Quantum-Based Non-linear Time Series Analysis

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel approach to non-linear time series analysis utilizing the unique capabilities of quantum computing. Traditional methods often struggle with the complexity of such sequences, limiting their analytical and modeling potential. We propose a quantum-enhanced algorithm that leverages quantum superposition and entanglement to achieve more accurate and efficient analysis, addressing limitations inherent in classical approaches. This work explores the potential of quantum computation to transform the analysis of non-linear time series data, offering a promising avenue for advanced modeling and forecasting. The core mechanism involves a quantum-enhanced Fourier transform coupled with a tailored optimization algorithm. The paper details the algorithm's design, implementation, and preliminary results demonstrating improved accuracy and efficiency compared to established classical methods. Finally, we discuss the challenges and future directions for this technology.

DOI: 10.5281/zenodo.22302706

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