论文标题

评估禁忌增强杂种量子优化的收敛性

Evaluating the Convergence of Tabu Enhanced Hybrid Quantum Optimization

论文作者

Blanzieri, Enrico, Pastorello, Davide, Cavecchia, Valter, Rumyantsev, Alexander, Maltseva, Mariia

论文摘要

在本文中,我们介绍了Tabu增强的混合量子优化的元神经化方法,可用于优化量子硬件解决问题。我们从基于ISING模型的对象中的碰撞的角度来解决所提出的方案的理论融合。还展示了对量子硬件以及经典半导体硬件模型上算法的数值评估结果。

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.

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