Differential rotation in hybrid stars with deconfinement phase transition allows quasi-toroidal configurations with quark matter rings and leads to degeneracies in rotational profiles at mass-radius curve intersections.
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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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Hybrid Stars with Post-Merger Rotation Profiles
Differential rotation in hybrid stars with deconfinement phase transition allows quasi-toroidal configurations with quark matter rings and leads to degeneracies in rotational profiles at mass-radius curve intersections.
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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.