Papers
Topics
Authors
Recent
Search
2000 character limit reached

A Probabilistic Mean Field Limit for the Vlasov-Poisson System for Ions

Published 14 Oct 2024 in math.AP, math-ph, and math.MP | (2410.10612v1)

Abstract: The Vlasov-Poisson system for ions is a kinetic equation for dilute, unmagnetised plasma. It describes the evolution of the ions in a plasma under the assumption that the electrons are thermalized. Consequently, the Poisson coupling for the electrostatic potential contains an additional exponential nonlinearity not present in the electron Vlasov-Poisson system. The system can be formally derived through a mean field limit from a microscopic system of ions interacting with a thermalized electron distribution. However, it is an open problem to justify this limit rigorously for ions modelled as point charges. Existing results on the derivation of the three-dimensional ionic Vlasov-Poisson system require a truncation of the singularity in the Coulomb interaction at spatial scales of order $N{- \beta}$ with $\beta < 1/15$, which is more restrictive than the available results for the electron Vlasov-Poisson system. In this article, we prove that the Vlasov-Poisson system for ions can be derived from a microscopic system of ions and thermalized electrons with interaction truncated at scale $N{- \beta}$ with $\beta < 1/3$. We develop a generalisation of the probabilistic approach to mean field limits that is applicable to interaction forces defined through a nonlinear coupling with the particle density. The proof is based on a quantitative uniform law of large numbers for convolutions between empirical measures of independent, identically distributed random variables and locally Lipschitz functions.

Summary

Paper to Video (Beta)

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

Collections

Sign up for free to add this paper to one or more collections.

Tweets

Sign up for free to view the 1 tweet with 1 like about this paper.