2009
DOI: 10.1007/s00211-009-0269-8
|View full text |Cite
|
Sign up to set email alerts
|

Preconditioners for pseudodifferential equations on the sphere with radial basis functions

Abstract: In a previous paper a preconditioning strategy based on overlapping domain decomposition was applied to the Galerkin approximation of elliptic partial differential equations on the sphere. In this paper the methods are extended to more general pseudodifferential equations on the sphere, using as before spherical radial basis functions for the approximation space, and again preconditioning the illconditioned linear systems of the Galerkin approximation by the additive Schwarz method. Numerical results are prese… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
15
0

Year Published

2010
2010
2014
2014

Publication Types

Select...
5
1

Relationship

2
4

Authors

Journals

citations
Cited by 16 publications
(15 citation statements)
references
References 20 publications
0
15
0
Order By: Relevance
“…Hence K is a pseudodifferential operator of order 1. This allows us to extend our analysis [17] for the overlapping Schwarz preconditioner on the sphere to the prolate spheroid. The preconditioner is defined by the additive Schwarz operator, using a subspace decomposition of V τ as V τ = V 0 + .…”
Section: Numerical Experimentsmentioning
confidence: 98%
“…Hence K is a pseudodifferential operator of order 1. This allows us to extend our analysis [17] for the overlapping Schwarz preconditioner on the sphere to the prolate spheroid. The preconditioner is defined by the additive Schwarz operator, using a subspace decomposition of V τ as V τ = V 0 + .…”
Section: Numerical Experimentsmentioning
confidence: 98%
“…Thus, we can viewû h (z j ) as a Galerkin approximation toû(z j ). Concretely, to computeû h (z) = K p=1Û p (z)Φ p we form the K × K matrices B and S, with entries 15) form the load vector G(z) ∈ C K with components G p (z) = g h (z), Φ p , and then solve the K × K complex linear system 16) to obtain the solution vectorÛ(z) ∈ C K with componentsÛ p (z). In contrast to finite element mass and stiffness matrices, B and S are not sparse because the SRBFs have large supports.…”
Section: Galerkin Approximation By Srbfsmentioning
confidence: 99%
“…Spherical radial basis functions seem to be a better choice [18]. However, the resulting matrix system from this approximation is very ill-conditioned.…”
Section: )mentioning
confidence: 99%
“…However, the resulting matrix system from this approximation is very ill-conditioned. Even though overlapping additive Schwarz preconditioners can be designed for this problem, the condition number of the preconditioned system still depends on the number of subdomains and the angles between subspaces; see [18].…”
Section: )mentioning
confidence: 99%