基于量子纠缠的模式识别算法

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel pattern recognition algorithm leveraging the unique properties of quantum entanglement. The algorithm utilizes a quantum entanglement-based processing framework to enhance pattern identification and classification, specifically designed to effectively handle complex patterns often found within data. Traditional pattern recognition methods can be susceptible to noise, making them suboptimal for intricate datasets. Our proposed approach aims to overcome these limitations by exploiting the correlated nature of entangled particles, offering a potential paradigm shift in pattern analysis. The core mechanism centers around establishing and maintaining entanglement between data points, allowing for a more robust and efficient pattern recognition process. This paper details the algorithm's design, implementation, and preliminary experimental results demonstrating its effectiveness in identifying patterns within complex datasets.

DOI: 10.5281/zenodo.22278856

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