Quantum-Enhanced Geometric Pattern Recognition (QGERP)

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the potential of quantum-enhanced geometric pattern recognition, focusing on the application of quantum entanglement to improve the speed and accuracy of pattern detection in geometric data. We introduce a novel algorithm, the "Quantum Correlation Matrix" (QCM), designed to identify subtle correlations inherent in geometric data that are often missed by classical algorithms. This research investigates the feasibility of utilizing quantum entanglement to create a 'quantum correlation matrix' that can facilitate faster and more reliable pattern recognition. We detail the mathematical framework of the QCM and present preliminary results demonstrating its effectiveness in identifying specific geometric patterns across diverse datasets. The study concludes with a discussion of the challenges and future directions for this rapidly evolving field.

DOI: 10.5281/zenodo.22294937

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