Convergence of spatial branching processes to $α$-stable CSBPs: Genealogy of semi-pushed fronts
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| Format: | Preprint |
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2024
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| author | Foutel-Rodier, Félix Schertzer, Emmanuel Tourniaire, Julie |
| author_facet | Foutel-Rodier, Félix Schertzer, Emmanuel Tourniaire, Julie |
| contents | We consider inhomogeneous branching diffusions on an infinite domain of $\mathbb{R}^d$. The first aim of this article is to derive a general criterium under which the size process (number of particles) and the genealogy of the particle system become undistinguishable from the ones of an $α$-stable CSBP, with $α\in(1,2)$. The branching diffusion is encoded as a random metric space capturing all the information about the positions and the genealogical structure of the population. Our convergence criterium is based on the convergence of the moments for random metric spaces, which in turn can be efficiently computed through many-to-few formulas. It requires an extension of the method of moments to general CSBPs (with or without finite second moment).
In a recent work, Tourniaire introduced a branching Brownian motion which can be thought of as a toy model for fluctuating pushed fronts. The size process was shown to converge to an $α$-stable CSBP and it was conjectured that a genealogical convergence should occur jointly. We prove this result as an application of our general methodology. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2402_05096 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Convergence of spatial branching processes to $α$-stable CSBPs: Genealogy of semi-pushed fronts Foutel-Rodier, Félix Schertzer, Emmanuel Tourniaire, Julie Probability We consider inhomogeneous branching diffusions on an infinite domain of $\mathbb{R}^d$. The first aim of this article is to derive a general criterium under which the size process (number of particles) and the genealogy of the particle system become undistinguishable from the ones of an $α$-stable CSBP, with $α\in(1,2)$. The branching diffusion is encoded as a random metric space capturing all the information about the positions and the genealogical structure of the population. Our convergence criterium is based on the convergence of the moments for random metric spaces, which in turn can be efficiently computed through many-to-few formulas. It requires an extension of the method of moments to general CSBPs (with or without finite second moment). In a recent work, Tourniaire introduced a branching Brownian motion which can be thought of as a toy model for fluctuating pushed fronts. The size process was shown to converge to an $α$-stable CSBP and it was conjectured that a genealogical convergence should occur jointly. We prove this result as an application of our general methodology. |
| title | Convergence of spatial branching processes to $α$-stable CSBPs: Genealogy of semi-pushed fronts |
| topic | Probability |
| url | https://arxiv.org/abs/2402.05096 |