Title: Quantum-Enhanced Topological Data Analysis for Signal Processing

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum-enhanced Topological Data Analysis (QETA) presents a novel approach to signal processing, specifically focusing on the extraction of meaningful features from complex data like electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). This paper introduces a quantum-enhanced algorithm designed to overcome the limitations of conventional methods by exploiting quantum interference effects to improve detection accuracy and processing speed. The core mechanism involves utilizing a quantum circuit to perform a computationally intensive feature extraction operation, demonstrating a significant advancement in the field of topological data analysis. We present a preliminary implementation demonstrating the potential of QETA to achieve superior performance in data analysis tasks compared to existing techniques.

DOI: 10.5281/zenodo.22298739

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