RMF-CC models with ωρ coupling better match multi-messenger NS data and LQCD/NEP constraints than the baseline, yet standard RMF remains preferred without core phase transitions, requiring high Ksat ~300 MeV.
F., Gulminelli, F., & Read, J
2 Pith papers cite this work. Polarity classification is still indexing.
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Causal convolutional neural networks reconstruct neutron star observables for static, Keplerian, and rotating configurations in about 50 milliseconds per equation of state, compared to 30 minutes with traditional RNS calculations.
citing papers explorer
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Relativistic Mean Field Approach with Chiral Symmetry Breaking and Quark Confinement in the light of Astrophysical Observations
RMF-CC models with ωρ coupling better match multi-messenger NS data and LQCD/NEP constraints than the baseline, yet standard RMF remains preferred without core phase transitions, requiring high Ksat ~300 MeV.
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Reconstruction of fast-rotating neutron star observables with the neural network
Causal convolutional neural networks reconstruct neutron star observables for static, Keplerian, and rotating configurations in about 50 milliseconds per equation of state, compared to 30 minutes with traditional RNS calculations.