Liang Xiaoming, Liu Zonghua, Li Baowen
Institute of Theoretical Physics, Department of Physics, East China Normal University, Shanghai, China.
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Oct;80(4 Pt 2):046102. doi: 10.1103/PhysRevE.80.046102. Epub 2009 Oct 6.
We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.
我们提出了一个耦合振子网络模型,以研究弱信号在复杂网络中是如何传输的。通过理论分析和数值模拟,我们发现其他节点对弱信号的响应随着它们与信号源的拓扑距离呈指数衰减,并且两个相邻节点之间的耦合强度可以通过这些响应来确定。通过反复选择不同节点作为信号源,这一发现可方便地用于检测未知网络的拓扑结构,如度分布、聚类系数和社区结构等。通过四个典型网络,即规则一维网络、小世界网络、随机网络和无标度网络,我们表明,通过研究比网络规模少得多的节点,就可以近似给出网络的特征,因此我们检测未知网络拓扑结构的方法在网络规模较大的实际情况下可能是有效的。