9 papers
Markov chain Monte Carlo (MCMC) based Likelihood Extraction of Chiral-Odd Compton Form Factors from Deeply Virtual Exclusive Experiments
Saraswati Pandey, Douglas Q. Adams, Simonetta Liuti
We present a likelihood analysis of observables in deeply virtual exclusive meson production off the proton. The study uses experimental data for cross sections together with beam…
Neural Network Generalized Parton Distributions (NNGPD)
Zaki Panjsheeri, Simonetta Liuti
Generalized parton distributions (GPDs) serve as indispensable tools for the exploration of proton structure. In this study, we offer a deep learning-assisted framework for the ext…
Neural Network Representation of Generalized Parton Distributions (NNGPD)
Jitao Xu, Ho Jang, Zaki Panjsheeri +10
We present a neural-network-based framework for modeling generalized parton distributions, referred to as NNGPD, in which GPDs are represented as flexible functions constrained thr…
Connected and disconnected contributions to nucleon form factors and parton distributions
Zaki Panjsheeri, Saraswati Pandey, Brannon Semp +1
Using the framework of generalized parton distribution, we provide a unified interpretation of the connected and disconnected contributions from the ab-initio Euclidean path-integr…
Updated flexible global parametrization of generalized parton distributions from elastic and deep inelastic inclusive scattering data
Zaki Panjsheeri, Douglas Q. Adams, Adil Khawaja +3
An updated flexible parametrization of the generalized parton distributions in the quark, antiquark and gluon sectors is presented using constraints from high precision electron nu…
Generalized Parton Distributions from Symbolic Regression
Andrew Dotson, Zaki Panjsheeri, Anusha Reddy Singireddy +11
AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package ``PySR" to model the and dependenc…