Dynamics and self-similarity in min-driven clustering

Details Dynamics and self-similarity in min-driven clustering Dynamics and self-similarity in min-driven clustering

2008-07-28

arxiv.org/abs/0807.4473v1

Nonlinear Sciences

Adaptation and Self-Organizing Systems

Scientific paper

We study a mean-field model for a clustering process that may be described informally as follows. At each step a random integer $k$ is chosen with probability $p_k$, and the smallest cluster merges with $k$ randomly chosen clusters. We prove that the model determines a continuous dynamical system on the space of probability measures supported in $(0,\infty)$, 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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