Graphon-valued stochastic processes from population genetics
Abstract
The goal of this paper is to develop a theory of graphon-valued stochastic processes, and to construct and analyse a natural class of such processes arising from population genetics. We consider finite populations where individuals change type according to Wright-Fisher resampling. At any time, each pair of individuals is linked by an edge with a probability that is given by a type-connection matrix, whose entries depend on the current empirical type distribution of the entire population via a fitness function. We show that, in the large-population-size limit and with an appropriate scaling of time, the evolution of the associated adjacency matrix converges to a random process in the space of graphons, driven by the type-connection matrix and the underlying Wright-Fisher diffusion on the multi-type simplex. In the limit as the number of types tends to infinity, the limiting process is driven by the type-connection kernel and the underlying Fleming-Viot diffusion.
Cite
@article{arxiv.1908.06241,
title = {Graphon-valued stochastic processes from population genetics},
author = {Siva Athreya and Frank den Hollander and Adrian Röllin},
journal= {arXiv preprint arXiv:1908.06241},
year = {2019}
}