Systems and methods for hybrid quantum-classical computing

Abstract

Hybrid quantum-classical approaches for solving computational problems in which results from a quantum processor are combined with an exact method executed on a classical processor are described. Quantum processors can generate candidate solutions to a combinatorial optimization problem, but since quantum processors can be probabilistic, they are unable to certify that a solution is an optimal solution. A hybrid quantum-classical exact solver addresses this problem by combining outputs from a quantum annealing processor with a classical exact algorithm that is modified to exploit properties of the quantum computation. The exact method executed on a classical processor can be a Branch and Bound algorithm. A Branch and Bound algorithm can be modified to exploit properties of quantum computation including a) the sampling of multiple low-energy solutions by a quantum processor, and b) the embedding of solutions in a regular structure such as a native hardware graph of a quantum processor.