- -

Inertia-based spectrum slicing for symmetric quadratic eigenvalue problems

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Inertia-based spectrum slicing for symmetric quadratic eigenvalue problems

Mostrar el registro completo del ítem

Campos, C.; Román Moltó, JE. (2020). Inertia-based spectrum slicing for symmetric quadratic eigenvalue problems. Numerical Linear Algebra with Applications. 27(4):1-17. https://doi.org/10.1002/nla.2293

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/163192

Ficheros en el ítem

Thumbnail
Nombre: Campos;Román - ...
Tamaño: 509.5Kb
Formato: PDF
Descripción: Versión del Autor.
Abrir/Preview
[Cerrado]
Nombre: nla.2293.pdf
Tamaño: 568.6Kb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor

Metadatos del ítem

Título: Inertia-based spectrum slicing for symmetric quadratic eigenvalue problems
Autor: Campos, Carmen Román Moltó, José Enrique
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] In the quadratic eigenvalue problem (QEP) with all coefficient matrices symmetric, there can be complex eigenvalues. However, some applications need to compute real eigenvalues only. We propose a Lanczos-based method ...[+]
Palabras clave: Inertia , Parallel computing , Pseudo-Lanczos , Quadratic eigenvalue problem , SLEPc , Symmetric linearization
Derechos de uso: Reserva de todos los derechos
Fuente:
Numerical Linear Algebra with Applications. (issn: 1070-5325 )
DOI: 10.1002/nla.2293
Editorial:
John Wiley & Sons
Versión del editor: https://doi.org/10.1002/nla.2293
Código del Proyecto:
info:eu-repo/grantAgreement/MINECO//TIN2016-75985-P/ES/SOLVERS DE VALORES PROPIOS ALTAMENTE ESCALABLES EN EL CONTEXTO DE LA BIBLIOTECA SLEPC/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107379RB-I00/ES/ALGORITMOS PARALELOS Y SOFTWARE PARA METODOS ALGEBRAICOS EN ANALISIS DE DATOS/
Agradecimientos:
Agencia Estatal de Investigacion, Grant/Award Number: TIN2016-75985-P
Tipo: Artículo

References

Tisseur, F., & Meerbergen, K. (2001). The Quadratic Eigenvalue Problem. SIAM Review, 43(2), 235-286. doi:10.1137/s0036144500381988

Veselić, K. (2011). Damped Oscillations of Linear Systems. Lecture Notes in Mathematics. doi:10.1007/978-3-642-21335-9

Grimes, R. G., Lewis, J. G., & Simon, H. D. (1994). A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems. SIAM Journal on Matrix Analysis and Applications, 15(1), 228-272. doi:10.1137/s0895479888151111 [+]
Tisseur, F., & Meerbergen, K. (2001). The Quadratic Eigenvalue Problem. SIAM Review, 43(2), 235-286. doi:10.1137/s0036144500381988

Veselić, K. (2011). Damped Oscillations of Linear Systems. Lecture Notes in Mathematics. doi:10.1007/978-3-642-21335-9

Grimes, R. G., Lewis, J. G., & Simon, H. D. (1994). A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems. SIAM Journal on Matrix Analysis and Applications, 15(1), 228-272. doi:10.1137/s0895479888151111

Campos, C., & Roman, J. E. (2012). Strategies for spectrum slicing based on restarted Lanczos methods. Numerical Algorithms, 60(2), 279-295. doi:10.1007/s11075-012-9564-z

Li, R., Xi, Y., Vecharynski, E., Yang, C., & Saad, Y. (2016). A Thick-Restart Lanczos Algorithm with Polynomial Filtering for Hermitian Eigenvalue Problems. SIAM Journal on Scientific Computing, 38(4), A2512-A2534. doi:10.1137/15m1054493

Guo, C.-H., Higham, N. J., & Tisseur, F. (2010). An Improved Arc Algorithm for Detecting Definite Hermitian Pairs. SIAM Journal on Matrix Analysis and Applications, 31(3), 1131-1151. doi:10.1137/08074218x

Niendorf, V., & Voss, H. (2010). Detecting hyperbolic and definite matrix polynomials. Linear Algebra and its Applications, 432(4), 1017-1035. doi:10.1016/j.laa.2009.10.014

NakatsukasaY NoferiniV. Inertia laws and localization of real eigenvalues for generalized indefinite eigenvalue problems;2017. Preprint arXiv:1711.00495.

Parlett, B. N., & Chen, H. C. (1990). Use of indefinite pencils for computing damped natural modes. Linear Algebra and its Applications, 140, 53-88. doi:10.1016/0024-3795(90)90222-x

Campos, C., & Roman, J. E. (2016). Restarted Q-Arnoldi-type methods exploiting symmetry in quadratic eigenvalue problems. BIT Numerical Mathematics, 56(4), 1213-1236. doi:10.1007/s10543-016-0601-5

Guo, C.-H., & Lancaster, P. (2005). Algorithms for hyperbolic quadratic eigenvalue problems. Mathematics of Computation, 74(252), 1777-1792. doi:10.1090/s0025-5718-05-01748-5

Li, H., & Cai, Y. (2015). Solving the real eigenvalues of hermitian quadratic eigenvalue problems via bisection. The Electronic Journal of Linear Algebra, 30, 721-743. doi:10.13001/1081-3810.1979

RomanJE CamposC RomeroE andTomasA. SLEPc users manual. DSIC‐II/24/02–Revision 3.9. D. Sistemes Informàtics i Computació Universitat Politècnica de València;2018.

Hernandez, V., Roman, J. E., & Vidal, V. (2005). SLEPc. ACM Transactions on Mathematical Software, 31(3), 351-362. doi:10.1145/1089014.1089019

Guo, J.-S., Lin, W.-W., & Wang, C.-S. (1995). Numerical solutions for large sparse quadratic eigenvalue problems. Linear Algebra and its Applications, 225, 57-89. doi:10.1016/0024-3795(93)00318-t

Sleijpen, G. L. G., Booten, A. G. L., Fokkema, D. R., & van der Vorst, H. A. (1996). Jacobi-davidson type methods for generalized eigenproblems and polynomial eigenproblems. BIT Numerical Mathematics, 36(3), 595-633. doi:10.1007/bf01731936

Bai, Z., & Su, Y. (2005). SOAR: A Second-order Arnoldi Method for the Solution of the Quadratic Eigenvalue Problem. SIAM Journal on Matrix Analysis and Applications, 26(3), 640-659. doi:10.1137/s0895479803438523

Güttel, S., & Tisseur, F. (2017). The nonlinear eigenvalue problem. Acta Numerica, 26, 1-94. doi:10.1017/s0962492917000034

Yang, L., Sun, Y., & Gong, F. (2018). The inexact residual iteration method for quadratic eigenvalue problem and the analysis of convergence. Journal of Computational and Applied Mathematics, 332, 45-55. doi:10.1016/j.cam.2017.10.003

Keçeli, M., Corsetti, F., Campos, C., Roman, J. E., Zhang, H., Vázquez-Mayagoitia, Á., … Wagner, A. F. (2018). SIESTA-SIPs: Massively parallel spectrum-slicing eigensolver for an ab initio molecular dynamics package. Journal of Computational Chemistry, 39(22), 1806-1814. doi:10.1002/jcc.25350

Voss, H., Werner, B., & Hadeler, K. P. (1982). A minimax principle for nonlinear eigenvalue problems with applications to nonoverdamped systems. Mathematical Methods in the Applied Sciences, 4(1), 415-424. doi:10.1002/mma.1670040126

Higham, N. J., Mackey, D. S., & Tisseur, F. (2009). Definite Matrix Polynomials and their Linearization by Definite Pencils. SIAM Journal on Matrix Analysis and Applications, 31(2), 478-502. doi:10.1137/080721406

Al-Ammari, M., & Tisseur, F. (2012). Hermitian matrix polynomials with real eigenvalues of definite type. Part I: Classification. Linear Algebra and its Applications, 436(10), 3954-3973. doi:10.1016/j.laa.2010.08.035

Gohberg, I., Lancaster, P., & Rodman, L. (1980). Spectral Analysis of Selfadjoint Matrix Polynomials. The Annals of Mathematics, 112(1), 33. doi:10.2307/1971320

RozložnÍk, M., Okulicka-DŁużewska, F., & Smoktunowicz, A. (2015). Cholesky-Like Factorization of Symmetric Indefinite Matrices and Orthogonalization with Respect to Bilinear Forms. SIAM Journal on Matrix Analysis and Applications, 36(2), 727-751. doi:10.1137/130947003

Lu, D., Su, Y., & Bai, Z. (2016). Stability Analysis of the Two-level Orthogonal Arnoldi Procedure. SIAM Journal on Matrix Analysis and Applications, 37(1), 195-214. doi:10.1137/151005142

Campos, C., & Roman, J. E. (2016). Parallel Krylov Solvers for the Polynomial Eigenvalue Problem in SLEPc. SIAM Journal on Scientific Computing, 38(5), S385-S411. doi:10.1137/15m1022458

Higham, N. J., Mackey, D. S., Mackey, N., & Tisseur, F. (2007). Symmetric Linearizations for Matrix Polynomials. SIAM Journal on Matrix Analysis and Applications, 29(1), 143-159. doi:10.1137/050646202

BalayS AbhyankarS AdamsM et al. PETSc users manual. ANL‐95/11 ‐ Revision 3.10. Argonne National Laboratory;2018.

Betcke, T., Higham, N. J., Mehrmann, V., Schröder, C., & Tisseur, F. (2013). NLEVP. ACM Transactions on Mathematical Software, 39(2), 1-28. doi:10.1145/2427023.2427024

Assink, J., Waxler, R., & Velea, D. (2017). A wide-angle high Mach number modal expansion for infrasound propagation. The Journal of the Acoustical Society of America, 141(3), 1781-1792. doi:10.1121/1.4977578

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem