Wasserstein convergence rates in the invariance principle for sequential dynamical systems

Fuente: arXiv
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Main Authors: Liu, Zhenxin, Wang, Zhe
Format: Preprint
Published: 2023
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author Liu, Zhenxin
Wang, Zhe
author_facet Liu, Zhenxin
Wang, Zhe
contents In this paper, we consider the convergence rate with respect to the Wasserstein distance in the invariance principle for sequential dynamical systems. We utilize and modify the techniques previously employed for stationary sequences to address our non-stationary case. Under certain assumptions, we can apply our result to a large class of dynamical systems, including sequential $β_n$-transformations, piecewise uniformly expanding maps with additive noise in one-dimensional and multidimensional case, and so on.
format Preprint
id arxiv_https___arxiv_org_abs_2307_13913
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Wasserstein convergence rates in the invariance principle for sequential dynamical systems
Liu, Zhenxin
Wang, Zhe
Dynamical Systems
37A50, 60F17, 37C99, 60B10
In this paper, we consider the convergence rate with respect to the Wasserstein distance in the invariance principle for sequential dynamical systems. We utilize and modify the techniques previously employed for stationary sequences to address our non-stationary case. Under certain assumptions, we can apply our result to a large class of dynamical systems, including sequential $β_n$-transformations, piecewise uniformly expanding maps with additive noise in one-dimensional and multidimensional case, and so on.
title Wasserstein convergence rates in the invariance principle for sequential dynamical systems
topic Dynamical Systems
37A50, 60F17, 37C99, 60B10
url https://arxiv.org/abs/2307.13913