Analysis of the SORAS domain decomposition preconditioner for non-self-adjoint or indefinite problems - Archive ouverte HAL Access content directly
Journal Articles Journal of Scientific Computing Year : 2021

Analysis of the SORAS domain decomposition preconditioner for non-self-adjoint or indefinite problems

Abstract

We analyze the convergence of the one-level overlapping domain decomposition preconditioner SORAS (Symmetrized Optimized Restricted Additive Schwarz) applied to a generic linear system whose matrix is not necessarily symmetric/self-adjoint nor positive definite. By generalizing the theory for the Helmholtz equation developed in [I.G. Graham, E.A. Spence, and J. Zou, SIAM J.Numer.Anal., 2020], we identify a list of assumptions and estimates that are sufficient to obtain an upper bound on the norm of the preconditioned matrix, and a lower bound on the distance of its field of values from the origin. We stress that our theory is general in the sense that it is not specific to one particular boundary value problem. Moreover, it does not rely on a coarse mesh whose elements are sufficiently small. As an illustration of this framework, we prove new estimates for overlapping domain decomposition methods with Robin-type transmission conditions for the heterogeneous reaction-convection-diffusion equation (to prove the stability assumption for this equation we consider the case of a coercive bilinear form, which is non-symmetric, though).
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Dates and versions

hal-02513123 , version 1 (20-03-2020)
hal-02513123 , version 2 (08-11-2020)
hal-02513123 , version 3 (26-05-2021)

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Marcella Bonazzoli, Xavier Claeys, Frédéric Nataf, Pierre-Henri Tournier. Analysis of the SORAS domain decomposition preconditioner for non-self-adjoint or indefinite problems. Journal of Scientific Computing, 2021, 89, ⟨10.1007/s10915-021-01631-8⟩. ⟨hal-02513123v3⟩
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