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

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Detaylı Bibliyografya
Yayımlandı:	Symmetry vol. 17, no. 9 (2025), p. 1409-1426
Yazar:	Kacmaz Semih
Diğer Yazarlar:	Haas, Roland, Huerta, E A
Baskı/Yayın Bilgisi:	MDPI AG
Konular:	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
Online Erişim:	Citation/Abstract Full Text + Graphics Full Text - PDF
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