A Central Limit Theorem for Time-Dependent Dynamical Systems
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The work by Ott et al. (Math. Res. Lett. 16:463–475, 2009) established memory loss in the time-dependent (non-random) case of uniformly expanding maps of the interval. Here we find conditions under which we have convergence to the normal distribution of the appropriately scaled Birkhoff-like partial sums of appropriate test functions. A substantial part of the problem is to ensure that the variances of the partial sums tend to infinity (cf. the zero-cohomology condition in the autonomous case). In fact, the present paper is the first one where non-random examples are also found, which are not small perturbations of a given map. Our approach uses martingale approximation technique in the form of Sethuraman and Varadhan (Electron. J. Probab. 10:121–1235, 2005).
KeywordsCentral limit theorem Limiting variance Time-dependent systems
The authors are highly indebted to Mikko Stenlund and Lai-Sang Young for first explaining their result in October 2010 and second for a most valuable discussion in April 2011. They are also most grateful to the referee for his very useful remarks.
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