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An alternating LHSS preconditioner for saddle point problems

In this paper, we present a new alternating local Hermitian and skew-Hermitian splitting preconditioner for solving saddle point problems. The spectral property of the preconditioned matrices is studies in detail. Theoretical results show all eigenvalues of the preconditioned matrices will generate two tight clusters, one is near (0, 0) and the other is near (2, 0) as the iteration parameter tends to zero from positive. Numerical experiments are given to validate the performances of the preconditioner. Mathematical suject classification: Primary: 65F10; Secondary: 65F50.

saddle point problems; matrix splitting; preconditioner; eigenvalue distribution


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