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Author

Estuti Shukla

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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

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