Natural preconditioning and iterative methods for saddle point systems

The solution of quadratic or locally quadratic extremum problems subject to linear(ized) constraints gives rise to linear systems in saddle point form. This is true whether in the continuous or the discrete setting, so saddle point systems arising from the discretization of partial differential equa...

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Main Authors: Pestana, J, Wathen, AJ
Format: Journal article
Published: Society for Industrial and Applied Mathematics 2015
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author Pestana, J
Wathen, AJ
author_facet Pestana, J
Wathen, AJ
author_sort Pestana, J
collection OXFORD
description The solution of quadratic or locally quadratic extremum problems subject to linear(ized) constraints gives rise to linear systems in saddle point form. This is true whether in the continuous or the discrete setting, so saddle point systems arising from the discretization of partial differential equation problems, such as those describing electromagnetic problems or incompressible flow, lead to equations with this structure, as do, for example, interior point methods and the sequential quadratic programming approach to nonlinear optimization. This survey concerns iterative solution methods for these problems and, in particular, shows how the problem formulation leads to natural preconditioners which guarantee a fast rate of convergence of the relevant iterative methods. These preconditioners are related to the original extremum problem and their effectiveness---in terms of rapidity of convergence---is established here via a proof of general bounds on the eigenvalues of the preconditioned saddle point matrix on which iteration convergence depends.
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spelling oxford-uuid:fe93a977-3f2c-406a-9f92-6f211c642c6d2022-03-27T13:37:49ZNatural preconditioning and iterative methods for saddle point systemsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:fe93a977-3f2c-406a-9f92-6f211c642c6dSymplectic Elements at OxfordSociety for Industrial and Applied Mathematics2015Pestana, JWathen, AJThe solution of quadratic or locally quadratic extremum problems subject to linear(ized) constraints gives rise to linear systems in saddle point form. This is true whether in the continuous or the discrete setting, so saddle point systems arising from the discretization of partial differential equation problems, such as those describing electromagnetic problems or incompressible flow, lead to equations with this structure, as do, for example, interior point methods and the sequential quadratic programming approach to nonlinear optimization. This survey concerns iterative solution methods for these problems and, in particular, shows how the problem formulation leads to natural preconditioners which guarantee a fast rate of convergence of the relevant iterative methods. These preconditioners are related to the original extremum problem and their effectiveness---in terms of rapidity of convergence---is established here via a proof of general bounds on the eigenvalues of the preconditioned saddle point matrix on which iteration convergence depends.
spellingShingle Pestana, J
Wathen, AJ
Natural preconditioning and iterative methods for saddle point systems
title Natural preconditioning and iterative methods for saddle point systems
title_full Natural preconditioning and iterative methods for saddle point systems
title_fullStr Natural preconditioning and iterative methods for saddle point systems
title_full_unstemmed Natural preconditioning and iterative methods for saddle point systems
title_short Natural preconditioning and iterative methods for saddle point systems
title_sort natural preconditioning and iterative methods for saddle point systems
work_keys_str_mv AT pestanaj naturalpreconditioninganditerativemethodsforsaddlepointsystems
AT wathenaj naturalpreconditioninganditerativemethodsforsaddlepointsystems