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arXiv 2003.04040math.PR
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权重依赖随机连接模型中的渗流相变

Percolation phase transition in weight-dependent random connection models

Peter Gracar, Lukas Lüchtrath, Peter Mörters

AI总结:

研究权重依赖随机连接模型中的渗流相变,发现其由度分布幂律指数和几何参数共同决定,并应用于刻画基于年龄的空间优先连接网络的鲁棒性。

摘要:

我们研究定义在 $d$ 维空间泊松过程点上的空间随机图,这些图结合了无标度度分布和长程效应。每个泊松点被赋予一个独立权重。给定点的权重和位置,我们以依赖于两点权重及其距离的概率独立地在任意点对之间形成边。偏好短边以及与权重大的顶点连接。我们刻画了存在非平凡渗流相变的参数区域,并表明该区域不仅取决于度分布的幂律指数,还取决于一个几何模型参数。我们将此结果应用于刻画基于年龄的空间优先连接网络的鲁棒性。

英文摘要:

We investigate spatial random graphs defined on the points of a Poisson process in $d$-dimensional space, which combine scale-free degree distributions and long-range effects. Every Poisson point is assigned an independent weight. Given the weight and position of the points, we form an edge between any pair of points independently with a probability depending on the two weights of the points and their distance. Preference is given to short edges and connections to vertices with large weights. We characterize the parameter regime where there is a nontrivial percolation phase transition and show that it depends not only on the power-law exponent of the degree distribution but also on a geometric model parameter. We apply this result to characterize robustness of age-based spatial preferential attachment networks.

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