skip to main content
research-article
Public Access

A Nonlinear QR Algorithm for Banded Nonlinear Eigenvalue Problems

Authors Info & Claims
Published:13 August 2016Publication History
Skip Abstract Section

Abstract

A variation of Kublanovskaya's nonlinear QR method for solving banded nonlinear eigenvalue problems is presented in this article. The new method is iterative and specifically designed for problems too large to use dense linear algebra techniques. For the unstructurally banded nonlinear eigenvalue problem, a new data structure is used for storing the matrices to keep memory and computational costs low. In addition, an algorithm is presented for computing several nearby nonlinear eigenvalues to already-computed ones. Finally, numerical examples are given to show the efficacy of the new methods, and the source code has been made publicly available.

References

  1. T. Betcke, N. J. Higham, V. Mehrmann, C. Schröder, and F. Tisseur. 2008. NLEVP: A Collection of Nonlinear Eigenvalue Problems. MIMS EPrint 2008.40, Manchester Institute for Mathematical Sciences, The University of Manchester, UK, Apr. 2008.Google ScholarGoogle Scholar
  2. T. Betcke, N. J. Higham, V. Mehrmann, C. Schröder, and F. Tisseur. 2013. NLEVP: A collection of nonlinear eigenvalue problems. ACM Trans. Math. Softw. 39 (2013), 7:1--7:28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. T. Chan. 1987. Rank-revealing QR factorizations, Linear Algebr. Appl. 88/89 (1987), 67--82.Google ScholarGoogle ScholarCross RefCross Ref
  4. S. Chandrasekaran and I. C. F. Ipsen. 1994. On rank-revealing factorisations. SIAM J. Matrix Anal. Appl. 15 (1994), 592--622. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Demmel. 1997. Applied Numerical Linear Algebra. SIAM, Philadelphia, PA, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. L. Foster. 1986. Rank and Null Space Calculations using Matrix. Decomposition Without Column Interchanges. Linear Algebr. Appl. 74 (1986), 47--71.Google ScholarGoogle ScholarCross RefCross Ref
  7. C. K. Garrett and R.-C. Li. 2013. Unstructurally Banded Nonlinear. Eigenvalue Solver Software, http://www.csm.ornl.gov/newsite/software.html, (2013).Google ScholarGoogle Scholar
  8. G. H. Golub and C. F. Van Loan. 1996. Matrix Computations, 3rd ed. John Hopkins University Press, Baltimore, MD, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Gu and S. C. Eisenstat. 1996. Efficient algorithms for computing a strong rank-revealing QR factorization. SIAM J. Sci. Comput. 17 (1996), 848--869. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. S. Güttel, R. Van Beeumen, K. Meerbergen, and W. Michiels. 2014. NLEIGS: A Class of Fully Rational Krylov Methods for Nonlinear Eigenvalue Problems. SIAM J. Sci. Comput. 36(6) (2014), A2842--A2864.Google ScholarGoogle Scholar
  11. Y. P. Hong and C.-T. Pan. 1992. Rank-Revealing QR Factorizations and the Singular Value Decomposition. Math. Comp. 58 (1992), 213--232.Google ScholarGoogle Scholar
  12. X. Huang, Z. Bai, and Y. Su. 2010. Nonlinear Rank-One Modification of the Symmetric Eigenvalue Problem, J. Comp. Math. 28 (2010), 218--234.Google ScholarGoogle ScholarCross RefCross Ref
  13. N. K. Jain and K. Singhal. 1983. On Kublanovskaya's Approach to the Solution of the Generalized Latent Value Problems for Functional λ-Matrices. SIAM J. Numer. Anal. 20 (1983), 1062--1067.Google ScholarGoogle ScholarCross RefCross Ref
  14. W. Kahan. 1966. Numerical Linear Algebra. Can. Math. Bull. (1966). 757--801.Google ScholarGoogle Scholar
  15. V. N. Kublanovskaya. 1970. On an Approach to the Solution of the Generalized Latent Value Problems for λ-Matrices. SIAM J. Numer. Anal. 7 (1970), 532--537.Google ScholarGoogle ScholarCross RefCross Ref
  16. R.-C. Li. 1989. QR decomposition and nonlinear eigenvalue problems. Math. Numer. Sinica 11 (1989), 374--385. {in Chinese}Google ScholarGoogle Scholar
  17. R.-C. Li. 1992. Compute multiple nonlinear eigenvalues. J. Comp. Math. 10 (1992), 1--20.Google ScholarGoogle Scholar
  18. V. Mehrmann and H. Voss. 2004. Nonlinear eigenvalue problems: A challenge for modern eigenvalue methods. GAMM Rep. 27 (2004), 121--152.Google ScholarGoogle ScholarCross RefCross Ref
  19. G. W. Stewart. 1998. Matrix Algorithms Vol. I: Basic Decompositions. SIAM, Philadelphia, PA, 1998.Google ScholarGoogle ScholarCross RefCross Ref
  20. D. B. Szyld and F. Xue. 2013. Local Convergence Analysis of Several Inexact Newton-Type Algorithms for General Nonlinear Eigenvalue Problems. Numer. Math. 123 (2013), 333--362. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. F. Tisseur and K. Meerbergen. 2001. The quadratic eigenvalue problem. SIAM Rev. 43 (2001), 235--386. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. R. Van Beeumen, K. Meerbergen, and W. Michiels. 2015. Compact rational Krylov methods for nonlinear eigenvalue problems. SIAM. J. Matrix Anal. Appl. 36(2) (2015), 820--838.Google ScholarGoogle Scholar
  23. H. Voss. 2004. An Arnoldi method for nonlinear eigenvalue problems. BIT Numer Math. 44 (2004), 387--401.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. J. H. Wilkinson. 1965. The Algebraic Eigenvalue Problem. Oxford University Press, London, 1965.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. A Nonlinear QR Algorithm for Banded Nonlinear Eigenvalue Problems

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on Mathematical Software
        ACM Transactions on Mathematical Software  Volume 43, Issue 1
        March 2017
        202 pages
        ISSN:0098-3500
        EISSN:1557-7295
        DOI:10.1145/2987591
        Issue’s Table of Contents

        Copyright © 2016 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 13 August 2016
        • Revised: 1 December 2015
        • Accepted: 1 December 2015
        • Received: 1 February 2014
        Published in toms Volume 43, Issue 1

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader