基于量子纠缠的几何变换的动态优化

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

This paper investigates the potential of quantum entanglement to revolutionize geometric optimization, proposing a novel dynamic optimization algorithm leveraging the unique properties of quantum entanglement. We present a theoretical framework that establishes a mechanism for automatically adjusting geometric transformation parameters to achieve enhanced computational efficiency. The core of this approach centers on utilizing entanglement to create a fundamentally different approach to geometric manipulation compared to traditional methods. The paper details the proposed algorithm's structure, discusses potential advantages and challenges, and concludes with a discussion of future research directions. The research aims to explore whether quantum entanglement can offer a paradigm shift in geometric optimization, pushing the boundaries of computational capabilities.

DOI: 10.5281/zenodo.22153063

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