Artificial Intelligence (AI)

Image courtesy of Thomas Jefferson National Accelerator Facility

A.I. for Nuclear Physics workshop hosted by Thomas Jefferson National Accelerator Facility (TJNAF) explored the ways in which artificial intelligence can be used to advance research in fundamental nuclear physics and in the design and operation of large-scale accelerator facilities. Logo graphic from the A.I. for Nuclear Physics workshop website was provided courtesy of TJNAF.


The Nuclear Physics (NP) program supports fundamental research to understand nuclear matter for public benefit. NP has been supporting applications of artificial neural networks in the analysis of nuclear physics data for decades. Additionally, NP is supporting technical development at the intersections between real-time machine learning and control, and the optimization of accelerator systems and detector design using artificial intelligence (AI) models. That foundation in the use of machine learning techniques is now revolutionizing how extremely large and information-rich data sets are interpreted, greatly increasing the discovery potential of present and future experiments at NP facilities and future machines, such as the Electron-Ion Collider (EIC). These facilities and scientific instrumentation face a variety of technical challenges in simulations, control, data acquisition, and analysis. Data analytics and AI methods and techniques promise to address these challenges and shorten the timeline for experimental and computational discovery. NP has expanded the FY2023 AI-ML funding opportunity to all areas of Nuclear Physics Research areas.


DOE Press Releases


NP Funding Opportunity Announcements & Awards Lists

  • Data, Artificial Intelligence, and Machine Learning at Scientific User Facilities (LAB 20-2261 FOA), (Award List), 2020.
  • Data Analytics for Autonomous Optimization and Control of Accelerators and Detectors (FOA-0002490), 2021.
  • Artificial intelligence and Machine Learning for Autonomous Optimization and Control of Accelerators and Detectors (DE-FOA-0002875), 2023.


NP Workshops



Manouchehr Farkhondeh
Advanced Technology R&D