Speaker
Prof.
Liuti Simonetta
Description
I will present a framework for the analysis of deeply virtual exclusive scattering experiments to enable the extraction of observables from data with a faithful representation of uncertainty. The extraction is focused on obtaining the different quark flavor and scale dependence of the various observables at NLO in perturbative QCD, while using the azimuthal phase dependence as a discriminant of twist three terms. Establishing benchmarks in both the phenomenology and computational/machine learning sectors is critical to this effort which is poised for optimizing and generalizing the information extracted from data.
| Submitted on behalf of a Collaboration? | No |
|---|---|
| Participate in poster competition? | No |
Primary authors
Adil Khawaja
(University of Virginia)
Joshua Bautista
(University of Virginia)
Prof.
Liuti Simonetta
Zaki Panjsheeri
