Department of Energy Announces $16 Million for Research on Artificial Intelligence and Machine Learning (AI/ML) for Nuclear Physics Accelerators and Detectors

Projects will advance understanding of atomic structure and the nature of matter

The following news bulletin was issued by the U.S. Department of Energy (DOE) Office of Science. It includes funding for a project led by DOE’s Brookhaven National Laboratory to increase the polarization (magnetic alignment) of atomic nuclei in beams fed into the Relativistic Heavy Ion Collider (RHIC)—a DOE Office of Science user facility for nuclear physics research at DOE’s Brookhaven National Laboratory—and the future Electron-Ion Collider (EIC), now under construction at Brookhaven. The announcement also includes funding for a project on beam polarization led by Thomas Jefferson National Laboratory, Brookhaven’s partner in building the EIC; one led by Los Alamos National Laboratory on fast data processing and artificial-intelligence (AI)-driven detector control for the sPHENIX detector at RHIC and for a future EIC detector; and a project led by The College of William & Mary on AI-assisted detector design for the EIC. For more information about these projects or the EIC, contact Karen McNulty Walsh,, 631-344-8350.

Today, the U.S. Department of Energy (DOE) announced $16 million for fifteen projects that will implement artificial intelligence methods to accelerate scientific discovery in nuclear physics research.

These projects will use AI/ML tools and methods for nuclear physics experiments, simulation, theory, and accelerator operation to expand and accelerate scientific reach.

“Artificial intelligence has the potential to shorten the timeline for experimental discovery in nuclear physics,” said Timothy Hallman, DOE Associate Director of Science for Nuclear Physics. “Particle accelerator facilities and nuclear physics instrumentation face a variety of technical challenges in simulations, control, data acquisition, and analysis that artificial intelligence holds promise to address.”

The fifteen projects will be conducted by nuclear physics researchers at eight DOE national laboratories and 22 universities. Projects will include the development of deep learning algorithms to identify a unique signal for studying physics of fundamental symmetry in extremely rare nuclear decays that if observed would demonstrate how our universe could have become dominated by matter rather than antimatter. Supported efforts also include AI-driven detector design for the Electron-Ion Collider (EIC) accelerator project under construction at Brookhaven National Laboratory (BNL) that will probe the internal structure and forces of protons and neutrons that compose the atomic nucleus. Also, several accelerator beam optimization projects using AI/ML tools will be funded at scientific user facilities supported by Nuclear Physics including the Facility for Rare Isotope Beams at Michigan State University, the Relativistic Heavy Ion Collider at BNL, and the future EIC, to be located at BNL.

The projects are supported by the DOE Office of Science, Nuclear Physics Program. 

Awards were selected by competitive peer review. Total planned funding is $16 million, with $8 million in Fiscal Year 2023 dollars and outyear funding contingent on congressional appropriations. The list of projects and more information can be found on the Nuclear Physics homepage.

Selection for award negotiations is not a commitment by DOE to issue an award or provide funding. Before funding is issued, DOE and the applicants will undergo a negotiation process, and DOE may cancel negotiations and rescind the selection for any reason during that time.

2023-21408  |  INT/EXT  |  Newsroom