Simple nonparametric reconstruction of parton distributions from limited Fourier information
Some calculations of parton distributions from first principles only give access to a limited range of Fourier modes of the function to reconstruct. We present a physically motivated procedure to regularize the inverse integral problem using a Gaussian process as a Bayesian prior. We propose to fix the hyperparameters of the prior in a meaningful physical fashion, offering a simple implementation, great numerical efficiency, and allowing us to understand and keep control easily of the uncertainty of the reconstruction.
Authors
- Joseph Karpie (ORCID: https://orcid.org/0000-0001-8999-9014)
- Savvas Zafeiropoulos (ORCID: https://orcid.org/0000-0003-0157-4770)
- Hervé Dutrieux (ORCID: https://orcid.org/0000-0001-8334-4885)
- Kostas Orginos (ORCID: https://orcid.org/0000-0002-3535-7865)
Institutions
- Université de Toulon (FR)
- William & Mary (US)
- Aix-Marseille Université (FR)
- Thomas Jefferson National Accelerator Facility (US)
Publication Details
- Journal
- Physical review. D/Physical review. D.
- Published
- 2025-02-28
- DOI
- https://doi.org/10.1103/physrevd.111.034515
- Citations
- 4
- Primary Topic
- Particle physics theoretical and experimental studies
- Type
- article
- Field-Weighted Citation Impact
- 7.48
Funders
- National Science Foundation
- U.S. Department of Energy
- Commonwealth of Virginia
- College of William and Mary
- University of Texas at Austin
- National Energy Research Scientific Computing Center
- Agence Nationale de la Recherche
- Grand Équipement National De Calcul Intensif
- Office of Science
- Advanced Scientific Computing Research
- Nuclear Physics
- Laboratory Directed Research and Development
- Oak Ridge National Laboratory
- Thomas Jefferson National Accelerator Facility