Time reversal of spinal processes for linear and non-linear branching processes near stationarity

Benoît Henry, Sylvie Méléard, Viet Chi Tran

Research output: Contribution to journalArticlepeer-review

Abstract

We consider a stochastic individual-based population model with competition, trait-structure affecting reproduction and survival, and changing environment. The changes of traits are described by jump processes, and the dynamics can be approximated in large population by a non-linear PDE with a non-local mutation operator. Using the fact that this PDE admits a non-trivial stationary solution, we can approximate the non-linear stochastic population process by a linear birth-death process where the interactions are frozen, as long as the population remains close to this equilibrium. This allows us to derive, when the population is large, the equation satisfied by the ancestral lineage of an individual uniformly sampled at a fixed time T, which is the path constituted of the traits of the ancestors of this individual in past times t ≤ T . This process is a time inhomogeneous Markov process, but we show that the time reversal of this process possesses a very simple structure (e.g. time-homogeneous and independent of T ). This extends recent results where the authors studied a similar model with a Laplacian operator but where the methods essentially relied on the Gaussian nature of the mutations.

Original languageEnglish
Article number32
JournalElectronic Journal of Probability
Volume28
DOIs
Publication statusPublished - 1 Jan 2023
Externally publishedYes

Keywords

  • ancestral path
  • birth-death processes
  • competition
  • genealogy
  • interaction
  • jump process
  • many-to-one formula
  • non-local mutation operator
  • phylogeny
  • stochastic individual-based models

Fingerprint

Dive into the research topics of 'Time reversal of spinal processes for linear and non-linear branching processes near stationarity'. Together they form a unique fingerprint.

Cite this