Speaker
Description
We extend the asymmetric frame formalism for Generalized Parton Distributions (GPDs) to nonzero skewness by incorporating longitudinal momentum transfer. This framework, based on Lorentz-invariant amplitudes, provides efficient access to broad kinematics for mapping GPDs from the lattice. We validate the formalism using lattice data, extracting coordinate-space amplitudes to determine GPDs H and E, followed by quasi-distribution reconstruction and matching to the light cone. Additionally, we present an analysis of Mellin moments using neural network parameterizations to fit lattice data. This approach incorporates Next-to-Leading Order matching and renormalization group resumation evolution to obtain the final results. The principal challenges for nonzero skewness GPDs are also identified and discussed.