wmin-model

wmin-model is a Colibri PDF-model that implements the Proper Orthogonal Decomposition (POD) parametrisation presented in arXiv:2507.16913.

Primary Workflows:

1. PDF Fits with POD Parametrisation: Perform parton distribution function (PDF) fits on NNPDF data using the Colibri Bayesian workflow and the linear POD parametrisation.
2. POD-Basis Construction: Generate a Proper Orthogonal Decomposition (POD) basis.

wmin-model implements the NNPOD methodology, providing a linear PDF model optimized for Bayesian inference in high-energy physics.

Installation:

git clone https://github.com/HEP-PBSP/wmin-model.git
cd wmin-model
conda env create -f environment.yml

Citation:

@article{Costantini:2025wxp,
    author = "Costantini, Mark N. and Mantani, Luca and Moore, James M. and Ubiali, Maria",
    title = "{A linear PDF model for Bayesian inference}",
    eprint = "2507.16913",
    archivePrefix = "arXiv",
    primaryClass = "hep-ph",
    month = "7",
    year = "2025"
}

Languages: Python (100%)

License: GPL-3.0