Systems and methods for accelerated quantum optimization

Abstract

Example methods for quantum optimization include applying an optimization algorithm to a problem Hamiltonian (defined by qubit interaction constraint coefficients based on a binary optimization problem to find a local minimum state with initial total energy). The method further includes selecting a target energy that is less than the initial energy based on the binary optimization problem, modifying a subset of the qubit interaction constraint coefficient of the interaction constraint coefficients by a selected amount to reduce a total energy of the local minimum state to approximate the target total energy to provide an updated problem Hamiltonian, evolving a many-body quantum system (MBQS) based on the updated problem Hamiltonian by applying oscillating fields to single qubit transverse field terms and/or to transverse inter-qubit couplings of the MBQS for a time period, determining the total energy relative to the problem Hamiltonian based on the MBQS after expiration of the time period.