Non-parametric EOS construction from crust to pQCD forces a sound-speed peak and softening that realizes a generalized quark-hadron crossover in massive neutron stars.
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A physics-informed Bayesian neural network learns neutron-star equations of state from theoretical priors and constraints, then generates posterior mass-radius and mass-tidal-deformability distributions consistent with NICER radii and 2-solar-mass limits.
RGOPT-resummed NNLO pQCD EoS for massive quarks in beta equilibrium is fitted and applied to construct pure quark stars (X=3.08-3.58) and hybrid stars (X~2-2.98) compatible with PSR J0740+6620 and GW190814.
citing papers explorer
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The Non-parametric Equation of State Realizes a Generalized Quark-Hadron Crossover
Non-parametric EOS construction from crust to pQCD forces a sound-speed peak and softening that realizes a generalized quark-hadron crossover in massive neutron stars.
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A Physics Informed Bayesian Neural Network for the Neutron Star Equation of State
A physics-informed Bayesian neural network learns neutron-star equations of state from theoretical priors and constraints, then generates posterior mass-radius and mass-tidal-deformability distributions consistent with NICER radii and 2-solar-mass limits.
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Quark and hybrid stars with renormalization group improvement of NNLO perturbative QCD
RGOPT-resummed NNLO pQCD EoS for massive quarks in beta equilibrium is fitted and applied to construct pure quark stars (X=3.08-3.58) and hybrid stars (X~2-2.98) compatible with PSR J0740+6620 and GW190814.