NANAAPNov 22, 2011

Iterative methods for shifted positive definite linear systems and time discretization of the heat equation

arXiv:1111.51053 citationsh-index: 28
Originality Synthesis-oriented
AI Analysis

For researchers in numerical analysis and scientific computing, it provides theoretical and algorithmic insights into solving complex-shifted systems, but the contribution is incremental.

The paper studies iterative methods for solving shifted positive definite linear systems arising from a complex quadrature-based time discretization of the heat equation, analyzing Richardson and conjugate gradient methods with preconditioning.

In earlier work we have studied a method for discretization in time of a parabolic problem which consists in representing the exact solution as an integral in the complex plane and then applying a quadrature formula to this integral. In application to a spatially semidiscrete finite element version of the parabolic problem, at each quadrature point one then needs to solve a linear algebraic system having a positive definite matrix with a complex shift, and in this paper we study iterative methods for such systems. We first consider the basic and a preconditioned version of the Richardson algorithm, and then a conjugate gradient method as well as a preconditioned version thereof.

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