# Linear Differential Equations for the Resolvents of the Classical Matrix Ensembles

## TL;DR

This paper derives explicit linear differential equations characterizing spectral densities and resolvents for classical random matrix ensembles at specific beta values, enabling systematic analysis of spectral moments and edge behaviors.

## Contribution

It provides explicit differential equations for spectral densities and resolvents for classical ensembles at various beta values, including dualities and edge scaling forms.

## Key findings

- Explicit differential equations for beta=2,4,6 in classical ensembles.
- Systematic derivation of recurrences for spectral moments.
- First-order differential equations for 1/N expansion coefficients.

## Abstract

The spectral density for random matrix $\beta$ ensembles can be written in terms of the average of the absolute value of the characteristic polynomial raised to the power of $\beta$, which for even $\beta$ is a polynomial of degree $\beta(N-1)$. In the cases of the classical Gaussian, Laguerre, and Jacobi weights, we show that this polynomial, and moreover the spectral density itself, can be characterised as the solution of a linear differential equation of degree $\beta+1$. This equation, and its companion for the resolvent, are given explicitly for $\beta=2$ and $4$ for all three classical cases, and also for $\beta=6$ in the Gaussian case. Known dualities for the spectral moments relating $\beta$ to $4/\beta$ then imply corresponding differential equations in the case $\beta=1$, and for the Gaussian ensemble, the case $\beta=2/3$. We apply the differential equations to give a systematic derivation of recurrences satisfied by the spectral moments and by the coefficients of their $1/N$ expansions, along with first-order differential equations for the coefficients of the $1/N$ expansions of the corresponding resolvents. We also present the form of the differential equations when scaled at the hard or soft edges.