基于量子纠缠的非线性优化算法

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper investigates the potential of utilizing quantum entanglement for optimization algorithms, specifically targeting complex optimization problems with non-linear constraints. We propose a novel non-linear optimization algorithm predicated on quantum entanglement, aiming to enhance the exploration of the solution space and facilitate the discovery of global optima. The core mechanism revolves around leveraging entanglement to induce non-linearity within the optimization process, thereby enabling the algorithm to navigate complex landscapes more effectively than classical methods. This work explores the theoretical underpinnings and potential practical applications of this approach, highlighting its novelty through the design of a fundamentally new modeling methodology. The paper details the proposed algorithm's structure, analysis of its performance characteristics, and initial experimental results demonstrating the algorithm's efficacy in challenging optimization scenarios.

DOI: 10.5281/zenodo.22281227

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