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 Office of Nuclear Physics (NP) has supported applications of artificial neural networks in the analysis of nuclear physics data for decades. Today, AI-ML scope can be found in all NP research subprograms. Technical developments at the intersections between real-time machine learning and control, and the optimization of accelerator systems and detector design using AI models and ML techniques manage extremely large and information-rich data sets, increase 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 technical challenges in simulations, control, data acquisition, and analysis. AI-ML methods and techniques address these challenges and shorten the timeline for experimental and computational discovery.

 

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

 

Contacts

Manouchehr Farkhondeh
Advanced Technology R&D
[email protected]