Reweighting the Sivers function with jet data from STAR

TL;DR

This paper applies a Bayesian reweighting method to update the quark Sivers function using new jet asymmetry data from STAR, significantly improving our understanding without re-fitting.

Contribution

It extends the reweighting technique to handle asymmetric errors and demonstrates its effectiveness with STAR jet data.

Findings

Enhanced constraints on the quark Sivers function.

Significant reduction in uncertainties of the Sivers function.

Broader x coverage from jet data improves the extraction.

Abstract

The reweighting procedure that using Bayesian statistics incorporates the information contained in a new data set, without the need of re-fitting, is applied to the quark Sivers function extracted from Semi-Inclusive Deep Inelastic Scattering (SIDIS) data. We exploit the recently published single spin asymmetry data for the inclusive jet production in polarized $pp$ collisions from the STAR Collaboration at RHIC, which cover a much wider $x$ region compared to SIDIS measurements. The reweighting method is extended to the case of asymmetric errors and the results show a remarkable improvement of the knowledge of the quark Sivers function.