多维时间序列的量子纠缠解耦

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the potential of quantum entanglement to enhance data analysis and prediction in time series data. Traditional approaches often rely on computationally intensive methods, and this research proposes a novel mechanism leveraging quantum entanglement to decouple different time points, mitigating information leakage and enabling more efficient processing. The core concept centers around establishing a quantum entanglement between data points, effectively isolating information and allowing for a more robust and accurate analysis. We detail the design of a quantum entanglement protocol, its potential benefits, and preliminary results demonstrating improved data coherence and prediction accuracy compared to classical methods. The investigation highlights the transformative implications of this approach for complex time series data analysis.

DOI: 10.5281/zenodo.22190468

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