Border and skewness functions from a leading order fit to DVCS data

TL;DR

This paper introduces new parameterizations for GPD border and skewness functions, enabling a comprehensive analysis of DVCS data to enhance understanding of nucleon structure and parton distributions.

Contribution

It presents novel GPD parameterizations that satisfy fundamental properties and are constrained through a global fit to DVCS data using the PARTONS framework.

Findings

Successful fit to almost all existing proton DVCS measurements

Enables nucleon tomography and insights into parton force distributions

Careful uncertainty propagation using the replica method

Abstract

We propose new parameterizations for the border and skewness functions appearing in the description of 3D nucleon structure in the language of Generalized Parton Distributions (GPDs). These parameterizations are constructed in a way to fulfill the basic properties of GPDs, like their reduction to Parton Density Functions and Elastic Form Factors. They also rely on the power behavior of GPDs in the $x \to 1$ limit and the propounded analyticity property of Mellin moments of GPDs. We evaluate Compton Form Factors (CFFs), the sub-amplitudes of the Deeply Virtual Compton Scattering (DVCS) process, at the leading order and leading twist accuracy. We constrain the restricted number of free parameters of these new parameterizations in a global CFF analysis of almost all existing proton DVCS measurements. The fit is performed within the PARTONS framework, being the modern tool for generic GPD studies. A distinctive feature of this CFF fit is the careful propagation of uncertainties based on the replica method. The fit results genuinely permit nucleon tomography and may give some insight into the distribution of forces acting on partons.