A modified lookdown construction for the Xi-Fleming-Viot process with mutation and populations with recurrent bottlenecks
Matthias Birkner, Jochen Blath, Martin Moehle, Matthias Steinruecken, and Johanna Tams

TL;DR
This paper constructs a dual process for the $ ext{Xi}$-Fleming-Viot process with mutation, using a modified lookdown approach, and analyzes populations with recurrent bottlenecks, extending classical models to more complex coalescent structures.
Contribution
It introduces a new lookdown construction for the $ ext{Xi}$-Fleming-Viot process with mutation and provides convergence results and alternative semigroup representations.
Findings
Explicit dual process construction for $ ext{Xi}$-Fleming-Viot with mutation.
Pathwise convergence of particle systems to the limiting process.
Limiting models for populations with recurrent bottlenecks.
Abstract
Let be a finite measure on the unit interval. A -Fleming-Viot process is a probability measure valued Markov process which is dual to a coalescent with multiple collisions (-coalescent) in analogy to the duality known for the classical Fleming Viot process and Kingman's coalescent, where is the Dirac measure in 0. We explicitly construct a dual process of the coalescent with simultaneous multiple collisions (-coalescent) with mutation, the -Fleming-Viot process with mutation, and provide a representation based on the empirical measure of an exchangeable particle system along the lines of Donnelly and Kurtz (1999). We establish pathwise convergence of the approximating systems to the limiting -Fleming-Viot process with mutation. An alternative construction of the semigroup based on the Hille-Yosida theorem is provided and various…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and statistical mechanics · Algorithms and Data Compression
