Law of iterated logarithm for supercritical non-symmetric branching Markov process

Fuente: arXiv
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Hauptverfasser: Hou, Haojie, Ren, Yan-Xia, Song, Renming
Format: Preprint
Veröffentlicht: 2025
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author Hou, Haojie
Ren, Yan-Xia
Song, Renming
author_facet Hou, Haojie
Ren, Yan-Xia
Song, Renming
contents Let $\{(X_t)_{t\geq 0}, \mathbb{P}_{δ_x}, x\in E\}$ be a supercritical branching Markov process (which is not necessary symmetric) on a locally compact metric measure space $(E,μ)$ with spatially dependent local branching mechanism. Under some assumptions on the semigroup of the spatial motion, we first prove law of iterated logarithm type results for $\langle f, X_t\rangle$ under the second moment condition on the branching mechanism, where $f$ is a linear combination of eigenfunctions of the mean semigroup $\{T_t, t\geq0\}$ of $X$. Then we prove law of iterated logarithm type results for $\langle f, X_t\rangle$ under the fourth moment condition, where $f$ belongs to a larger class of functions.
format Preprint
id arxiv_https___arxiv_org_abs_2505_12691
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Law of iterated logarithm for supercritical non-symmetric branching Markov process
Hou, Haojie
Ren, Yan-Xia
Song, Renming
Probability
Let $\{(X_t)_{t\geq 0}, \mathbb{P}_{δ_x}, x\in E\}$ be a supercritical branching Markov process (which is not necessary symmetric) on a locally compact metric measure space $(E,μ)$ with spatially dependent local branching mechanism. Under some assumptions on the semigroup of the spatial motion, we first prove law of iterated logarithm type results for $\langle f, X_t\rangle$ under the second moment condition on the branching mechanism, where $f$ is a linear combination of eigenfunctions of the mean semigroup $\{T_t, t\geq0\}$ of $X$. Then we prove law of iterated logarithm type results for $\langle f, X_t\rangle$ under the fourth moment condition, where $f$ belongs to a larger class of functions.
title Law of iterated logarithm for supercritical non-symmetric branching Markov process
topic Probability
url https://arxiv.org/abs/2505.12691