Measuring the skewness dependency of Generalized Parton Distributions

TL;DR

This paper explores how the Double Deeply Virtual Compton Scattering process can be used to measure the skewness dependence of Generalized Parton Distributions, offering insights into nucleon structure and nuclear forces.

Contribution

It demonstrates the feasibility of extracting GPD skewness dependence from DDVCS experiments using model predictions and a fitting algorithm at JLab 12 GeV.

Findings

Feasibility of measuring GPD skewness dependence via DDVCS.

Model-based pseudo-data supports extraction of Compton Form Factors.

Potential to improve understanding of nuclear force distributions.

Abstract

Generalized Parton Distributions (GPDs) have emerged over the 1990s as a powerful concept and tool to study nucleon structure. They provide nucleon tomography from the correlation between transverse position and longitudinal momentum of partons. The Double Deeply Virtual Compton Scattering (DDVCS) process consists of the Deeply Virtual Compton Scattering (DVCS) process with a virtual photon in the final state eventually generating a lepton pair, which can be either an electron-positron or a muon-antimuon pair. The virtuality of the final time-like photon can be measured and varied, thus providing an extra lever arm and allowing one to measure the GPDs for the initial and transferred momentum dependences independently. This unique feature of DDVCS is of relevance, among others, for the determination of the distribution of nuclear forces which is accessed through the skewness dependency of GPDs. This proceeding discusses the feasibility and merits of a DDVCS experiment in the context of JLab 12 GeV based on model-predicted pseudo-data and the capability of extraction of Compton Form Factors based on a fitter algorithm.