自适应拓扑结构驱动的量子系统优化

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel optimization framework leveraging adaptive topology to guide the optimization of quantum systems. Traditional optimization methods often require manual parameter tuning, presenting a challenge in the complex landscape of quantum systems. We propose a method that utilizes the inherent topological properties of the system to simplify the problem space and facilitate the discovery of optimal parameter configurations. The framework employs a self-organizing map (SOM) inspired approach to represent the system's state, allowing for efficient exploration of the parameter space. The core mechanism centers on adapting the topology structure to the system's specific characteristics, enabling the system to converge to a solution that maximizes performance metrics. This approach offers a significant advancement over traditional optimization techniques, particularly for complex quantum systems, and holds the potential for enhanced performance and reduced computational effort.

DOI: 10.5281/zenodo.22320974

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