Statistically self-similar mixing by Gaussian random fields

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.