2 citations · 2 across the 7 of their papers we have counts for
8 papers · 1 filter
Likelihood \& Correlation Analysis of Electroproduction for Proton Tensor Charge Extraction
Saraswati Pandey, Douglas Q. Adams, Simonetta Liuti +3
We present a likelihood analysis of observables in deeply virtual exclusive electro-production off the proton. We use experimental data for the cross section as well as the b…
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…
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…
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…
Likelihood and Correlation Analysis of Compton Form Factors for Deeply Virtual Exclusive Scattering on the Nucleon
Douglas Q. Adams, Joshua Bautista, Marija Cuic +11
A likelihood analysis of the observables in deeply virtual exclusive photoproduction off a proton target, , is presented. Two processes contribute to the r…
Variational autoencoder inverse mapper for extraction of Compton form factors: Benchmarks and conditional learning
Fayaz Hossen, Douglas Adams, Joshua Bautista +8
Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from gene…
VAIM-CFF: A variational autoencoder inverse mapper solution to Compton form factor extraction from deeply virtual exclusive reactions
Manal Almaeen, Tareq Alghamdi, Brandon Kriesten +4
We develop a new methodology for extracting Compton form factors (CFFs) in from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized in…