Journal
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Volume 44, Issue 2, Pages A825-A842Publisher
SIAM PUBLICATIONS
DOI: 10.1137/21M1400717
Keywords
stochastic partial differential equations; Gaussian random fields; fractional operators; parametric finite element methods; strong convergence; surface finite element method
Categories
Funding
- Swedish Research Council (VR) [2017-04274, 2020-04170]
- Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation
- Chalmers AI Research Centre (CHAIR)
- Marsden Fund of the Royal Society of New Zealand [18-UOO-143]
- NKFIH [131545]
- Vinnova [2017-04274] Funding Source: Vinnova
- Swedish Research Council [2020-04170, 2017-04274] Funding Source: Swedish Research Council
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This paper considers the solution of fractional elliptic stochastic partial differential equations on the sphere using Spherical Whittle--Mate'\rn Gaussian random fields. The approximation is done using surface finite elements and a quadrature of the Dunford-Taylor integral representation. Strong error analysis is performed and the computational complexity is bounded. Numerical experiments confirm the theoretical findings.
Spherical Whittle--Mate'\rn Gaussian random fields are considered as solutions to fractional elliptic stochastic partial differential equations on the sphere. Approximation is done with surface finite elements. While the nonfractional part of the operator is solved by a recursive scheme, a quadrature of the Dunford-Taylor integral representation is employed for the fractional part. Strong error analysis is performed, and the computational complexity is bounded in terms of the accuracy. Numerical experiments for different choices of parameters confirm the theoretical findings.
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