A remark on uniform expansion

IF 0.6 4区 数学 Q3 MATHEMATICS
R. Potrie
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引用次数: 1

Abstract

For every U ⊂ Diffvol(T) there is a measure of finite support contained in U which is uniformly expanding. 0. Introduction Let μ be a probability measure in Diff(M) where M is a closed manifold of dimension d := dim(M). We denote μ(1) = μ and μ(n) = μ∗μ(n−1). Note that μ(n) is the pushforward by the composition of the product measure μ in (Diff(M))n. Definition 0.1 ([8, 4]). A probability measure μ in Diff(M) is uniformly expanding if there exists N > 0 such that for every (x, v) ∈ T 1M one has that ∫ log ‖Dxfv‖ dμ(N)(f) > 2. This is a robust1 condition on μ. This notion as well as similar ones have been studied extensively recently, as it allows one to describe quite precisely the stationary measures for random walks with μ as law (see below for more discussion). Here we will make a remark (which can be related to some results, e.g. in [3, 6, 14]) that points in the direction of the abundance of uniform expansion. Theorem 0.2. For every open set U in Diffvol(T) there is a finitely supported probability measure μ whose support is contained in U and μ is uniformly expanding. As a consequence of the results of [5, 13, 6] one deduces that: Corollary 0.3. For every U ⊂ Diffvol(T) there is a probability measure μ finitely supported in U such that the orbit of every point under the random walk on T2 produced by μ equidistributes in T2. Moreover, for every μ′ close to μ in the weak-∗ 2020 Mathematics Subject Classification. 37H15. Rafael Potrie was partially supported by CSIC 618, FCE-1-2017-1-135352. This work was started while the author was a Von Neumann fellow at IAS, funded by the Minerva Research Foundation Membership Fund and NSF DMS-1638352. 1To be precise, if μ has compact support, then there is a neighborhood U of its support such that any measure μ′ which has support in U and is weak-∗-close to μ, is also uniformly expanding (see (3.1) below).
关于均匀膨胀的评论
对于每一个U∧Diffvol(T), U中都有一个有限支持的度量,它是均匀膨胀的。0. 设μ是Diff(M)中的一个概率测度,其中M是维数d:= dim(M)的封闭流形。我们令μ(1) = μ, μ(n) = μ∗μ(n−1)。请注意,μ(n)是由乘积度量μ in (Diff(M))n组成的推入。定义0.1([8,4])。如果存在N >,则在Diff(M)中的概率测度μ是均匀展开的,使得对于每一个(x, v)∈t1m,有∫log‖Dxfv‖dμ(N)(f) > 2。这是μ的鲁棒条件。这个概念以及类似的概念最近得到了广泛的研究,因为它允许人们相当精确地描述具有μ as定律的随机游走的平稳测度(见下文进行更多讨论)。在这里,我们将做一个注释(这可能与一些结果有关,例如在[3,6,14]中),指向均匀膨胀丰度的方向。定理0.2。对于Diffvol(T)中的每一个开集U,存在一个有限支持的概率测度μ,其支持度包含在U中,且μ是均匀展开的。根据[5,13,6]的结果,可以得出:推论0.3。对于每一个U∧Diffvol(T),在U中存在一个μ有限支持的概率测度,使得在T2上由μ产生的随机漫步下的每一点的轨道在T2中均匀分布。此外,对于每一个μ '接近μ弱-∗2020数学主题分类。37H15。Rafael Potrie得到CSIC 618, FCE-1-2017-1-135352的部分支持。这项工作开始于作者在IAS担任Von Neumann研究员期间,由Minerva研究基金会会员基金和NSF DMS-1638352资助。确切地说,如果μ有紧支持,则存在其支持的邻域U,使得任何在U中有支持且弱- * -接近μ的测度μ '也均匀展开(见下文(3.1))。
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来源期刊
Revista De La Union Matematica Argentina
Revista De La Union Matematica Argentina MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
0.70
自引率
0.00%
发文量
39
审稿时长
>12 weeks
期刊介绍: Revista de la Unión Matemática Argentina is an open access journal, free of charge for both authors and readers. We publish original research articles in all areas of pure and applied mathematics.
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