# Random regular graph

A random r-regular graph is a graph selected from ${\mathcal {G}}_{n,r}$ , which denotes the probability space of all r-regular graphs on n vertices, where 3 ≤ r < n and nr is even. It is therefore a particular kind of random graph, but the regularity restriction significantly alters the properties that will hold, since most graphs are not regular.

## Properties of random regular graphs

As with more general random graphs, it is possible to prove that certain properties of random r-regular graphs hold almost surely. In particular, for $r\geq 3$ , a random r-regular graph of large size is almost surely r-connected. In other words, although r-regular graphs with connectivity less than r exist, the probability of selecting such a graph tends to 0 as n increases.

If $\epsilon$ > 0 is a positive constant, and d is the least integer satisfying

then, almost surely, a random r-regular graph has diameter at most d. There is also a (more complex) lower bound on the diameter of r-regular graphs, so that almost all r-regular graphs (of the same size) have almost the same diameter.

The distribution of the number of short cycles is also known: for fixed m ≥ 3, let Y3,Y4,…,Ym be the number of cycles of lengths up to m. Then the Yi are asymptotically independent Poisson random variables with means

## Algorithms for random regular graphs

It is non-trivial to implement the random selection of r-regular graphs efficiently and in an unbiased way, since most graphs are not regular. The pairing model (also configuration model) is a method which takes nr points, and partitions them into n buckets with r points in each of them. Taking a random matching of the nr points, and then contracting the r points in each bucket into a single vertex, yields an r-regular graph or multigraph. If this object has no multiple edges or loops (i.e. it is a graph), then it is the required result. If not, a restart is required.

A refinement of this method was developed by Brendan McKay and Nicholas Wormald.