拓扑优化算法的量子化驱动

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper explores the application of quantum-enhanced optimization algorithms to complex geometric structures, specifically focusing on topology optimization. Traditional optimization methods often struggle with intricate geometries, leading to computational bottlenecks and suboptimal solutions. We propose a novel approach that leverages quantum entanglement to encode and manipulate topological structures, enabling a fundamentally different optimization process. This research investigates the potential of quantum-driven optimization to address challenges in fields like engineering design, materials science, and computational geometry. The core of our work centers on a quantum-based representation of topological properties and the utilization of entangled quantum states to guide the optimization process towards efficient solutions. We detail the proposed quantum mechanism, the mathematical foundations underpinning the algorithm, and preliminary experimental results demonstrating improved performance compared to classical optimization techniques in specific geometric datasets. This work contributes to the advancement of quantum-enhanced optimization, offering a pathway towards solving complex problems with enhanced efficiency and robustness.

DOI: 10.5281/zenodo.22267855

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