CosmoGAN: Training a neural network to study dark matter
As cosmologists and astrophysicists delve deeper into the darkest recesses of the universe, their need for increasingly powerful observational and computational tools has expanded exponentially. From facilities such as the Dark Energy Spectroscopic Instrument to supercomputers like Lawrence Berkeley National Laboratory’s Cori system at the National Energy Research Scientific Computing (NERSC) facility, they are on a quest to collect, simulate, and analyze increasing amounts of data that can help explain the nature of things we can’t see, as well as those we can.
phys.org
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2019-05-16
