Ágnes Backhausz: On the convergence of dense preferential attachment multigraphs

Speaker: Ágnes Backhausz

Title: On the convergence of dense preferential attachment multigraphs

Abstract: We give an upper bound for the speed of convergence of certain random multigraphs with respect to the so-called jumble norm. We consider a preferential attachment random graph model on n vertices with cn^2 edges (with c>0 fixed). It is known that this sequence converges with probability 1, and the limit is also known. We prove that this preferential attachment graph and the random multigraph corresponding to the limit object (both on n vertices) are at most at distance O(n^{-1/3}) in jumble norm. Joint work with Dávid Kunszenti-Kovács.