arXiv Analytics

Sign in

arXiv:2309.15744 [math.PR]AbstractReferencesReviewsResources

Statistically self-similar mixing by Gaussian random fields

Michele Coti Zelati, Theodore D. Drivas, Rishabh S. Gvalani

Published 2023-09-27Version 1

We study the passive transport of a scalar field by a spatially smooth but white-in-time incompressible Gaussian random velocity field on $\mathbb{R}^d$. If the velocity field $u$ is homogeneous, isotropic, and statistically self-similar, we derive an exact formula which captures non-diffusive mixing. For zero diffusivity, the formula takes the shape of $\mathbb{E}\ \| \theta_t \|_{\dot{H}^{-s}}^2 = \mathrm{e}^{-\lambda_{d,s} t} \| \theta_0 \|_{\dot{H}^{-s}}^2$ with any $s\in (0,d/2)$ and $\frac{\lambda_{d,s}}{D_1}:= s(\frac{\lambda_{1}}{D_1}-2s)$ where $\lambda_1/D_1 = d$ is the top Lyapunov exponent associated to the random Lagrangian flow generated by $u$ and $ D_1$ is small-scale shear rate of the velocity. Moreover, the mixing is shown to hold $\textit{uniformly}$ in diffusivity.

Related articles: Most relevant | Search more
arXiv:2206.13834 [math.PR] (Published 2022-06-28)
Complexity of Gaussian random fields with isotropic increments: critical points with given indices
arXiv:0710.2506 [math.PR] (Published 2007-10-12)
Stochastic Integrals and Evolution Equations with Gaussian Random Fields
arXiv:2108.09225 [math.PR] (Published 2021-08-20)
Extremes of Gaussian random fields with non-additive dependence structure