5 papers
Holographic Learning from Fermionic Spectra: Application to Strange Metal Phenomenology
Hong-Zhi Xiao, Zhan-Zhi He, Zhuo-Yu Xian +1
We develop a data-driven framework based on Neural ODEs that learns the effective bulk metric functions and the charge-weighted gauge potential of a static, planar-symmetric…
Learning geometries beyond asymptotic AdS
Cheng Ran, Shao-Feng Wu, Zhuo-Yu Xian
We present a data-driven method for holographic bulk reconstruction that works even when the spacetime is not asymptotically AdS. Given the data of boundary Green functions within…
The Algebraic Structure Underlying Pole-Skipping Points
Zhenkang Lu, Cheng Ran, Shao-feng Wu
The holographic Green's function becomes ambiguous, taking the indeterminate form `', at an infinite set of special frequencies and momenta known as ``pole-skipping points''.…
Bulk Spacetime Encoding via Boundary Ambiguities
Zhenkang Lu, Cheng Ran, Shao-feng Wu
We propose a method to reconstruct the metric and its arbitrary-order derivatives at the horizon for any static, planar-symmetric black hole, using an infinite set of discrete pole…
Discover physical concepts and equations with machine learning
Bao-Bing Li, Yi Gu, Shao-Feng Wu
Machine learning can uncover physical concepts or physical equations when prior knowledge from the other is available. However, these two aspects are often intertwined and cannot b…