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AI for Nuclear Physics: the EXCLAIM project

Authors :
Liuti, Simonetta
Adams, Douglas
Boër, Marie
Chern, Gia-Wei
Cuic, Marija
Engelhardt, Michael
Kriesten, Gary R. Goldstein Brandon
Li, Yaohang
Lin, Huey-Wen
Sievert, Matt
Sivers, Dennis
Liuti, Simonetta
Adams, Douglas
Boër, Marie
Chern, Gia-Wei
Cuic, Marija
Engelhardt, Michael
Kriesten, Gary R. Goldstein Brandon
Li, Yaohang
Lin, Huey-Wen
Sievert, Matt
Sivers, Dennis
Publication Year :
2024

Abstract

In overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, maximizing the information that can be extracted from various sets of experimental data, while implementing theoretical constraints from lattice QCD. A specific perspective embraced by EXCLAIM is to use the methods of theoretical physics to understand the working of ML, beyond its standardized applications to physics analyses which most often rely on industrially provided tools, in an automated way.<br />Comment: 9 pages, 3 figures

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1477691477
Document Type :
Electronic Resource