GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems
SIAM Journal on Scientific and Statistical Computing
Conjugate gradient-type methods for linear systems with complex symmetric coefficient matrices
SIAM Journal on Scientific and Statistical Computing - Special issue on iterative methods in numerical linear algebra
Multigrid
Solving Complex-Valued Linear Systems via Equivalent Real Formulations
SIAM Journal on Scientific Computing
Hermitian and Skew-Hermitian Splitting Methods for Non-Hermitian Positive Definite Linear Systems
SIAM Journal on Matrix Analysis and Applications
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Algebraic multigrid for complex symmetric matrices and applications
Journal of Computational and Applied Mathematics
SIAM Journal on Scientific Computing
A Novel Multigrid Based Preconditioner For Heterogeneous Helmholtz Problems
SIAM Journal on Scientific Computing
Spatial Multigrid for Isotropic Neutron Transport
SIAM Journal on Scientific Computing
SIAM Journal on Matrix Analysis and Applications
Algebraic Multigrid Solvers for Complex-Valued Matrices
SIAM Journal on Scientific Computing
Algebraic Multilevel Preconditioner for the Helmholtz Equation in Heterogeneous Media
SIAM Journal on Scientific Computing
Improved Multiple-Coarsening Methods for Sn Discretizations of the Boltzmann Equation
SIAM Journal on Scientific Computing
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We consider the numerical solution of linear systems of the form (A+i@kB)x=y, which arise in many applications, e.g., in time-harmonic acoustics, electromagnetics, or radiative transfer. We propose and analyze a class of preconditioners leading to complex symmetric iteration operators and investigate convergence of corresponding preconditioned iterative methods. Under mild assumptions on the operators A and B, we establish parameter and dimension independent convergence. The proposed methods are then applied to the solution of even-parity formulations of time-harmonic radiative transfer. For this application, we verify all assumptions required for our convergence analysis. The performance of the preconditioned iterations is then demonstrated by numerical tests supporting the theoretical results.