TY - JOUR

T1 - Jacobi-Davidson methods for polynomial two-parameter eigenvalue problems

AU - Hochstenbach, M.E.

AU - Muhic, A.

AU - Plestenjak, Bor

PY - 2015

Y1 - 2015

N2 - We propose Jacobi–Davidson type methods for polynomial two-parameter eigenvalue problems (PMEP). Such problems can be linearized as singular two-parameter eigenvalue problems, whose matrices are of dimension k(k+1)n/2k(k+1)n/2, where kk is the degree of the polynomial and nn is the size of the matrix coefficients in the PMEP. When k2nk2n is relatively small, the problem can be solved numerically by computing the common regular part of the related pair of singular pencils. For large k2nk2n, computing all solutions is not feasible and iterative methods are required.
When kk is large, we propose to linearize the problem first and then apply Jacobi–Davidson to the obtained singular two-parameter eigenvalue problem. The resulting method may for instance be used for computing zeros of a system of scalar bivariate polynomials close to a given target. On the other hand, when kk is small, we can apply a Jacobi–Davidson type approach directly to the original matrices. The original matrices are projected onto a low-dimensional subspace, and the projected polynomial two-parameter eigenvalue problems are solved by a linearization.
Keywords: Polynomial two-parameter eigenvalue problem (PMEP); Jacobi–Davidson; Singular generalized eigenvalue problem; Bivariate polynomial equations; Determinantal representation; Delay differential equations (DDEs)

AB - We propose Jacobi–Davidson type methods for polynomial two-parameter eigenvalue problems (PMEP). Such problems can be linearized as singular two-parameter eigenvalue problems, whose matrices are of dimension k(k+1)n/2k(k+1)n/2, where kk is the degree of the polynomial and nn is the size of the matrix coefficients in the PMEP. When k2nk2n is relatively small, the problem can be solved numerically by computing the common regular part of the related pair of singular pencils. For large k2nk2n, computing all solutions is not feasible and iterative methods are required.
When kk is large, we propose to linearize the problem first and then apply Jacobi–Davidson to the obtained singular two-parameter eigenvalue problem. The resulting method may for instance be used for computing zeros of a system of scalar bivariate polynomials close to a given target. On the other hand, when kk is small, we can apply a Jacobi–Davidson type approach directly to the original matrices. The original matrices are projected onto a low-dimensional subspace, and the projected polynomial two-parameter eigenvalue problems are solved by a linearization.
Keywords: Polynomial two-parameter eigenvalue problem (PMEP); Jacobi–Davidson; Singular generalized eigenvalue problem; Bivariate polynomial equations; Determinantal representation; Delay differential equations (DDEs)

U2 - 10.1016/j.cam.2015.04.019

DO - 10.1016/j.cam.2015.04.019

M3 - Article

VL - 288

SP - 251

EP - 263

JO - Journal of Computational and Applied Mathematics

JF - Journal of Computational and Applied Mathematics

SN - 0377-0427

ER -