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arXiv · 2004.08958

Solving the migration-recombination equation from a genealogical point of view

Abstract

We consider the discrete-time migration-recombination equation, a deterministic, nonlinear dynamical system that describes the evolution of the genetic type distribution of a population evolving under migration and recombination in a law of large numbers setting. We relate this dynamics (forward in time) to a Markov chain, namely a labelled partitioning process, backward in time. This way, we obtain a stochastic representation of the solution of the migration-recombination equation. As a consequence, one obtains an explicit solution of the nonlinear dynamics, simply in terms of powers of the transition matrix of the Markov chain. Finally, we investigate the limiting and quasi-limiting behaviour of the Markov chain, which gives immediate access to the asymptotic behaviour of the dynamical system. We finally sketch the analogous situation in continuous time.

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Frederic Alberti, Ellen Baake, Ian Letter, Servet Martinez. 2020-04-19. Solving the migration-recombination equation from a genealogical point of view. https://doi.org/10.1007/s00285-021-01584-4

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