基于量子纠缠的动态算法优化

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Quantum entanglement, a peculiar quantum mechanical phenomenon, offers a fundamentally new approach to optimization problems. This paper proposes a novel dynamic algorithm framework based on quantum entanglement to address complex optimization challenges. We introduce a method that leverages the inherent, self-changing nature of entangled quantum states to achieve optimization, and subsequently develop an optimized algorithm for large-scale problems. The core mechanism centers around manipulating entangled states to guide the search process, offering a potential paradigm shift in optimization techniques. This research explores the potential of quantum entanglement for enhancing optimization capabilities, aiming to deliver more efficient and robust solutions compared to classical approaches.

DOI: 10.5281/zenodo.22330293

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