基于量子纠缠的动态概率分布优化算法

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum entanglement offers a fundamentally different approach to optimization compared to classical algorithms. This paper proposes a novel dynamic probability distribution optimization algorithm utilizing quantum entanglement to dynamically adjust probability distribution parameters during the optimization process. We demonstrate the effectiveness of this approach through a series of simulations, showcasing improved performance and robustness compared to traditional methods. The core mechanism involves leveraging the inherent properties of entangled states to create a more adaptive and efficient optimization strategy.

DOI: 10.5281/zenodo.22635152

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