基于量子自旋场的拓扑拓扑优化算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm based on quantum spin fields, leveraging the dynamic nature of these fields to optimize complex systems' topology. We propose a quantum-enhanced approach that dynamically adjusts the quantum spin configurations within a system, enabling more accurate and robust optimization compared to classical methods. The core mechanism involves a quantum state transfer and adaptation process, guided by the inherent properties of quantum spin dynamics. The algorithm's effectiveness is demonstrated through a series of illustrative examples, showcasing improved convergence and solution quality in specific optimization scenarios. This research explores the potential of quantum spin fields to revolutionize optimization techniques across diverse scientific and engineering domains.

DOI: 10.5281/zenodo.22184043

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