cs.AI updates on arXiv.org 07月08日
Particle Swarm Optimization for Quantum Circuit Synthesis: Performance Analysis and Insights
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本文探讨粒子群优化(PSO)在生成量子电路解决MaxOne问题中的应用,分析进化算法在电路合成中的研究,并通过实验比较PSO与遗传算法在量子电路合成中的性能。

arXiv:2507.02898v1 Announce Type: cross Abstract: This paper discusses how particle swarm optimization (PSO) can be used to generate quantum circuits to solve an instance of the MaxOne problem. It then analyzes previous studies on evolutionary algorithms for circuit synthesis. With a brief introduction to PSO, including its parameters and algorithm flow, the paper focuses on a method of quantum circuit encoding and representation as PSO parameters. The fitness evaluation used in this paper is the MaxOne problem. The paper presents experimental results that compare different learning abilities and inertia weight variations in the PSO algorithm. A comparison is further made between the PSO algorithm and a genetic algorithm for quantum circuit synthesis. The results suggest PSO converges more quickly to the optimal solution.

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粒子群优化 量子电路 MaxOne问题 算法比较 进化算法
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