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Random Matrix Model with External Source and a Constrained Vector Equilibrium Problem
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DOI：10.1002/cpa.20339.png)
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Abstract
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We consider the random matrix model with external source in the case where the potential V(x) is an even polynomial and the external source has two eigenvalues +/- a of equal multiplicity We show that the limiting mean eigenvalue distribution of this model can be characterized as the first component of a pair of measures (mu(1) mu(2)) that solve a constrained vector equilibrium problem The proof is based on the steepest descent analysis of the associated Riemann-Hilbert problem for multiple orthogonal polynomials We Illustrate our results in detail for the case of a quartic double well potential V(x) = 1/4 x(4) - 1/2 x(2) We are able to determine the precise location of the phase transitions in the ta plane where either the constraint becomes active or the two intervals in the support come together (or both) (C) 2010 Wiley Periodicals Inc
Keywords:
DOUBLE SCALING LIMIT
MULTIPLE ORTHOGONAL POLYNOMIALS
GAUSSIAN RANDOM MATRICES
LARGE-N LIMIT
EXPONENTIAL WEIGHTS
PEARCEY PROCESS
UNIVERSALITY
ASYMPTOTICS
FIELD
RESPECT
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