The elephant random walk (ERW), first introduced by Sch\"utz and Trimper (2004), is a one-dimensional simple random walk on $ \mathbb{Z} $ having a memory about the whole past. We study the shark random walk, a random walk whose steps are $ \alpha $-stable distributed with memory about the whole past. In contrast with the ERW, the steps of the shark random walk have a heavy tailed distribution. Our aim in this work is to study the impact of the heavy tailed step distributions on the asymptotic behavior of the random walk. We shall see that, as for the ERW, the asymptotic behavior of the shark random walk depends on its memory parameter $ p $, and that a phase transition can be observed at the critical value $ p=\frac{1}{\alpha} $.
翻译:由Sch\"utz"和Trimper(2004年)首次引入的大象随机行走(ERW)是用对过去有记忆的$\mathbb ⁇ 美元进行的单维简单随机行走。我们研究了鲨鱼随机行走,这是随机行走,其步骤为$\alpha美元,与整个过去的记忆分布相仿。与战争遗留爆炸物相比,鲨鱼随机行走的步骤的尾巴分布严重尾细小。我们这项工作的目的是研究重尾巴行走分布对随机行走的无药行为的影响。我们可以看到,就战争遗留爆炸物而言,鲨鱼随机行走的无药行为取决于其记忆参数$p $,并且可以以临界值 $ p ⁇ frac{1úllpha} 观察到一个阶段的转变。