Continuous spin gravity yields GW time-delay deviations of order ρ_g/ω from GR predictions for frequencies above ρ_g, with damping below, enabling sensitivity to spin scales ~10^{-14} eV at ground interferometers and ~10^{-24} eV at PTAs.
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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.
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First look at continuous spin gravity: Time delay signatures
Continuous spin gravity yields GW time-delay deviations of order ρ_g/ω from GR predictions for frequencies above ρ_g, with damping below, enabling sensitivity to spin scales ~10^{-14} eV at ground interferometers and ~10^{-24} eV at PTAs.
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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.