Arithmetic, geometric, and harmonic means for accretive-dissipative matrices

The concept of Loewner (partial) order for general complex matrices is introduced. After giving the definition of arithmetic, geometric, and harmonic mean for accretive-dissipative matrices, we study their basic properties. An AM-GM-HM inequality is established for two accretive-dissipative matrices in the sense of this extended Loewner order. We also compare the harmonic mean and parallel sum of two accretive-dissipative matrices, revealing an interesting relation between them. A number of examples are included.Comment: The paper is not matur

A weakly stable algorithm for general Toeplitz systems

We show that a fast algorithm for the QR factorization of a Toeplitz or Hankel matrix A is weakly stable in the sense that R^T.R is close to A^T.A. Thus, when the algorithm is used to solve the semi-normal equations R^T.Rx = A^Tb, we obtain a weakly stable method for the solution of a nonsingular Toeplitz or Hankel linear system Ax = b. The algorithm also applies to the solution of the full-rank Toeplitz or Hankel least squares problem.Comment: 17 pages. An old Technical Report with postscript added. For further details, see http://wwwmaths.anu.edu.au/~brent/pub/pub143.htm

Verified partial eigenvalue computations using contour integrals for Hermitian generalized eigenproblems

We propose a verified computation method for partial eigenvalues of a Hermitian generalized eigenproblem. The block Sakurai-Sugiura Hankel method, a contour integral-type eigensolver, can reduce a given eigenproblem into a generalized eigenproblem of block Hankel matrices whose entries consist of complex moments. In this study, we evaluate all errors in computing the complex moments. We derive a truncation error bound of the quadrature. Then, we take numerical errors of the quadrature into account and rigorously enclose the entries of the block Hankel matrices. Each quadrature point gives rise to a linear system, and its structure enables us to develop an efficient technique to verify the approximate solution. Numerical experiments show that the proposed method outperforms a standard method and infer that the proposed method is potentially efficient in parallel.Comment: 15 pages, 4 figures, 1 tabl

Fast solvers for tridiagonal Toeplitz linear systems

Let A be a tridiagonal Toeplitz matrix denoted by A=Tritoep(β,α,γ). The matrix A is said to be: strictly diagonally dominant if |α|>|β|+|γ|, weakly diagonally dominant if |α|≥|β|+|γ|, subdiagonally dominant if |β|≥|α|+|γ|, and superdiagonally dominant if |γ|≥|α|+|β|. In this paper, we consider the solution of a tridiagonal Toeplitz system Ax=b, where A is subdiagonally dominant, superdiagonally dominant, or weakly diagonally dominant, respectively. We first consider the case of A being subdiagonally dominant. We transform A into a block 2×2 matrix by an elementary transformation and then solve such a linear system using the block LU factorization. Compared with the LU factorization method with pivoting, our algorithm takes less flops, and needs less memory storage and data transmission. In particular, our algorithm outperforms the LU factorization method with pivoting in terms of computing efficiency. Then, we deal with superdiagonally dominant and weakly diagonally dominant cases, respectively. Numerical experiments are finally given to illustrate the effectiveness of our algorithmsNational Natural Science Foundation of China under Grant no. 11371075, the Hunan Key Laboratory of mathematical modeling and analysis in engineering, the research innovation program of Changsha University of Science and Technology for postgraduate students under Grant (CX2019SS34), and the Portuguese Funds through FCT-Fundação para a Ciência, within the Project UIDB/00013/2020 and UIDP/00013/202