Quantum-Enhanced Topological Data Analysis - Adaptive Topological Clustering

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of quantum computing to enhance the process of topological data analysis, specifically focusing on the identification of underlying patterns and relationships within complex topological data structures. We propose an adaptive clustering algorithm that leverages quantum properties, aiming to surpass classical clustering methods in terms of speed and accuracy. The core mechanism centers around quantum entanglement to facilitate the exploration of intricate correlations within the data, leading to a more nuanced understanding of the underlying structure. The paper details the theoretical framework, the implementation of the quantum algorithm, and initial results demonstrating improvements over traditional clustering techniques.

DOI: 10.5281/zenodo.22201423

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