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#
Take a look at these Examples to get an overview of the usage and capabilities of FlavorPy.
Development#
This project is under active development! The objectives of current development are:
extending ModelFitting by a MCMC method to study the vicinity of minima
implementing quark models in ModelFitting
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.
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.
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 = {v0.1.0},
doi = {10.5281/zenodo.11060597},
url = "\url{https://doi.org/10.5281/zenodo.11060597}"
}
When using the NuFit experimental data, please also cite: