Quantitative invertibility of non-Hermitian random matrices

Abstract

The problem of estimating the smallest singular value of random square matrices is important in connection with matrix computations and analysis of the spectral distribution. In this survey, we consider recent developments in the study of quantitative invertibility in the non-Hermitian setting, and review some applications of this line of research.

arXiv commentA short survey for ICM 2022 proceedings