Spectrum and pseudospectrum for quadratic polynomials in Ginibre matrices

preprint2020arXivOpen access

Abstract

For a fixed quadratic polynomial p\mathfrak{p} in nn non-commuting variables, and nn independent N×NN\times N complex Ginibre matrices X1N,…,XnNX_1^N,\dots, X_n^N, we establish the convergence of the empirical spectral distribution of PN=p(X1N,…,XnN)P^N =\mathfrak{p}(X_1^N,\dots, X_n^N) to the Brown measure of p\mathfrak{p} evaluated at nn freely independent circular elements c1,…,cnc_1,\dots, c_n in a non-commutative probability space. The main step of the proof is to obtain quantitative control on the pseudospectrum of PNP^N. Via the well-known linearization trick this hinges on anti-concentration properties for certain matrix-valued random walks, which we find can fail for structural reasons of a different nature from the arithmetic obstructions that were illuminated in works on the Littlewood--Offord problem for discrete scalar random walks.

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