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Standard Model Effective Field Theory Fitter

Reason this release was yanked:

incorrectly assumes python 3.13 support

Project description

SMEFiT

Tests CodeFactor

SMEFiT is a python program for Standard Model Effective Field Theory fits

Installation

To install the smefit release on PYPI you can do:

pip install smefit

Installation for developers

If you are interested in developing smefit or having the latest smefit code not yet released, you should clone the smefit repository and then install in editable mode:

cd smefit_release
pip install -e .

If one is interested in having smefit installed in a conda environment, this can be done by creating the environment (for example with python 3.12), activating it and then installing inside the environment.

conda create python=3.12 -n smefit-dev
conda activate smefit-dev
pip install -e .

Running

The fitting code provide two fitting strategies. To run the code with Nested Sampling you can do:

smefit NS <path_to_runcard>

To run the code suing the analytic method (valid only for linear fits) you can do:

smefit A <path_to_runcard>

An runcard example is provided in runcards/test_runcard.yaml. You can also do smefit -h for more help.

Running in parallel

To run smefit with Nested Sampling in parallel you can do:

mpiexec -n number_of_cores smefit NS <path_to_runcard>

Documentation

If you want to build the documentation do:

cd docs
make html

Unit tests

To run the unit test you need to install:

pip install pytest pytest-env pytest-cov

And then simply run:

pytest

Reports

To run reports and produce PDF and HTML output you need to have pandoc and pdflatex installed. The first one is available in conda the latter can be sourced in:

souce /cvmfs/sft.cern.ch/lcg/external/texlive/2020/bin/x86_64-linux/pdflatex

Citation policy

Please cite our paper when using the code:

@article{Giani:2023gfq,
    author = "Giani, Tommaso and Magni, Giacomo and Rojo, Juan",
    title = "{SMEFiT: a flexible toolbox for global interpretations of particle physics data with effective field theories}",
    eprint = "2302.06660",
    archivePrefix = "arXiv",
    primaryClass = "hep-ph",
    reportNumber = "Nikhef-2022-023",
    month = "2",
    year = "2023"
}

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