arXiv2014
Random hyperbolic graphs were recently introduced by Krioukov et. al. [KPKVB10] as a model for large networks. Gugelmann, Panagiotou, and Peter [GPP12] then initiated the rigorous study of random hyperbolic graphs using the following model: for $α> \tfrac{1}{2}$, $C\in\mathbb{R}$, $n\in\mathbb{N}$, set $R=2\ln n+C$ and build the graph $G=(V,E)$ with $|V|=n$ as follows: For each $v\in V$, generate i.i.d. polar coordinates $(r_{v},θ_{v})$ using the joint density function $f(r,θ)$, with $θ_{v}$ chosen uniformly from $[0,2π)$ and $r_{v}$ with density $f(r)=\frac{α\sinh(αr)}{\cosh(αR)-1}$ for $0\leq r< R$. Then, join two vertices by an edge, if their hyperbolic distance is at most $R$. We prove that in the range $\tfrac{1}{2} < α< 1$ a.a.s. for any two vertices of the same component, their graph distance is $O(\log^{C_0+1+o(1)}n)$, where $C_0=2/(\tfrac{1}{2}-\frac{3}{4}α+\tfrac{α^2}{4})$, thus answering a question raised in [GPP12] concerning the diameter of such random graphs. As a corollary from our proof we obtain that the second largest component has size $O(\log^{2C_0+1+o(1)}n)$, thus answering a question of Bode, Fountoulakis and Müller [BFM13]. We also show that a.a.s. there exist isolated components forming a path of length $Ω(\log n)$, thus yielding a lower bound on the size of the second largest component.