Journal Articles The Annals of Applied Probability Year : 2022

Weak and strong error analysis for mean-field rank based particle approximations of one dimensional viscous scalar conservation law

Abstract

In this paper, we analyse the rate of convergence of a system of $N$ interacting particles with mean-field rank based interaction in the drift coefficient and constant diffusion coefficient. We first adapt arguments by Kolli and Shkolnikhov to check trajectorial propagation of chaos with optimal rate $N^{-1/2}$ to the associated stochastic differential equations nonlinear in the sense of McKean. We next relax the assumptions needed by Bossy to check convergence in $L^1(\mathbb{R})$ with rate ${\mathcal O}(\frac{1}{\sqrt N} + h)$ of the empirical cumulative distribution function of the Euler discretization with step $h$ of the particle system to the solution of a one dimensional viscous scalar conservation law. Last, we prove that the bias of this stochastic particle method behaves in ${\mathcal O}(\frac{1}{N} + h)$. We provide numerical results which confirm our theoretical estimates.

Dates and versions

hal-02332760 , version 1 (25-10-2019)

Identifiers

Cite

Oumaima Bencheikh, Benjamin Jourdain. Weak and strong error analysis for mean-field rank based particle approximations of one dimensional viscous scalar conservation law. The Annals of Applied Probability, 2022, 32 (6), pp.4143-4185. ⟨10.1214/21-AAP1776⟩. ⟨hal-02332760⟩
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