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arXiv 1709.01253math.PR
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随机游动上的随机游动:高维

Random walk on random walks: higher dimensions

Oriane Blondel, Marcelo R. Hilario, Renato Soares dos Santos, Vladas Sidoravicius, Augusto Teixeira

摘要:

我们研究了由独立粒子组成的保守动态随机环境中的随机游动粒子的演化,这些粒子执行简单的对称随机游动,将[16]的结果推广到更高的维度和更一般的过渡核,而无需假设一致椭圆性或最近邻跳跃。具体地说,我们得到了一个强大数律,一个泛函中心极限定理和大偏差估计下的退火法律在高密度制度下的随机游动的位置。主要的障碍是在高维,非最近邻设置的内在缺乏单调性。在这里,我们开发更一般的重整化和更新计划,使我们能够克服这个问题。作为我们方法的第二个应用,我们提供了[23]中引入的感染模型(离散时间版本)的前沿弹道行为的另一种证明。

英文摘要:

We study the evolution of a random walker on a conservative dynamic random environment composed of independent particles performing simple symmetric random walks, generalizing results of [16] to higher dimensions and more general transition kernels without the assumption of uniform ellipticity or nearest-neighbour jumps. Specifically, we obtain a strong law of large numbers, a functional central limit theorem and large deviation estimates for the position of the random walker under the annealed law in a high density regime. The main obstacle is the intrinsic lack of monotonicity in higher-dimensional, non-nearest neighbour settings. Here we develop more general renormalization and renewal schemes that allow us to overcome this issue. As a second application of our methods, we provide an alternative proof of the ballistic behaviour of the front of (the discrete-time version of) the infection model introduced in [23].

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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