基于自适应的量子态的非线性时间积分

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper presents a novel approach to time-series analysis utilizing a dynamically evolving quantum state. We propose a model, termed "Quantum Time Integration," that leverages the inherent quantum properties of a state to accurately capture and predict complex temporal patterns. Unlike traditional time integration methods, our model employs a self-adaptive evolution of the quantum state, allowing for a more nuanced and accurate representation of the underlying dynamics. The core mechanism involves constructing a "quantum time integral" through iterative quantum state adjustments, resulting in enhanced predictive capabilities. This research addresses the limitations of conventional methods by offering a fundamentally different perspective on time-series modeling, potentially enabling superior accuracy and robustness in forecasting challenging scenarios. The paper concludes with a detailed discussion of the model's architecture, mathematical foundations, and experimental validation, demonstrating its efficacy in simulating and predicting time-dependent data.

DOI: 10.5281/zenodo.22301036

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