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On the quasi-Monte Carlo method with Halton points for elliptic PDEs with log-normal diffusion


Authors: Helmut Harbrecht, Michael Peters and Markus Siebenmorgen
Journal: Math. Comp. 86 (2017), 771-797
MSC (2010): Primary 65C05, 65C30, 60H25, 65N30
DOI: https://doi.org/10.1090/mcom/3107
Published electronically: March 24, 2016
MathSciNet review: 3584548
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Abstract: This article is dedicated to the computation of the moments of the solution to elliptic partial differential equations with random, log-normally distributed diffusion coefficients by the quasi-Monte Carlo method. Our main result is that the convergence rate of the quasi-Monte Carlo method based on the Halton sequence for the moment computation depends only linearly on the dimensionality of the stochastic input parameters. In particular, we attain this rather mild dependence on the stochastic dimensionality without any randomization of the quasi-Monte Carlo method under consideration. For the proof of the main result, we require related regularity estimates for the solution and its powers. These estimates are also provided here. Numerical experiments are given to validate the theoretical findings.


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Additional Information

Helmut Harbrecht
Affiliation: Departement Mathematik und Informatik, Universität Basel, Spiegelgasse 1, 4051 Basel, Switzerland
Email: helmut.harbrecht

Michael Peters
Affiliation: Departement Mathematik und Informatik, Universität Basel, Spiegelgasse 1, 4051 Basel, Switzerland
Email: michael.peters,markus

Markus Siebenmorgen
Affiliation: Departement Mathematik und Informatik, Universität Basel, Spiegelgasse 1, 4051 Basel, Switzerland
Email: siebenmorgen@unibas.ch

DOI: https://doi.org/10.1090/mcom/3107
Received by editor(s): November 6, 2013
Received by editor(s) in revised form: December 18, 2014, and July 6, 2015
Published electronically: March 24, 2016
Additional Notes: This research was supported by the Swiss National Science Foundation (SNSF) through the project “Rapid Solution of Boundary Value Problems on Stochastic Domains”.
Article copyright: © Copyright 2016 American Mathematical Society

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