This release is a pre-release and may not be stable for production use.
EOS - A software for Flavor Physics Phenomenology
EOS is a software package that addresses several use cases in the field of high-energy flavor physics:
- theory predictions of and uncertainty estimation for flavor observables within the Standard Model or within the Weak Effective Theory;
- Bayesian parameter inference from both experimental and theoretical constraints; and
- Monte Carlo simulation of pseudo events for flavor processes.
An up-to-date list of publications that use EOS can be found here.
EOS is written in C++20 and designed to be used through its Python 3 interface, ideally within a Jupyter notebook environment. It depends on as a small set of external software:
- the GNU Scientific Library (libgsl),
- a subset of the BOOST C++ libraries,
- the Python 3 interpreter.
For details on these dependencies we refer to the online documentation.
Installation
EOS supports several methods of installation. For Linux users, the recommended method is installation via PyPI:
pip3 install eoshep
Development versions tracking the master branch are also available via PyPi:
pip3 install --pre eoshep
For instructions on how to build and install EOS on your computer please have a look at the online documentation.
Attribution
When you use EOS for a project that results in a publication, please cite the appropriate / most recent Zenodo release as well as the publication
@article{EOSAuthors:2021xpv,
author = "van Dyk, Danny and others", collaboration = "EOS Authors",
title = "{EOS: a software for flavor physics phenomenology}",
eprint = "2111.15428", archivePrefix = "arXiv", primaryClass = "hep-ph",
reportNumber = "EOS-2021-04, TUM-HEP 1371/21, P3H-21-094, SI-HEP-2021-32",
doi = "10.1140/epjc/s10052-022-10177-4",
journal = "Eur. Phys. J. C", volume = "82", number = "6", pages = "569", year = "2022"
}
Contact
If you want to report an error or file a request, please file an issue here. For additional information, please contact any of the main authors, e.g. via our Discord server.
To approach individual developers, please look here.
Acknowledgments
We would like to extend our thanks to the following people whose input and support were most helpful in either the development or the maintenance of EOS:
- Gudrun Hiller
- Gino Isidori
- David Leverton
- Thomas Mannel
- Ciaran McCreesh
- Hideki Miyake
- Konstantinos Petridis
- Nicola Serra
- Alexander Shires
Release files for eoshep 1.0.22.dev1568
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 157.0 MB
Release files / eoshep-1.0.22.dev1568-cp314-cp314-manylinux_2_34_x86_64.whl
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Release files / eoshep-1.0.22.dev1568-cp314-cp314-manylinux_2_34_aarch64.whl
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Release files / eoshep-1.0.22.dev1568-cp314-cp314-macosx_14_0_arm64.whl
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Release files / eoshep-1.0.22.dev1568-cp313-cp313-manylinux_2_34_x86_64.whl
| Download URL | eoshep-1.0.22.dev1568-cp313-cp313-manylinux_2_34_x86_64.whl |
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Release files / eoshep-1.0.22.dev1568-cp313-cp313-manylinux_2_34_aarch64.whl
| Download URL | eoshep-1.0.22.dev1568-cp313-cp313-manylinux_2_34_aarch64.whl |
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| Size | 18.9 MB |
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Release files / eoshep-1.0.22.dev1568-cp313-cp313-macosx_14_0_arm64.whl
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Release files / eoshep-1.0.22.dev1568-cp312-cp312-manylinux_2_34_x86_64.whl
| Download URL | eoshep-1.0.22.dev1568-cp312-cp312-manylinux_2_34_x86_64.whl |
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| Size | 21.9 MB |
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Release files / eoshep-1.0.22.dev1568-cp312-cp312-manylinux_2_34_aarch64.whl
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| Tags | CPython 3.12 Linux glibc 2.34+ ARM64 |
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Release files / eoshep-1.0.22.dev1568-cp312-cp312-macosx_14_0_arm64.whl
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