基于自组织网络的量子机器学习算法验证

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper presents a novel quantum machine learning algorithm based on a self-organizing network (SON). The core principle of this algorithm is to dynamically allocate quantum machine learning tasks to nodes within the SON, optimizing for computational efficiency and performance. We introduce a framework that leverages the inherent properties of SONs to enhance the training and inference processes of quantum algorithms. This approach offers a potential advancement over traditional quantum machine learning, particularly in scenarios where computational efficiency is paramount. This work details the design of the SON architecture, the algorithm's implementation, and the results demonstrating its effectiveness in validating quantum machine learning algorithms. The paper concludes by discussing the potential implications and future directions of this research.

DOI: 10.5281/zenodo.22192811

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