A Linear Stochastic Model of Turbulent Cascades and Fractional Fields
Gabriel B. Apolin\'ario, Geoffrey Beck, Laurent Chevillard, Isabelle, Gallagher, Ricardo Grande

TL;DR
This paper introduces a linear stochastic model that captures the essence of turbulent energy cascades, showing convergence to fractional Gaussian fields and providing insights into the statistical properties of turbulence.
Contribution
It constructs a novel linear equation model for turbulent cascades that reproduces key statistical features and convergence behavior observed in turbulence phenomena.
Findings
Solution is smooth at finite times.
Converges to a fractional Gaussian field at infinite time.
Model captures power-law behaviors of turbulence statistics.
Abstract
Turbulent cascades characterize the transfer of energy injected by a random force at large scales towards the small scales. In hydrodynamic turbulence, when the Reynolds number is large, the velocity field of the fluid becomes irregular and the rate of energy dissipation remains bounded from below even if the fluid viscosity tends to zero. A mathematical description of the turbulent cascade is a very active research topic since the pioneering work of Kolmogorov in hydrodynamic turbulence and that of Zakharov in wave turbulence. In both cases, these turbulent cascade mechanisms imply power-law behaviors of several statistical quantities such as power spectral densities. For a long time, these cascades were believed to be associated with nonlinear interactions, but recent works have shown that they can also take place in a dynamics governed by a linear equation with a differential…
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