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Multilevel quasi Monte Carlo methods for elliptic PDEs with random field coefficients via fast white noise sampling

Abstract:

When solving partial differential equations (PDEs) with random fields as coefficients, the efficient sampling of random field realizations can be challenging. In this paper we focus on the fast sampling of Gaussian fields using quasi-random points in a finite element and multilevel quasi Monte Carlo (MLQMC) setting. Our method uses the stochastic PDE (SPDE) approach of Lindgren et al. combined with a new fast algorithm for white noise sampling which is tailored to (ML)QMC. We express white no...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1137/20M1329044

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More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0003-1669-9445
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0002-5445-3721
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0002-1241-7060
Publisher:
Society for Industrial and Applied Mathematics Publisher's website
Journal:
SIAM Journal on Scientific Computing Journal website
Volume:
43
Issue:
4
Pages:
A2840–A2868
Publication date:
2021-08-09
Acceptance date:
2021-06-01
DOI:
EISSN:
1095-7197
ISSN:
1064-8275
Language:
English
Keywords:
Pubs id:
1180279
Local pid:
pubs:1180279
Deposit date:
2021-06-03

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