  We study the partition function from random matrix theory using a well known
connection to orthogonal polynomials, and a recently developed Riemann-Hilbert
approach to the computation of detailed asymptotics for these orthogonal
polynomials. We obtain the first proof of a complete large N expansion for the
partition function, for a general class of probability measures on matrices,
originally conjectured by Bessis, Itzykson, and Zuber. We prove that the
coefficients in the asymptotic expansion are analytic functions of parameters
in the original probability measure, and that they are generating functions for
the enumeration of labelled maps according to genus and valence. Central to the
analysis is a large N expansion for the mean density of eigenvalues, uniformly
valid on the entire real axis.
