论文标题
增长信号决定了不断发展的网络的拓扑
Growth signals determine the topology of evolving networks
论文作者
论文摘要
网络科学提供了一个必不可少的理论框架，用于研究实际复杂系统的结构和功能。通常使用不同的网络模型来查找控制其演变的规则，因此，正确选择模型细节对于获得相关见解至关重要。我们在这里研究了使用衰老节点模型产生的网络结构取决于生长信号的特性。我们使用不同的波动信号，并将网络的结构差异与具有恒定生长信号的结构差异进行比较。我们表明，具有随着时变的生长信号获得的具有幂律度分布的网络是相关的和聚集的，而以恒定生长信号获得的网络不是。实际上，生长信号的特性显着确定了所获得的网络的拓扑，因此在复杂系统模型中应该显着考虑。
Network science provides an indispensable theoretical framework for studying the structure and function of real complex systems. Different network models are often used for finding the rules that govern their evolution, whereby the correct choice of model details is crucial for obtaining relevant insights. We here study how the structure of networks generated with the aging nodes model depends on the properties of the growth signal. We use different fluctuating signals and compare structural dissimilarities of the networks with those obtained with a constant growth signal. We show that networks with power-law degree distributions, which are obtained with time-varying growth signals, are correlated and clustered, while networks obtained with a constant growth signal are not. Indeed, the properties of the growth signal significantly determine the topology of the obtained networks and thus ought to be considered prominently in models of complex systems.
