Misc,

Quasi-Stationary distributions for randomly perturbed dynamical systems

, and .
(2011)cite arxiv:1101.3420 Comment: 31 pages.

Abstract

We analyze quasi-stationary distributions $\mu^\epsilon$ of a family of Markov chains $\X^\epsilon\_\epsilon>0$ that are random perturbations of a bounded, continuous map $F:MM$ where $M$ is a subset of $\R^k$. Consistent with many models in biology, these Markov chains have a closed absorbing set $M_0M$ such that $F(M_0)=M_0$ and $F(MM_0)=MM_0$. Under some large deviations assumptions on the random perturbations, we show that if there exists a positive attractor for $F$ (i.e. an attractor for $F$ in $MM_0$), then the weak* limit points of $\mu_\epsilon$ are supported by the positive attractors of $F$. To illustrate the broad applicability of these results, we apply them to nonlinear branching process models of mutation-selection balance, nonequilibrium population dynamics, and evolutionary games.

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