Topic: correlation functions

Cenke Xu shows how local-spin snapshots from quantum simulators contain information beyond standard correlation functions. The data can recover conformal boundary and defect entropy in the Ising conformal field theory and identify a line of defect fixed points, with a route to higher dimensions. The talk also constructs an interacting spin-liquid wavefunction from experimentally available weakly interacting fermions and discusses initial tests on experimental data.

Deep neural network learning dynamics are very complex with large numbers of learnable weights and many sources of disorder. In this talk, I will discuss mean field approaches to analyze the learning dynamics of neural networks in large system size limits when starting from random initial conditions. The result of this analysis is a dynamical mean field theory (DMFT) where all neurons obey independent stochastic single site dynamics. Correlation functions (kernels) and response functions for the features and gradients at each layer can be computed self-consistently from these stochastic proces