2 citations · 2 across the 1 of their papers we have counts for
3 papers
hep-ph2020
Deep Learning Analysis of Deeply Virtual Exclusive Photoproduction
Jake Grigsby, Brandon Kriesten, Joshua Hoskins +3
We present a Machine Learning based approach to the cross section and asymmetries for deeply virtual Compton scattering from an unpolarized proton target using both an unpolarized…
hep-ph2020★ 2 cited
Novel Rosenbluth Extraction Framework for Compton Form Factors from Deeply Virtual Exclusive Experiments
Brandon Kriesten, Simonetta Liuti
We use a generalization of the Rosenbluth separation method for a model independent simultaneous extraction of the Compton Form Factors and , from virtual Comp…
hep-ph2019
Extraction of Generalized Parton Distribution Observables from Deeply Virtual Electron Proton Scattering Experiments
Brandon Kriesten, Simonetta Liuti, Liliet Calero-Diaz +4
We provide the general expression of the cross section for exclusive deeply virtual photon electroproduction from a spin 1/2 target using current parameterizations of the off-forwa…