Union of Random Trees and Applications

Abstract

In 1986, Janson showed that the number of edges in the union of $k$ random spanning trees in the complete graph $K_n$ is a shifted Poisson distribution. Using results from the theory of electrical networks, we provide a new proof of this result, and we obtain an explicit rate of convergence. This rate of convergence allows us to show a new upper tail bound on the number of trees in $G(n,p)$, for $p$ a constant not depending on $n$. The number of edges in the union of $k$ random trees is related to moments of the number of spanning trees in $G(n,p)$. As an application, we prove the law of the iterated logarithm for the number of spanning trees in $G(n,p)$. More precisely, consider the infinite random graph $G(\mathbb{N},p)$, with vertex set $\mathbb{N}$ and where each edge appears independently with constant probability $p$. By restricting to $\{1,2,\dots ,n\}$, we obtain a series of nested Erdös-Réyni random graphs $G(n,p)$. We show that a scaled version of the number of spanning trees satisfies the law of the iterated logarithm.

References in corpus (1)

• Random matrices: Law of the iterated logarithm