Speaker
Geoffrey Fox
(University of Virginia)
Description
We consider the task of using AI for hadron spectroscopy using partial wave analysis combined with production models. There are new challenges not seen in similar tasks at the LHC coming from the parameterization of amplitudes and not cross sections directly. We also have the opportunity and challenge of combining data from the full reaction with reactions with one or more, and even all particles missing in the final state. AI surrogates can speed up the unfolding process. The extension to a 22 GeV accelerator is considered. We suggest this work should be carefully positioned to make good use of the High Performance Data Facility (HPDF) and help Jefferson Lab configure HPDF to support related AI applications across DOE.
Author
Geoffrey Fox
(University of Virginia)
