Dynamics and self-similarity in min-driven clustering

preprint2008arXivOpen access

Abstract

We study a mean-field model for a clustering process that may be described informally as follows. At each step a random integer kk is chosen with probability pkp_k, and the smallest cluster merges with kk randomly chosen clusters. We prove that the model determines a continuous dynamical system on the space of probability measures supported in (0,∞)(0,\infty), and we establish necessary and sufficient conditions for approach to self-similar form. We also characterize eternal solutions for this model via a Levy-Khintchine formula. The analysis is based on an explicit solution formula discovered by Gallay and Mielke, extended using a careful choice of time scale.

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