Iterative Monte Carlo analysis of spin-dependent parton distributions

TL;DR

This paper introduces a new iterative Monte Carlo method for analyzing polarized parton distributions, incorporating recent high-precision data to improve uncertainty estimates and determine flavor-separated twist-3 PDFs.

Contribution

It presents a novel Monte Carlo fitting technique for polarized PDFs, including the first global analysis of flavor-separated twist-3 distributions and the $d_2$ moment.

Findings

Reduced PDF errors for valence and sea quarks due to Jefferson Lab data

Lowered gluon polarization uncertainty at high x

First determination of flavor-separated twist-3 PDFs and the $d_2$ moment

Abstract

We present a comprehensive new global QCD analysis of polarized inclusive deep-inelastic scattering, including the latest high-precision data on longitudinal and transverse polarization asymmetries from Jefferson Lab and elsewhere. The analysis is performed using a new iterative Monte Carlo fitting technique which generates stable fits to polarized parton distribution functions (PDFs) with statistically rigorous uncertainties. Inclusion of the Jefferson Lab data leads to a reduction in the PDF errors for the valence and sea quarks, as well as in the gluon polarization uncertainty at $x \gtrsim 0.1$. The study also provides the first determination of the flavor-separated twist-3 PDFs and the $d_2$ moment of the nucleon within a global PDF analysis.