Hostname: page-component-848d4c4894-4hhp2 Total loading time: 0 Render date: 2024-05-31T16:17:50.857Z Has data issue: false hasContentIssue false

Equilibrium states for non-transitive random open and closed dynamical systems

Published online by Cambridge University Press:  13 October 2022

JASON ATNIP*
Affiliation:
School of Mathematics and Statistics, University of New South Wales, Sydney, NSW 2052, Australia
GARY FROYLAND
Affiliation:
School of Mathematics and Statistics, University of New South Wales, Sydney, NSW 2052, Australia (e-mail: g.froyland@unsw.edu.au)
CECILIA GONZÁLEZ-TOKMAN
Affiliation:
School of Mathematics and Physics, The University of Queensland, St Lucia, QLD 4072, Australia (e-mail: cecilia.gt@uq.edu.au)
SANDRO VAIENTI
Affiliation:
Aix Marseille Université, Université de Toulon, CNRS, CPT, 13009 Marseille, France (e-mail: vaienti@cpt.univ-mrs.fr)

Abstract

We prove a random Ruelle–Perron–Frobenius theorem and the existence of relative equilibrium states for a class of random open and closed interval maps, without imposing transitivity requirements, such as mixing and covering conditions, which are prevalent in the literature. This theorem provides the existence and uniqueness of random conformal and invariant measures with exponential decay of correlations, and allows us to expand the class of examples of (random) dynamical systems amenable to multiplicative ergodic theory and the thermodynamic formalism. Applications include open and closed non-transitive random maps, and a connection between Lyapunov exponents and escape rates through random holes. We are also able to treat random intermittent maps with geometric potentials.

Type
Original Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Atnip, J., Froyland, G., González-Tokman, C. and Vaienti, S.. Thermodynamic formalism for random interval maps with holes. Preprint, 2021, arXiv:2103.04712.CrossRefGoogle Scholar
Atnip, J., Froyland, G., González-Tokman, C. and Vaienti, S.. Thermodynamic formalism for random weighted covering systems. Comm. Math. Phys. 386 (2021), 819902.CrossRefGoogle Scholar
Atnip, J. and Urbański, M.. Critically finite random maps of an interval. Discrete Contin. Dyn. Syst. Ser. A 40(8) (2020), 4839.CrossRefGoogle Scholar
Baladi, V.. Correlation spectrum of quenched and annealed equilibrium states for random expanding maps. Comm. Math. Phys. 186(3) (1997), 671700.CrossRefGoogle Scholar
Bogenschütz, T. and Gundlach, V. M.. Ruelle’s transfer operator for random subshifts of finite type. Ergod. Th. & Dynam. Sys. 15 (1995), 413447.CrossRefGoogle Scholar
Buzzi, J.. Exponential decay of correlations for random Lasota–Yorke maps. Comm. Math. Phys. 208(1) (1999), 2554.CrossRefGoogle Scholar
Demers, M. F. and Liverani, C.. Projective cones for generalized dispersing billiards. Preprint, 2021, arXiv:2104.06947.Google Scholar
Demers, M. F. and Todd, M.. Equilibrium states, pressure and escape for multimodal maps with holes. Israel J. Math. 221(1) (2017), 367424.CrossRefGoogle Scholar
Demers, M. F. and Todd, M.. Slow and fast escape for open intermittent maps. Comm. Math. Phys. 351(2) (2017), 775835.CrossRefGoogle Scholar
Dragičević, D., Froyland, G., González-Tokman, C. and Vaienti, S.. A spectral approach for quenched limit theorems for random expanding dynamical systems. Comm. Math. Phys. 360(3) (2018), 11211187.CrossRefGoogle Scholar
Froyland, G., Lloyd, S. and Quas, A.. A semi-invertible Oseledets theorem with applications to transfer operator cocycles. Discrete Contin. Dyn. Syst. 33(9) (2013), 38353860.CrossRefGoogle Scholar
Gantmacher, F. R.. The Theory of Matrices. Vols. 1, 2. Chelsea Publishing Co., New York, 1959, translated by K. A. Hirsch.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.CrossRefGoogle Scholar
Horan, J.. Asymptotics for the second-largest Lyapunov exponent for some Perron–Frobenius operator cocycles. Nonlinearity 34(4) (2021), 25632610.CrossRefGoogle Scholar
Kifer, Y.. Thermodynamic formalism for random transformations revisited. Stoch. Dyn. 8(1) (2008), 77102.CrossRefGoogle Scholar
Liverani, C. and Maume-Deschamps, V.. Lasota–Yorke maps with holes: conditionally invariant probability measures and invariant probability measures on the survivor set. Ann. Inst. Henri Poincaré B Probab. Stat. 39(3) (2003), 385412.CrossRefGoogle Scholar
Liverani, C., Saussol, B. and Vaienti, S.. Conformal measure and decay of correlation for covering weighted systems. Ergod. Th. & Dynam. Sys. 18(6) (1998), 13991420.CrossRefGoogle Scholar
Liverani, C., Saussol, B. and Vaienti, S.. A probabilistic approach to intermittency. Ergod. Th. & Dynam. Sys. 19(3) (1999), 671685.CrossRefGoogle Scholar
Mayer, V. and Urbański, M.. Countable alphabet random subhifts of finite type with weakly positive transfer operator. J. Stat. Phys. 160(5) (2015), 14051431.CrossRefGoogle Scholar
Mayer, V., Urbański, M. and Skorulski, B.. Distance Expanding Random Mappings, Thermodynamical Formalism, Gibbs Measures and Fractal Geometry (Lecture Notes in Mathematics, 2036). Springer, Berlin, 2011.CrossRefGoogle Scholar
Mohapatra, A. and Ott, W.. Memory loss for nonequilibrium open dynamical systems. Discrete Contin. Dyn. Syst. 34(9) (2014), 37473759.CrossRefGoogle Scholar
Ott, W., Stenlund, M. and Young, L.-S.. Memory loss for time-dependent dynamical systems. Math. Res. Lett. 16(3) (2009), 463475.CrossRefGoogle Scholar
Rychlik, M.. Bounded variation and invariant measures. Studia Math. 76 (1983), 6980.CrossRefGoogle Scholar
Stadlbauer, M., Suzuki, S. and Varandas, P.. Thermodynamic formalism for random non-uniformly expanding maps. Comm. Math. Phys. 385 (2021), 369427.CrossRefGoogle Scholar
Stenlund, M., Young, L.-S. and Zhang, H.. Dispersing billiards with moving scatterers. Comm. Math. Phys. 322(3) (2013), 909955.CrossRefGoogle Scholar
Young, L.-S.. Understanding chaotic dynamical systems. Comm. Pure Appl. Math. 66(9) (2013), 14391463.CrossRefGoogle Scholar