自适应拓扑几何的基于量子纠缠的拓扑变换

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper investigates the application of self-adaptive topology and quantum entanglement to transform geometric data. Traditional topological analysis often relies on static models, while this work proposes a novel algorithm leveraging quantum entanglement to induce dynamic and complex geometric transformations. The core mechanism centers around utilizing the entanglement-induced correlations to generate novel geometric structures, offering a potential pathway for enhanced quantum computation. We introduce a novel approach to quantum geometry, detailing the algorithm's design, key steps, and preliminary results demonstrating the feasibility of its implementation. This work explores how entanglement can be harnessed to create and manipulate geometric space, paving the way for new computational paradigms.

DOI: 10.5281/zenodo.22495411

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