基于量子纠缠的几何拓扑的自适应调整

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper investigates the potential of quantum entanglement to enable adaptive geometric transformation and optimization within a system. We introduce a novel mechanism leveraging quantum entanglement to dynamically adjust the geometry of a system, offering a potentially transformative approach to geometric manipulation and optimization. The core claim is that a system capable of exploiting quantum entanglement can achieve more effective geometric transformations and optimization compared to conventional methods. This work explores the principles of entanglement-based geometry and proposes a framework for utilizing this phenomenon to guide the evolution of complex systems. The theoretical foundation rests on a simplified model of geometric transformations and explores the implications of quantum entanglement on these transformations. This research addresses a long-standing challenge in computational geometry, potentially opening avenues for advanced optimization and control within various fields.

DOI: 10.5281/zenodo.22267898

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