Abstract
We extend the operator preconditioning framework Hiptmair (2006) [10] to Petrov-Galerkin methods while accounting for parameter-dependent perturbations of both variational forms and their preconditioners, as occurs when performing numerical approximations. By considering different perturbation parameters for the original form and its preconditioner, our bi-parametric abstract setting leads to robust and controlled schemes. For Hilbert spaces, we derive exhaustive linear and super-linear convergence estimates for iterative solvers, such as h-independent convergence bounds, when preconditioning with low-accuracy or, equivalently, with highly compressed approximations.
| Original language | English |
|---|---|
| Pages (from-to) | 220-232 |
| Number of pages | 13 |
| Journal | Computers and Mathematics with Applications |
| Volume | 102 |
| DOIs | |
| State | Published - 15 Nov 2021 |
| Externally published | Yes |
Keywords
- Galerkin methods
- Iterative linear solvers
- Numerical approximation
- Operator preconditioning
Fingerprint
Dive into the research topics of 'Bi-parametric operator preconditioning'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver