Library for calculations around discrete flavor symmetries in particle physics
Project description
FlavorPy
What is FlavorPy?
FlavorPy is a Python library for calculations around discrete flavor symmetries in particle physics. Currently, it is split into two parts:
-
The constructterms part allows you to calculate group theoretical tensor products and therefore find the invariant terms in the action.
-
The modelfitting part is concerned with fitting a model to experimental data. More specifically flavor observables, i.e. masses and mixing, for given mass matrices with an associated parameter space can be compared and fitted to experimental data. The minimization heavily relies on lmfit.
How to install FlavorPy?
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 = "home/.../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 FlavorPy packages imported as
ct
andmf
!
Documentation
A documentation is hosted on https://flavorpy.github.io/FlavorPy/. This site also contains examples of how to use the code.
Current development
The goal of current development is bringing the two parts together and integrating GAP or SageMath to ConstructTerms. 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 = {v0.1.0},
doi = {10.5281/zenodo.11060597},
url = "\url{https://doi.org/10.5281/zenodo.11060597}"
}
When using the NuFit experimental data, please also cite
Credit
This package uses experimental data obtained by NuFit published in JHEP 09 (2020) 178, arXiv:2007.14792, and their website www.nu-fit.org.
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