AI for Nuclear Physics: the EXCLAIM project

TL;DR

The EXCLAIM project aims to develop AI and machine learning frameworks tailored for high energy nuclear physics, integrating experimental data with theoretical constraints from lattice QCD to enhance understanding of scattering processes.

Contribution

It introduces a novel AI framework specifically designed for nuclear physics phenomenology, combining experimental data analysis with theoretical physics constraints.

Findings

Framework maximizes information extraction from experimental data.

Integrates lattice QCD constraints into AI models.

Provides insights into the workings of ML in physics contexts.

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.