Today, the U.S. Department of Energy (DOE) announced $4.3 million in funding for 16 projects in artificial intelligence (AI) research for high energy physics (HEP). These awards support the DOE Office of Science initiative in artificial intelligence research to use AI techniques to deliver scientific discoveries that would not otherwise be possible, and to broaden participation in high energy physics research.
“AI and Machine Learning (ML) techniques in high energy physics are vitally important for advancing the field,” said Gina Rameika, DOE Associate Director of Science for High Energy Physics. “These awards represent new opportunities for university researchers that will enable the next discoveries in high energy physics.”
Funded projects include constructing models to increase the speed of simulations for cosmology and particle physics; the use of deep learning to develop governing theories; and ML techniques to efficiently and thoroughly search the parameter spaces of likely new theories of particle physics that have their origins at the highest energy scales. These investments also include development of new methods for machine learning in real-time (known as edge computing) for data collection and efforts toward performing robust data analysis with self-consistent ML measurement techniques.