论文标题
具有度度相关性的网络是边彩随机图的特殊情况
Networks with degree-degree correlations is a special case of edge-coloured random graphs
论文作者
论文摘要
在复杂的网络中，相邻节点的程度通常可能显得依赖 - 这提出了建模挑战。我们提出了一个工作框架，用于研究与相邻节点程度的任意关节分布的网络，这是通过表明此类网络是边缘色随机图的一种特殊情况。我们使用此映射来研究具有分类混合的网络中的键渗透，并表明，与具有独立学位的网络不同，连接组件的大小可能具有对度分布中扰动的意外敏感性。结果还表明，即使度量分布的第二刻是有限的，程度依赖性也可能具有消失的渗滤阈值。这些结果可用于设计人工网络，该网络有效地承受链接故障，并表明在没有明显不同集线器的网络中超级传播的可能性
In complex networks the degrees of adjacent nodes may often appear dependent -- which presents a modelling challenge. We present a working framework for studying networks with an arbitrary joint distribution for the degrees of adjacent nodes by showing that such networks are a special case of edge-coloured random graphs. We use this mapping to study bond percolation in networks with assortative mixing and show that, unlike in networks with independent degrees, the sizes of connected components may feature unexpected sensitivity to perturbations in the degree distribution. The results also indicate that degree-degree dependencies may feature a vanishing percolation threshold even when the second moment of the degree distribution is finite. These results may be used to design artificial networks that efficiently withstand link failures and indicate possibility of super spreading in networks without clearly distinct hubs
