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Author

D. Radice

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Preprint Oct 2026

Puncture Evolution with Physics-Informed Neural Networks

We investigate the application of physics-informed neural networks (PINNs) to solve the vacuum Einstein equations in spherical symmetry. Our neural network architecture is designed to solve the 1+1D moving-puncture evolution, by minimizing a loss that combines a data term, the Ricci tensor of the reconstructed spacetim...

Estuti Shukla, Ashwin Suriyanarayanan, D. Radice et al. · 1 citation
Preprint Oct 2026

Adiabatic evolution of hadronic neutron stars

In this paper we compute several structural properties of static and rotating neutron stars, considering both rigid and differential rotation. To this end, we use a finite-temperature beta-stable equation of state (EOS) extending the zero-temperature hadronic EOS derived by Fortin et al. (2017). We account for the form...

D. Logoteta, Francesco Zeno Constanzo, I. Bombaci et al. · 0 citations

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