论文标题
身体对网络结构的影响
Impact of physicality on network structure
论文作者
论文摘要
物理网络的详细地图的出现,例如大脑连接组,血管网络或超材料中的复合网络,其节点和链接是物理实体,已经证明了当前网络科学工具集的限制。链接物理性施加了一种非交叉条件,该条件会影响网络的演变和结构,以一种单独的邻接矩阵(所有基于图的方法的起点)无法捕获的方式。在这里,我们介绍了一种元图,该元图可帮助我们发现线性物理网络和独立集合之间的精确映射,这是图理论中的一个核心概念。该映射使我们能够在分析中得出物理效应的开始和堵塞过渡的出现,并表明即使链接的总体积可忽略不计,物理性也会影响网络结构。最后,我们构建了几个真实物理网络的荟萃图,这使我们能够预测功能特征,例如在脑连接组中的突触形成,与经验数据一致。总体而言,我们的结果表明,为了了解实际复杂网络的演变和行为,必须完全量化身体的作用。
The emergence of detailed maps of physical networks, like the brain connectome, vascular networks, or composite networks in metamaterials, whose nodes and links are physical entities, have demonstrated the limits of the current network science toolset. Link physicality imposes a non-crossing condition that affects both the evolution and the structure of a network, in a way that the adjacency matrix alone -- the starting point of all graph-based approaches -- cannot capture. Here, we introduce a meta-graph that helps us discover an exact mapping between linear physical networks and independent sets, a central concept in graph theory. The mapping allows us to analytically derive both the onset of physical effects and the emergence of a jamming transition, and show that physicality impacts the network structure even when the total volume of the links is negligible. Finally, we construct the meta-graphs of several real physical networks, which allows us to predict functional features, such as synapse formation in the brain connectome, that agree with empirical data. Overall, our results show that, in order to understand the evolution and behavior of real complex networks, the role of physicality must be fully quantified.