论文标题
分层复杂网络作为波动放大器
Layered Complex Networks as Fluctuation Amplifiers
论文作者
论文摘要
在复杂的网络系统理论中，一个重要的问题是如何评估系统对外部扰动的鲁棒性。考虑到这项任务，我研究了多层网络系统中噪声的传播。我发现，对于一个两层网络，最初以一层注入的噪声可以在另一层中强烈放大，这取决于连接的良好是每个层中的复杂网络以及其laplacian矩阵的特征码的重叠程度。这些结果允许预测系统及其子网络的潜在有害条件，其中波动水平很重要，以及如何避免它们。分析结果在各种合成网络上进行数值说明。
In complex networked systems theory, an important question is how to evaluate the system robustness to external perturbations. With this task in mind, I investigate the propagation of noise in multi-layer networked systems. I find that, for a two layer network, noise originally injected in one layer can be strongly amplified in the other layer, depending on how well-connected are the complex networks in each layer and on how much the eigenmodes of their Laplacian matrices overlap. These results allow to predict potentially harmful conditions for the system and its sub-networks, where the level of fluctuations is important, and how to avoid them. The analytical results are illustrated numerically on various synthetic networks.
