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Computational and Applied Mathematics

, Volume 37, Issue 2, pp 1959–1970 | Cite as

A low-order block preconditioner for saddle point linear systems

Article
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Abstract

A preconditioner is proposed for the large and sparse linear saddle point problems, which is based on a low-order three-by-three block saddle point form. The eigenvalue distribution and an upper bound of the degree of the minimal polynomial for the preconditioned matrix are discussed. Numerical results show that the optimal convergence behavior can be achieved when the new preconditioner is used to accelerate the convergence rate of Krylov subspace methods such as GMRES.

Keywords

Saddle point problem Preconditioner Eigenvalue distribution 

Mathematics Subject Classification

65F10 65F08 65F50 

Notes

Acknowledgements

The authors would like to express their great thankfulness to the referees for the comments and constructive suggestions very much, which are valuable in improving the quality of the original paper.

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Copyright information

© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2017

Authors and Affiliations

  1. 1.School of Mathematics and Computer Science and FJKLMAAFujian Normal UniversityFuzhouPeople’s Republic of China

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