Quantum-Enhanced Topological Data Analysis for Image Recognition

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the potential of quantum computing to revolutionize topological data analysis (TDA) techniques, specifically within image recognition. Traditional TDA methods often struggle with the computational complexity of analyzing high-dimensional data, limiting their applicability to complex image datasets. We propose a quantum-enhanced approach that leverages quantum feature extraction and pattern recognition to accelerate the identification of subtle correlations, ultimately improving the speed and accuracy of image classification. This work investigates the feasibility of quantum algorithms to address these computational bottlenecks, demonstrating a promising pathway for enhanced image recognition capabilities.

DOI: 10.5281/zenodo.22300174

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