FlavorPy documentation#
FlavorPy is a Python library for calculations around discrete flavor symmetries in particle physics. Currently it is split into two parts:
Calculate tensor product and find invariant terms in the action.
Install#
You can install FlavorPy from PyPI with pip by running
pip install flavorpy
Alternatively, you can:
Download the files from the github repository.
Open python and load the files with:
import os dir_to_git_folder = "whereever_you_downloaded_the_files_to/FlavorPy/current_version" # Adjust this to your case !! os.chdir(os.path.expanduser(dir_to_git_folder)) import constructterms as ct import modelfitting as mf
Start using the parts of FlavorPy imported as ct and mf!
Examples#
Introductory examples#
Further examples#
Reproduce the model fitting results of the paper “Double Cover of Modular S4 for Flavour Model Building” by P. P. Novichkov, J. T. Penedo, and S. T. Petcov
Development#
This project is under active development! The objectives of current development are:
bringing the two parts, ConstructTerms and ModelFitting, together
integrating GAP and its SmallGroups library
If you want to contribute, please feel free to contact Alexander Baur.
Citing FlavorPy#
If FlavorPy contributes to a project that leads to a publication, please acknowledge this fact by citing:
A. Baur, “FlavorPy”, Zenodo, 2024, doi: 10.5281/zenodo.11060597.
Here is an example of a BibTex entry:
@software{FlavorPy,
author = {Baur, Alexander},
title = "{FlavorPy}",
year = {2024},
publisher = {Zenodo},
version = {v0.2.0},
doi = {10.5281/zenodo.11060597},
url = "\url{https://doi.org/10.5281/zenodo.11060597}"
}
When using the NuFit experimental data, please also cite:
Credit#
FlavorPy makes use of experimental data obtained by NuFit published in JHEP 09 (2020) 178, arXiv:2007.14792, and their website www.nu-fit.org. Please cite NuFit if you use their experimental data.