基于量子纠缠的非线性拓扑优化算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the application of quantum entanglement to optimize complex, non-linear topological structures. Traditional optimization algorithms often struggle with the inherent complexity of these problems, especially when dealing with non-linear constraints. We propose a novel algorithm, termed "Entangled Optimization," that leverages quantum entanglement to accelerate search and potentially discover optimal solutions by introducing entangled states that guide the optimization process. We demonstrate the effectiveness of this approach through a simplified, yet illustrative, example involving a constrained topological structure. The core mechanism centers around manipulating entanglement to effectively "tunnel" solutions within the search space, leading to improved efficiency and the potential for discovering novel topological configurations. We discuss the challenges and future directions of this research, highlighting the promise of quantum optimization for tackling complex topological problems.

DOI: 10.5281/zenodo.22186228

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