Quantum Adaptive Time Series Prediction

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum Adaptive Time Series Prediction (QASP) is a novel time series forecasting model designed to address the limitations of traditional approaches by employing an adaptive algorithm. The model leverages the inherent parallelism and quantum properties of quantum computation to enhance the prediction process. This research introduces a framework that dynamically adjusts model parameters based on historical data, enabling a more efficient and accurate forecasting outcome. The core claim of this paper is that QASP can achieve significantly improved prediction performance compared to existing time series models, particularly in scenarios involving complex dynamic environments.

DOI: 10.5281/zenodo.22263588

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