Can machine learning improve computer models enough to ignite internal-confinement fusion?

摘要

Machine learning applied to the University of Rochester's OMEGA laser increased fusion yields; the same could happen at the National Ignition facility (NIF), too. Laser-fusion researchers have turned to machine-learning techniques to seek the combinations of laser pulse characteristics and target design needed to optimize target implosions for inertial confinement fusion (ICF). This could be an important boost for a program that has struggled to meet the ambitious goal of igniting a fusion plasma, which is a crucial milestone for ICF energy production.