Poisson convergence and poisson processes with applications to random graphs

We give a new sufficient condition for convergence to a Poisson distribution of a sequence of sums of dependent variables. The condition allows each summand to depend strongly on a few of the other variables and to depend weakly on the remaining ones. As a consequence we obtain sufficient conditions for the convergence of point processes, constructed as sets of (weakly) dependent random points in some space S, to a Poisson process. The main applications are to random graph theory. In particular, we solve the problem (proposed by Erdös) of finding the size of the first cycle in a random graph.