Small Ball Probability for the Smallest Singular Value of a Complex Random Matrix

Series
High Dimensional Seminar
Time
Wednesday, February 19, 2020 - 3:00pm for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Michail Sarantis – GeorgiaTech
Organizer
Konstantin Tikhomirov

Let $N_n$ be an $n\times n$ matrix whose entries are i.i.d. copies of a random variable $\zeta=\xi+i\xi'$, where $\xi,\xi'$ are i.i.d., mean zero, variance one, subgaussian random variables. We will present a result of Luh, according to which the probability that $N_n$ has a real eigenvalue is exponentially small in $n$. An interesting part of the proof is a small ball probability estimate for the smallest singular value of a complex perturbation $M_n=M+N_n$ of the original matrix.