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An indefinite variant of LOBPCG for definite matrix pencils

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Abstract

In this paper, we propose a novel preconditioned solver for generalized Hermitian eigenvalue problems. More specifically, we address the case of a definite matrix pencil \(A-\lambda B\), that is, A, B are Hermitian and there is a shift \(\lambda _{0}\) such that \(A-\lambda _{0} B\) is definite. Our new method can be seen as a variant of the popular LOBPCG method operating in an indefinite inner product. It also turns out to be a generalization of the recently proposed LOBP4DCG method by Bai and Li for solving product eigenvalue problems. Several numerical experiments demonstrate the effectiveness of our method for addressing certain product and quadratic eigenvalue problems.

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References

  1. HSL.: A collection of Fortran codes for large scale scientific computation. Available from http://www.hsl.rl.ac.uk/catalogue/ (2011)

  2. Arbenz, P., Drmač, Z.: On positive semidefinite matrices with known null space. SIAM J. Matrix Anal. Appl. 24(1), 132–149 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  3. Bai, Z., Demmel, J.W., Dongarra, J.J., Ruhe, A., van der Vorst, H. (eds.): Templates for the solution of algebraic eigenvalue problems. Software, Environments, and Tools. SIAM, Philadelphia (2000)

    Google Scholar 

  4. Bai, Z., Li, R.-C.: Minimization principles for the linear response eigenvalue problem I: theory. SIAM J. Matrix Anal. Appl. 33(4), 1075–1100 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  5. Bai, Z., Li, R.-C.: Minimization principles for the linear response eigenvalue problem II: computation. SIAM J. Matrix Anal. Appl. 34(2), 392–416 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  6. Bai, Z., Li, R.-C.: Minimization principles for the linear response eigenvalue problem III: general case. Mathematics preprint series. The University of Texas, Arlington (2013)

    Google Scholar 

  7. Benner, P., Kressner, D., Mehrmann, V.: Skew-Hamiltonian and Hamiltonian eigenvalue problems: theory, algorithms and applications. In: Drmač, Z., Marušić, M., Tutek, Z. (eds.) Proceedings of the Conference on Applied Mathematics and Scientific Computing, Brijuni (Croatia), June 23-27, 2003, pp. 3–39. Springer-Verlag (2005)

  8. Betcke, T., Higham, N.J., Mehrmann, V., Schröder, C., Tisseur, F.: NLEVP: a collection of nonlinear eigenvalue problems. ACM Trans. Math. Software 39(2), 7:1–7:28 (2013). Also available from http://www.mims.manchester.ac.uk/research/numerical-analysis/nlevp.html.

    Article  Google Scholar 

  9. D′yakonov, E.G.: Optimization in Solving Elliptic Problems. CRC Press, Boca Raton (1996)

    MATH  Google Scholar 

  10. Fan, H.-Y., Lin, W.-W., Van Dooren, P.: Normwise scaling of second order polynomial matrices. SIAM J. Matrix Anal. Appl. 26(1), 252–256 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  11. Gohberg, I., Lancaster, P., Rodman, L.: Matrices and indefinite scalar products. Operator Theory: Advances and Applications, vol. 8. Birkhäuser Verlag, Basel (1983)

    Google Scholar 

  12. Hansen, P.C., Yalamov, P.Y.: Symmetric rank revealing factorizations. In: Recent Advances in Numerical Methods and Applications, II (Sofia, 1998), pp. 687–695. World Sci. Publ., River Edge (1999)

  13. Hari, V., Singer, S., Singer, S.: Block-oriented J-Jacobi methods for Hermitian matrices. Linear Algebra Appl. 433(8–10), 1491–1512 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  14. Hetmaniuk, U., Lehoucq, R.: Basis selection in LOBPCG. J. Comput. Phys. 218(1), 324–332 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  15. Higham, N.J., Tisseur, F., Van Dooren, P.: Detecting a definite Hermitian pair and a hyperbolic or elliptic quadratic eigenvalue problem, and associated nearness problems. Linear Algebra Appl. 351/352, 455–474 (2002)

    Article  Google Scholar 

  16. Knyazev, A.V.: Toward the optimal preconditioned eigensolver: Locally optimal block preconditioned conjugate gradient method. SIAM J. Sci. Comput. 23(2), 517–541 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  17. Knyazev, A.V., Neymeyr, K.: Efficient solution of symmetric eigenvalue problems using multigrid preconditioners in the locally optimal block conjugate gradient method. Electron. Trans. Numer. Anal. 15, 38–55 (2003)

    MATH  MathSciNet  Google Scholar 

  18. Knyazev, A.V., Neymeyr, K.: A geometric theory for preconditioned inverse iteration. III: a short and sharp convergence estimate for generalized eigenvalue problems. Linear Algebra Appl. 358, 95–114 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  19. Knyazev, A.V., Neymeyr, K.: Gradient flow approach to geometric convergence analysis of preconditioned eigensolvers. SIAM J. Matrix Anal. Appl. 31(2), 621–628 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  20. Kovač-Striko, J., Veselić, K.: Trace minimization and definiteness of symmetric pencils. Linear Algebra Appl. 216, 139–158 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  21. Lancaster, P., Rodman, L.: Canonical forms for Hermitian matrix pairs under strict equivalence and congurence. SIAM Rev. 47(3), 407–443 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  22. Lancaster, P., Ye, Q.: Variational and numerical methods for symmetric matrix pencils. Bull. Austral. Math. Soc. 43(1), 1–17 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  23. Lashuk, I., Argentati, M., Ovtchinnikov, E., Knyazev, A.: Preconditioned eigensolver LOBPCG in hypre and PETSc. In: Widlund, O., Keyes, D. (eds.) Domain Decomposition Methods in Science and Engineering XVI, vol. 55 , pp. 635–642. Lecture Notes Computation Science Engineering, (2007)

  24. Liang, X., Li, R.-C., Bai, Z.: Trace minimization principles for positive semi-definite pencils. Linear Algebra Appl. 438(7), 3085–3106 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  25. Mathias, R.: Quadratic residual bounds for the Hermitian eigenvalue problem. SIAM J. Matrix Anal. Appl. 19(2), 541–550 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  26. Miloloža Pandur, M.: Some iterative methods for solving the symmetric generalized eigenvelue problem. PhD thesis, Department of Mathematics, University of Zagreb, in preparation

  27. Neymeyr, K.: A geometric theory for preconditioned inverse iteration. I: extrema of the Rayleigh quotient. Linear Algebra Appl. 322(1–3), 61–85 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  28. Neymeyr, K.: A geometric theory for preconditioned inverse iteration. II: convergence estimates. Linear Algebra Appl. 322(1–3), 87–104 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  29. Neymeyr, K.: A geometric theory for preconditioned inverse iteration applied to a subspace. Math. Comp. 71(237), 197–216 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  30. Neymeyr, K.: A geometric convergence theory for the preconditioned steepest descent iteration. SIAM Numer. Anal. 50(6), 3188–3207 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  31. Neymeyr, K., Ovtchinnikov, E., Zhou, M.: Convergence analysis of gradient iterations for the symmetric eigenvalue problem. SIAM J. Matrix Anal. Appl. 32(2), 443–456 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  32. Parlett, B.N.: The Symmetric Eigenvalue Problem, Classics in Applied Mathematics, vol. 20. Corrected reprint of the 1980 original. SIAM, Philadelphia (1998)

    Google Scholar 

  33. Stewart, G.W.: Basic decompositions. Matrix Algorithms, vol. I. SIAM, Philadelphia (1998)

    Book  Google Scholar 

  34. Stewart, G.W., Sun, J.-G.: Matrix Perturbation Theory. Academic, New York (1990)

  35. Truhar, N.: Relative Perturbation Theory for Matrix Spectral Decompositions. PhD thesis, Department of Mathematics, University of Zagreb (2000)

  36. Veselić, K.: A Jacobi eigenreduction algorithm for definite matrix pairs. Numer. Math. 64(2), 241–269 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  37. Veselić, K.: A mathematical introduction. Damped Oscillations of Linear Systems, vol. 2023. Lecture Notes in Mathematics.Springer, Heidelberg (2011)

    Google Scholar 

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Correspondence to Meiyue Shao.

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Kressner, D., Pandur, M.M. & Shao, M. An indefinite variant of LOBPCG for definite matrix pencils. Numer Algor 66, 681–703 (2014). https://doi.org/10.1007/s11075-013-9754-3

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