A Homographic Best Approximation Problem with Application to Optimized Schwarz Waveform Relaxation

Daniel Bennequin (1) , Martin J. Gander (2) , Laurence Halpern (3)

1 IMJ - Institut de Mathématiques de Jussieu
2 Section de mathématiques [Genève]
3 LAGA - Laboratoire Analyse, Géométrie et Applications

We present and study a homographic best approximation problem, which arises in the analysis of waveform relaxation algorithms with optimized transmission conditions. Its solution characterizes in each class of transmission conditions the one with the best performance of the associated waveform relaxation algorithm. We present the particular class of first order transmission conditions in detail and show that the new waveform relaxation algorithms are well posed and converge much faster than the classical one: the number of iterations to reach a certain accuracy can be orders of magnitudes smaller. We illustrate our analysis with numerical experiments.

Mots clés: Schwarz Method; Domain Decomposition; Best Approximation.; Best Approximation

Domaines: Analyse numérique [math.NA]

Daniel Bennequin, Martin J. Gander, Laurence Halpern. A Homographic Best Approximation Problem with Application to Optimized Schwarz Waveform Relaxation. 2006. ⟨hal-00111643⟩