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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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.
Long-term numerical-relativity runs find isolated neutron stars with an external dipole relax to a stable mixed poloidal-toroidal field with toroidal energy ≲10% after Tayler saturation.
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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Magnetic field dynamics in isolated neutron stars with an external dipole field
Long-term numerical-relativity runs find isolated neutron stars with an external dipole relax to a stable mixed poloidal-toroidal field with toroidal energy ≲10% after Tayler saturation.