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We present a hybrid classical-quantum algorithm to solve optimizationproblems in current quantum computers, whose basic idea is to assistvariational quantum eigensolvers (VQE) with adiabatic change of theHamiltonian. The rational for this new algorithm is to circumvent the problemof facing very small gradients in the classical optimization piece of a VQE,while being able to run in current hardware efficient devices. A discreteconcatenation of VQEs adapted to interpolating Hamiltonians provides a methodto keep the quantum state always close to a path faithfully directed to findthe final solution. We benchmark this Adiabatically Assisted VariationalQuantum Eigensolver (AAVQE) on quantum Hamiltonians and hard classicalproblems, for which our approach shows fast convergence.

Addressing hard classical problems with Adiabatically Assisted Variational Quantum Eigensolvers