Statistically self-similar mixing by Gaussian random fields

TL;DR

This paper derives an exact formula for non-diffusive mixing of a scalar field transported by a self-similar Gaussian velocity field, revealing uniform mixing properties independent of diffusivity.

Contribution

It introduces a precise mathematical formula capturing mixing behavior in a self-similar Gaussian velocity field, extending understanding of passive scalar transport.

Findings

Exact formula for scalar mixing in self-similar Gaussian fields

Mixing is uniform across different diffusivity levels

Relation between Lyapunov exponent and mixing rate

Abstract

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.