A direct adaptive poisson solver of arbitrary order accuracy

Leslie Greengard; June Yub Lee

doi:10.1006/jcph.1996.0103

A direct adaptive poisson solver of arbitrary order accuracy

Leslie Greengard, June Yub Lee

Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

We present a direct, adaptive solver for the Poisson equation which can achieve any prescribed order of accuracy. It is based on a domain decomposition approach using local spectral approximation, as well as potential theory and the fast multipole method. In two space dimensions, the algorithm requires O(NK) work, where N is the number of discretization points and K is the desired order of accuracy.

Original language	English (US)
Pages (from-to)	415-424
Number of pages	10
Journal	Journal of Computational Physics
Volume	125
Issue number	2
DOIs	https://doi.org/10.1006/jcph.1996.0103
State	Published - May 1996

ASJC Scopus subject areas

Numerical Analysis
Modeling and Simulation
Physics and Astronomy (miscellaneous)
Physics and Astronomy(all)
Computer Science Applications
Computational Mathematics
Applied Mathematics

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10.1006/jcph.1996.0103

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abstract = "We present a direct, adaptive solver for the Poisson equation which can achieve any prescribed order of accuracy. It is based on a domain decomposition approach using local spectral approximation, as well as potential theory and the fast multipole method. In two space dimensions, the algorithm requires O(NK) work, where N is the number of discretization points and K is the desired order of accuracy.",

author = "Leslie Greengard and Lee, {June Yub}",

note = "Funding Information: * The authors were supported by the Applied Mathematical Sciences Program of the U.S. Department of Energy under Contract DEFGO288ER25053, by the Office of Naval Research under Contract N00014-91-J-1312, by a NSF Presidential Young Investigator Award to L.G. and by a Packard Foundation Fellowship to L.G.",

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N2 - We present a direct, adaptive solver for the Poisson equation which can achieve any prescribed order of accuracy. It is based on a domain decomposition approach using local spectral approximation, as well as potential theory and the fast multipole method. In two space dimensions, the algorithm requires O(NK) work, where N is the number of discretization points and K is the desired order of accuracy.

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