Skip to Main content Skip to Navigation
Book sections

Adaptive semi-Lagrangian schemes for Vlasov equations

Martin Campos Pinto 1, 2
2 CALVI - Scientific computation and visualization
IRMA - Institut de Recherche Mathématique Avancée, LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection, Inria Nancy - Grand Est, IECL - Institut Élie Cartan de Lorraine
Abstract : This lecture presents a new class of adaptive semi-Lagrangian schemes - based on performing a semi-Lagrangian method on adaptive interpolation grids - in the context of solving Vlasov equations with underlying "smooth" flows, such as the one-dimensional Vlasov-Poisson system. After recalling the main features of the semi-Lagrangian method and its error analysis in a uniform setting, we describe two frameworks for implementing adaptive interpolations, namely multilevel meshes and interpolatory wavelets. For both discretizations, we introduce a notion of good adaptivity to a given function and show that it is preserved by a low-cost prediction algorithm which transports multilevel grids along any "smooth" flow. As a consequence, error estimates are established for the resulting predict and readapt schemes under the essential assumption that the flow underlying the transport equation, as well as its approximation, is a stable diffeomorphism. Some complexity results are stated in addition, together with a conjecture of the convergence rate for the overall adaptive scheme. As for the wavelet case, these results are new and also apply to high-order interpolation.
Document type :
Book sections
Complete list of metadata
Contributor : Martin Campos Pinto <>
Submitted on : Thursday, November 22, 2012 - 3:22:45 PM
Last modification on : Tuesday, March 2, 2021 - 5:12:04 PM




Martin Campos Pinto. Adaptive semi-Lagrangian schemes for Vlasov equations. Etienne Emmrich and Petra Wittbold. Analytical and numerical aspects of partial differential equations, de Gruyter, pp.69-114, 2009, 978-3-11-020447-6. ⟨10.1515/9783110212105.69⟩. ⟨hal-00756127⟩



Record views