On the pointwise convergence of multiple ergodic averages
classification
🧮 math.DS
keywords
ergodicaveragesconvergencemultiplenon-singularpointwisealmostcommuting
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It is shown that there exist a subsequence for which the multiple ergodic averages of commuting invertible measure preserving transformations of a Lebesgue probability space converge almost everywhere provided that the maps are weakly mixing with an ergodic extra condition. The proof provides a example of non-singular dynamical system for which the maximal ergodic inequality does not hold. We further get that the non-singular strategy to solve the pointwise convergence of the Furstenberg ergodic averages fails.
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