Projection of Markov measures may be Gibbsian

We study the induced measure obtained from a 1-step Markov measure, supported by a topological Markov chain, after the mapping of the original alphabet onto another one. We give sufficient conditions for the induced measure to be a Gibbs measure (in the sense of Bowen) when the factor system is again a topological Markov chain. This amounts to constructing, when it does exist, the induced potential and proving its Holder continuity. This is achieved through a matrix method. We provide examples and counterexamples to illustrate our results.Comment: 4 latex figure

Birkhoff averages of Poincare cycles for Axiom-A diffeomorphisms

We study the time of $n$th return of orbits to some given (union of) rectangle(s) of a Markov partition of an Axiom A diffeomorphism. Namely, we prove the existence of a scaled generating function for these returns with respect to any Gibbs measure (associated to a Holderian potential). As a by-product, we derive precise large deviation estimates and a central limit theorem for Birkhoff averages of Poincare cycles. We emphasize that we look at the limiting behavior in term of number of visits (the size of the visited set is kept fixed). Our approach relies on the spectral properties of a one-parameter family of induced transfer operators on unstable leaves crossing the visited set.Comment: 17 pages; submitte

Multifractals via recurrence times ?

This letter is a comment on an article by T.C. Halsey and M.H. Jensen in Nature about using recurrence times as a reliable tool to estimate multifractal dimensions of strange attractors. Our aim is to emphasize that in the recent mathematical literature (not cited by these authors), there are positive as well as negative results about the use of such techniques. Thus one may be careful in using this tool in practical situations (experimental data).Comment: This is a very short and non-technical note written after an article published in Nature by T.C. Halsey and M.H. Jense

On almost-sure versions of classical limit theorems for dynamical systems

The purpose of this article is to construct a toolbox, in Dynamical Systems, to support the idea that ``whenever we can prove a limit theorem in the classical sense for a dynamical system, we can prove a suitable almost-sure version based on an empirical measure with log-average''. We follow three different approaches: martingale methods, spectral methods and induction arguments. Our results apply among others to Axiom A maps or flows, to systems inducing a Gibbs-Markov map and to the stadium billiard.Comment: 41 pages; submitted v2: replaced the argument for Gibbs-Markov maps with a general spectral argumen

Testing the irreversibility of a Gibbsian process via hitting and return times

We introduce estimators for the entropy production of a Gibbsian process based on the observation of a single or two typical trajectories. These estimators are built with adequate hitting and return times. We then study their convergence and fluctuation properties. This provides statisticals test for the irreversibility of Gibbsian processes.Comment: 16 pages; Corrected version; To appear in Nonlinearit