This analysis explores how empirical measures evolve in colony populations, uncovering connections between coagulation equations and branching processes.
Consider a structured population consisting of d colonies, with migration rates that are proportional to a positive parameter K. We sample NK individuals distributed evenly across the d colonies and trace their ancestral lineages back. Within a colony, we assume that pairs of ancestral lineages coalesce at a constant rate, as in a Kingman's coalescent. We identify each ancestral lineage with the set, or block, of its descendants in the sample and we encode the state of the system using a d-dimensional vector of empirical measures; the i-th component records the blocks present in colony i and the initial location of the lineages composing each block. We are interested in the asymptotic behaviour of the process of empirical measures as K→∞. We consider two regimes: the critical sampling regime, where NK ~ K and the large sampling regime where NK K. After an appropriate time-space scaling, we show that the process of empirical measures converges to the solution of a d-dimensional coagulation equation. In the critical sampling regime, the solution can be represented in terms of a multi-type branching process. In the large sampling regime, the solution can be represented in terms of the entrance law of a multi-type continuous state branching process.
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Cordero et al. (2025) studied this question.
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