Inviscid Large deviation principle and the 2D Navier Stokes equations with a free boundary condition

Abstract

Using a weak convergence approach, we prove a LPD for the solution of 2D stochastic Navier Stokes equations when the viscosity converges to 0 and the noise intensity is multiplied by the square root of the viscosity. Unlike previous results on LDP for hydrodynamical models, the weak convergence is proven by tightness properties of the distribution of the solution in appropriate functional spaces.

References in corpus (4)

• Large deviations for infinite dimensional stochastic dynamical systems
• Stochastic 2D hydrodynamical type systems: Well posedness and large deviations
• Large Deviations for Stochastic Evolution Equations with Small Multiplicative Noise
• Large deviations for the Boussinesq Equations under Random Influences

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• LDP and CLT for SPDEs with Transport Noise
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• Asymptotic behavior for the 1-D stochastic Landau Lifshitz Bloch equation
• Fokker-Planck equation for dissipative 2D Euler equations with cylindrical noise
• Uniform large deviation principles for Banach space valued stochastic differential equations
• Invariant measure for 2D stochastic Cahn-Hilliard-Navier-Stokes equations
• Large Deviations for Nonlinear Stochastic Schrodinger Equation
• Large deviations for stochastic models of two-dimensional second grade fluids
• Well-posedness for the stochastic electrokinetic flow
• Large, moderate deviations principle and $\alpha$-limit for the 2D Stochastic LANS-$\alpha$