A RANDOM GRAPH
The construction.
A random (undirected) graph with n vertices is constructed in the
following way: pairs of vertices are randomly selected one at a time in
such a way that each pair has the same probability of being selected on
any given occasion, and, each selection is made independently of
previous selections. If the vertex pair is selected, then
an edge is constructed which connects x and y.
Are multiple edges possible?
Yes. For example, if the vertex pair were to be
selected subsequently, there would now be more than one
edge connecting x and y: a multiple edge
or cycle of length 2.
ASYMPTOTIC BEHAVIOUR
Suppose that m edges have been selected. We shall be concerned with the
behaviour of the graph in the limit as n and m become large, but in
such a way that .
The problem.
Our problem is to determine the limiting probability that the graph is
acyclic.
Motivation.
Havas and Majewski present an algorithm for
minimal perfect hashing
(used for memory-efficient storage and fast retrieval of items from
static sets) based on this random graph.
Their algorithm is optimal when the graph is acyclic.
WHY ACYCLIC?
Consider a set W of m words (or keys). Every
bijection
, where ,
is called a minimal perfect hash function.
HM find hash functions of the form
map keys to integers (they identify the pair of vertices
of the graph corresponding to the edge w) and
g maps integers to I.
Given and ,
can g be chosen so that h is a bijection?
If the graph is acyclic then, yes, it is easy to construct
g from h. Traverse the graph: if vertex w is reached from
vertex u then set
where .
EFFICIENCY
HM's algorithm generates and at random until an acyclic
graph is found:
where and are tables of random integers and
denotes the i-th character (an integer) of key i.
The efficiency of the algorithm is determined by the probability
that the graph is acyclic: the expected number of iterations
needed to find an acyclic graph will be (typically between 2
and 3).
EVALUATING
Conjecture.
If n and
m tend to in such a way that n=cm, where c is a positive
constant, the limiting probability, p, that the graph is acyclic is
given by
``Proof''.
Let be the number of cycles of length k
and let . Following [HM] write
Now let , so that and
Erdös and Renyi
show that the distribution of
is asymptotically Poisson: in particular,
where
It follows that
So, formally,
and hence
where
By Fatou's Lemma, we always have
from which it follows immediately that
this argument is valid even if the sum in (1) is divergent. Thus, we may
deduce immediately that if , exists
and equals 0.
The interesting case c>2 is also easily dealt with. When c>2,
we have that and that
From Markov's inequality we have
and so
But, by Lemma 2 of [HM], we know have that, for each fixed ,
, as .
In particular, for each fixed , the sequence is bounded above by . It follows that is bounded above by .
Further, since , we have
Thus, by the Lebesgue Dominated Convergence Theorem, we have that
and, hence, that exists and is equal to
.