Convergence from Boltzmann to Landau Processes with Soft Potential and Particle Approximations

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Abstract

Our aim in this paper is to show how a probabilistic interpretation of the Boltzmann and Landau equations gives a microscopic understanding of these equations. We firstly associate stochastic jump processes with the Boltzmann equations we consider. Then we renormalize these equations following asymptotics which make prevail the grazing collisions, and prove the convergence of the associated Boltzmann jump processes to a diffusion process related to the Landau equation. The convergence is pathwise and also implies a convergence at the level of the partial differential equations. The best feature of this approach is the microscopic understanding of the transition between the Boltzmann and the Landau equations, by an accumulation of very small jumps. We deduce from this interpretation an approximation result for a solution of the Landau equation via colliding stochastic particle systems. This result leads to a Monte-Carlo algorithm for the simulation of solutions by a conservative particle method which enables to observe the transition from Boltzmann to Landau equations. Numerical results are given.

Original languageEnglish
Pages (from-to)931-966
Number of pages36
JournalJournal of Statistical Physics
Volume111
Issue number3-4
DOIs
Publication statusPublished - 1 Jan 2003
Externally publishedYes

Keywords

  • Interacting particle systems
  • Landau equation with soft potential
  • Monte-Carlo algorithm
  • Nonlinear stochastic differential equations
  • Soft potential Boltzmann equations without cutoff

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