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October 2010 Stochastic vortex method for forced three-dimensional Navier–Stokes equations and pathwise convergence rate
J. Fontbona
Ann. Appl. Probab. 20(5): 1761-1800 (October 2010). DOI: 10.1214/09-AAP672

Abstract

We develop a McKean–Vlasov interpretation of Navier–Stokes equations with external force field in the whole space, by associating with local mild Lp-solutions of the 3d-vortex equation a generalized nonlinear diffusion with random space–time birth that probabilistically describes creation of rotation in the fluid due to nonconservativeness of the force. We establish a local well-posedness result for this process and a stochastic representation formula for the vorticity in terms of a vector-weighted version of its law after its birth instant. Then we introduce a stochastic system of 3d vortices with mollified interaction and random space–time births, and prove the propagation of chaos property, with the nonlinear process as limit, at an explicit pathwise convergence rate. Convergence rates for stochastic approximation schemes of the velocity and the vorticity fields are also obtained. We thus extend and refine previous results on the probabilistic interpretation and stochastic approximation methods for the nonforced equation, generalizing also a recently introduced random space–time-birth particle method for the 2d-Navier–Stokes equation with force.

Citation

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J. Fontbona. "Stochastic vortex method for forced three-dimensional Navier–Stokes equations and pathwise convergence rate." Ann. Appl. Probab. 20 (5) 1761 - 1800, October 2010. https://doi.org/10.1214/09-AAP672

Information

Published: October 2010
First available in Project Euclid: 25 August 2010

zbMATH: 1222.60077
MathSciNet: MR2724420
Digital Object Identifier: 10.1214/09-AAP672

Subjects:
Primary: 60K35 , 65C35 , 76D17 , 76M23
Secondary: 35Q30

Keywords: 3d-Navier–Stokes equation with external force , convergence rate , McKean–Vlasov model with random space–time birth , propagation of chaos , stochastic vortex method

Rights: Copyright © 2010 Institute of Mathematical Statistics

Vol.20 • No. 5 • October 2010
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