Title: Asymptotic Distribution of Quadratic Forms
Speaker: Sumit Mukherjee (Columbia University)
Abstract: In this talk we will give an exact characterization for the asymptotic distribution of quadratic forms in IID random variables with finite second moment, where the underlying matrix is the adjacency matrix of a graph. In particular we will show that the limit distribution of such a quadratic form can always be expressed as the sum of three independent components: a Gaussian, a (possibly) infinite sum of centered chi-squares, and a Gaussian with a random variance. As a consequence, we derive necessary and sufficient conditions for asymptotic normality, and universality of the limiting distribution.
This talk is based on joint work with B. B. Bhattacharya, S. Das, and S. Mukherjee.
