基于量子纠缠的拓扑信息预测模型

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel quantum entanglement-based topology information prediction model designed to enhance the accuracy of topology information analysis. Traditional approaches rely on classical computational methods, which often struggle to capture the subtle nuances and dynamic behavior of complex topological structures. This model leverages the unique properties of quantum entanglement to generate a more precise and robust representation of topological information. The core mechanism involves encoding topology information as entangled states, enabling a fundamentally different approach to prediction. This approach offers the potential for significantly improved prediction accuracy, particularly for intricate topological landscapes. We present a theoretical framework and initial experimental validation demonstrating the model's efficacy in predicting topological structure characteristics and stability. The results suggest a substantial improvement over existing methods, highlighting the transformative potential of quantum entanglement in topology analysis.

DOI: 10.5281/zenodo.22195881

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