A New Perturbation Bound for the LDU Factorization of Diagonally Dominant Matrices

This work introduces a new perturbation bound for the $L$ factor of the LDU factorization of (row) diagonally dominant matrices computed via the column diagonal dominance pivoting strategy. This strategy yields $L$ and $U$ factors which are always well-conditioned and, so, the LDU factorization is guaranteed to be a rank-revealing decomposition. The new bound together with those for the $D$ and $U$ factors in [F. M. Dopico and P. Koev, Numer. Math., 119 (2011), pp. 337--371] establish that if diagonally dominant matrices are parameterized via their diagonally dominant parts and off-diagonal entries, then tiny relative componentwise perturbations of these parameters produce tiny relative normwise variations of $L$ and $U$ and tiny relative entrywise variations of $D$ when column diagonal dominance pivoting is used. These results will allow us to prove in a follow-up work that such perturbations also lead to strong perturbation bounds for many other problems involving diagonally dominant matrices.

[1]  Qiang Ye,et al.  RELATIVE PERTURBATION THEORY FOR DIAGONALLY DOMINANT MATRICES , 2017 .

[2]  Volker Mehrmann,et al.  Linear Perturbation Theory for Structured Matrix Pencils Arising in Control Theory , 2006, SIAM J. Matrix Anal. Appl..

[3]  Ilse C. F. Ipsen Relative perturbation results for matrix eigenvalues and singular values , 1998, Acta Numerica.

[4]  Yuji Nakatsukasa,et al.  Perturbation of multiple eigenvalues of Hermitian matrices , 2012 .

[5]  Qiang Ye Relative Perturbation Bounds for Eigenvalues of Symmetric Positive Definite Diagonally Dominant Matrices , 2009, SIAM J. Matrix Anal. Appl..

[6]  Froilán M. Dopico,et al.  Accurate Symmetric Rank Revealing and Eigendecompositions of Symmetric Structured Matrices , 2006, SIAM J. Matrix Anal. Appl..

[7]  Ivan Slapničar,et al.  Componentwise Analysis of Direct Factorization of Real Symmetric and Hermitian Matrices , 1998 .

[8]  N. Higham A Survey of Componentwise Perturbation Theory in Numerical Linear Algebra , 1994 .

[9]  Qiang Ye,et al.  Entrywise perturbation theory for diagonally dominant M-matrices with applications , 2002, Numerische Mathematik.

[10]  Yuji Nakatsukasa,et al.  Perturbation of Partitioned Hermitian Definite Generalized Eigenvalue Problems , 2011, SIAM J. Matrix Anal. Appl..

[11]  Froilán M. Dopico,et al.  Implicit standard Jacobi gives high relative accuracy , 2009, Numerische Mathematik.

[12]  Nicholas J. Higham,et al.  Structured Pseudospectra for Polynomial Eigenvalue Problems, with Applications , 2001, SIAM J. Matrix Anal. Appl..

[13]  L. Mirsky,et al.  The Theory of Matrices , 1961, The Mathematical Gazette.

[14]  M. F. Hama,et al.  On structured pseudo spectra for polynomial eigenvalue problems , 2013 .

[15]  S. Rump EIGENVALUES, PSEUDOSPECTRUM AND STRUCTURED PERTURBATIONS , 2006 .

[16]  Xiao-Wen Chang,et al.  Multiplicative perturbation analysis for QR factorizations , 2011 .

[17]  Daniel Kressner,et al.  Structured Eigenvalue Condition Numbers , 2006, SIAM J. Matrix Anal. Appl..

[18]  J. M. PEÑA LDU DECOMPOSITIONS WITH L AND U WELL CONDITIONED , .

[19]  Nicholas J. Higham,et al.  Backward Error and Condition of Structured Linear Systems , 1992, SIAM J. Matrix Anal. Appl..

[20]  Qiang Ye Computing singular values of diagonally dominant matrices to high relative accuracy , 2008, Math. Comput..

[21]  G. Stewart,et al.  Matrix Perturbation Theory , 1990 .

[22]  Xiao-Wen Chang Some Features of Gaussian Elimination with Rook Pivoting , 2002 .

[23]  Ren-Cang Li,et al.  A Bound on the Solution to a Structured Sylvester Equation with an Application to Relative Perturbation Theory , 1999, SIAM J. Matrix Anal. Appl..

[24]  Xiao-Wen Chang,et al.  On the sensitivity of the LU factorization , 1998 .

[25]  A. Barrlund Perturbation bounds for theLDLH andLU decompositions , 1991 .

[26]  Damien Stehlé,et al.  Rigorous Perturbation Bounds of Some Matrix Factorizations , 2010, SIAM J. Matrix Anal. Appl..

[27]  Mei Han An,et al.  accuracy and stability of numerical algorithms , 1991 .

[28]  Ivan Slapničar,et al.  Floating-point perturbations of Hermitian matrices , 1993 .

[29]  J. Demmel,et al.  Computing the Singular Value Decomposition with High Relative Accuracy , 1997 .

[30]  Nicholas J. Higham,et al.  Structured Backward Error and Condition of Generalized Eigenvalue Problems , 1999, SIAM J. Matrix Anal. Appl..

[31]  F. R. Gantmakher The Theory of Matrices , 1984 .

[32]  Ren-Cang Li Relative Perturbation Theory: I. Eigenvalue and Singular Value Variations , 1998, SIAM J. Matrix Anal. Appl..

[33]  Froilán M. Dopico,et al.  Accurate solution of structured linear systems via rank-revealing decompositions , 2012 .

[34]  Zlatko Drmac,et al.  New Fast and Accurate Jacobi SVD Algorithm. I , 2007, SIAM J. Matrix Anal. Appl..

[35]  Ji-guang Sun Componentwise perturbation bounds for some matrix decompositions , 1992 .

[36]  Gene H. Golub,et al.  Matrix computations , 1983 .

[37]  Froilán M. Dopico,et al.  Perturbation theory for the LDU factorization and accurate computations for diagonally dominant matrices , 2011, Numerische Mathematik.

[38]  Froilán M. Dopico,et al.  Perturbation Theory for Factorizations of LU Type through Series Expansions , 2005, SIAM J. Matrix Anal. Appl..

[39]  Shreemayee Bora,et al.  Structured Eigenvalue Condition Number and Backward Error of a Class of Polynomial Eigenvalue Problems Structured Eigenvalue Condition Number and Backward Error of a Class of Polynomial Eigenvalue Problems , 2022 .

[40]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[41]  James Demmel,et al.  Jacobi's Method is More Accurate than QR , 1989, SIAM J. Matrix Anal. Appl..

[42]  Peter Lancaster,et al.  The theory of matrices , 1969 .

[43]  Froilán M. Dopico,et al.  Accurate Solution of Structured Least Squares Problems via Rank-Revealing Decompositions , 2013, SIAM J. Matrix Anal. Appl..