Quantum-Enhanced Pattern Recognition in Complex Data

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum-enhanced pattern recognition aims to accelerate and improve the identification of subtle patterns and correlations in complex datasets, offering a potential paradigm shift compared to classical methods. This paper explores the application of quantum machine learning techniques to address challenges posed by high-dimensional data. We propose a novel quantum algorithm designed to efficiently explore the data space and uncover hidden correlations, ultimately surpassing classical approaches in specific tasks. The core mechanism centers around leveraging quantum superposition and entanglement to enhance data representation and pattern recognition capabilities. The paper will detail the proposed quantum algorithm, its potential advantages, and the challenges associated with its implementation.

DOI: 10.5281/zenodo.22188524

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