arXiv Machine Learning September 17, 2026 By Koji Hashimoto, Hyun-Sik Jeong, Keun-Young Kim, Daichi Takeda, Kwan Yun

Deep learning emergent spacetime from fermionic spectral functions in holography

Read the original on arXiv Machine Learning →

arXiv:2609. 18566v1 Announce Type: cross Abstract: We present a physics-informed machine learning framework based on Neural Ordinary Differential Equations that solves the holographic inverse problem: reconstructing the bulk spacetime and gauge field of a charged AdS black hole directly from boundary fermionic spectral functions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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