Numerische Mathematik

, Volume 122, Issue 1, pp 169–195 | Cite as

A linear eigenvalue algorithm for the nonlinear eigenvalue problem

  • Elias Jarlebring
  • Wim Michiels
  • Karl Meerbergen


The Arnoldi method for standard eigenvalue problems possesses several attractive properties making it robust, reliable and efficient for many problems. The first result of this paper is a characterization of the solutions to an arbitrary (analytic) nonlinear eigenvalue problem (NEP) as the reciprocal eigenvalues of an infinite dimensional operator denoted \({\mathcal {B}}\) . We consider the Arnoldi method for the operator \({\mathcal {B}}\) and show that with a particular choice of starting function and a particular choice of scalar product, the structure of the operator can be exploited in a very effective way. The structure of the operator is such that when the Arnoldi method is started with a constant function, the iterates will be polynomials. For a large class of NEPs, we show that we can carry out the infinite dimensional Arnoldi algorithm for the operator \({\mathcal {B}}\) in arithmetic based on standard linear algebra operations on vectors and matrices of finite size. This is achieved by representing the polynomials by vector coefficients. The resulting algorithm is by construction such that it is completely equivalent to the standard Arnoldi method and also inherits many of its attractive properties, which are illustrated with examples.

Mathematics Subject Classification

65F15 65H17 


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  1. 1.
    Arnoldi W.: The principle of minimized iterations in the solution of the matrix eigenvalue problem. Q. Appl. Math. 9, 17–29 (1951)MathSciNetzbMATHGoogle Scholar
  2. 2.
    Asakura J., Sakurai T., Tadano H., Ikegami T., Kimura K.: A numerical method for nonlinear eigenvalue problems using contour integrals. JSIAM Lett. 1, 52–55 (2009)Google Scholar
  3. 3.
    Bai Z., Su Y.: SOAR: A second-order Arnoldi method for the solution of the quadratic eigenvalue problem. SIAM J. Matrix Anal. Appl. 26(3), 640–659 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Betcke, T., Higham, N.J., Mehrmann, V., Schröder, C., Tisseur, F.: NLEVP: a collection of nonlinear eigenvalue problems. Technical report, University of Manchester (2010)Google Scholar
  5. 5.
    Beyn, W.J.: An integral method for solving nonlinear eigenvalue problems. Linear Algebra Appl. (2011, in press). doi: 10.1016/j.laa.2011.03.030
  6. 6.
    Breda D., Maset S., Vermiglio R.: Pseudospectral approximation of eigenvalues of derivative operators with non-local boundary conditions. Appl. Numer. Math. 56, 318–331 (2006)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Fassbender H., Mackey D., Mackey N., Schröder C.: Structured polynomial eigenproblems related to time-delay systems. Electron. Trans. Numer. Anal. 31, 306–330 (2008)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Gohberg I., Lancaster P., Rodman L.: Matrix polynomials. Academic press, New York (1982)zbMATHGoogle Scholar
  9. 9.
    Hale J., Verduyn Lunel S.M.: Introduction to functional differential equations. Springer, Berlin (1993)zbMATHGoogle Scholar
  10. 10.
    Hochstenbach M.E., Sleijpen G.L.: Harmonic and refined Rayleigh–Ritz for the polynomial eigenvalue problem. Numer. Linear Algebra Appl. 15(1), 35–54 (2008)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Jarlebring E., Meerbergen K., Michiels W.: A Krylov method for the delay eigenvalue problem. SIAM J. Sci. Comput. 32(6), 3278–3300 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  12. 12.
    Kressner D.: A block Newton method for nonlinear eigenvalue problems. Numer. Math. 114(2), 355–372 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Kressner D., Schröder C., Watkins D.S.: Implicit QR algorithms for palindromic and even eigenvalue problems. Numer. Algorithms 51(2), 209–238 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  14. 14.
    Lehoucq R., Sorensen D., Yang C.: ARPACK user’s guide. Solution of large-scale eigenvalue problems with implicitly restarted Arnoldi methods. SIAM publications, Philadelphia (1998)zbMATHGoogle Scholar
  15. 15.
    Liao B.-S., Bai Z., Lee L.-Q., Ko K.: Nonlinear Rayleigh–Ritz iterative method for solving large scale nonlinear eigenvalue problems. Taiwan. J. Math. 14(3), 869–883 (2010)MathSciNetzbMATHGoogle Scholar
  16. 16.
    Mackey D., Mackey N., Mehl C., Mehrmann V.: Numerical methods for palindromic eigenvalue problems: Computing the anti-triangular Schur form. Numer. Linear Algebra 16, 63–86 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  17. 17.
    Meerbergen K.: The quadratic Arnoldi method for the solution of the quadratic eigenvalue problem. SIAM J. Matrix Anal. Appl. 30(4), 1463–1482 (2008)MathSciNetzbMATHCrossRefGoogle Scholar
  18. 18.
    Mehrmann V., Voss H.: Nonlinear eigenvalue problems: a challenge for modern eigenvalue methods. GAMM Mitteilungen 27, 121–152 (2004)MathSciNetzbMATHGoogle Scholar
  19. 19.
    Neumaier A.: Residual inverse iteration for the nonlinear eigenvalue problem. SIAM J. Numer. Anal. 22, 914–923 (1985)MathSciNetzbMATHCrossRefGoogle Scholar
  20. 20.
    Peters G., Wilkinson J.: Inverse iterations, ill-conditioned equations and Newton’s method. SIAM Rev. 21, 339–360 (1979)MathSciNetzbMATHCrossRefGoogle Scholar
  21. 21.
    Ruhe A.: Algorithms for the nonlinear eigenvalue problem. SIAM J. Numer. Anal. 10, 674–689 (1973)MathSciNetzbMATHCrossRefGoogle Scholar
  22. 22.
    Sleijpen G.L., Booten A.G., Fokkema D.R., van der Vorst H.A.: Jacobi–Davidson type methods for generalized eigenproblems and polynomial eigenproblems. BIT 36(3), 595–633 (1996)MathSciNetzbMATHCrossRefGoogle Scholar
  23. 23.
    Su, Y., Bai, Z.: Solving rational eigenvalue problems via linearization. Technical report, Department of Computer Science and Mathematics, University of California, Davis (2008)Google Scholar
  24. 24.
    Trefethen L.N.: Spectral Methods in MATLAB. SIAM Publications, Philadelphia (2000)zbMATHCrossRefGoogle Scholar
  25. 25.
    Unger, H.: Nichtlineare Behandlung von Eigenwertaufgaben. Z. Angew. Math. Mech. 30, 281–282 (1950). English translation:
  26. 26.
    Voss H.: An Arnoldi method for nonlinear eigenvalue problems. BIT 44, 387–401 (2004)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Elias Jarlebring
    • 1
  • Wim Michiels
    • 2
  • Karl Meerbergen
    • 2
  1. 1.Royal Institute of Technology (KTH)StockholmSweden
  2. 2.Katholieke Universiteit LeuvenLeuvenBelgium

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