Arbenz, Peter; Hochstenbach, Michiel E. A Jacobi-Davidson method for solving complex symmetric eigenvalue problems. (English) Zbl 1061.65027 SIAM J. Sci. Comput. 25, No. 5, 1655-1673 (2004). Summary: We discuss variants of the Jacobi–Davidson method for solving the generalized complex symmetric eigenvalue problem. The Jacobi–Davidson algorithm can be considered as an accelerated inexact Rayleigh quotient iteration. We show that it is appropriate to replace the Euclidean inner product in \({\mathbb C}^n\) with an indefinite inner product. The Rayleigh quotient based on this indefinite inner product leads to an asymptotically cubically convergent Rayleigh quotient iteration. Advantages of the method are illustrated by numerical examples. We deal with problems from electromagnetics that require the computation of interior eigenvalues. The main drawback that we experience in these particular examples is the lack of efficient preconditioners. Cited in 9 Documents MSC: 65F15 Numerical computation of eigenvalues and eigenvectors of matrices 65F50 Computational methods for sparse matrices 65F35 Numerical computation of matrix norms, conditioning, scaling Keywords:generalized complex symmetric eigenvalue problem; interior eigenvalues; Jacobi-Davidson algorithm; Rayleigh quotient iteration; cubic convergence; large sparse matrix; numerical examples; preconditioners Software:ARPACK PDFBibTeX XMLCite \textit{P. Arbenz} and \textit{M. E. Hochstenbach}, SIAM J. Sci. Comput. 25, No. 5, 1655--1673 (2004; Zbl 1061.65027) Full Text: DOI