Random Embeddings of Graphs: The Expected Number of Faces in Most Graphs is Logarithmic

TL;DR

This paper analyzes the expected number of faces in random graph embeddings, showing it is typically logarithmic, which explains the limitations of Monte Carlo methods for genus approximation.

Contribution

It provides new bounds on the expected number of faces in random embeddings for various graph classes, extending topological graph theory results.

Findings

Expected faces in complete graphs grow logarithmically with n

Random graphs have expected faces bounded by logarithmic functions

Graphs with bounded degree also exhibit logarithmic expected faces

Abstract

A random 2-cell embedding of a connected graph $G$ in some orientable surface is obtained by choosing a random local rotation around each vertex. Under this setup, the number of faces or the genus of the corresponding 2-cell embedding becomes a random variable. Random embeddings of two particular graph classes, those of a bouquet of $n$ loops and those of $n$ parallel edges connecting two vertices, have been extensively studied and are well-understood. However, little is known about more general graphs. The results of this paper explain why Monte Carlo methods cannot work for approximating the minimum genus of graphs. In his breakthrough work [Permutation-partition pairs, JCTB 1991], Stahl developed the foundation of "random topological graph theory". Most of his results have been unsurpassed until today. In our work, we analyze the expected number of faces of random embeddings (equivalently, the average genus) of a graph $G$. It was very recently shown that for any graph $G$, the expected number of faces is at most linear. We show that the actual expected number of faces $F(G)$ is almost always much smaller. In particular, we prove: 1) $\frac{1}{2}\ln n - 2 < \mathbb{E}[F(K_n)] \le 3.65 \ln n +o(1)$. 2) For random graphs $G(n,p)$ ($p=p(n)$), we have $\mathbb{E}[F(G(n,p))] \le \ln^2 n+\frac{1}{p}$. 3) For random models $B(n,\Delta)$ containing only graphs, whose maximum degree is at most $\Delta$, we obtain stronger bounds by showing that the expected number of faces is $\Theta(\log n)$.