Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics
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DOI: 10.3390/sym13112157
Abstract: The numerical solution of relativistic hydrodynamics equations in conservative form requires root-finding algorithms that invert the conservative-to-primitive variables map. These algorithms employ the equation of state of the fluid and can be computationally demanding for… read more here.
Keywords: relativistic hydrodynamics; machine learning; neural networks; hydrodynamics ... See more keywords