Quaternionic R transform and non-hermitian random matrices

TL;DR

This paper introduces a quaternionic R transform to analyze non-hermitian random matrices, enabling calculation of eigenvalue densities and extending free probability to complex matrix ensembles.

Contribution

It develops a quaternionic extension of the R transform for non-hermitian matrices, providing a new tool for analyzing their spectral properties.

Findings

Derived the quaternionic R transform for Gaussian elliptic laws.

Showed the R transform generates all connected averages of matrix powers.

Calculated eigenvalue densities for products of Gaussian random matrices.

Abstract

Using the Cayley-Dickson construction we rephrase and review the non-hermitian diagrammatic formalism [R. A. Janik, M. A. Nowak, G. Papp and I. Zahed, Nucl.Phys. B $\textbf{501}$, 603 (1997)], that generalizes the free probability calculus to asymptotically large non-hermitian random matrices. The main object in this generalization is a quaternionic extension of the R transform which is a generating function for planar (non-crossing) cumulants. We demonstrate that the quaternionic R transform generates all connected averages of all distinct powers of $X$ and its hermitian conjugate $X^\dagger$: $\langle\langle \frac{1}{N} \mbox{Tr} X^{a} X^{\dagger b} X^c \ldots \rangle\rangle$ for $N\rightarrow \infty$. We show that the R transform for gaussian elliptic laws is given by a simple linear quaternionic map $\mathcal{R}(z+wj) = x + \sigma^2 \left(\mu e^{2i\phi} z + w j\right)$ where $(z,w)$ is the Cayley-Dickson pair of complex numbers forming a quaternion $q=(z,w)\equiv z+ wj$. This map has five real parameters $\Re e x$, $\Im m x$, $\phi$, $\sigma$ and $\mu$. We use the R transform to calculate the limiting eigenvalue densities of several products of gaussian random matrices.