EKO is a Python module to solve the DGLAP equations in N-space in terms of Evolution Kernel Operators in x-space.

Installation

EKO is available via

• PyPI: : $ pip install eko
• conda-forge: : $ conda install eko

The documentation is available here:

ekore

We also provide a convenient access to the core elements of EKO: the anomalous dimensions $\gamma$ and operator matrix elements/transition matrix elements $\mathbf A$. These are collected from various references (see our documentation) and provide the current state of the art in one single place.

Python

In Python you can access these elements through the ekore module installed together with the main Python library - see our documentation.

This module is scheduled for removal once we move the ekore content to Rust (see below).

Rust

In Rust you can access these elements through the ekore crate

C

In C you can access these elements through the ekore_capi crate

For installation instructions and usage see the documentation:

Python (via Rust)

In Python you can access these elements through the ekore-rs module : $ pip install ekore-rs

Citation policy

When using our code please cite

• our DOI:
• our paper:

Contributing

• Your feedback is welcome! If you want to report a (possible) bug or want to ask for a new feature, please raise an issue:
• If you need help, for installation, usage, or anything related, feel free to open a new discussion in the "Support" section
• Please follow our Code of Conduct and read the Contribution Guidelines

Development installation

If you want to install from source you can run

git clone git@github.com:N3PDF/eko.git
cd eko
poetry install

To setup poetry, and other tools, see Contribution Guidelines.

Building the documentation

• The documentation is available here:
• To build the documentation from source install graphviz and run in addition to the installation commands

poe docs

Tests and benchmarks

• To run unit test you can do

poe tests

• Benchmarks of specific part of the code, such as the strong coupling or msbar masses running, are available doing

poe bench

• The complete list of benchmarks with external codes is available through ekomark: documentation