Halu Arda, Mukherjee Satyam, Bianconi Ginestra
Department of Physics, Northeastern University, Boston, Massachusetts 02115, USA.
Kellogg School of Management, Northwestern University, Evanston, Illinois 60208, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jan;89(1):012806. doi: 10.1103/PhysRevE.89.012806. Epub 2014 Jan 14.
Spatial networks range from the brain networks, to transportation networks and infrastructures. Recently interacting and multiplex networks are attracting great attention because their dynamics and robustness cannot be understood without treating at the same time several networks. Here we present maximal entropy ensembles of spatial multiplex and spatial interacting networks that can be used in order to model spatial multilayer network structures and to build null models of real data sets. We show that spatial multiplexes naturally develop a significant overlap of the links, a noticeable property of many multiplexes that can affect significantly the dynamics taking place on them. Additionally, we characterize ensembles of spatial interacting networks and we analyze the structure of interacting airport and railway networks in India, showing the effect of space in determining the link probability.
空间网络涵盖从大脑网络到交通网络和基础设施。最近,相互作用的多重网络备受关注,因为如果不同时考虑多个网络,就无法理解它们的动态特性和鲁棒性。在此,我们展示了空间多重网络和空间相互作用网络的最大熵系综,可用于对空间多层网络结构进行建模以及构建真实数据集的零模型。我们表明,空间多重网络自然会形成链路的显著重叠,这是许多多重网络的一个显著特性,会对其上发生的动态过程产生重大影响。此外,我们对空间相互作用网络的系综进行了表征,并分析了印度相互作用的机场和铁路网络的结构,展示了空间在确定链路概率方面的作用。