On the Giant Component of Geometric Inhomogeneous Random Graphs

Thomas Bläsius, T. Friedrich, Maximilian Katzmann, János Ruff, Ziena Zeif
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引用次数: 1

Abstract

In this paper we study the threshold model of \emph{geometric inhomogeneous random graphs} (GIRGs); a generative random graph model that is closely related to \emph{hyperbolic random graphs} (HRGs). These models have been observed to capture complex real-world networks well with respect to the structural and algorithmic properties. Following comprehensive studies regarding their \emph{connectivity}, i.e., which parts of the graphs are connected, we have a good understanding under which circumstances a \emph{giant} component (containing a constant fraction of the graph) emerges. While previous results are rather technical and challenging to work with, the goal of this paper is to provide more accessible proofs. At the same time we significantly improve the previously known probabilistic guarantees, showing that GIRGs contain a giant component with probability $1 - \exp(-\Omega(n^{(3-\tau)/2}))$ for graph size $n$ and a degree distribution with power-law exponent $\tau \in (2, 3)$. Based on that we additionally derive insights about the connectivity of certain induced subgraphs of GIRGs.
几何非齐次随机图的巨分量
本文研究了几\emph{何非齐次随机图}的阈值模型;与\emph{双曲随机图(hrg)密切相关的生成型随机图}模型。这些模型已经被观察到可以很好地捕捉复杂的现实世界网络的结构和算法属性。在对它们的\emph{连通性}(即图的哪些部分是连接的)进行全面研究之后,我们很好地理解了在什么情况下会出现一个\emph{巨大}的组件(包含图的恒定部分)。虽然以前的结果相当技术性和挑战性,但本文的目标是提供更容易获得的证明。同时,我们显著改进了以前已知的概率保证,表明girg包含一个巨大的分量,对于图大小$n$具有概率$1 - \exp(-\Omega(n^{(3-\tau)/2}))$和一个幂律指数$\tau \in (2, 3)$的度分布。在此基础上,我们还获得了关于某些诱导子图的连通性的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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