# Crystallization of random matrix orbits

## TL;DR

This paper explores the asymptotic behavior of eigenvalues of random matrices under various operations as the parameter beta approaches infinity, revealing a crystallization phenomenon and connections to Gaussian Free Fields.

## Contribution

It introduces a beta-infinity limit for eigenvalue operations, showing eigenvalues crystallize on roots of polynomial derivatives and relate to Gaussian Free Fields.

## Key findings

- Eigenvalues crystallize on roots of polynomial derivatives as beta approaches infinity.
- The beta-infinity limit corresponds to finite free convolutions and projections.
- A connection between eigenvalue distributions and Gaussian Free Fields is established.

## Abstract

Three operations on eigenvalues of real/complex/quaternion (corresponding to $\beta=1,2,4$) matrices, obtained from cutting out principal corners, adding, and multiplying matrices can be extrapolated to general values of $\beta>0$ through associated special functions. We show that $\beta\to\infty$ limit for these operations leads to the finite free projection, additive convolution, and multiplicative convolution, respectively. The limit is the most transparent for cutting out the corners, where the joint distribution of the eigenvalues of principal corners of a uniformly-random general $\beta$ self-adjoint matrix with fixed eigenvalues is known as $\beta$-corners process. We show that as $\beta\to\infty$ these eigenvalues crystallize on the irregular lattice of all the roots of derivatives of a single polynomial. In the second order, we observe a version of the discrete Gaussian Free Field (dGFF) put on top of this lattice, which provides a new explanation of why the (continuous) Gaussian Free Field governs the global asymptotics of random matrix ensembles.