Constraints on polarized parton distributions from open charm and W production data

TL;DR

This paper assesses how new open charm muoproduction and W production data influence the understanding of polarized parton distributions, using Bayesian reweighting to update the NNPDFpol1.0 set without full refitting.

Contribution

It introduces a Bayesian reweighting approach to incorporate new experimental data into polarized parton distribution functions efficiently.

Findings

COMPASS data improves gluon polarization knowledge.

STAR data enhances understanding of antiquark polarization.

New data sets significantly refine polarized parton distribution uncertainties.

Abstract

We study the impact of new open charm muoproduction data from COMPASS and preliminary W production data from STAR on NNPDFpol1.0, the first unbiased set of polarized parton distributions recently delivered by the NNPDF Collaboration and based on inclusive Deep-Inelastic Scattering data only. The information contained in the new data sets is incorporated in our Monte Carlo parton determination via Bayesian reweighting, a method based on statistical inference which avoids the need for a global refitting. We explicitly show to which extent COMPASS and STAR data can improve our knowledge of gluon and antiquark polarized parton distributions respectively.