Zusammenfassung für den Vortrag am 11.01.2023 (11:00 Uhr)

Networks Seminar

Ágnes Backhaus (ELTE Eötvös Loránd University and Alfréd Rényi Institute of Mathematics, Budapest, Hungary)
A graph limit approach to the eigenvectors of non-symmetric random sign matrices

Random matrix theory is a quickly evolving area of probability theory, which has interesting connections to other fields of mathematics and physics as well. In this work we consider non-symmetric random matrices with independent, zero mean, plus-minus \(n^{-1/2}\) entries. It is well known that the eigenvalues of such a matrix are distributed approximately uniformly on the unit disk of the complex plane; however, less is known about the eigenvectors. In the talk we present a result stating that the empirical distribution of the delocalized eigenvectors are in some sense close to a Gaussian distribution. We will summarize the concentration result for random matrices with respect to a metric coming from graph limit theory, which is an important element in the proofs – together with other tools from probability theory and information theory. Joint work with Balázs Szegedy.


13.01.2023, 00:08