Self-learning AI separates particle jets from background noise in simulated heavy-ion collisions
A team of physicists and computer scientists led by researchers at the U.S. Department of Energy's (DOE) Brookhaven National Laboratory developed a new artificial intelligence (AI) approach that learns on its own to separate important high-energy particle jet signals from the eno
A team of physicists and computer scientists led by researchers at the U.S. Department of Energy's (DOE) Brookhaven National Laboratory developed a new artificial intelligence (AI) approach that learns on its own to separate important high-energy particle jet signals from the eno This story matters for Science & Discovery readers tracking student. Reported by phys.org. Read the full original at the source link below.
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