Machine Learning-Driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State

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書目詳細資料
發表在:	Symmetry vol. 17, no. 9 (2025), p. 1409-1426
主要作者:	Kacmaz Semih
其他作者:	Haas, Roland, Huerta, E A
出版:	MDPI AG
主題:	Accuracy Relativistic effects Neutrons Neutron stars Artificial neural networks Supercomputers Numerical analysis Hydrodynamics Theory of relativity Machine learning Performance evaluation Numerical methods Data points Simulation Datasets Graphics processing units Equations of state Neural networks Optimization Inference Variables Spacetime Methods Algorithms Fluid mechanics Parameter estimation
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