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Original Articles

Preconditioning and convergence in the right norm

Pages 1199-1209 | Received 12 Mar 2007, Accepted 17 Mar 2007, Published online: 28 Aug 2007
 

Abstract

The convergence of numerical approximations to the solutions of differential equations is a key aspect of numerical analysis and scientific computing. Iterative solution methods for the systems of linear(ized) equations which often result are also underpinned by analyses of convergence. In the function space setting, it is widely appreciated that there are appropriate ways in which to assess convergence and it is well-known that different norms are not equivalent. In the finite dimensional linear algebra setting, however, all norms are equivalent and little attention is often paid to the norms used. In this paper, we highlight this consideration in the context of preconditioning for minimum residual methods (MINRES and GMRES/GCR/ORTHOMIN) and argue that even in the linear algebra setting there is a ‘right’ norm in which to consider convergence: stopping an iteration which is rapidly converging in an irrelevant or highly scaled norm at some tolerance level may still give a poor answer.

Acknowledgements

I am grateful to an anonymous referee for comments which improved this manuscript and to Professor Ke Chen for his patience.

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