Amortized neural posterior estimation reproduces nested sampling constraints on RMF couplings for neutron-star EOS with no bias and generates 30,000 samples in 2.5 seconds.
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Bayesian modeling with informed priors reduces uncertainties in neutron-star crust shear properties, predicting torsional mode frequencies of 20-50 Hz compatible with observations.
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Amortized Simulation-Based Inference of Relativistic Mean-Field Couplings for Neutron-Star Equations of State
Amortized neural posterior estimation reproduces nested sampling constraints on RMF couplings for neutron-star EOS with no bias and generates 30,000 samples in 2.5 seconds.
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Bayesian analysis of the shear modulus in the neutron-star crust
Bayesian modeling with informed priors reduces uncertainties in neutron-star crust shear properties, predicting torsional mode frequencies of 20-50 Hz compatible with observations.