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Asymptotic expansion for additive measure of branching Brownian motion (2310.18632v1)

Published 28 Oct 2023 in math.PR

Abstract: Let $N(t)$ be the collection of particles alive at time $t$ in a branching Brownian motion in $\mathbb{R}d$, and for $u\in N(t)$, let $\mathbf{X}u(t)$ be the position of particle $u$ at time $t$. For $\theta\in \mathbb{R}d$, we define the additive measures of the branching Brownian motion by$$\mu_t\theta (\mathrm{d}\mathbf{x}):= e{-(1+\frac{\Vert\theta\Vert2}{2})t}\sum{u\in N(t)} e{-\theta \cdot \mathbf{X}u(t)} \delta{\left(\mathbf{X}_u(t)+\theta t\right)}(\mathrm{d}\mathbf{x}).$$ In this paper, under some conditions on the offspring distribution, we give asymptotic expansions of arbitrary order for $\mu_t\theta ((\mathbf{a}, \mathbf{b}])$ and $\mu_t\theta ((-\infty, \mathbf{a}])$ for $\theta\in \mathbb{R}d$ with $\Vert \theta \Vert <\sqrt{2}$. These expansions sharpen the asymptotic results of Asmussen and Kaplan (1976) and Kang (1999), and are analogs of the expansions in Gao and Liu (2021) and R\'{e}v\'{e}sz, Rosen and Shi (2005) for branching Wiener processes (a particular class of branching random walks) corresponding to $\theta=\mathbf{0}$.

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