Road to conquer the hardness - solving hard computational problems with generic tensor networks

Abstract

I will introduce a tensor network-based method to compute the solution space properties of a broad class of combinatorial optimization problems (e.g. spin glasses and hard core lattice gases). These properties include finding one of the optimum solutions, counting the number of solutions of a given size, and enumeration and sampling of solutions of a given size. Using the hard core lattice gas as an example, I will demonstrate how the solution space properties can deepen our understanding, and help design better quantum algorithms.