EOS -- A HEP program for Flavor Observables

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dvandyk from gravatar.com dvandyk Avatar for mreboud from gravatar.com mreboud

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers
Report project as malware

Project description

PyPi version Build Status Build Status Discord

EOS logo

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:

  1. theory predictions of and uncertainty estimation for flavor observables within the Standard Model or within the Weak Effective Theory;
  2. Bayesian parameter inference from both experimental and theoretical constraints; and
  3. 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:

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

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dvandyk from gravatar.com dvandyk Avatar for mreboud from gravatar.com mreboud

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

1.0.16.dev895 pre-release

1.0.16.dev890 pre-release

1.0.16.dev874 pre-release

1.0.16.dev848 pre-release

This version

1.0.15

1.0.14

1.0.13

1.0.12

1.0.11

1.0.10

1.0.9

1.0.8

1.0.7

1.0.6

1.0.5

1.0.2

1.0.1

1.0

0.3.3

0.3.2

0.3.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

eoshep-1.0.15-cp313-cp313-manylinux_2_28_x86_64.whl (79.4 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

eoshep-1.0.15-cp313-cp313-manylinux_2_28_aarch64.whl (73.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ ARM64

eoshep-1.0.15-cp312-cp312-manylinux_2_28_x86_64.whl (79.4 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

eoshep-1.0.15-cp312-cp312-manylinux_2_28_aarch64.whl (73.5 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ ARM64

eoshep-1.0.15-cp311-cp311-manylinux_2_28_x86_64.whl (79.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

eoshep-1.0.15-cp311-cp311-manylinux_2_28_aarch64.whl (73.5 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ ARM64

eoshep-1.0.15-cp310-cp310-manylinux_2_28_x86_64.whl (79.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

eoshep-1.0.15-cp310-cp310-manylinux_2_28_aarch64.whl (73.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ ARM64

File details

Details for the file eoshep-1.0.15-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 977f80e8bd0709c3a224e66c77800ff5897f153464d4afd8edb2f39c7755990f
MD5 1e9202993f9e0e39475906d2d63a7158
BLAKE2b-256 486f2ef1bd7dd4d1de60cc67244ae970208e15833cd0636983c49b01cd93b8f5

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp313-cp313-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp313-cp313-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 43b75f99d2d9a36e39c10a96fe9b72af9bef58d403f996b1c4211e63a5ea9e70
MD5 c44799ca05f85054cfb02fb35ede9d16
BLAKE2b-256 0c2f98ab44d0b67595ad90515e5dd3c204cfed66a221c6bc0a45de081ba60e60

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 4418059f2a865949472468589f0f5e65729b6842b18a9c9c4fae7ad8067934db
MD5 0ba6da4578a9a0af59b5b849b4adc125
BLAKE2b-256 b5a659fb16260c32229b7c29a6b94985feed45cb83dd4a1e7920d4c8eced45c3

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 9ba384aa109cd5ffdb279ac36b6250cd09023a30785939ee211e85e21b631866
MD5 4c22c6236029f4e9822af5dafb6ba15f
BLAKE2b-256 35bed11267911f76978e3919c00030dae34dd5563cdefd758dead6084415b71e

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 05a1172f14ccdfb639e9b4918c1e144558cc5ab09d28a7d2e9cc0e8412bd89df
MD5 5bd66f2c8c45c4d4877bd6e5beb7b1ba
BLAKE2b-256 9fd3ed448335d550e55d3f02d8c7de9dc175fc14f4c36f07495196dc4e48c6ba

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 842c664047b4a658e55632b661b5527a6cc64d79a8a7223b456d014edda8ab53
MD5 3fe545bb1a58cd8a5b50ec6acb9f42fe
BLAKE2b-256 ab701bede1af0a8de6714febe3214fbd6545896dd5b65bf2ca78711ad92ab2c9

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ff8bd6a8024c03956da855423b65827db869632fc5a5e376addd9357ea9288c6
MD5 6a523b5bdc0a2cb97a781f3b9520c649
BLAKE2b-256 7766e48f61d4b6bcacfb7bd82663d925b1d5edf65744c354d2af0ff2fe9e1bbc

See more details on using hashes here.

File details

Details for the file eoshep-1.0.15-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for eoshep-1.0.15-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 318c9256697bcb6d192f1021487bbb15459fff300f6760dcc8fa12b1de5755d3
MD5 cc1b76ec48aaab3d84e49a399056e59d
BLAKE2b-256 894a72063db83222263c1ef0e1b6019766bedcb72962740665294f4949657863

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page