Statistical Properties of 2D Stochastic Navier-Stokes Equations with Time-Periodic Forcing and Degenerate Stochastic Forcing

TL;DR

This paper studies the 2D stochastic Navier-Stokes equations with periodic deterministic forcing and degenerate noise, establishing ergodic, mixing, and statistical properties independent of noise strength and viscosity.

Contribution

It proves the existence of a unique ergodic periodic invariant measure and demonstrates exponential mixing and statistical laws for the system under broad conditions.

Findings

Existence of a unique ergodic periodic invariant measure.

Exponential mixing under Wasserstein metric.

Weak law of large numbers and central limit theorem for the system.

Abstract

We consider the incompressible 2D Navier-Stokes equations with periodic boundary conditions driven by a deterministic time periodic forcing and a degenerate stochastic forcing. We show that the system possesses a unique ergodic periodic invariant measure which is exponentially mixing under a Wasserstein metric. We also prove the weak law of large numbers for the continuous time inhomogeneous solution process. In addition, we obtain the weak law of large numbers and central limit theorem by restricting the inhomogeneous solution process to periodic times. The results are independent of the strength of the noise and hold true for any value of viscosity with a lower bound $\nu_1$ characterized by the Grashof number $G_1$ associated with the deterministic forcing. In the laminar case, there is a larger lower bound $\nu_2$ of the viscosity characterized by the Grashof number $G_2$ associated with both the deterministic and random forcing. We prove that in this laminar case, the system has trivial dynamics for any viscosity larger than $\nu_2$ by demonstrating the existence of a unique globally exponentially stable random periodic solution that supports the unique periodic invariant measure.