<div class="csl-bib-body">
<div class="csl-entry">Achleitner, F., Arnold, A., & A. Carlen, E. (2018). On multi-dimensional hypocoercive BGK models. <i>Kinetic and Related Models</i>, <i>11</i>(4), 953–1009. https://doi.org/10.3934/krm.2018038</div>
</div>
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dc.identifier.issn
1937-5093
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/145804
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dc.description.abstract
We study hypocoercivity for a class of linearized BGK models for continuous phase spaces. We develop methods for constructing entropy functionals that enable us to prove exponential relaxation to equilibrium with explicit and physically meaningful rates. In fact, we not only estimate the exponential rate, but also the second time scale governing the time one must wait before one begins to see the exponential relaxation in the L1 distance. This waiting time phenomenon, with a long plateau before the exponential decay 'kicks in' when starting from initial data that is well-concentrated in phase space, is familiar from work of Aldous and Diaconis on Markov chains, but is new in our continuous phase space setting. Our strategies are based on the entropy and spectral methods, and we introduce a new 'index of hypocoercivity' that is relevant to models of our type involving jump processes and not only diffusion. At the heart of our method is a decomposition technique that allows us to adapt Lyapunov's direct method to our continuous phase space setting in order to construct our entropy functionals. These are used to obtain precise information on linearized BGK models. Finally, we also prove local asymptotic stability of a nonlinear BGK model.
en
dc.language.iso
en
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dc.publisher
American Institute of Mathematical Sciences (AIMS)
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dc.relation.ispartof
Kinetic and Related Models
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dc.subject
Modeling and Simulation
en
dc.subject
Numerical Analysis
en
dc.subject
hypocoercivity
en
dc.subject
BGK models
en
dc.subject
Lyapunov functionals
en
dc.subject
perturbation methods for matrix equations
en
dc.subject
Kinetic equations
en
dc.title
On multi-dimensional hypocoercive BGK models
en
dc.type
Artikel
de
dc.type
Article
en
dc.contributor.affiliation
Rutgers, The State University of New Jersey, United States of America (the)
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dc.description.startpage
953
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dc.description.endpage
1009
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dc.type.category
Original Research Article
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tuw.container.volume
11
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tuw.container.issue
4
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tuw.journal.peerreviewed
true
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tuw.peerreviewed
true
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tuw.researchTopic.id
C4
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.value
100
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dcterms.isPartOf.title
Kinetic and Related Models
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tuw.publication.orgunit
E101-01 - Forschungsbereich Analysis
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tuw.publisher.doi
10.3934/krm.2018038
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dc.identifier.eissn
1937-5077
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dc.description.numberOfPages
57
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wb.sci
true
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1010
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wb.facultyfocus
Analysis und Scientific Computing
de
wb.facultyfocus
Analysis and Scientific Computing
en
wb.facultyfocus.faculty
E100
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item.languageiso639-1
en
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item.openairetype
research article
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item.grantfulltext
none
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item.fulltext
no Fulltext
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_2df8fbb1
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crisitem.author.dept
E101 - Institut für Analysis und Scientific Computing