Deep learning the holographic black hole with charge

DOI10.1142/S0218271819501530zbMath1432.83010arXiv1908.01470OpenAlexW3102158583WikidataQ127434423 ScholiaQ127434423MaRDI QIDQ5221253

Chong-Bin Chen, Jing Tan

Publication date: 25 March 2020

Published in: International Journal of Modern Physics D (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.01470

zbMATH Keywords

black holeReissner-Nordström black holeholographicdeep learning

Mathematics Subject Classification ID

Black holes (83C57) Geometrodynamics and the holographic principle (83E05) Computational methods for problems pertaining to relativity and gravitational theory (83-08)

Related Items (3)

Reconstructing black hole exteriors and interiors using entanglement and complexity ⋮ Black holes and the loss landscape in machine learning ⋮ Bulk reconstruction of metrics inside black holes by complexity

Uses Software

• PyTorch

Cites Work

• Gauge theory correlators from non-critical string theory
• Non-perturbative 2 particle scattering amplitudes in \(2+1\) dimensional quantum gravity
• Reducing the Dimensionality of Data with Neural Networks
• Causal structure of the entanglement renormalization ansatz
• Learning representations by back-propagating errors

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