Holographic reconstruction of black hole spacetime: machine learning and entanglement entropy
arXiv:2406.07395 · doi:10.1007/JHEP01(2025)025
Abstract
We investigate the bulk reconstruction of AdS black hole spacetime emergent from quantum entanglement within a machine learning framework. Utilizing neural ordinary differential equations alongside Monte-Carlo integration, we develop a method tailored for continuous training functions to extract the general isotropic bulk metric from entanglement entropy data. To validate our approach, we first apply our machine learning algorithm to holographic entanglement entropy data derived from the Gubser-Rocha and superconductor models, which serve as representative models of strongly coupled matters in holography. Our algorithm successfully extracts the corresponding bulk metrics from these data. Additionally, we extend our methodology to many-body systems by employing entanglement entropy data from a fermionic tight-binding chain at half filling, exemplifying critical one-dimensional systems, and derive the associated bulk metric. We find that the metrics for a tight-binding chain and the Gubser-Rocha model are similar. We speculate this similarity is due to the metallic property of these models.
v1: 44 pages, 14 figures; v2: references added and matching the published version in JHEP
References in corpus (54)
- Building an AdS/CFT superconductor
- A class of quantum many-body states that can be efficiently simulated
- Lectures on Holographic Superfluidity and Superconductivity
- Identifying Topological Order by Entanglement Entropy
- Holographic representation of local bulk operators
- Entropy scaling and simulability by Matrix Product States
- Measuring entanglement growth in quench dynamics of bosons in an optical lattice
- Holographic superconductivity in M-Theory
- Superconductors from Superstrings
- Critical fermi surfaces and non-fermi liquid metals
- Momentum dissipation and effective theories of coherent and incoherent transport
- Holographic Polarons, the Metal-Insulator Transition and Massive Gravity
- Hydrodynamics of Holographic Superconductors
- Entanglement entropy of critical spin liquids
- Thermal diffusivity and chaos in metals without quasiparticles
- Does Complexity Equal Anything?
- Introduction to Holographic Superconductor Models
- Holographic Holes in Higher Dimensions
- Diffusion and Chaos from near AdS horizons
- Nuts and Bolts for Creating Space
- Exploring QCD matter in extreme conditions with Machine Learning
- AdS/CFT as a deep Boltzmann machine
- Colloquium: Hydrodynamics and holography of charge density wave phases
- Deep Learning and AdS/QCD
- Gapless and gapped holographic phonons
- Extracting the bulk metric from boundary information in asymptotically AdS spacetimes
- Magnetophonons & type-B Goldstones from Hydrodynamics to Holography
- Extracting Spacetimes using the AdS/CFT Conjecture: Part II
- Deriving dilaton potential in improved holographic QCD from meson spectrum
- Planar Black Holes in Holographic Axion Gravity: Islands, Page Times, and Scrambling Times
- Numerical metric extraction in AdS/CFT
- Quasi-normal modes of dyonic black holes and magneto-hydrodynamics
- Deep learning bulk spacetime from boundary optical conductivity
- Holographic cameras: an eye for the bulk
- Homes' law in holographic superconductor with linear- resistivity
- Collective dynamics and the Anderson-Higgs mechanism in a bona fide holographic superconductor
- Learning the black hole metric from holographic conductivity
- Kasner interiors from analytic hairy black holes
- T-linear resistivity, optical conductivity and Planckian transport for a holographic local quantum critical metal in a periodic potential
- Breakdown of hydrodynamics from holographic pole collision
- Upper bound of the charge diffusion constant in holography
- Inability of linear axion holographic Gubser-Rocha model to capture all the transport anomalies of strange metals
- Disentangling the gravity dual of Yang-Mills theory
- Machine Learning Statistical Gravity from Multi-Region Entanglement Entropy
- Gravitational Duals from Equations of State
- Aspects of univalence in holographic axion models
- Dual Geometry of Entanglement Entropy via Deep Learning
- On pole-skipping with gauge-invariant variables in holographic axion theories
- Thermo-electric Transport of Dyonic Gubser-Rocha Black Holes
- Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE
- Reconstructing black hole exteriors and interiors using entanglement and complexity
- Transverse Goldstone mode in holographic fluids with broken translations
- Doped Holographic Superconductors in Gubser-Rocha model
- Deep Learning Metric Detectors in General Relativity
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- Learning holographic QCD with unflavored meson spectra