cstegr(3S)

CSTEGR - compute selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix T

As shipped in IRIX 6.5.22. Added in IRIX 6.5.15.

NAME
     CSTEGR - compute selected eigenvalues and, optionally, eigenvectors of a
     real symmetric tridiagonal matrix T

SYNOPSIS
     SUBROUTINE CSTEGR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, M, W, Z,
                        LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO )

         CHARACTER      JOBZ, RANGE

         INTEGER        IL, INFO, IU, LDZ, LIWORK, LWORK, M, N

         REAL           ABSTOL, VL, VU

         INTEGER        ISUPPZ( * ), IWORK( * )

         REAL           D( * ), E( * ), W( * ), WORK( * )

         COMPLEX        Z( LDZ, * )

IMPLEMENTATION
     These routines are part of the SCSL Scientific Library and can be loaded
     using either the -lscs or the -lscs_mp option.  The -lscs_mp option
     directs the linker to use the multi-processor version of the library.

     When linking to SCSL with -lscs or -lscs_mp, the default integer size is
     4 bytes (32 bits). Another version of SCSL is available in which integers
     are 8 bytes (64 bits).  This version allows the user access to larger
     memory sizes and helps when porting legacy Cray codes.  It can be loaded
     by using the -lscs_i8 option or the -lscs_i8_mp option. A program may use
     only one of the two versions; 4-byte integer and 8-byte integer library
     calls cannot be mixed.

PURPOSE
     CSTEGR computes selected eigenvalues and, optionally, eigenvectors of a
     real symmetric tridiagonal matrix T. Eigenvalues and






        (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T
            is a relatively robust representation,
        (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high
            relative accuracy by the dqds algorithm,
        (c) If there is a cluster of close eigenvalues, "choose" sigma_i
            close to the cluster, and go to step (a),
        (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T,
            compute the corresponding eigenvector by forming a
            rank-revealing twisted factorization.
     The desired accuracy of the output can be specified by the input
     parameter ABSTOL.

     For more details, see "A new O(n^2) algorithm for the symmetric
     tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon,
     Computer Science Division Technical Report No. UCB/CSD-97-971, UC
     Berkeley, May 1997.

     Note 1 : Currently CSTEGR is only set up to find ALL the n eigenvalues
     and eigenvectors of T in O(n^2) time
     Note 2 : Currently the routine CSTEIN is called when an appropriate
     sigma_i cannot be chosen in step (c) above. CSTEIN invokes modified
     Gram-Schmidt when eigenvalues are close.
     Note 3 : CSTEGR works only on machines which follow ieee-754 floating-
     point standard in their handling of infinities and NaNs.  Normal
     execution of CSTEGR may create NaNs and infinities and hence may abort
     due to a floating point exception in environments which do not conform to
     the ieee standard.


ARGUMENTS
     JOBZ    (input) CHARACTER*1
             = 'N':  Compute eigenvalues only;
             = 'V':  Compute eigenvalues and eigenvectors.

     RANGE   (input) CHARACTER*1
             = 'A': all eigenvalues will be found.
             = 'V': all eigenvalues in the half-open interval (VL,VU] will be
             found.  = 'I': the IL-th through IU-th eigenvalues will be found.

     N       (input) INTEGER
             The order of the matrix.  N >= 0.

     D       (input/output) REAL array, dimension (N)
             On entry, the n diagonal elements of the tridiagonal matrix T. On
             exit, D is overwritten.

     E       (input/output) REAL array, dimension (N)
             On entry, the (n-1) subdiagonal elements of the tridiagonal
             matrix T in elements 1 to N-1 of E; E(N) need not be set.  On
             exit, E is overwritten.

     VL      (input) REAL
             VU      (input) REAL If RANGE='V', the lower and upper bounds of
             the interval to be searched for eigenvalues. VL < VU.  Not
             referenced if RANGE = 'A' or 'I'.

     IL      (input) INTEGER
             IU      (input) INTEGER If RANGE='I', the indices (in ascending
             order) of the smallest and largest eigenvalues to be returned.  1
             <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.  Not
             referenced if RANGE = 'A' or 'V'.

     ABSTOL  (input) REAL
             The absolute error tolerance for the eigenvalues/eigenvectors. IF
             JOBZ = 'V', the eigenvalues and eigenvectors output have residual
             norms bounded by ABSTOL, and the dot products between different
             eigenvectors are bounded by ABSTOL. If ABSTOL is less than
             N*EPS*|T|, then N*EPS*|T| will be used in its place, where EPS is
             the machine precision and |T| is the 1-norm of the tridiagonal
             matrix. The eigenvalues are computed to an accuracy of EPS*|T|
             irrespective of ABSTOL. If high relative accuracy is important,
             set ABSTOL to DLAMCH( 'Safe minimum' ).  See Barlow and Demmel
             "Computing Accurate Eigensystems of Scaled Diagonally Dominant
             Matrices", LAPACK Working Note #7 for a discussion of which
             matrices define their eigenvalues to high relative accuracy.

     M       (output) INTEGER
             The total number of eigenvalues found.  0 <= M <= N.  If RANGE =
             'A', M = N, and if RANGE = 'I', M = IU-IL+1.

     W       (output) REAL array, dimension (N)
             The first M elements contain the selected eigenvalues in
             ascending order.

     Z       (output) COMPLEX array, dimension (LDZ, max(1,M) )
             If JOBZ = 'V', then if INFO = 0, the first M columns of Z contain
             the orthonormal eigenvectors of the matrix T corresponding to the
             selected eigenvalues, with the i-th column of Z holding the
             eigenvector associated with W(i).  If JOBZ = 'N', then Z is not
             referenced.  Note: the user must ensure that at least max(1,M)
             columns are supplied in the array Z; if RANGE = 'V', the exact
             value of M is not known in advance and an upper bound must be
             used.

     LDZ     (input) INTEGER
             The leading dimension of the array Z.  LDZ >= 1, and if JOBZ =
             'V', LDZ >= max(1,N).

     ISUPPZ  (output) INTEGER ARRAY, dimension ( 2*max(1,M) )
             The support of the eigenvectors in Z, i.e., the indices
             indicating the nonzero elements in Z. The i-th eigenvector is
             nonzero only in elements ISUPPZ( 2*i-1 ) through ISUPPZ( 2*i ).

     WORK    (workspace/output) REAL array, dimension (LWORK)
             On exit, if INFO = 0, WORK(1) returns the optimal (and minimal)
             LWORK.

     LWORK   (input) INTEGER
             The dimension of the array WORK.  LWORK >= max(1,18*N)

             If LWORK = -1, then a workspace query is assumed; the routine
             only calculates the optimal size of the WORK array, returns this
             value as the first entry of the WORK array, and no error message
             related to LWORK is issued by XERBLA.
     IWORK   (workspace/output) INTEGER array, dimension (LIWORK)
             On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.

     LIWORK  (input) INTEGER
             The dimension of the array IWORK.  LIWORK >= max(1,10*N)

             If LIWORK = -1, then a workspace query is assumed; the routine
             only calculates the optimal size of the IWORK array, returns this
             value as the first entry of the IWORK array, and no error message
             related to LIWORK is issued by XERBLA.

     INFO    (output) INTEGER
             = 0:  successful exit
             < 0:  if INFO = -i, the i-th argument had an illegal value
             > 0:  if INFO = 1, internal error in SLARRE, if INFO = 2,
             internal error in CLARRV.

FURTHER DETAILS
     Based on contributions by
        Inderjit Dhillon, IBM Almaden, USA
        Osni Marques, LBNL/NERSC, USA
        Ken Stanley, Computer Science Division, University of
          California at Berkeley, USA


SEE ALSO
     INTRO_LAPACK(3S), INTRO_SCSL(3S)

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