Abstract
We present NeoPDF, an interpolation library that supports both collinear and transverse momentum-dependent parton distribution functions. NeoPDF is designed to be fast and reliable, with modern functionalities that target both current and future hadron collider experiments. It aims to address the shortcomings of existing interpolation libraries while providing additional features to support generic non-perturbative functions. Some of the features include a new interpolation based on Chebyshev polynomials, as well as the ability to interpolate along the nucleon number A, the reference strong coupling αs(MZ), and the parton’s intrinsic transverse momentum kT. NeoPDF implements its own file format using binary serialisation and lossless compression, prioritising speed and efficiency. A no-code migration design is provided for LHAPDF in order to remove the friction associated with transitioning to NeoPDF. The library is written in Rust, with interfaces for various programming languages such as Fortran, C, C++, Python, and Mathematica. We benchmark NeoPDF against LHAPDF and TMDlib for various sets and show that it is both fast and accurate.
| Original language | English |
|---|---|
| Article number | 1480 |
| Pages (from-to) | 1-24 |
| Number of pages | 24 |
| Journal | European Physical Journal C |
| Volume | 85 |
| Issue number | 12 |
| Early online date | 29 Dec 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
Bibliographical note
Publisher Copyright:© The Author(s) 2025.
Funding
The author wishes to acknowledge Valerio Bertone for inspiring the support for TMD distributions. The author gratefully acknowledges Simone Rodini for various discussions regarding the design of NeoPDF and the Chebyshev interpolation. The author also wishes to thank Juan M. Cruz-Martinez for stressing the relevance of the LHAPDF no-code migration. Finally, the author thanks Valerio Bertone, Stefano Forte, Felix Hekhorn, Juan Rojo, and the members of the NNPDF collaboration for a careful reading of the manuscript and for providing invaluable feedback. The work of T.R.R. was partially supported by an Accelerating Scientific Discoveries (ASDI2021) grant from the Netherlands eScience Center (NLeSC), grant number 027.020.G05.
| Funders | Funder number |
|---|---|
| Valerio Bertone | ASDI2021 |
| Netherlands eScience Center | G05, 027.020 |
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