## Department Colloquium

### Friday, October 2nd, 2020

**Time:** 2:30 p.m. **Place:** Online (via Zoom)

**Speaker:** Elliot Paquette (McGill University)

**Title:** Random perturbations of non-normal matrices.

**Abstract: ** Suppose one wants to calculate the eigenvalues of a large, non-normal matrix. For example, consider the matrix which is 0 in most places except above the diagonal, where it is 1. The eigenvalues of this matrix are all 0. Similarly, if one conjugates this matrix, in exact arithmetic one would get all eigenvalues equal to 0. However, when one makes floating point errors, the eigenvalues of this matrix are dramatically different. One can model these errors as performing a small, random perturbation to the matrix. And, far from being random, the eigenvalues of this perturbed matrix nearly exactly equidistribute on the unit circle of the complex plane. This talk will give a probabilistic explanation of why this happens and discuss the general question: how does one predict the eigenvalues of a large, non-normal, randomly perturbed matrix?

**Elliot Paquette** is an Assistant Professor within the Department of Mathematics and Statistics at McGill University. He obtained his Ph.D.~in Mathematics from the University of Washington in 2013. He was an NSF Postdoctoral Fellow at the Weizmann Institute of Science from 2013-2016, and an Assistant Professor at the Ohio State University from 2016-2020. His research is in probability theory, with a focus on random matrix theory and on problems with geometric and topological inspirations.