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Quantum-Enhanced Topological Data Analysis – Beyond Correlation

Jincheng Zhang

Published Sep 5, 2026• 0 citations
Publisher

Abstract

This paper explores the application of quantum entanglement to enhance topological data analysis (TDA). Traditional TDA methods often rely on simple correlation analysis, limiting their ability to discern subtle structural patterns within complex datasets. We propose a novel quantum algorithm designed to measure distances between data points within a graph, revealing hidden relationships and potentially uncovering deeper topological structures. This approach goes beyond correlation analysis, offering a fundamentally new path towards identifying more complex and nuanced data representations. The core mechanism leverages quantum entanglement to enable a non-classical measurement, significantly improving the accuracy and insightfulness of the analysis. We demonstrate the effectiveness of this method through a series of illustrative examples, highlighting its potential for uncovering previously inaccessible topological features.

DOI
10.5281/zenodo.22314517

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