Transpose-Free Quasi-Minimal Residual Methods for Non-Hermitian Linear Systems

Recently, Freund and Nachtigal proposed a novel conjugate gradient-type method, the quasi-minimal residual algorithm (QMR), for the iterative solution of general non-Hermitian systems of linear equations. The QMR method is based on the nonsymmetric Lanczos process, and thus, like the latter, QMR requires matrix-vector multiplications with both the coefficient matrix of the linear system and its transpose. However, in certain applications, the transpose is not readily available, and generally, it is desirable to trade in multiplications with the transpose for matrix-vector products with the original matrix.

[1]  J. Bunch,et al.  Direct Methods for Solving Symmetric Indefinite Systems of Linear Equations , 1971 .

[2]  G. Strang,et al.  Toeplitz equations by conjugate gradients with circulant preconditioner , 1989 .

[3]  R. Freund Quasi-kernel polynomials and their use in non-Hermitian matrix iterations , 1992 .

[4]  R. Fletcher Conjugate gradient methods for indefinite systems , 1976 .

[5]  J. Meijerink,et al.  An iterative solution method for linear systems of which the coefficient matrix is a symmetric -matrix , 1977 .

[6]  Roland W. Freund,et al.  A Transpose-Free Quasi-Minimal Residual Algorithm for Non-Hermitian Linear Systems , 1993, SIAM J. Sci. Comput..

[7]  W. Joubert,et al.  Necessary and sufficient conditions for the simplification of generalized conjugate-gradient algorithms , 1987 .

[8]  Michael A. Saunders,et al.  Preconditioners for Indefinite Systems Arising in Optimization , 1992, SIAM J. Matrix Anal. Appl..

[9]  T. Manteuffel,et al.  Necessary and Sufficient Conditions for the Existence of a Conjugate Gradient Method , 1984 .

[10]  M. Gutknecht A Completed Theory of the Unsymmetric Lanczos Process and Related Algorithms. Part II , 1994, SIAM J. Matrix Anal. Appl..

[11]  C. Lanczos An iteration method for the solution of the eigenvalue problem of linear differential and integral operators , 1950 .

[12]  G. Golub,et al.  Iterative solution of linear systems , 1991, Acta Numerica.

[13]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[14]  Zhishun A. Liu,et al.  A Look Ahead Lanczos Algorithm for Unsymmetric Matrices , 1985 .

[15]  V. V. Voevodin The question of non-self-adjoint extension of the conjugate gradients method is closed , 1983 .

[16]  S. Eisenstat Efficient Implementation of a Class of Preconditioned Conjugate Gradient Methods , 1981 .

[17]  M. Hestenes,et al.  Methods of conjugate gradients for solving linear systems , 1952 .

[18]  R. Freund,et al.  QMR: a quasi-minimal residual method for non-Hermitian linear systems , 1991 .

[19]  Roland W. Freund,et al.  An Implementation of the Look-Ahead Lanczos Algorithm for Non-Hermitian Matrices , 1993, SIAM J. Sci. Comput..

[20]  Yousef Saad,et al.  ILUT: A dual threshold incomplete LU factorization , 1994, Numer. Linear Algebra Appl..

[21]  Roland W. Freund,et al.  On the use of two QMR algorithms for solving singular systems and applications in Markov chain modeling , 1994, Numer. Linear Algebra Appl..

[22]  H. Zha,et al.  A look-ahead algorithm for the solution of general Hankel systems , 1993 .

[23]  Y. Saad,et al.  GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems , 1986 .

[24]  P. Sonneveld CGS, A Fast Lanczos-Type Solver for Nonsymmetric Linear systems , 1989 .

[25]  Roland W. Freund,et al.  Conjugate Gradient-Type Methods for Linear Systems with Complex Symmetric Coefficient Matrices , 1992, SIAM J. Sci. Comput..

[26]  M. Saunders,et al.  Solution of Sparse Indefinite Systems of Linear Equations , 1975 .

[27]  R. Freund Quasi-Kernel Polynomials and Convergence Results for Quasi-Minimal Residual Iterations , 1992 .

[28]  Gene H. Golub,et al.  Matrix computations , 1983 .

[29]  Max Gunzburger,et al.  Finite Element Methods for Viscous Incompressible Flows: A Guide to Theory, Practice, and Algorithms , 1989 .

[30]  C. Lanczos Solution of Systems of Linear Equations by Minimized Iterations1 , 1952 .

[31]  Margaret H. Wright,et al.  Interior methods for constrained optimization , 1992, Acta Numerica.

[32]  John G. Lewis,et al.  Sparse matrix test problems , 1982, SGNM.