Error Bounds for the Symmetric Eigenproblem     Next: Further Details: Error Up: Accuracy and Stability Previous: Error Bounds for

# Error Bounds for the Symmetric Eigenproblem

The eigendecomposition  of an n-by-n real symmetric matrix is the factorization ( in the complex Hermitian case), where Z is orthogonal (unitary) and is real and diagonal, with . The are the eigenvalues  of Aand the columns of Z are the eigenvectors . This is also often written . The eigendecomposition of a symmetric matrix is computed by the driver routines xSYEV, xSYEVX, xSYEVD, xSBEV, xSBEVX, xSBEVD, xSPEV, xSPEVX, xSPEVD, xSTEV, xSTEVX and xSTEVD. The complex counterparts of these routines, which compute the eigendecomposition of complex Hermitian matrices, are the driver routines xHEEV, xHEEVX, xHEEVD, xHBEV, xHBEVX, xHBEVD, xHPEV, xHPEVX, and xHPEVD (see subsection 2.2.4).

The approximate error bounds       for the computed eigenvalues are The approximate error bounds for the computed eigenvectors , which bound the acute angles between the computed eigenvectors and true eigenvectors , are: These bounds can be computed by the following code fragment:

```      EPSMCH = SLAMCH( 'E' )
*     Compute eigenvalues and eigenvectors of A
*     The eigenvalues are returned in W
*     The eigenvector matrix Z overwrites A
CALL SSYEV( 'V', UPLO, N, A, LDA, W, WORK, LWORK, INFO )
IF( INFO.GT.0 ) THEN
PRINT *,'SSYEV did not converge'
ELSE IF ( N.GT.0 ) THEN
*        Compute the norm of A
ANORM = MAX( ABS( W(1) ), ABS( W(N) ) )
EERRBD = EPSMCH * ANORM
*        Compute reciprocal condition numbers for eigenvectors
CALL SDISNA( 'Eigenvectors', N, N, W, RCONDZ, INFO )
DO 10 I = 1, N
ZERRBD( I ) = EPSMCH * ( ANORM / RCONDZ( I ) )
10       CONTINUE
ENDIF```

For example, if and then the eigenvalues, approximate error bounds, and true errors are Tue Nov 29 14:03:33 EST 1994