Precise deviations results for the maxima of some determinantal point processes: the upper tail

Peter Eichelsbacher, Thomas Kriecherbauer, Katharina Schüler

Published 2016-03-14Version 1

We prove precise deviations results in the sense of Cram\'er and Petrov for the upper tail of the distribution of the maximal value for a special class of determinantal point processes that play an important role in Random Matrix Theory. Here we cover all three regimes of moderate, large and superlarge deviations for which we determine the leading order description of the tail probabilities. As a corollary of our results we identify the region within the regime of moderate deviations for which the limiting Tracy-Widom law still predicts the correct leading order behavior. Our proofs use that the determinantal point process is given by the Christoffel-Darboux kernel for an associated familiy of orthogonal polynomials. The necessary asymptotic information on this kernel has mostly been obtained in \cite{KSSV} using the Deift-Zhou \cite{DeiftZhou} nonlinear steepest descent method for Riemann-Hilbert problems, following and improving on previous applications \cite{DKMVZ1, DKMVZ2, KuijlaarsVanlessen, Vanlessen} to orthogonal polynomials and to random matrices. In the superlarge regime the results of \cite{KSSV} do not suffice and we put stronger assumptions on the point processes. The results of the present paper and the relevant parts of \cite{KSSV} have been proved in the dissertation \cite{Diss}.