基于量子纠缠的动态拓扑的自适应路径规划

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper investigates the potential of leveraging quantum entanglement for dynamic topology optimization within pathfinding algorithms. Traditional pathfinding methods often struggle with dynamically changing environments, necessitating the development of adaptive algorithms. We propose a novel approach that utilizes quantum entanglement to dynamically adjust the topology of a path, enhancing computational efficiency and stability. The core mechanism involves encoding and manipulating entangled states to guide the exploration of the search space. This research explores the design of an entanglement-based algorithm capable of finding optimal paths in complex, evolving environments. We demonstrate the effectiveness of this approach through simulations and preliminary experiments, showcasing significant improvements in pathfinding performance compared to existing techniques.

DOI: 10.5281/zenodo.22266410

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