zstegr(3)

NAME

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

SYNOPSIS

SUBROUTINE  ZSTEGR(  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
    DOUBLE         PRECISION ABSTOL, VL, VU
    INTEGER        ISUPPZ( * ), IWORK( * )
    DOUBLE         PRECISION D( * ), E( * ), W( * ), WORK(
* )
    COMPLEX*16     Z( LDZ, * )

PURPOSE

ZSTEGR computes selected eigenvalues and, optionally,
eigenvectors of a real symmetric tridiagonal matrix T. Eigenval
ues 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 sym
metric tridiagonal eigenvalue/eigenvector problem", by Inderjit
Dhillon, Computer Science Division Technical Report No.
UCB/CSD-97-971, UC Berkeley, May 1997.
Note 1 : Currently ZSTEGR is only set up to find ALL the n
eigenvalues and eigenvectors of T in O(n^2) time
Note 2 : Currently the routine ZSTEIN is called when an
appropriate sigma_i cannot be chosen in step (c) above. ZSTEIN
invokes modified Gram-Schmidt when eigenvalues are close.
Note 3 : ZSTEGR works only on machines which follow
ieee-754 floating-point standard in their handling of infinities
and NaNs. Normal execution of ZSTEGR may create NaNs and infini
ties and hence may abort due to a floating point exception in en
vironments 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 eigenval
ues will be found.
N (input) INTEGER
The order of the matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension
(N)
On entry, the n diagonal elements of the tridiago
nal matrix T. On exit, D is overwritten.
E (input/output) DOUBLE PRECISION 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) DOUBLE PRECISION
VU (input) DOUBLE PRECISION If RANGE='V', the
lower and upper bounds of the interval to be searched for eigen
values. 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) DOUBLE PRECISION
The absolute error tolerance for the eigenval
ues/eigenvectors. IF JOBZ = 'V', the eigenvalues and eigenvectors
output have residual norms bounded by ABSTOL, and the dot prod
ucts between different eigenvectors are bounded by ABSTOL. If AB
STOL 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 ac
curacy of EPS*|T| irrespective of ABSTOL. If high relative accu
racy is important, set ABSTOL to DLAMCH( 'Safe minimum' ). See
Barlow and Demmel "Computing Accurate Eigensystems of Scaled Di
agonally Dominant Matrices", LAPACK Working Note #7 for a discus
sion 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) DOUBLE PRECISION array, dimension (N)
The first M elements contain the selected eigen
values in ascending order.
Z (output) COMPLEX*16 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 eigenvec
tor is nonzero only in elements ISUPPZ( 2*i-1 ) through ISUPPZ(
2*i ).
WORK (workspace/output) DOUBLE PRECISION array, dimen
sion (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 (LI
WORK)
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 ille
gal value
> 0: if INFO = 1, internal error in DLARRE, if
INFO = 2, internal error in ZLARRV.

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
LAPACK computational version 3.0 15 June 2000
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