The Department of Energy (DoE) has announced $16 million in funding for 15 different projects that will use artificial intelligence (AI) and machine learning (ML) technologies to further research in nuclear physics.
These projects – supported by the DOE Office of Science’s Nuclear Physics Program – will use AI and ML tools in simulations, physics experimentation, and accelerator operations “to expand and accelerate scientific reach,” stated the department.
“Artificial intelligence has the potential to shorten the timeline for experimental discovery in nuclear physics,” said Timothy Hallman, associate director of science for nuclear physics at the DoE.
“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,” stated Hallman.
The projects will be conducted by eight national laboratories and 22 universities from around the country, and employ “deep learning algorithms to identify a unique signal for studying physics of fundamental symmetry in extremely rare nuclear decays,” stated the department.
The funding will also support the study and research for an AI-driven detector design for the Electron-Ion Collider (EIC) accelerator project that is being created at the Brookhaven National Laboratory (BNL), as well as research into beam optimization projects using AI/ML for Rare Isotope Beams at Michigan State University.
All rewards given for the research were given out as a result of “competitive peer review,” with “with $8 million in Fiscal Year 2023 dollars and outyear funding contingent on congressional appropriations,” stated the department.
