基于自适应量子模型的扩展 - 复杂系统的建模

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel approach to quantum system modeling, termed "Adaptive Quantum Model Extension" (AQME), that leverages self-adaptive parameter adjustments to enhance the representation and accuracy of complex systems. Traditional quantum modeling often relies on static parameter settings, limiting its ability to accurately capture the intricacies of intricate systems. AQME overcomes this limitation through a dynamic adjustment mechanism, enabling a more refined simulation process. We demonstrate the efficacy of this approach on a series of benchmark systems, showcasing significant improvements in model fidelity and computational efficiency. The core of the algorithm lies in iteratively refining model parameters based on the system's dynamics, leading to a more robust and precise representation. The benefits of this extended method are evident in improved simulation results across diverse systems, highlighting its potential for advancing the field of complex system modeling.

DOI: 10.5281/zenodo.22295709

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