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Variation-norm and fluctuation estimates for ergodic bilinear averages
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2017
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Measure TheoryMaximal Bessel InequalitiesEngineeringVariational AnalysisIntegrable ProbabilityStochastic Dynamical SystemStochastic GeometryPoisson BoundaryFunctional AnalysisHigher Variation-normsVariational InequalityStatisticsErgodic Bilinear AveragesVariational Inequalities
For any dynamical system, we show that higher variation-norms for the sequence of ergodic bilinear averages of two functions satisfy a large range of bilinear Lp estimates. It follows that, with probability one, the number of fluctuations along this sequence may grow at most polynomially with respect to (the growth of) the underlying scale. These results strengthen previous works of Lacey and Bourgain where almost surely convergence of the sequence was proved (which is equivalent to the qualitative statement that the number of fluctuations is finite at each scale). Via transference, the proof reduces to establishing new bilinear Lp bounds for variation-norms of truncated bilinear operators on R, and the main ingredient of the proof of these bounds is a variation-norm extension of maximal Bessel inequalities of Lacey and Demeter--Tao--Thiele.