A hierarchy of reduced models to approximate Vlasov–Maxwell equations for slow time variations

Franck Assous; Yevgeni Furman

doi:10.5802/CRMECA.50

A hierarchy of reduced models to approximate Vlasov–Maxwell equations for slow time variations

Translated title of the contribution: A hierarchy of reduced models to approximate Vlasov–Maxwell equations for slow time variations

Franck Assous, Yevgeni Furman

Ariel University

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

We introduce a new family of paraxial asymptotic models that approximate the Vlasov–Maxwell equations in non-relativistic cases. This formulation is nth order accurate in a parameter η, which denotes the ratio between the characteristic velocity of the beam and the speed of light. This family of models is interesting, first because it is simpler than the complete Vlasov–Maxwell equation and then because it allows us to choose the model complexity according to the expected accuracy.

Translated title of the contribution	A hierarchy of reduced models to approximate Vlasov–Maxwell equations for slow time variations
Original language	English
Pages (from-to)	969-981
Number of pages	13
Journal	Comptes Rendus - Mecanique
Volume	348
Issue number	12
DOIs	https://doi.org/10.5802/CRMECA.50
State	Published - 2021
Externally published	Yes

Bibliographical note

Publisher Copyright:
© Académie des sciences, Paris and the authors, 2020. Some rights reserved.

Keywords

Asymptotic analysis
Non-relativistic
Paraxial model
Reduced models
Vlasov–Maxwell equations

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10.5802/CRMECA.50

Cite this

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abstract = "We introduce a new family of paraxial asymptotic models that approximate the Vlasov–Maxwell equations in non-relativistic cases. This formulation is nth order accurate in a parameter η, which denotes the ratio between the characteristic velocity of the beam and the speed of light. This family of models is interesting, first because it is simpler than the complete Vlasov–Maxwell equation and then because it allows us to choose the model complexity according to the expected accuracy.",

keywords = "Asymptotic analysis, Non-relativistic, Paraxial model, Reduced models, Vlasov–Maxwell equations",

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AU - Furman, Yevgeni

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PY - 2021

Y1 - 2021

N2 - We introduce a new family of paraxial asymptotic models that approximate the Vlasov–Maxwell equations in non-relativistic cases. This formulation is nth order accurate in a parameter η, which denotes the ratio between the characteristic velocity of the beam and the speed of light. This family of models is interesting, first because it is simpler than the complete Vlasov–Maxwell equation and then because it allows us to choose the model complexity according to the expected accuracy.

AB - We introduce a new family of paraxial asymptotic models that approximate the Vlasov–Maxwell equations in non-relativistic cases. This formulation is nth order accurate in a parameter η, which denotes the ratio between the characteristic velocity of the beam and the speed of light. This family of models is interesting, first because it is simpler than the complete Vlasov–Maxwell equation and then because it allows us to choose the model complexity according to the expected accuracy.

KW - Asymptotic analysis

KW - Non-relativistic

KW - Paraxial model

KW - Reduced models

KW - Vlasov–Maxwell equations

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ER -

A hierarchy of reduced models to approximate Vlasov–Maxwell equations for slow time variations

Abstract

Bibliographical note

Keywords

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