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Robustness of ergodic properties of non-autonomous piecewise expanding maps

Published online by Cambridge University Press:  25 September 2017

MATTEO TANZI
Affiliation:
Department of Mathematics, South Kensington Campus, London SW7 2AZ, UK email m.tanzi13@imperial.ac.uk, tiago.pereira@imperial.ac.uk, s.van-strien@imperial.ac.uk
TIAGO PEREIRA
Affiliation:
Department of Mathematics, South Kensington Campus, London SW7 2AZ, UK email m.tanzi13@imperial.ac.uk, tiago.pereira@imperial.ac.uk, s.van-strien@imperial.ac.uk Institute of Mathematical and Computer Sciences, Universidade de São Paulo, São Carlos 13566-590, São Paulo, Brazil
SEBASTIAN VAN STRIEN
Affiliation:
Department of Mathematics, South Kensington Campus, London SW7 2AZ, UK email m.tanzi13@imperial.ac.uk, tiago.pereira@imperial.ac.uk, s.van-strien@imperial.ac.uk

Abstract

Recently, there has been an increasing interest in non-autonomous composition of perturbed hyperbolic systems: composing perturbations of a given hyperbolic map $F$ results in statistical behaviour close to that of $F$. We show this fact in the case of piecewise regular expanding maps. In particular, we impose conditions on perturbations of this class of maps that include situations slightly more general than what has been considered so far, and prove that these are stochastically stable in the usual sense. We then prove that the evolution of a given distribution of mass under composition of time-dependent perturbations (arbitrarily—rather than randomly—chosen at each step) close to a given map $F$ remains close to the invariant mass distribution of $F$. Moreover, for almost every point, Birkhoff averages along trajectories do not fluctuate wildly. This result complements recent results on memory loss for non-autonomous dynamical systems.

Type
Original Article
Copyright
© Cambridge University Press, 2017 

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References

Alves, J. F. and Araujo, V.. Random perturbations of nonuniformly expanding maps. Astérisque 286 (2003), 2562.Google Scholar
Aimino, R., Hu, H., Nicol, M., Török, A. and Vaienti, S.. Polynomial loss of memory for maps of the interval with a neutral fixed point. Discrete Contin. Dyn. Syst. 35(3) (2015), 793806.Google Scholar
Aimino, R. and Rousseau, J.. Concentration inequalities for sequential dynamical systems of the unit interval. Ergod. Th. & Dynam. Sys. 36(8) (2016), 23842407.Google Scholar
Araujo, V. and Tahzibi, A.. Stochastic stability at the boundary of expanding maps. Nonlinearity 18(3) (2005), 939958.Google Scholar
Baladi, V.. Positive Transfer Operators and Decay of Correlations. World Scientific, River Edge, NJ, 2000.Google Scholar
Boyarsky, A. and Gora, P.. Absolutely continuous invariant measures for piecewise expanding C 2 transformations in ℝ n . Israel J. Math. 67(3) (1989), 272286.Google Scholar
Boyarsky, A. and Gora, P.. Laws of Chaos: Invariant Measures and Dynamical Systems in One Dimension. Birkhauser, Boston, MA, 1997.Google Scholar
Blank, M., Keller, G. and Liverani, C.. Ruelle–Perron–Frobenius spectrum for Anosov maps. Nonlinearity 15(6) (2002), 19051973.Google Scholar
Baladi, V. and Young, L.-S.. On the spectra of randomly perturbed expanding maps. Comm. Math. Phys. 156(2) (1993), 355385.Google Scholar
Cowieson, W. J.. Stochastic stability for piecewise expanding maps in R d . Nonlinearity 13 (2000), 17451760.Google Scholar
Conze, J.-P. and Raugi, A.. Limit theorems for sequential expanding dynamical systems on [0, 1]. Contemp. Math. 430 (2007), 89122.Google Scholar
Dobbs, N. and Stenlund, M.. Quasistatic dynamical systems. Ergod. Th. & Dynam. Sys. (2016), 141 doi:10.1017/etds.2016.9.Google Scholar
Gupta, C., Ott, W. and Török, A.. Memory loss for time-dependent piecewise-expanding systems in higher dimension. Math. Res. Lett. 20(1) (2013), 141161.Google Scholar
Haydn, N., Nicol, M., Török, A. and Vaienti, S.. Almost sure invariance principle for sequential and non-stationary dynamical systems. Trans. Amer. Math. Soc. 369(8) (2017), 52935316.Google Scholar
Ionescu-Tulcea, C. T. and Marinescu, G.. Théorie ergodique pour des classes d’opérations non complètement continues. Ann. of Math. (2) 52(1) (1950), 140147.Google Scholar
Keller, G.. Stochastic stability in some chaotic dynamical systems. Monatsh. Math. 94(4) (1982), 313333 in English.Google Scholar
Keller, G.. Stochastic stability of some one-dimensional dynamical systems. Ergodic Theory and Related Topics, Proc. Conf. held in Vitte/Hiddensee, 19–23 October 1981. Akademie, 1982, pp. 123127.Google Scholar
Keller, G. and Liverani, C.. Stability of the spectrum for transfer operators. Ann. Sc. Norm. Super. Pisa Cl. Sci. (4) 28 (1998), 141152.Google Scholar
Kloeden, P. E. and Rasmussen, M.. Nonautonomous Dynamical Systems. American Mathematical Society, Providence, RI, 2011, 176.Google Scholar
Liverani, C.. Decay of correlations. Ann. of Math. (2) 142(2) (1995), 239301.Google Scholar
Liverani, C.. Decay of correlations for piecewise expanding maps. J. Stat. Phys. 78(3–4) (1995), 11111129.Google Scholar
Liverani, C.. Rigorous numerical investigation of the statistical properties of piecewise expanding maps. A feasibility study. Nonlinearity 14(3) (2001), 463490.Google Scholar
Luzzatto, S. and Melbourne, I.. Statistical properties and decay of correlations for interval maps with critical points and singularities. Comm. Math. Phys. 320(1) (2013), 2135.Google Scholar
Lasota, A. and Mackey, M. C.. Probabilistic Properties of Deterministic Systems. Cambridge University Press, New York, 1985.Google Scholar
Lasota, A. and Yorke, J. A.. On the existence of invariant measures for piecewise monotonic transformations. Trans. Amer. Math. Soc. 186 (1973), 481488.Google Scholar
Nándori, P., Szász, D. and Varjú, T.. A central limit theorem for time-dependent dynamical systems. J. Stat. Phys. 146(6) (2012), 12131220.Google Scholar
Ott, E., Grebogi, C. and Yorke, J. A.. Controlling chaos. Phys. Rev. Lett. 64(11) (1990), 11961199.Google Scholar
Ott, W., Stenlund, M. and Young, L.-S.. Memory loss for time-dependent dynamical systems. Math. Res. Lett. 16(3) (2009), 436475.Google Scholar
Saussol, B.. Absolutely continuous invariant measures for multidimensional expanding maps. Israel J. Math. 116(1) (2000), 223248.Google Scholar
Stenlund, M.. Non-stationary compositions of Anosov diffeomorphisms. Nonlinearity 24(10) (2011), 29913018.Google Scholar
Shen, W. and van Strien, S.. On stochastic stability of expanding circle maps with neutral fixed points. Dyn. Syst. 28(3) (2013), 423452.Google Scholar
Stenlund, M., Young, L.-S. and Zhang, H.. Dispersing billiards with moving scatterers. Comm. Math. Phys. 322(3) (2013), 909955.Google Scholar
Viana, M.. Stochastic Dynamics of Deterministic Systems. IMPA, Rio de Janeiro, 1997.Google Scholar
Walk, H.. Strong laws of large numbers by elementary Tauberian arguments. Monatsh. Math. 144(4) (2004), 329346.Google Scholar
Young, L.-S.. Statistical properties of dynamical systems with some hyperbolicity. Ann. of Math. (2) 147(3) (1998), 585650.Google Scholar
Young, L.-S.. Recurrence times and rates of mixing. Israel J. Math. 110(1) (1999), 153188.Google Scholar