Neural-network analysis of Parton Distribution Functions from Ioffe-time pseudodistributions

Luigi del Debbio , Tommaso Giani , Joseph Karpie , Kostas Orginos , Anatoly Radyushkin , Savvas Zafeiropoulos (1)

1 CPT - Centre de Physique Théorique - UMR 7332

We extract two nonsinglet nucleon Parton Distribution Functions from lattice QCD data for reduced Ioffe-time pseudodistributions. We perform such analysis within the NNPDF framework, considering data coming from different lattice ensembles and dis- cussing in detail the treatment of the different source of systematics involved in the fit. We introduce a recipe for taking care of systematics and use it to perform our extraction of light-cone PDFs.

Mots clés: Lattice field theory simulation; QCD Phenomenology; nucleon: parton: distribution function; quantum chromodynamics; lattice field theory; neural network; light cone

Domaines: Physique des Hautes Energies - Phénoménologie [hep-ph]; Physique des Hautes Energies - Réseau [hep-lat]

Luigi del Debbio, Tommaso Giani, Joseph Karpie, Kostas Orginos, Anatoly Radyushkin, et al.. Neural-network analysis of Parton Distribution Functions from Ioffe-time pseudodistributions. Journal of High Energy Physics, 2021, 02, pp.138. ⟨10.1007/JHEP02(2021)138⟩. ⟨hal-02981231⟩