The smallest eigenvalue of $\beta$-Laguerre and $\beta$-Jacobi ensembles and multivariate orthogonal polynomials

We study the smallest eigenvalue statistics of the $\beta$-Laguerre and $\beta$-Jacobi ensembles. Using Kaneko's integral formula, we show that the smallest eigenvalue marginal density and distribution functions of the two ensembles for any $\beta>0$ can be represented in terms of multivariate Laguerre and Jacobi polynomials evaluated at a multiple of the identity, provided that the exponent of $x$ in the Laguerre and Jacobi weights is an integer. These representations are readily computable in explicit form using existing symbolic algorithms for multivariate orthogonal polynomials. From these expressions, we derive new differentiation formulas for the multivariate Laguerre and Jacobi polynomials. Furthermore, we derive explicit solutions to the Painleve V and VI differential equations associated with the smallest eigenvalue of the LUE and JUE. We provide numerical experiments and examples.