Splitting integrators for linear Vlasov equations with stochastic perturbations

Fuente: arXiv
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Autori principali: Bréhier, Charles-Edouard, Cohen, David
Natura: Preprint
Pubblicazione: 2024
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author Bréhier, Charles-Edouard
Cohen, David
author_facet Bréhier, Charles-Edouard
Cohen, David
contents We consider a class of linear Vlasov partial differential equations driven by Wiener noise. Different types of stochastic perturbations are treated: additive noise, multiplicative Itô and Stratonovich noise, and transport noise. We propose to employ splitting integrators for the temporal discretization of these stochastic partial differential equations. These integrators are designed in order to preserve qualitative properties of the exact solutions depending on the stochastic perturbation, such as preservation of norms or positivity of the solutions. We provide numerical experiments in order to illustrate the properties of the proposed integrators and investigate mean-square rates of convergence.
format Preprint
id arxiv_https___arxiv_org_abs_2402_18982
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Splitting integrators for linear Vlasov equations with stochastic perturbations
Bréhier, Charles-Edouard
Cohen, David
Numerical Analysis
Probability
We consider a class of linear Vlasov partial differential equations driven by Wiener noise. Different types of stochastic perturbations are treated: additive noise, multiplicative Itô and Stratonovich noise, and transport noise. We propose to employ splitting integrators for the temporal discretization of these stochastic partial differential equations. These integrators are designed in order to preserve qualitative properties of the exact solutions depending on the stochastic perturbation, such as preservation of norms or positivity of the solutions. We provide numerical experiments in order to illustrate the properties of the proposed integrators and investigate mean-square rates of convergence.
title Splitting integrators for linear Vlasov equations with stochastic perturbations
topic Numerical Analysis
Probability
url https://arxiv.org/abs/2402.18982