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Connectivity of Random High Dimensional Geometric Graphs

机译:随机高维几何图的连通性

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We consider graphs obtained by placing n points at random on a unit sphere in R~d, and connecting two points by an edge if they are close to each other (e.g., the angle at the origin that their corresponding unit vectors make is at most π /3). We refer to these graphs as geometric graphs. We also consider a complement family of graphs in which two points are connected by an edge if they are far away from each other (e.g., the angle is at least 2π/3). We refer to these graphs as anti-geometric graphs. The families of graphs that we consider come up naturally in the context of semidefinite relaxations of graph optimization problems such as graph coloring. For both distributions, we show that the largest dimension for which a random graph is likely to be connected is the same (up to an additive constant) as the largest dimension for which a random graph is likely not to have isolated vertices. The phenomenon that connectivity of random graphs is tightly related to nonexistence of isolated vertices is not new, and appeared in earlier work both on nongeometric models and on other geometric models. The fact that in our model the dimension d is allowed to grow as a function of n distinguishes our results from earlier results on connectivity of random geometric graphs.
机译:我们考虑通过在R〜d的单位球面上随机放置n个点,并且如果两个点彼此靠近(例如,其对应的单位向量所成的原点处的角度最大)而通过边缘连接两个点而获得的图π/ 3)。我们将这些图称为几何图。我们还考虑了补图族,其中如果两个点彼此远离(例如,角度至少为2π/ 3),则两个点通过一条边连接。我们将这些图称为反几何图。我们考虑的图族是在图优化问题(例如图着色)的半确定松弛下自然而然地出现的。对于这两种分布,我们都表明,可能连接随机图的最大尺寸与可能不具有孤立顶点的最大尺寸相同(最大为加法常数)。随机图的连通性与孤立顶点的不存在紧密相关的现象并不是什么新鲜事,并且在非几何模型和其他几何模型的早期工作中均已出现。在我们的模型中,维d可以作为n的函数增长的事实将我们的结果与早期关于随机几何图的连通性的结果区分开。

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