First neural-network subgrid model for special relativistic MHD reproduces 4x-higher-resolution magnetic field amplification in 3D Kelvin-Helmholtz tests at 44x speedup.
Aguilera-Miret, D
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Resistive GRMHD simulations of rotating neutron stars show resistivity changes magnetic field geometries, suppresses instabilities, and lowers GW emission amplitude while maintaining a consistent 9:1 poloidal-to-toroidal energy ratio over 100 ms.
High-resolution GR neutrino-radiation MHD simulation of 1.35-1.35 Msun BNS merger shows KHI-driven B-field amplification to magnetar levels (~10^50 erg, factor >=316) in 3 ms post-merger.
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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General-relativistic resistive-magnetohydrodynamics simulations of self-consistent magnetized rotating neutron stars
Resistive GRMHD simulations of rotating neutron stars show resistivity changes magnetic field geometries, suppresses instabilities, and lowers GW emission amplitude while maintaining a consistent 9:1 poloidal-to-toroidal energy ratio over 100 ms.
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A magnetar formation in binary neutron star merger
High-resolution GR neutrino-radiation MHD simulation of 1.35-1.35 Msun BNS merger shows KHI-driven B-field amplification to magnetar levels (~10^50 erg, factor >=316) in 3 ms post-merger.