English

The hierarchical Cannings process in random environment

Probability 2017-03-10 v1

Abstract

In an earlier paper, we introduced and studied a system of hierarchically interacting measure-valued random processes which describes a large population of individuals carrying types and living in colonies labelled by the hierarchical group of order NN. The individuals are subject to migration, resampling on all hierarchical scales simultaneously. Upon resampling, a random positive fraction of the population in a block of colonies inherits the type of a random single individual in that block, which is why we refer to our system as the hierarchical Cannings process. In the present paper, we study a version of the hierarchical Cannings process in random environment, namely, the resampling measures controlling the change of type of individuals in different blocks are chosen randomly with a given mean and are kept fixed in time (= the quenched setting). We give a necessary and sufficient condition under which a multi-type equilibrium is approached (= coexistence) as opposed to a mono-type equilibrium (= clustering). Moreover, in the hierarchical mean-field limit NN \to \infty, with the help of a renormalization analysis, we obtain a full picture of the space-time scaling behaviour of block averages on all hierarchical scales simultaneously. We show that the kk-block averages are distributed as the superposition of a Fleming-Viot diffusion with a deterministic volatility constant dkd_k and a Cannings process with a random jump rate, both depending on kk. In the random environment, dkd_k turns out to be smaller than in the homogeneous environment of the same mean. We investigate how dkd_k scales with kk. This leads to five universality classes of cluster formation in the mono-type regime. We find that if clustering occurs, then the random environment slows down the growth of the clusters, i.e., enhances the diversity of types.

Keywords

Cite

@article{arxiv.1703.03061,
  title  = {The hierarchical Cannings process in random environment},
  author = {Andreas Greven and Frank den Hollander and Anton Klimovsky},
  journal= {arXiv preprint arXiv:1703.03061},
  year   = {2017}
}

Comments

56 pages, 5 figures

R2 v1 2026-06-22T18:40:18.168Z