Аннотация:
We prove precise deviations results in the sense of Cramér 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 family of orthogonal polynomials. The necessary asymptotic information on this kernel has mostly been obtained in [Kriecherbauer T., Schubert K., Schüler K., Venker M., Markov Process. Related Fields21 (2015), 639–694]. In the superlarge regime these results of do not suffice and we put stronger assumptions on the point processes. The results of the present paper and the relevant parts of [Kriecherbauer T., Schubert K., Schüler K., Venker M., Markov Process. Related Fields21 (2015), 639–694] have been proved in the dissertation [Schüler K., Ph.D. Thesis, Universität Bayreuth, 2015].
Ключевые слова:determinantal point process; extreme value distribution; Tracy–Widom distribution; moderate deviations; large deviations; superlarge deviations; random matrix theory; Christoffel–Darboux kernel; Riemann–Hilbert problem.