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gr-qc2026
Towards solving General Relativity with Physics-Informed Neural Networks
Juan A. Carretero, Jorge F. Urbán, Fernando Abalos +4
Physics-Informed Neural Networks (PINNs) are a machine-learning framework for approximating solutions to systems of partial differential equations by constraining neural networks t…
astro-ph.HE2026
Signatures of Compact Object Mergers Inside Stars in AGN Disks
Matteo Cantiello, Alexander J. Dittmann, Saavik Ford +4
Disks of gas accreting onto supermassive black holes, powering active galactic nuclei (AGN), can capture stars from nuclear star clusters or form stars in situ via gravitational in…