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Convergence of multiple ergodic averages  [PDF]
Bernard Host
Mathematics , 2006,
Abstract: These notes are based on a course for a general audience given at the Centro de Modeliamento Matem\'atico of the University of Chile, in December 2004. We study the mean convergence of multiple ergodic averages, that is, averages of a product of functions taken at different times. We also describe the relations between this area of ergodic theory and some classical and some recent results in additive number theory.
Bounds for estimators of ergodic averages  [PDF]
A. Meson,F. Vericat
International Journal of Mathematical Analysis , 2013,
Abstract: We consider different ergodic averages and estimate the measure of the set ofpoints in which the averages apart from a given value. The cases considered areempirical measures of cylinders in symbolic spaces and averages of maps given a kindLyapunov exponents, in a such spaces. Besides we obtain bounds for the fluctuationsof ergodic averages from amenable action groups. The bounds obtained are validfor any ¨time¨, not only, like in case of large deviations, for asymptotic values.
Local stability of ergodic averages  [PDF]
Jeremy Avigad,Philipp Gerhardy,Henry Towsner
Mathematics , 2007,
Abstract: The mean ergodic theorem is equivalent to the assertion that for every function K and every epsilon, there is an n with the property that the ergodic averages A_m f are stable to within epsilon on the interval [n,K(n)]. We show that even though it is not generally possible to compute a bound on the rate of convergence of a sequence of ergodic averages, one can give explicit bounds on n in terms of K and || f || / epsilon. This tells us how far one has to search to find an n so that the ergodic averages are "locally stable" on a large interval. We use these bounds to obtain a similarly explicit version of the pointwise ergodic theorem, and show that our bounds are qualitatively different from ones that can be obtained using upcrossing inequalities due to Bishop and Ivanov. Finally, we explain how our positive results can be viewed as an application of a body of general proof-theoretic methods falling under the heading of "proof mining."
On the pointwise convergence of multiple ergodic averages  [PDF]
E. H. El Abdalaoui
Mathematics , 2014,
Abstract: It is shown that the multiple ergodic averages of commuting invertible measure preserving transformations of a Lebesgue probability space converge almost everywhere provided that the maps are weakly mixing with an ergodic extra condition.
Level sets of multiple ergodic averages  [PDF]
Fan Ai-Hua,Lingmin Liao,Ji-Hua Ma
Mathematics , 2011,
Abstract: We propose to study multiple ergodic averages from multifractal analysis point of view. In some special cases in the symbolic dynamics, Hausdorff dimensions of the level sets of multiple ergodic average limit are determined by using Riesz products.
Ergodic averages with deterministic weights  [PDF]
Fabien Durand,Dominique Schneider
Mathematics , 2008,
Abstract: The purpose of this paper is to study ergodic averages with deterministic weights. More precisely we study the convergence of the ergodic averages of the type $\frac{1}{N} \sum_{k=0}^{N-1} \theta (k) f \circ T^{u_k}$ where $\theta = (\theta (k) ; k\in \NN)$ is a bounded sequence and $u = (u_k ; k\in \NN)$ a strictly increasing sequence of integers such that for some $\delta<1$ $$ S_N (\theta, u) := \sup_{\alpha \in \pRR} | \sum_{k=0}^{N-1} \theta (k) \exp (2i\pi \alpha u_k) | = O (N^{\delta}) \leqno{({\cal H}_1)} $$ i.e., there exists a constant $C$ such that $S_N (\theta, u) \leq C N^{\delta} $. We define $\delta (\theta, u)$ to be the infimum of the $\delta $ satisfying $\H_1$ for $\theta $ and $u$.
Multifractal Analysis of Multiple Ergodic Averages  [PDF]
Ai-Hua Fan,Joerg Schmeling,Meng Wu
Mathematics , 2011,
Abstract: In this paper we present a complete solution to the problem of multifractal analysis of multiple ergodic averages in the case of symbolic dynamics for functions of two variables depending on the first coordinate.
Norm convergence of nilpotent ergodic averages  [PDF]
Miguel N. Walsh
Mathematics , 2011,
Abstract: We show that multiple polynomial ergodic averages arising from nilpotent groups of measure preserving transformations of a probability space always converge in the L^2 norm.
Powers of sequences and convergence of ergodic averages  [PDF]
Nikos Frantzikinakis,Michael Johnson,Emmanuel Lesigne,Mate Wierdl
Mathematics , 2008,
Abstract: A sequence $(s_n)$ of integers is good for the mean ergodic theorem if for each invertible measure preserving system $(X,\mathcal{B},\mu,T)$ and any bounded measurable function $f$, the averages $ \frac1N \sum_{n=1}^N f(T^{s_n}x)$ converge in the $L^2$ norm. We construct a sequence $(s_n)$ that is good for the mean ergodic theorem, but the sequence $(s_n^2)$ is not. Furthermore, we show that for any set of bad exponents $B$, there is a sequence $(s_n)$ where $(s_n^k)$ is good for the mean ergodic theorem exactly when $k$ is not in $B$. We then extend this result to multiple ergodic averages. We also prove a similar result for pointwise convergence of single ergodic averages.
On the norm convergence of nonconventional ergodic averages  [PDF]
Tim Austin
Mathematics , 2008,
Abstract: We offer a generalization of the recent result of Tao (building on earlier results of Conze and Lesigne, Furstenberg and Weiss, Zhang, Host and Kra, Frantzikinakis and Kra and Ziegler) that the nonconventional ergodic averages associated to an arbitrary number of commuting probability-preserving transformations always converge to some limit in L^2. We prove the corresponding result for a collection of commuting actions of a larger discrete Abelian group, and gives convergence that is uniform in the start-point of the averages. While Tao's proof rests on a conversion to a finitary problem, we invoke only techniques from classical ergodic theory, so giving a new proof of his result.
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