Aspects of holographic entanglement using physics-informed-neural-networks

Anirudh Deb; Yaman Sanghavi

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arXiv · 2509.25311

Aspects of holographic entanglement using physics-informed-neural-networks

Anirudh Deb·Yaman Sanghavi

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Abstract

We implement physics-informed-neural-networks (PINNs) to compute holographic entanglement entropy and entanglement wedge cross section. This technique allows us to compute these quantities for arbitrary shapes of the subregions in any asymptotically AdS metric. We test our computations against some known results and further demonstrate the utility of PINNs in examples, where it is not straightforward to perform such computations.

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Anirudh Deb, Yaman Sanghavi. 2025-09-29. Aspects of holographic entanglement using physics-informed-neural-networks. https://arxiv.org/abs/2509.25311

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