Abstract
The two-sided Rayleigh quotient iteration proposed by Ostrowski computes a pair of corresponding left–right eigenvectors of a matrix C. We propose a Grassmannian version of this iteration, i.e., its iterates are pairs of p-dimensional subspaces instead of one-dimensional subspaces in the classical case. The new iteration generically converges locally cubically to the pairs of left–right p-dimensional invariant subspaces of C. Moreover, Grassmannian versions of the Rayleigh quotient iteration are given for the generalized Hermitian eigenproblem, the Hamiltonian eigenproblem and the skew-Hamiltonian eigenproblem.
Similar content being viewed by others
References
Abraham, R., Marsden, J.E., Ratiu, T.: Manifolds, Tensor Analysis, and Applications. Applied Mathematical Sciences, vol. 75, 2nd edn. Springer, New York (1988)
Absil P.-A., Mahony R., Sepulchre R.: Riemannian geometry of Grassmann manifolds with a view on algorithmic computation. Acta Appl. Math. 80(2), 199–220 (2004)
Absil P.-A., Mahony R., Sepulchre R.: Optimization Algorithms on Matrix Manifolds. Princeton University Press, Princeton (2008)
Absil P.-A., Mahony R., Sepulchre R., Van Dooren P.: A Grassmann–Rayleigh quotient iteration for computing invariant subspaces. SIAM Rev. 44(1), 57–73 (2002)
Absil P.-A., Sepulchre R., Van Dooren P., Mahony R.: Cubically convergent iterations for invariant subspace computation. SIAM J. Matrix Anal. Appl. 26(1), 70–96 (2004)
Benner P., Byers R., Mehrmann V., Xu H.: Numerical computation of deflating subspaces of skew-Hamiltonian/Hamiltonian pencils. SIAM J. Matrix Anal. Appl. 24(1), 165–190 (2002)
Brandts J.: Computing tall skinny solutions of AX−XB = C. Math. Comput. Simul. 61(3–6), 385–397 (2003) MODELLING 2001 (Pilsen)
Bartels R.H., Stewart G.W.: Algorithm 432: solution of the matrix equation AX + XB = C. Commun. ACM 15, 820–826 (1972)
Batterson S., Smillie J.: The dynamics of Rayleigh quotient iteration. SIAM J. Numer. Anal. 26(3), 624–636 (1989)
Batterson S., Smillie J.: Rayleigh quotient iteration for nonsymmetric matrices. Math. Comp. 55(191), 169–178 (1990)
Chatelin, F.: Simultaneous Newton’s iteration for the eigenproblem. In: Defect Correction Methods (Oberwolfach, 1983), vol. 5 of Comput. Suppl., pp. 67–74. Springer, Vienna (1984).
Crandall S.H.: Iterative procedures related to relaxation methods for eigenvalue problems. Proc. R. Soc. Lond. 207(1090), 416–423 (1951)
Demmel J.W.: Three methods for refining estimates of invariant subspaces. Computing 38(1), 43–57 (1987)
Dongarra J.J., Moler C.B., Wilkinson J.H.: Improving the accuracy of computed eigenvalues and eigenvectors. SIAM J. Numer. Anal. 20(1), 23–45 (1983)
Edelman A., Arias T.A., Smith S.T.: The geometry of algorithms with orthogonality constraints. SIAM J. Matrix Anal. Appl. 20(2), 303–353 (1998)
Gardiner J.D., Laub A.J., Amato J.J., Moler C.B.: Solution of the Sylvester matrix equation AXB T + CXD T = E. ACM Trans. Math. Softw. 18(2), 223–231 (1992)
Gohberg, I., Lancaster, P., Rodman, L.: Invariant subspaces of matrices with applications. Canadian Mathematical Society Series of Monographs and Advanced Texts. Wiley, New York, Republished 2006 as Classics in Applied Mathematics 51 by SIAM, Philadelphia (1986)
Golub G.H., Nash S., Van Loan C.F.: A Hessenberg–Schur method for the problem AX + XB = C. IEEE Trans. Automat. Control 24, 909–913 (1979)
Gu, M.: Single- and multiple-vector iterations. In: Bai, Z., Demmel, J., Dongarra, J., Ruhe, A., van der Vorst, H. (eds.) Templates for the Solution of Algebraic Eigenvalue Problems, pp. 51–56. SIAM, Philadelphia (2000)
Golub, G.H., Van Loan, C.F.: Matrix Computations. Johns Hopkins Studies in the Mathematical Sciences, 3rd edn. Johns Hopkins University Press, Baltimore (1996)
Ipsen I.C.F.: Computing an eigenvector with inverse iteration. SIAM Rev. 39(2), 254–291 (1997)
Lundström, E., Eldén, L.: Adaptive eigenvalue computations using Newton’s method on the Grassmann manifold. SIAM J. Matrix Anal. Appl., 23(3), 819–839 (2001/2002)
Lösche R., Schwetlick H., Timmermann G.: A modified block Newton iteration for approximating an invariant subspace of a symmetric matrix. Linear Algebra Appl. 275/276, 381–400 (1998)
Ostrowski, A.M.: On the convergence of the Rayleigh quotient iteration for the computation of the characteristic roots and vectors. I–VI. Arch. Ration. Mech. Anal., 1, 233–241, 2, 423–428, 3, 325–340, 3, 341–347, 3, 472–481, and 4, 153–165 (1959)
Ostrowski A.M.: On the convergence of the Rayleigh quotient iteration for the computation of the characteristic roots and vectors. III. Arch. Ration. Mech. Anal. 3, 325–340 (1959)
Parlett B.N.: The Rayleigh quotient iteration and some generalizations for nonnormal matrices. Math. Comp. 28, 679–693 (1974)
Parlett, B.N.: The Symmetric Eigenvalue Problem. Prentice-Hall, Englewood Cliffs. Republished 1998 as Classics in Applied Mathematics 20 by SIAM, Philadelphia (1980)
Parlett, B.N., Kahan, W.: On the convergence of a practical QR algorithm. In: Information Processing 68 (Proc. IFIP Congress, Edinburgh, 1968), vol. 1. Mathematics, Software, pp 114–118, North-Holland, Amsterdam (1969)
Peters G., Wilkinson J.H.: Inverse iteration, ill-conditioned equations and Newton’s method. SIAM Rev. 21(3), 339–360 (1979)
Qiu L., Zhang Y., Li C.-K.: Unitarily invariant metrics on the Grassmann space. SIAM J. Matrix Anal. Appl. 27(2), 507–531 (2005) (electronic)
Rayleigh J.W.: The Theory of Sound. Macmillan, London (1877)
Scharnhorst K.: Angles in complex vector spaces. Acta Appl. Math. 69(1), 95–103 (2001)
Simoncini V.: On the numerical solution of AX−XB = C. BIT 36(4), 814–830 (1996)
Smit, P.: Numerical Analysis of Eigenvalue Algorithms Based on Subspace Iterations. Ph.D. Thesis, CentER, Tilburg University, Tilburg, The Netherlands (1997)
Stewart G.W., Sun J.G.: Matrix Perturbation Theory. Science And Scientific Computing. Academic Press, Boston (1990)
Stewart G.W.: Error and perturbation bounds for subspaces associated with certain eigenvalue problems. SIAM Rev. 15, 727–764 (1973)
Stewart G.W.: A generalization of Saad’s theorem on Rayleigh–Ritz approximations. Linear Algebra Appl. 327(1–3), 115–119 (2001)
Stewart, G.W.: Matrix Algorithms, vol. II. Society for Industrial and Applied Mathematics (SIAM), Philadelphia (Eigensystems) (2001)
Watkins D.S.: Understanding the QR algorithm. SIAM Rev. 24(4), 427–440 (1982)
Wielandt, H.: Beiträge zur mathematischen behandlung komplexer eigenwertprobleme, Teil V: Bestimmung höherer eigenwerte durch gebrochene iteration. Bericht B 44/J/37, Aerodynamische Versuchsanstalt, Göttingen, Germany (1944)
Wilkinson J.H.: The Algebraic Eigenvalue Problem. Clarendon Press, Oxford (1965)
Author information
Authors and Affiliations
Corresponding author
Additional information
This paper presents research results of the Belgian Network Dynamical systems, control, and optimization (DYSCO), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office. The scientific responsibility rests with its authors. This work was supported in part by the US National Science Foundation under Grant OCI-0324944 and by the School of Computational Science of Florida State University through a postdoctoral fellowship.
Rights and permissions
About this article
Cite this article
Absil, PA., Van Dooren, P. Two-sided Grassmann–Rayleigh quotient iteration. Numer. Math. 114, 549–571 (2010). https://doi.org/10.1007/s00211-009-0266-y
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00211-009-0266-y