The phase transition in site percolation on pseudo-random graphs

TL;DR

This paper proves the existence of a phase transition in site percolation on pseudo-random $d$-regular graphs, showing how the size of connected components sharply changes around a critical probability.

Contribution

It establishes the phase transition phenomenon for site percolation on pseudo-random graphs, connecting spectral properties to percolation behavior.

Findings

Below critical probability, components are logarithmic in size.

Above critical probability, a giant component emerges.

The size of the giant component scales with $rac{ ext{epsilon} imes n}{d}$.

Abstract

We establish the existence of the phase transition in site percolation on pseudo-random $d$-regular graphs. Let $G=(V,E)$ be an $(n,d,\lambda)$-graph, that is, a $d$-regular graph on $n$ vertices in which all eigenvalues of the adjacency matrix, but the first one, are at most $\lambda$ in their absolute values. Form a random subset $R$ of $V$ by putting every vertex $v\in V$ into $R$ independently with probability $p$. Then for any small enough constant $\epsilon>0$, if $p=\frac{1-\epsilon}{d}$, then with high probability all connected components of the subgraph of $G$ induced by $R$ are of size at most logarithmic in $n$, while for $p=\frac{1+\epsilon}{d}$, if the eigenvalue ratio $\lambda/d$ is small enough as a function of $\epsilon$, then typically $R$ spans a connected component of size at least $\frac{\epsilon n}{d}$ and a path of length proportional to $\frac{\epsilon^2n}{d}$.