Abstract
The analysis of random graphs developed by the author, principally as a model for polymerization processes, is extended to the case of directed random graphs, with models of neural nets in mind. The principal novelty of the directed case is the representation of the partition function by a complex rather than a real integral, and the replacement of simple maxima in asymptotic evaluations by an interesting form of saddle point.
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