Open Access
Translator Disclaimer
November 2016 Propagation of chaos for the Landau equation with moderately soft potentials
Nicolas Fournier, Maxime Hauray
Ann. Probab. 44(6): 3581-3660 (November 2016). DOI: 10.1214/15-AOP1056


We consider the 3D Landau equation for moderately soft potentials [$\gamma\in(-2,0)$ with the usual notation] as well as a stochastic system of $N$ particles approximating it. We first establish some strong/weak stability estimates for the Landau equation, which are fully satisfactory only when $\gamma\in[-1,0)$. We next prove, under some appropriate conditions on the initial data, the so-called propagation of molecular chaos, that is, that the empirical measure of the particle system converges to the unique solution of the Landau equation. The main difficulty is the presence of a singularity in the equation. When $\gamma\in(-1,0)$, the strong-weak uniqueness estimate allows us to use a coupling argument and to obtain a rate of convergence. When $\gamma\in(-2,-1]$, we use the classical martingale method introduced by McKean. To control the singularity, we have to take advantage of the regularity provided by the entropy dissipation. Unfortunately, this dissipation is too weak for some (very rare) aligned configurations. We thus introduce a perturbed system with an additional noise, show the propagation of chaos for this system and finally prove that the additional noise is almost never used in the limit $N\to\infty$.


Download Citation

Nicolas Fournier. Maxime Hauray. "Propagation of chaos for the Landau equation with moderately soft potentials." Ann. Probab. 44 (6) 3581 - 3660, November 2016.


Received: 1 January 2015; Revised: 1 July 2015; Published: November 2016
First available in Project Euclid: 14 November 2016

zbMATH: 1362.82045
MathSciNet: MR3572320
Digital Object Identifier: 10.1214/15-AOP1056

Primary: 82C40
Secondary: 60K35 , 65C05

Keywords: entropy dissipation , Fisher information , Landau equation , propagation of chaos , Stochastic particle systems , uniqueness

Rights: Copyright © 2016 Institute of Mathematical Statistics


Vol.44 • No. 6 • November 2016
Back to Top