Sharp asymptotics for the quasi-stationary distribution of birth-and-death processes

TL;DR

This paper analyzes the behavior and distribution of large population birth-and-death processes near extinction, providing precise asymptotics for the quasi-stationary distribution and mean time to extinction as the carrying capacity grows.

Contribution

It offers a detailed quantitative analysis of the quasi-stationary distribution and extinction times for birth-and-death processes with large carrying capacity, including Gaussian approximation.

Findings

Quasi-stationary distribution is approximately Gaussian for large carrying capacity.

Mean time to extinction grows exponentially with the carrying capacity.

Spectral gap estimates enable precise asymptotic descriptions.

Abstract

We study a general class of birth-and-death processes with state space $\mathbb{N}$ that describes the size of a population going to extinction with probability one. This class contains the logistic case. The scale of the population is measured in terms of a `carrying capacity' $K$. When $K$ is large, the process is expected to stay close to its deterministic equilibrium during a long time but ultimately goes extinct. Our aim is to quantify the behavior of the process and the mean time to extinction in the quasi-stationary distribution as a function of $K$, for large $K$. We also give a quantitative description of this quasi-stationary distribution. It turns out to be close to a Gaussian distribution centered about the deterministic long-time equilibrium, when $K$ is large. Our analysis relies on precise estimates of the maximal eigenvalue, of the corresponding eigenvector and of the spectral gap of a self-adjoint operator associated with the semigroup of the process.