The U.S. Department of Energy (DoE) has announced $16 million for fifteen projects that will implement artificial intelligence (AI) and machine learning (ML) methods to accelerate scientific discovery in nuclear physics research.
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.
“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 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.
Read more at Brookhaven National Laboratory
