Date/Time:22 Mar 2018 15:00Venue: S17 #04-06 SR1Speaker: Andrei Florin Deneanu, Yale UniversityHow often is a random matrix normal?When the matrix entries have a continuous distribution, the probability is zero, as the set of normal matrices, viewed as points in R^{n^2}, is not full dimensional. However, for discrete distributions, the situation is totally different. We are going to focus on the Rademacher matrix, whose entries take values 1 and -1 with equal probabilities and prove an upper bound of 2^{-(0.3+o(1))n^2} for the probability in question. Note also that a lower bound of 2^{-(0.5+o(1))n^2} is given by the fact that every symmetric matrix is normal.Add to calendar:
