Super-resolving Dark Matter Halos using Generative Deep Learning. (arXiv:2111.06393v2 [astro-ph.CO] UPDATED)

Generative deep learning methods built upon Convolutional Neural Networks
(CNNs) provide a great tool for predicting non-linear structure in cosmology.
In this work we predict high resolution dark matter halos from large scale, low
resolution dark matter only simulations. This is achieved by mapping lower
resolution to higher resolution density fields of simulations sharing the same
cosmology, initial conditions and box-sizes. To resolve structure down to a
factor of 8 increase in mass resolution, we use a variation of U-Net …

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