First neural-network subgrid model for special relativistic MHD reproduces 4x-higher-resolution magnetic field amplification in 3D Kelvin-Helmholtz tests at 44x speedup.
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A rescaling algorithm for artificial atmospheres achieves exact mass and electron number conservation to round-off precision in binary neutron star merger simulations.
citing papers explorer
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Subgrid Modelling for Relativistic Magnetohydrodynamics with Machine Learning
First neural-network subgrid model for special relativistic MHD reproduces 4x-higher-resolution magnetic field amplification in 3D Kelvin-Helmholtz tests at 44x speedup.
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Exact Mass Conservation in Binary Neutron Star Merger Simulations
A rescaling algorithm for artificial atmospheres achieves exact mass and electron number conservation to round-off precision in binary neutron star merger simulations.