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Register a new userInverse statistics of smooth signals: the case of two dimensional turbulence
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The problem of inverse statistics (statistics of distances for which the signal fluctuations are larger than a certain threshold) in differentiable signals with power law spectrum, $E(k) sim k^{-alpha}$, $3 le alpha < 5$, is discussed. We show that for these signals, with random phases, exit-distance moments follow a bi-fractal distribution. We also investigate two dimensional turbulent flows in the direct cascade regime, which display a more complex behavior. We give numerical evidences that the inverse statistics of 2d turbulent flows is described by a multi-fractal probability distribution, i.e. the statistics of laminar events is not simply captured by the exponent $alpha$ characterizing the spectrum.
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We present a numerical study of two-dimensional turbulent flows in the enstrophy cascade regime, with different large-scale forcings and energy sinks. In particular, we study the statistics of more-than-differentiable velocity fluctuations by means of two recently introduced sets of statistical estimators, namely {it inverse statistics} and {it second order differences}. We show that the 2D turbulent velocity field, $bm u$, cannot be simply characterized by its spectrum behavior, $E(k) propto k^{-alpha}$. There exists a whole set of exponents associated to the non-trivial smooth fluctuations of the velocity field at all scales. We also present a numerical investigation of the temporal properties of $bm u$ measured in different spatial locations.
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