Blagojević Luka, Pósfai Márton
Department of Network and Data Science, Central European University, Vienna, Austria.
Sci Rep. 2024 Jul 23;14(1):16874. doi: 10.1038/s41598-024-67359-1.
Data describing the three-dimensional structure of physical networks is increasingly available, leading to a surge of interest in network science to explore the relationship between the shape and connectivity of physical networks. We contribute to this effort by standardizing and analyzing 15 data sets from different domains. Each network is made of tube-like objects bound together at junction points, which we treat as nodes, with the connections between them considered as links. We divide these networks into three categories: lattice-like networks, trees, and linked trees. The degree distribution of these physical networks is bounded, with most nodes having degrees one or three. Characterizing the physical properties of links, we show that links have an elongated shape and tend to follow a nearly straight trajectory, while a small fraction of links follow a winding path. These typical node and link properties must be reflected by physical network models. We also measure how confined a link is in space by comparing its trajectory to a randomized null model, showing that links that are central in the abstract network tend to be physically confined by their neighbors. The fact that the shape and connectivity of the physical networks are intertwined highlights that their three-dimensional layout must be taken into account to understand the evolution and function of physical networks.
描述物理网络三维结构的数据越来越多，这引发了网络科学领域对探索物理网络形状与连通性之间关系的浓厚兴趣。我们通过对来自不同领域的15个数据集进行标准化和分析，为这项工作做出了贡献。每个网络由在连接点处绑定在一起的管状物体组成，我们将这些连接点视为节点，它们之间的连接视为边。我们将这些网络分为三类：类晶格网络、树状网络和链接树状网络。这些物理网络的度分布是有界的，大多数节点的度为1或3。通过表征边的物理特性，我们发现边具有细长的形状，并且倾向于遵循近乎直线的轨迹，而一小部分边则遵循蜿蜒的路径。这些典型的节点和边的特性必须由物理网络模型来反映。我们还通过将边的轨迹与随机化的零模型进行比较，来衡量边在空间中的受限程度，结果表明在抽象网络中处于中心位置的边往往会受到其邻居的物理限制。物理网络的形状和连通性相互交织这一事实突出表明，必须考虑其三维布局才能理解物理网络的演化和功能。
