From the Littlewood-Offord problem to the Circular Law: Universality of the spectral distribution of random matrices

Abstract

The famous circular law asserts that if $M_n$ is an $n \times n$ matrix with iid complex entries of mean zero and unit variance, then the empirical spectral distribution of the normalized matrix $\frac {1}{\sqrt {n}} M_n$ converges both in probability and almost surely to the uniform distribution on the unit disk $\{ z \in \mathbf {C}: |z| \leq 1 \}$. After a long sequence of partial results that verified this law under additional assumptions on the distribution of the entries, the circular law is now known to be true for arbitrary distributions with mean zero and unit variance. In this survey we describe some of the key ingredients used in the establishment of the circular law at this level of generality, in particular recent advances in understanding the Littlewood-Offord problem and its inverse.

Locations

• Bulletin of the American Mathematical Society - View - PDF
• arXiv (Cornell University) - View - PDF
• Bulletin of the American Mathematical Society - View - PDF
• arXiv (Cornell University) - View - PDF