Abstract

In this talk we consider a growing network which evolves under the action of two rules: at each time step, (1) a new node is attached to m different extant nodes selected with a probability which depends linearly on the degree, and (2) with probability r>0, a node selected uniformly at random is removed from the network. We study some long-time probabilistic and topological features of the resulting network. More precisely, we compute the long-time degree distribution and the two-node degree correlations.