Machine learning could solve riddles of galaxy formation

IMAGE: A new, faster modeling technique for galaxy formation has been developed by University of Illinois student Harshil Kamdar and professor Robert Brunner. The technique uses machine learning to cut down… view more Credit: Photo by Joyce Seay-Knoblauch CHAMPAIGN, Ill. — A new machine-learning simulation system developed at the University of Illinois promises cosmologists an expanded suite of galaxy models – a necessary first step to developing more accurate and relevant insights into the formation of the universe. The feasibility of this method has been laid out in two recent papers written by astronomy, physics and statistics professor Robert Brunner, his undergraduate student Harshil Kamdar and National Center for Supercomputing Applications research scientist Matthew Turk. Cosmologists currently use two simulation approaches. The first is an N-body simulation, which models how dark…


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