Extreme eigenvalues of random matrices from Jacobi ensembles

Abstract

Two-term asymptotic formulae for the probability distribution functions for the smallest eigenvalue of the Jacobi $ \beta $-Ensembles are derived for matrices of large size in the r\'egime where $ \beta > 0 $ is arbitrary and one of the model parameters $ \alpha_1 $ is an integer. By a straightforward transformation this leads to corresponding results for the distribution of the largest eigenvalue. The explicit expressions are given in terms of multi-variable hypergeometric functions, and it is found that the first-order corrections are proportional to the derivative of the leading order limiting distribution function. In some special cases $ \beta = 2 $ and/or small values of $ \alpha_1 $, explicit formulae involving more familiar functions, such as the modified Bessel function of the first kind, are presented.