattice-only Dispersive Matrix form factors enlarge large-recoil uncertainties and, with new angular data, favour long-distance hadronic effects over a short-distance C9 New Physics shift.

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    hep-ph 2026-04 unverdicted novelty 5.0

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  3. Closing the knowledge gap in semileptonic $B\rightarrow X_c\ell\nu$ decays

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  4. Flavour Changing Neutral Current decays at LHCb

    hep-ex 2026-05 unverdicted novelty 3.0

    LHCb reports updated FCNC decay measurements including a legacy analysis of B0 to K*0 mu+ mu- using 8.4 fb-1 of Run 1 and 2 data, noting persistent tensions with SM expectations in b to s mu mu channels.