论文标题
累积合并渗透:网络中的远程渗透过程
Cumulative Merging Percolation: A long-range percolation process in networks
论文作者
论文摘要
网络上的渗透是一个常见的框架,可以对广泛的过程进行建模,从级联故障到流行病扩散。标准渗透假定短距离相互作用,这意味着只有在群集最接近邻居时,节点才能合并为簇。累积合并渗透(CMP)是一个新的渗透过程,它假定远程相互作用,因此即使节点在拓扑上很远,也可以合并成簇。因此,在CMP渗透簇中,与网络的拓扑连接组件不一致。先前的工作表明,CMP的特定公式具有形成巨型群集的特殊机制,并允许对不同的网络动力学进行建模,例如复发性的流行过程。在这里,我们根据群集相互作用范围的功能形式开发了CMP的更一般的表述,显示出更丰富的相变情景,并具有不同机制的竞争,导致了交叉现象。我们的分析预测通过数值模拟证实。
Percolation on networks is a common framework to model a wide range of processes, from cascading failures to epidemic spreading. Standard percolation assumes short-range interactions, implying that nodes can merge into clusters only if they are nearest-neighbors. Cumulative Merging Percolation (CMP) is an new percolation process that assumes long-range interactions, such that nodes can merge into clusters even if they are topologically distant. Hence in CMP percolation clusters do not coincide with the topological connected components of the network. Previous work has shown that a specific formulation of CMP features peculiar mechanisms for the formation of the giant cluster, and allows to model different network dynamics such as recurrent epidemic processes. Here we develop a more general formulation of CMP in terms of the functional form of the cluster interaction range, showing an even richer phase transition scenario with competition of different mechanisms resulting in crossover phenomena. Our analytic predictions are confirmed by numerical simulations.