基于量子纠缠的自适应数据整合

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper introduces a novel data integration framework leveraging the unique properties of quantum entanglement to achieve significantly enhanced data processing efficiency and improved data quality. Traditional data integration methods often struggle with the inherent complexity and noise inherent in real-world datasets. This research proposes a quantum-inspired approach that exploits entanglement to facilitate rapid and accurate data association, leading to superior results compared to classical methods. The framework incorporates a quantum-enhanced data representation and an entanglement-based correlation mechanism, allowing for significantly faster and more robust data integration. We demonstrate the efficacy of this approach through simulation and preliminary experimental validation, showcasing potential improvements in data quality and processing speed.

DOI: 10.5281/zenodo.22489299

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