-

 

 

 




Optimization Online





 

BiLQ: An Iterative Method for Nonsymmetric Linear Systems with a Quasi-Minimum Error Property

Alexis Montoison(alexis.montoison***at***polymtl.ca)
Dominique Orban(dominique.orban***at***gerad.ca)

Abstract: We introduce an iterative method named BiLQ for solving general square linear systems Ax = b based on the Lanczos biorthogonalization process defined by least-norm subproblems, and is a natural companion to BiCG and QMR. Whereas the BiCG (Fletcher, 1976), CGS (Sonneveld, 1989) and BiCGSTAB (van der Vorst, 1992) iterates may not exist when the tridiagonal projection of A is singular, BiLQ is reliable on compatible systems even if A is ill-conditioned or rank deficient. As in the symmetric case, the BiCG residual is often smaller than the BiLQ residual and, when the BiCG iterate exists, an inexpensive transfer from the BiLQ iterate is possible. Although the Euclidean norm of the BiLQ error is usually not monotonic, it is monotonic in a different norm that depends on the Lanczos vectors. We establish a similar property for the QMR (Freund and Nachtigal, 1991) residual. BiLQ combines with QMR to take advantage of two initial vectors and solve a system and an adjoint system simultaneously at a cost similar to that of applying either method. We derive an analogous combination of USYMLQ and USYMQR based on the orthogonal tridiagonalization process (Saunders, Simon, and Yip, 1988). The resulting combinations, named BiLQR and TriLQR, may be used to estimate integral functionals involving the solution of a primal and an adjoint system. We compare BiLQR and TriLQR with MINRES-QLP on a related augmented system, which performs a comparable amount of work and requires comparable storage. In our experiments, BiLQR terminates earlier than TriLQR and MINRES-QLP in terms of residual and error of the primal and adjoint systems.

Keywords: iterative methods, Lanczos biorthogonalization process, quasi-minimal error method, least-norm subproblems, adjoint systems, integral functional, tridiagonalization process, multiprecision

Category 1: Other Topics (Other )

Citation: Cahier du GERAD G-2019-71, GERAD, Montréal, Canada. DOI 10.13140/RG.2.2.18287.59042

Download: [PDF]

Entry Submitted: 10/06/2019
Entry Accepted: 10/06/2019
Entry Last Modified: 10/06/2019

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society