Power integrity analysis of in-package and on-chip power supply needs to consider a large number of ports and handle magnetic coupling that is better represented by susceptance. The existing moment matching methods are not able to accurately model both large number of ports and susceptance. In this paper, we propose a generalized Second-order Arnoldi method for reducing Multiple SOurce Network ...

We study large, sparse generalized eigenvalue problems for matrix pencils, where one of the matrices is Hamiltonian and the other skew Hamiltonian. Problems of this form arise in the numerical simulation of elastic deformation of anisotropic materials, in structural mechanics and in the linear-quadratic control problem for partial diierential equations. We develop a structure-preserving skew-Ha...

A computational technique for computing relevant energy levels and corresponding wave functions of an electron confined by a 3D quantum dot embedded in a semiconductor matrix are studied. Assuming an energy and position dependent electron effective mass approximation this problem is governed by a rational eigenvalue problem. We discuss the application of iterative projection method of Arnoldi a...

In this paper, we present a new algorithm, which is called electromagnetism meta-heuristic restarted Arnoldi algorithm (EM-RA) for calculating eigenvalues and eigenvectors of a non-symmetric matrix. In most of the restarting methods the basic idea is a selection of the best initial eigenvector, but our aim is to improve the initial eigenvectors in each iteration of the restarting method. Numeri...

The Rational Krylov Sequence (RKS) method can be seen as a generalisation of Arnoldi's method. It projects a matrix pencil onto a smaller subspace; this projection results in a small upper Hessenberg pencil. As for the Arnoldi method, RKS can be restarted implicitly, using the QR decomposition of a Hessenberg matrix. This restart comes with a projection of the subspace using a rational function...

The shift-invert Arnoldi method is employed to generate an orthonormal basis from the Krylov subspace corresponding to a real Toeplitz matrix and an initial vector. The vectors and recurrence coefficients produced by this method are exploited to approximate the Toeplitz matrix exponential. Toeplitz matrix inversion formula and rapid Toeplitz matrix-vector multiplications are utilized to lower t...

In a recent paper [Rojas, Santos, Sorensen: ACM ToMS 34 (2008), Article 11] an efficient method for solving the Large-Scale Trust-Region Subproblem was suggested which is based on recasting it in terms of a parameter dependent eigenvalue problem and adjusting the parameter iteratively. The essential work at each iteration is the solution of an eigenvalue problem for the smallest eigenvalue of t...