Mathematical and numerical methods for Vlasov-Maxwell equations: The contribution of data mining

Franck Assous, Joël Chaskalovic

Research output: Contribution to journalShort surveypeer-review

Abstract

This paper deals with the applications of data mining techniques in the evaluation of numerical solutions of Vlasov-Maxwell models. This is part of the topic of characterizing the model and approximation errors via learning techniques. We give two examples of application. The first one aims at comparing two Vlasov-Maxwell approximate models. In the second one, a scheme based on data mining techniques is proposed to characterize the errors between a P1 and a P2 finite element Particle-In-Cell approach. Beyond these examples, this original approach should operate in all cases where intricate numerical simulations like for the Vlasov-Maxwell equations take a central part.

Original languageEnglish
Pages (from-to)560-569
Number of pages10
JournalComptes Rendus - Mecanique
Volume342
Issue number10-11
DOIs
StatePublished - 2014

Keywords

  • Asymptotic analysis
  • Data mining
  • Error estimate
  • Paraxial model
  • Vlasov-Maxwell equations

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • General Materials Science

Fingerprint

Dive into the research topics of 'Mathematical and numerical methods for Vlasov-Maxwell equations: The contribution of data mining'. Together they form a unique fingerprint.

Cite this