基于量子纠缠的动态时空优化算法

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper presents a novel dynamic time-space optimization algorithm based on quantum entanglement principles. Traditional optimization algorithms often rely on static parameter adjustments, limiting efficiency and generalization. We introduce a quantum state representation and a dynamically-adjusted optimization process that leverages the inherent properties of quantum entanglement to optimize solutions effectively. The algorithm's core mechanism involves creating and manipulating entangled quantum states to represent and modify the optimization landscape, resulting in improved performance across a range of problem instances. This work explores the potential of quantum mechanics to revolutionize optimization methodologies, offering a fundamentally different approach compared to conventional techniques. The proposed algorithm demonstrates promising results on several benchmark problems, showcasing its capability to navigate complex optimization landscapes with enhanced adaptability.

DOI: 10.5281/zenodo.22634972

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