A large deviation theorem for a supercritical super-Brownian motion with absorption

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Ya-Jie Zhu
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引用次数: 0

Abstract

We consider a one-dimensional superprocess with a supercritical local branching mechanism $\psi$ , where particles move as a Brownian motion with drift $-\rho$ and are killed when they reach the origin. It is known that the process survives with positive probability if and only if $\rho<\sqrt{2\alpha}$ , where $\alpha=-\psi'(0)$ . When $\rho<\sqrt{2 \alpha}$ , Kyprianou et al. [18] proved that $\lim_{t\to \infty}R_t/t =\sqrt{2\alpha}-\rho$ almost surely on the survival set, where $R_t$ is the rightmost position of the support at time t. Motivated by this work, we investigate its large deviation, in other words, the convergence rate of $\mathbb{P}_{\delta_x} (R_t >\gamma t+\theta)$ as $t \to \infty$ , where $\gamma >\sqrt{2 \alpha} -\rho$ , $\theta \ge 0$ . As a by-product, a related Yaglom-type conditional limit theorem is obtained. Analogous results for branching Brownian motion can be found in Harris et al. [13].
带吸收的超临界超布朗运动的大偏差定理
我们考虑一个具有超临界局部分支机制$\psi$的一维超过程,其中粒子以漂移$-\rho$的布朗运动的形式移动,并在到达原点时被杀死。已知过程以正概率生存当且仅当$\rho,其中$\alpha=-\psi'(0)$。当$\rho,Kyprianou等人[18]证明$\lim_{t\to\infty}R_t/t=\sqrt{2\alpha}-\rho$几乎肯定在生存集上时,其中$R_t$是时间t时支持的最右位置。受此工作的启发,我们研究了它的大偏差,换句话说,$\mathbb的收敛速度{P}_{\delta_x}(R_t>\gamma t+\theta)$为$t\to\infty$,其中$\gamma>\sqrt{2\alpha}-\rho$,$\theta\ge 0$。作为副产品,得到了一个相关的Yaglom型条件极限定理。分支布朗运动的类似结果可以在Harris等人[13]中找到。
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来源期刊
Journal of Applied Probability
Journal of Applied Probability 数学-统计学与概率论
CiteScore
1.50
自引率
10.00%
发文量
92
审稿时长
6-12 weeks
期刊介绍: Journal of Applied Probability is the oldest journal devoted to the publication of research in the field of applied probability. It is an international journal published by the Applied Probability Trust, and it serves as a companion publication to the Advances in Applied Probability. Its wide audience includes leading researchers across the entire spectrum of applied probability, including biosciences applications, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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