Speaker
Simonetta Liuti
(Argonne National Laboratory)
Description
I will describe a framework defining benchmarks for the analysis of polarized exclusive scattering cross sections using physics constraints including lattice QCD, built into machine learning (ML) algorithms. Both physics driven and ML based benchmarks are applied to a wide range of deeply virtual exclusive processes through explainable ML techniques with controllable uncertainties. The observables, namely the Compton Form Factors (CFFs) which are convolutions of Generalized Parton Distributions (GPDs), are extracted using a quantification technique, the random targets method, that allows us to address the separation of aleatoric and epistemic uncertainties in exclusive scattering analyses.
Primary author
Simonetta Liuti
(Argonne National Laboratory)
