Abstract
We discuss a number of results related to mixing and, in particular, to the rate of mixing. This is sometimes alternatively known as the rate of decay of correlations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
This doesn’t have finitely many branches but the same basic analysis applies.
- 2.
Actually, one needs a slightly weaker assumption: There exists \(\varepsilon > 0\) and (an arbitrary large) n such that \(T^n :X \rightarrow X\) has inverse branches \(T_i, T_j :X \rightarrow X\) (i.e. locally \(T^n \circ T_i =\) identity and \(T^n \circ T_j =\) identity) and \(R_{ij} := r(T_i x) - r(T_jx)\) satisfies \(|R^\prime _{ij}(x)| \ge \varepsilon \).
- 3.
In the detailed proof there remains a complicated technical argument to get bounds of iterates of the operator and thus the spectral radius.
References
A. Avila, S. Gouzel and J.-C. Yoccoz, Exponential mixing for the Teichmller flow. Publ. Math. Inst. Hautes tudes Sci. No. 104 (2006), 143–211.
V. Baladi and B. Vallée, Exponential decay of correlations for surface semi-flows without finite Markov partitions. Proc. Amer. Math. Soc. 133 (2005), no. 3, 865–874.
V. Baladi and B. Vallée, Euclidean algorithms are Gaussian. J. Number Theory 110 (2005), no. 2, 331–386
R. Bowen, Invariant measures for Markov maps of the interval (With an afterword by Roy L. Adler and additional comments by Caroline Series) Comm. Math. Phys. 69 (1979), no. 1, 1–17
P. Collet and J.-P. Eckmann, Iterated maps on the interval as dynamical systems. Progress in Physics, 1. Birkhuser, Boston, Mass., 1980.
W. Doeblin and R. Fortet, Sur des chanes à liaisons complètes, Bull. Soc. Math. France 65 (1937), 132–148.
D. Dolgopyat, On decay of correlations in Anosov flows. Ann. of Math. (2) 147 (1998), no. 2, 357–390.
D. Dolgopyat, On mixing properties of compact group extensions of hyperbolic systems, Israel J. Math. 130 (2002) 157–205.
D. Hensley, Continued fractions, World Scientific Publishing Co. Pte. Ltd., Hackensack, NJ, 2006.
H. Huber, Zur analytischen Theorie hyperbolischen Raumformen und Bewegungsgruppen, Math. Ann. 138 1959 1–26.
C.T. Ionescu Tulcea and G. Marinescu, Théorie ergodique pour des classes d’opérations non complètement continues, Ann. of Math. (2) 52, (1950). 140–147.
Donald E. Knuth, The art of computer programming, Vol. 2. Seminumerical algorithms, Addison-Wesley, Reading, MA, 2011.
A. Lasota and J. Yorke, On the existence of invariant measures for piecewise monotonic transformations. Trans. Amer. Math. Soc. 186 (1973) 481–488
F. Ledrappier and S. Lim, Local Limit Theorem in negative curvature, Preprint.
J. Lee and H.-S. Sun, Another note on “Euclidean algorithms are Gaussian” by V. Baladi and B. Valle, Acta Arith. 188 (2019), 241–251.
C. Liverani, On contact Anosov flows. Ann. of Math. (2) 159 (2004), no. 3, 1275–1312.
F. Naud, Dolgopyat’s estimates for the modular surface, lecture notes from IHP June 2005, workshop “time at work”.
W. Parry and M. Pollicott, Zeta functions and the periodic orbit structure of hyperbolic dynamics, Astrisque, 187–188, (1990) 268
M. Pollicott and R. Sharp, Exponential error terms for growth functions on negatively curved surfaces. Amer. J. Math. 120 (1998) 1019–1042
M. Reed and B. Simon, Methods of modern mathematical physics. I, Functional analysis. Academic Press, Inc., New York, 1980.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Pollicott, M. (2019). Exponential Mixing: Lectures from Mumbai. In: Dani, S., Ghosh, A. (eds) Geometric and Ergodic Aspects of Group Actions. Infosys Science Foundation Series(). Springer, Singapore. https://doi.org/10.1007/978-981-15-0683-3_4
Download citation
DOI: https://doi.org/10.1007/978-981-15-0683-3_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0682-6
Online ISBN: 978-981-15-0683-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)