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.
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.
Authors and Contributors
The main authors are:
- Frederik Beaujean,
- Christoph Bobeth,
- Carolina Bolognani carolinabolognani@gmail.com,
- Nico Gubernari nicogubernari@gmail.com,
- Florian Herren florian.s.herren@gmail.com,
- Matthew J. Kirk matthew.j.kirk@durham.ac.uk,
- Meril Reboud merilreboud@gmail.com,
- Danny van Dyk danny.van.dyk@gmail.com,
with further code contributions by:
- Marzia Bordone,
- Thomas Blake,
- Lorenz Gaertner,
- Elena Graverini,
- Stephan Jahn,
- Ahmet Kokulu,
- Viktor Kuschke,
- Stephan Kürten,
- Philip Lüghausen,
- Bastian Müller,
- Filip Novak,
- Stefanie Reichert,
- Eduardo Romero,
- Rafael Silva Coutinho,
- Ismo Tojiala,
- K. Keri Vos,
- Christian Wacker.
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
Metadata
Release files for eoshep 1.0.21.dev1372
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 830.8 MB
Release files / eoshep-1.0.21.dev1372-cp314-cp314-manylinux_2_34_x86_64.whl
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Release files / eoshep-1.0.21.dev1372-cp314-cp314-manylinux_2_34_aarch64.whl
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Release files / eoshep-1.0.21.dev1372-cp313-cp313-manylinux_2_34_x86_64.whl
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Release files / eoshep-1.0.21.dev1372-cp313-cp313-manylinux_2_34_aarch64.whl
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Release files / eoshep-1.0.21.dev1372-cp312-cp312-manylinux_2_34_aarch64.whl
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Release files / eoshep-1.0.21.dev1372-cp311-cp311-manylinux_2_34_x86_64.whl
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Release files / eoshep-1.0.21.dev1372-cp311-cp311-manylinux_2_34_aarch64.whl
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| Size | 85.6 MB |
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Release files / eoshep-1.0.21.dev1372-cp310-cp310-manylinux_2_34_aarch64.whl
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| Size | 80.5 MB |
| Tags | CPython 3.10 Linux glibc 2.34+ ARM64 |
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