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.
@article{arxiv.2209.01799,
title = {Evaluating the Convergence of Tabu Enhanced Hybrid Quantum Optimization},
author = {Enrico Blanzieri and Davide Pastorello and Valter Cavecchia and Alexander Rumyantsev and Mariia Maltseva},
journal= {arXiv preprint arXiv:2209.01799},
year = {2022}
}