Learning Effective Bulk Fields from Fermionic Spectra: Application to an Extended Power-Law Liquid Model for Cuprate Strange Metals
A data-driven Neural-ODE framework was developed to infer effective bulk metric functions and gauge potentials from fermionic spectral data of cuprate strange metals. The model successfully reproduced known black hole solutions at low temperatures, suggesting a geometric explanation for these materials' unusual electronic properties. However, the framework showed limitations at high temperatures where the geometry became less constrained.