This AI Paper from the University of Tokyo has Applied Deep Learning to the Problem of Supernova Simulation

Researchers from the University of Tokyo have developed a deep learning model called 3D-Memory In Memory (3D-MIM) to predict the expansion of a supernova (SN) shell following a SN explosion. This innovation addresses a critical issue in high-resolution galaxy simulations using massively parallel computing, where the short integration time-steps required for SNe pose significant bottlenecks. […]

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