Variational Amplitude Amplification for Solving QUBO Problems

Abstract

We investigate the use of amplitude amplification on the gate-based model of quantum computing as a means for solving combinatorial optimization problems. This study focuses primarily on quadratic unconstrained binary optimization (QUBO) problems, which are well-suited for qubit superposition states. Specifically, we demonstrate circuit designs which encode QUBOs as ‘cost oracle’ operations UC, which distribute phases across the basis states proportional to a cost function. We then show that when UC is combined with the standard Grover diffusion operator Us, one can achieve high probabilities of measurement for states corresponding to optimal and near optimal solutions while still only requiring O(π42N/M) iterations. In order to achieve these probabilities, a single scalar parameter ps is required, which we show can be found through a variational quantum–classical hybrid approach and can be used for heuristic solutions.