Efficient HSS-based preconditioners for generalized saddle point problems

2020 ◽  
Vol 39 (3) ◽  
Author(s):  
Ke Zhang ◽  
Lin-Na Wang
2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Wei-Hua Luo ◽  
Ting-Zhu Huang

By using Sherman-Morrison-Woodbury formula, we introduce a preconditioner based on parameterized splitting idea for generalized saddle point problems which may be singular and nonsymmetric. By analyzing the eigenvalues of the preconditioned matrix, we find that whenαis big enough, it has an eigenvalue at 1 with multiplicity at leastn, and the remaining eigenvalues are all located in a unit circle centered at 1. Particularly, when the preconditioner is used in general saddle point problems, it guarantees eigenvalue at 1 with the same multiplicity, and the remaining eigenvalues will tend to 1 as the parameterα→0. Consequently, this can lead to a good convergence when some GMRES iterative methods are used in Krylov subspace. Numerical results of Stokes problems and Oseen problems are presented to illustrate the behavior of the preconditioner.


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