Multidimensional Potential Burgers Turbulence

Abstract

We consider the multidimensional generalised stochastic Burgers equation in the space-periodic setting:

$$\frac{\partial \mathbf{u}}{\partial t}+(\nabla f(\mathbf{u}) \cdot \nabla) \mathbf{u}-\nu \Delta \mathbf{u}= \nabla \eta, \quad t \geq 0, \, \mathbf{x} \in\mathbb{T}^d=(\mathbb{R}/ \mathbb{Z})^d,$$

under the assumption that u is a gradient. Here f is strongly convex and satisfies a growth condition, ν is small and positive, while η is a random forcing term, smooth in space and white in time. For solutions u of this equation, we study Sobolev norms of u averaged in time and in ensemble: each of these norms behaves as a given negative power of ν. These results yield sharp upper and lower bounds for natural analogues of quantities characterising the hydrodynamical turbulence, namely the averages of the increments and of the energy spectrum. These quantities behave as a power of the norm of the relevant parameter, which is respectively the separation ℓ in the physical space and the wavenumber k in the Fourier space. Our bounds do not depend on the initial condition and hold uniformly in ${\nu}$. We generalise the results obtained for the one-dimensional case in [10], confirming the physical predictions in [4, 30]. Note that the form of the estimates does not depend on the dimension: the powers of ${\nu, |{\mathbf{k}}|, \ell}$ are the same in the one- and the multi-dimensional setting.