Universality of local spectral statistics of products of random matrices

TL;DR

This paper derives exact formulas for the local spectral statistics of products of Ginibre matrices, revealing a universal interpolation between different statistical regimes and connecting to Dyson Brownian motion.

Contribution

It provides explicit kernels for singular value correlations at various spectral edges for large matrix products, proposing their universality across a broad class of matrices.

Findings

Correlation functions expressed via a universal kernel.

Identification of a new transitional spectral regime.

Numerical evidence supporting universality conjecture.

Abstract

We derive exact analytical expressions for correlation functions of singular values of the product of $M$ Ginibre matrices of size $N$ in the double scaling limit $M,N\rightarrow \infty$. The singular value statistics is described by a determinantal point process with a kernel that interpolates between GUE statistic and Dirac-delta (picket-fence) statistic. In the thermodynamic limit, $N\rightarrow \infty$, the interpolation parameter is given by the limiting quotient $a=N/M$. One of our goals is to find an explicit form of the kernel at the hard edge, in the bulk and at the soft edge for any $a$. We find that in addition to the standard scaling regimes, there is a new transitional regime which interpolates between the hard edge and the bulk. We conjecture that these results are universal, and that they apply to a broad class of products of random matrices from the Gaussian basin of attraction, including correlated matrices. We corroborate this conjecture by numerical simulations. Additionally, we show that the local spectral statistics of the considered random matrix products is identical with the local statistics of Dyson Brownian motion with the initial condition given by equidistant {positions,} with the crucial difference that this equivalence holds only locally. Finally, we have identified a mesoscopic spectral scale at the soft edge which is crucial for the unfolding of the spectrum.