The spectrum of a tensor of random and deterministic matrices

TL;DR

This paper establishes bounds and convergence results for operator norms of polynomials in Gaussian Unitary Ensemble matrices, linking them to free probability theory and providing insights into the Peterson-Thom conjecture.

Contribution

It introduces new bounds on operator norms of polynomials in random matrices and demonstrates their convergence to free probability limits, offering a novel proof of the Peterson-Thom conjecture.

Findings

Operator norm bounds for polynomials in GUE matrices

Convergence of operator norms to free semicircular counterparts

New techniques for tensor operator norm estimation

Abstract

We consider operator-valued polynomials in Gaussian Unitary Ensemble random matrices and we show that its $L^p$-norm can be upper bounded, up to an asymptotically small error, by the operator norm of the same polynomial evaluated in free semicircular variables as long as $p=o(N^{2/3})$. As a consequence, if the coefficients are $M$-dimensional matrices with $M=\exp(o(N^{2/3}))$, then the operator norm of this polynomial converges towards the one of its free counterpart. In particular this provides another proof of the Peterson-Thom conjecture thanks to the result of Ben Hayes. We also obtain similar results for polynomials in random and deterministic matrices. The approach that we take in this paper is based on an asymptotic expansion obtained by the same author in a previous paper combined with a new result of independent interest on the norm of the composition of the multiplication operator and a permutation operator acting on a tensor of $\mathcal{C}^*$-algebras.