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Connectivity of Random High Dimensional Geometric Graphs

机译:随机高维几何图的连接

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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:我们认为通过在随机放置在中的R单位球体〜d n个点,并通过边缘连接两个点获得的曲线图,如果他们彼此接近(例如,在原点的角度,他们的相应单位矢量使得为至多π/ 3)。我们把这些图形几何图。我们还考虑其中两个点通过边缘连接的图的补体家族如果它们远离彼此(例如,角度为至少2π/ 3)。我们将这些图表作为抗几何图形。图的家庭,我们认为拿出自然在图形优化问题的半定松弛如图着色的范围内。对于这两种分布,我们表明,针对其随机图很可能被连接的最大尺寸是相同的(高达添加剂不变)针对其随机图可能不是有孤立的顶点的最大尺寸。该随机图的连通性是密切相关的孤立顶点的不存在的现象,是不是新的,并出现在早期的工作都在非几何模型和其他几何模型。在我们的模型尺寸d被允许成长为n的函数的事实根据与随机几何图的连通先前的结果区别我们的研究结果。

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