Abstract

The block cyclic reduction method is a finite-step direct method used for solving linear systems with block tridiagonal coefficient matrices. It iteratively uses transformations to reduce the number of non-zero blocks in coefficient matrices. With repeated block cyclic reductions, non-zero off-diagonal blocks in coefficient matrices incrementally leave the diagonal blocks and eventually vanish after a finite number of block cyclic reductions. In this paper, we focus on the roots of characteristic polynomials of coefficient matrices that are repeatedly transformed by block cyclic reductions. We regard each block cyclic reduction as a composition of two types of matrix transformations, and then attempt to examine changes in the existence range of roots. This is a block extension of the idea presented in our previous papers on simple cyclic reductions. The property that the roots are not very scattered is a key to accurately solve linear systems in floating-point arithmetic. We clarify that block cyclic reductions do not disperse roots, but rather narrow their distribution, if the original coefficient matrix is symmetric positive or negative definite.

Highlights

  • Solving systems of linear equations is one of the most important subjects in numerical linear algebra

  • This paper focused on coefficient matrices in linear systems obtained from block iterative cyclic reductions

  • We interpreted transformations from block M-tridiagonal matrices to block 2M-tridiagonal matrices as composite transformations of the block tridiagonalizations, with their inverses and transformations from block tridiagonal matrices to block 2-tridiagonal matrices appearing in the first step of the block cyclic reduction method

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Summary

Introduction

Solving systems of linear equations is one of the most important subjects in numerical linear algebra. Each stride reduction, including cyclic reduction, narrows the distribution of the roots of characteristic polynomials associated with the coefficient matrices if A are symmetric positive definite [6,7]. This is a desirable property that does not increase the difficulty of solving systems of linear systems.

Block Cyclic Reduction
Composite Transformation
Inverses of Block 1-Tridiagonal and 2-Tridiagonal Matrices
Roots of Characteristic Polynomial Sequence
Numerical Examples
Concluding Remarks
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