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dc.contributor.author
Herrmann, Lukas
dc.contributor.author
Schwab, Christoph
dc.contributor.editor
Tuffin, Bruno
dc.contributor.editor
L'Ecuyer, Pierre
dc.date.accessioned
2021-02-19T09:57:03Z
dc.date.available
2021-02-18T11:46:25Z
dc.date.available
2021-02-19T09:53:03Z
dc.date.available
2021-02-19T09:57:03Z
dc.date.issued
2020
dc.identifier.isbn
978-3-030-43464-9
en_US
dc.identifier.isbn
978-3-030-43465-6
en_US
dc.identifier.issn
2194-1009
dc.identifier.issn
2194-1017
dc.identifier.other
10.1007/978-3-030-43465-6_2
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/470220
dc.description.abstract
We survey the numerical analysis of a class of deterministic, higher-order QMC integration methods in forward and inverse uncertainty quantification algorithms for advection-diffusion-reaction (ADR) equations in polygonal domains D⊂R2 with distributed uncertain inputs. We admit spatially heterogeneous material properties. For the parametrization of the uncertainty, we assume at hand systems of functions which are locally supported in D. Distributed uncertain inputs are written in countably parametric, deterministic form with locally supported representation systems. Parametric regularity and sparsity of solution families and of response functions in scales of weighted Kontrat’ev spaces in D are quantified using analytic continuation.
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.subject
Higher order quasi-Monte Carlo
en_US
dc.subject
Parametric operator equations
en_US
dc.subject
Bayesian inverse problems
en_US
dc.subject
Uncertainty quantification
en_US
dc.title
Multilevel Quasi-Monte Carlo Uncertainty Quantification for Advection-Diffusion-Reaction
en_US
dc.type
Conference Paper
dc.date.published
2020-05-02
ethz.journal.title
Springer Proceedings in Mathematics & Statistics
ethz.journal.volume
324
en_US
ethz.journal.abbreviated
PROMS
ethz.pages.start
31
en_US
ethz.pages.end
67
en_US
ethz.event
MCQMC: International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
en_US
ethz.event.location
Rennes, France
en_US
ethz.event.date
July 1-6, 2018
en_US
ethz.grant
Numerical Analysis of PDEs with High-Dimensional Input Data
en_US
ethz.publication.place
Cham
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics::03435 - Schwab, Christoph / Schwab, Christoph
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics::03435 - Schwab, Christoph / Schwab, Christoph
en_US
ethz.grant.agreementno
159940
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
Projekte MINT
ethz.date.deposited
2021-02-18T11:51:51Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-02-19T09:57:14Z
ethz.rosetta.lastUpdated
2022-03-29T05:18:29Z
ethz.rosetta.versionExported
true
ethz.COinS
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