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

Installation from source

A the moment the code is not deployed yet, you can install it only from source using a conda environnement, which is provided. To install it you need a conda installation and run:

./install.sh -n <env_name='smefit_installation'>

This will download and install also the MULtiNest library, which is required to run Nested Sampling. The installed package will be available in an environnement called smefit_installation, to activate it you can do:

conda activate <env_name='smefit_installation'>
smefit -h

Running

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

smefit NS <path_to_runcard>

To run the code suing the Monte Carlo replica method you can do:

smefit MC <path_to_runcard> -n <replica_number>

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 pyetst 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"
}