Generalized preferential attachment models with random out-degrees and possibly negative affinity converge locally to a random Pólya point tree, from which percolation thresholds and Ising critical temperatures are derived.
Local weak limits for collapsed branching processes with random out-degrees
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abstract
We obtain local weak limits in probability for Collapsed Branching Processes (CBP), which are directed random networks obtained by collapsing random-sized families of individuals in a general continuous-time branching process. The local weak limit of a given CBP, as the network grows, is shown to be a related continuous-time branching process stopped at an independent exponential time. The proof involves the construction of an explicit coupling of the in-components of vertices with the limiting object. We also show that the in-components of a finite collection of uniformly chosen vertices locally weakly converge (in probability) to i.i.d. copies of the above limit, reminiscent of propagation of chaos in interacting particle systems. We obtain as special cases novel descriptions of the local weak limits of directed preferential and uniform attachment models. We also outline some applications of our results for analyzing the limiting in-degree and PageRank distributions. In particular, upper and lower bounds on the tail of the in-degree distribution are obtained and a phase transition is detected in terms of the growth rate of the attachment function governing reproduction rates in the branching process.
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Stochastic processes on preferential attachment models
Generalized preferential attachment models with random out-degrees and possibly negative affinity converge locally to a random Pólya point tree, from which percolation thresholds and Ising critical temperatures are derived.