Random Perfect Graphs

TL;DR

This paper studies the asymptotic properties of a uniformly sampled random perfect graph, revealing its typical structural features, coloring, Hamiltonicity, and convergence to a specific graphon.

Contribution

It provides a detailed analysis of the asymptotic structure of random perfect graphs, including their subgraph probabilities, coloring properties, and convergence behavior, using a new generation method.

Findings

Almost all perfect graphs are 2-clique-colorable.

Almost all perfect graphs are Hamiltonian.

They converge to a specific graphon $W_P(x,y)$.

Abstract

We investigate the asymptotic structure of a random perfect graph $P_n$ sampled uniformly from the perfect graphs on vertex set $\{1,\ldots,n\}$. Our approach is based on the result of Pr\"omel and Steger that almost all perfect graphs are generalised split graphs, together with a method to generate such graphs almost uniformly. We show that the distribution of the maximum of the stability number $\alpha(P_n)$ and clique number $\omega(P_n)$ is close to a concentrated distribution $L(n)$ which plays an important role in our generation method. We also prove that the probability that $P_n$ contains any given graph $H$ as an induced subgraph is asymptotically $0$ or $\frac12$ or $1$. Further we show that almost all perfect graphs are $2$-clique-colourable, improving a result of Bacs\'o et al from 2004; they are almost all Hamiltonian; they almost all have connectivity $\kappa(P_n)$ equal to their minimum degree; they are almost all in class one (edge-colourable using $\Delta$ colours, where $\Delta$ is the maximum degree); and a sequence of independently and uniformly sampled perfect graphs of increasing size converges almost surely to the graphon $W_P(x, y) = \frac12(\mathbb{1}[x \le 1/2] + \mathbb{1}[y \le 1/2])$.