Data underlying the publication: Surrogate-guided Optimization in Quantum Networks

This data is associated with the paper "Surrogate-guided Optimization in Quantum Networks".In this work we introduce an efficient optimization workflow using machine-learning models that outperforms traditional techniques, addressing the challenges of complex, computationally demanding simulations in quantum networking. Please find guidelines and more context in REAMDE.md file.本数据集与论文《代理引导的量子网络优化（Surrogate-guided Optimization in Quantum Networks）》相关联。本研究提出了一种依托机器学习模型的高效优化工作流，该方案性能优于传统技术，可有效解决量子网络领域内复杂且计算密集型模拟所面临的挑战。相关使用指南与更多背景信息请参阅README.md文件。