Title: Quantum-Enhanced Topological Data Analysis for Time Series Prediction

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum-enhanced topological data analysis (TDA) offers a novel approach to time series prediction, leveraging the unique properties of quantum mechanics. This paper proposes a new quantum algorithm designed to enhance the accuracy of predictive modeling by simultaneously exploring multiple temporal patterns. We explore the potential of quantum superposition and entanglement to identify subtle correlations that are often missed by classical methods. The core mechanism involves utilizing quantum algorithms to represent and process time series data in a fundamentally different manner, potentially leading to improved predictive capabilities. We detail the algorithm's design, its mathematical underpinnings, and preliminary experimental results demonstrating enhanced accuracy in a simulated time series dataset. The core claim centers on the potential for quantum algorithms to surpass classical methods in identifying complex, non-linear patterns inherent in time series data.

DOI: 10.5281/zenodo.22200197

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