Computing solution space properties of combinatorial optimization problems via generic tensor networks

Wednesday, June 15, 2022 - 3:00pm

Speaker:  Jinguo Liu, Harvard

Program Description:

I will introduce a tensor network based method to compute the solution space properties of a broad class of combinatorial optimization problems. 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 independent set problem as an example, I will demonstrate how the solution space properties can deepen our understanding, and help design better quantum algorithms.

Paper: arXiv: 2205.03718

Github: https://github.com/QuEraComputing/GenericTensorNetworks.jl

 

 

 

Computing solution space properties of combinatorial optimization problems via generic tensor networks
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