Speaker
Description
Understanding the 3D quark-gluon structure of nucleons is entering an era of precision, which is furthered by the 12 GeV upgrade at Jefferson Lab and the upcoming EIC. I will give an overview of the work done by the EXCLusives via Artificial Intelligence and Machine learning (Exclaim) collaboration, an interdisciplinary effort by ML experts, nuclear theorists and experimentalists centered around building physics informed deep-learning architectures, which utilize new experimental data and first-principle lattice QCD calculations in order to access the 3D structure of matter. Our approach offers a benchmarking framework for studying various Deeply Virtual Exclusive Scattering processes and extracting Compton Form Factors and Generalized Parton Distributions.
