Artificial Intelligence and Machine Learning for Autonomous Optimization and Control of Accelerators and Detectors
Funding Agency:
- Department of Energy
The DOE SC program in Nuclear Physics (NP) hereby announces its interest in receiving applications for research and development (R&D) efforts directed at artificial intelligence (AI) and machine learning (ML) for autonomous optimization and control of accelerators and detectors of relevance to current or next generation NP accelerator facilities and scientific instrumentation. Current and planned NP facilities and scientific instrumentation face a variety of technical challenges in simulations, control, data acquisition, and analysis. AI methods and techniques promise to address these challenges and shorten the timeline for experimental and computational discovery.
NP supports a broad range of activities aimed at R&D related to the science, engineering, and technology of heavy ion, electron, and proton accelerators and associated systems, as well as a suite of NP scientific instrumentation that operate at facilities around the world, and standalone. NP operates four accelerator-based national user facilities in accomplishing its mission: the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL), the Continuous Electron Beam Accelerator Facility (CEBAF) at the Thomas Jefferson National Accelerator Facility (TJNAF), the Argonne Tandem Linac Accelerator System (ATLAS) at Argonne National Laboratory (ANL), and the Facility for Rare Isotope Beams Facility (FRIB) at Michigan State University (MSU). Finally, NP is constructing a high energy, polarized electronion collider (EIC) that will be located at BNL.
Multiple awards are expected; $2,000,000 for two years
$16,000,000
January 11, 2023, at 11:59 PM Eastern Time
Dr. Manouchehr Farkhondeh 301-903-4398 Manouchehr.farkhondeh@science.doe.gov