{"title":"On multidimensional locally perturbed standard random walks","authors":"Congzao Dong, Alexander Iksanov, Andrey Pilipenko","doi":"10.1007/s10986-024-09639-x","DOIUrl":null,"url":null,"abstract":"<p>Let <i>d</i> be a positive integer, and let <i>A</i> be a set in <span>\\({\\mathbb{Z}}^{d}\\)</span> that contains finitely many points with integer coordinates. We consider a standard random walk <i>X</i> perturbed on the set <i>A</i>. This means that <i>X</i> is a Markov chain whose transition probabilities from the points outside <i>A</i> coincide with those of a standard random walk on <span>\\({\\mathbb{Z}}^{d}\\)</span>, whereas the transition probabilities from the points inside <i>A</i> are different. We investigate the impact of the perturbation on a scaling limit of <i>X</i>. It turns out that if <i>d</i> ⩾ 2, then in a typical situation the scaling limit of <i>X</i> coincides with that of the underlying standard random walk. This is unlike the case <i>d</i> = 1<i>,</i> in which the scaling limit of <i>X</i> is usually a skew Brownian motion, a skew stable Lévy process, or some other “skew” process. The distinction between the one-dimensional and multidimensional cases under comparable assumptions may simply be caused by transience of the underlying standard random walk in <span>\\({\\mathbb{Z}}^{d}\\)</span> for <i>d</i> ⩾ 3. More interestingly, in the situation where the standard random walk in <span>\\({\\mathbb{Z}}^{2}\\)</span> is recurrent, the preservation of its Donsker scaling limit is secured by the fact that the number of visits of <i>X</i> to the set <i>A</i> is much smaller than in the one-dimensional case. As a consequence, the influence of the perturbation vanishes upon the scaling. On the other edge of the spectrum, we have the situation in which the standard random walk admits a Donsker’s scaling limit, whereas its locally perturbed version does not because of huge jumps from the set <i>A,</i> which occur early enough.</p>","PeriodicalId":51108,"journal":{"name":"Lithuanian Mathematical Journal","volume":"11 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lithuanian Mathematical Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10986-024-09639-x","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
Let d be a positive integer, and let A be a set in \({\mathbb{Z}}^{d}\) that contains finitely many points with integer coordinates. We consider a standard random walk X perturbed on the set A. This means that X is a Markov chain whose transition probabilities from the points outside A coincide with those of a standard random walk on \({\mathbb{Z}}^{d}\), whereas the transition probabilities from the points inside A are different. We investigate the impact of the perturbation on a scaling limit of X. It turns out that if d ⩾ 2, then in a typical situation the scaling limit of X coincides with that of the underlying standard random walk. This is unlike the case d = 1, in which the scaling limit of X is usually a skew Brownian motion, a skew stable Lévy process, or some other “skew” process. The distinction between the one-dimensional and multidimensional cases under comparable assumptions may simply be caused by transience of the underlying standard random walk in \({\mathbb{Z}}^{d}\) for d ⩾ 3. More interestingly, in the situation where the standard random walk in \({\mathbb{Z}}^{2}\) is recurrent, the preservation of its Donsker scaling limit is secured by the fact that the number of visits of X to the set A is much smaller than in the one-dimensional case. As a consequence, the influence of the perturbation vanishes upon the scaling. On the other edge of the spectrum, we have the situation in which the standard random walk admits a Donsker’s scaling limit, whereas its locally perturbed version does not because of huge jumps from the set A, which occur early enough.
设 d 为正整数,设 A 是 \({\mathbb{Z}}^{d}\) 中的一个集合,其中包含有限多个具有整数坐标的点。这意味着 X 是一个马尔可夫链,它从 A 以外的点出发的过渡概率与在\({\mathbb{Z}}^{d}\)上的标准随机行走的过渡概率重合,而从 A 内的点出发的过渡概率则不同。我们研究了扰动对 X 的缩放极限的影响。结果发现,如果 d ⩾ 2,那么在典型情况下,X 的缩放极限与底层标准随机游走的缩放极限重合。这与 d = 1 的情况不同,在这种情况下,X 的缩放极限通常是偏布朗运动、偏稳定莱维过程或其他 "偏斜 "过程。在d ⩾ 3的情况下,一维和多维情况在可比假设下的区别可能仅仅是由于在 \({\mathbb{Z}}^{d}\) 中底层标准随机游走的瞬时性造成的。更有趣的是,在 \({\mathbb{Z}}^{2}\ 中的标准随机游走是经常性的情况下,由于 X 访问集合 A 的次数比在一维情况下少得多,它的唐斯克缩放极限得以保留。因此,扰动对缩放的影响消失了。在频谱的另一边缘,我们会遇到这样的情况:标准随机游走存在唐斯克缩放极限,而其局部扰动版本却不存在,因为从集合 A 开始的巨大跳跃发生得足够早。
期刊介绍:
The Lithuanian Mathematical Journal publishes high-quality original papers mainly in pure mathematics. This multidisciplinary quarterly provides mathematicians and researchers in other areas of science with a peer-reviewed forum for the exchange of vital ideas in the field of mathematics.
The scope of the journal includes but is not limited to:
Probability theory and statistics;
Differential equations (theory and numerical methods);
Number theory;
Financial and actuarial mathematics, econometrics.