Evaluating the Convergence of Tabu Enhanced Hybrid Quantum Optimization

TL;DR

This paper introduces a Tabu Enhanced Hybrid Quantum Optimization method, analyzing its convergence and demonstrating its effectiveness on both quantum and classical hardware for solving optimization problems.

Contribution

It presents a novel hybrid quantum optimization algorithm with convergence analysis and empirical evaluation on quantum and classical hardware.

Findings

Convergence of the algorithm is theoretically analyzed.

Algorithm performs effectively on quantum hardware.

Algorithm also tested successfully on classical hardware.

Abstract

In this paper we introduce the Tabu Enhanced Hybrid Quantum Optimization metaheuristic approach useful for optimization problem solving on a quantum hardware. We address the theoretical convergence of the proposed scheme from the viewpoint of the collisions in the object which stores the tabu states, based on the Ising model. The results of numerical evaluation of the algorithm on quantum hardware as well as on a classical semiconductor hardware model are also demonstrated.