基于自适应的量子计算的拓扑优化算法

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper presents a novel quantum computing algorithm for topology optimization, leveraging the inherent properties of quantum computation to dynamically adjust the structure of a given topology. Traditional topology optimization methods often rely on static, pre-defined structures, limiting their adaptability to complex, dynamic environments. Our proposed algorithm utilizes quantum superposition and entanglement to explore multiple solution spaces simultaneously, resulting in improved efficiency and the ability to find more optimal solutions. We demonstrate the effectiveness of this approach through simulations and preliminary experimental results. The core mechanism centers around a quantum-enhanced iterative adjustment of a topological structure, allowing the algorithm to efficiently explore a vast solution space and identify optimal configurations. We highlight the advantages of this approach, including robustness to noise and the potential for discovering novel topological structures.

DOI: 10.5281/zenodo.22504051

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