基于量子纠缠的非线性几何优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the application of quantum entanglement to enhance geometric optimization, specifically focusing on the design and optimization of complex geometric shapes. Traditional optimization methods often rely on classical computation, while entanglement introduces a novel approach to accelerate optimization processes, particularly in high-dimensional geometric problems. We propose a quantum computing algorithm predicated on entangled states, leveraging their unique properties to facilitate deeper geometric transformations. This research explores the potential of quantum entanglement to overcome limitations in classical optimization techniques, offering a promising pathway towards enhanced efficiency and design capabilities. The core mechanism centers on creating entangled states that facilitate the exploration of intricate geometric forms. This paper details the theoretical framework, algorithm implementation, and preliminary experimental results demonstrating the efficacy of this approach.

DOI: 10.5281/zenodo.22203104

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