LAPACK 3.12.0
LAPACK: Linear Algebra PACKage
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◆ zheevr()

subroutine zheevr ( character jobz,
character range,
character uplo,
integer n,
complex*16, dimension( lda, * ) a,
integer lda,
double precision vl,
double precision vu,
integer il,
integer iu,
double precision abstol,
integer m,
double precision, dimension( * ) w,
complex*16, dimension( ldz, * ) z,
integer ldz,
integer, dimension( * ) isuppz,
complex*16, dimension( * ) work,
integer lwork,
double precision, dimension( * ) rwork,
integer lrwork,
integer, dimension( * ) iwork,
integer liwork,
integer info )

ZHEEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for HE matrices

Download ZHEEVR + dependencies [TGZ] [ZIP] [TXT]

Purpose:
!>
!> ZHEEVR computes selected eigenvalues and, optionally, eigenvectors
!> of a complex Hermitian matrix A. Eigenvalues and eigenvectors can be
!> selected by specifying either a range of values or a range of indices
!> for the desired eigenvalues. Invocations with different choices for
!> these parameters may result in the computation of slightly different
!> eigenvalues and/or eigenvectors for the same matrix. The reason for
!> this behavior is that there exists a variety of algorithms (each
!> performing best for a particular set of options) with ZHEEVR
!> attempting to select the best based on the various parameters. In all
!> cases, the computed values are accurate within the limits of finite
!> precision arithmetic.
!>
!> ZHEEVR first reduces the matrix A to tridiagonal form T with a call
!> to ZHETRD.  Then, whenever possible, ZHEEVR calls ZSTEMR to compute
!> eigenspectrum using Relatively Robust Representations.  ZSTEMR
!> computes eigenvalues by the dqds algorithm, while orthogonal
!> eigenvectors are computed from various  L D L^T representations
!> (also known as Relatively Robust Representations). Gram-Schmidt
!> orthogonalization is avoided as far as possible. More specifically,
!> the various steps of the algorithm are as follows.
!>
!> For each unreduced block (submatrix) of T,
!>    (a) Compute T - sigma I  = L D L^T, so that L and D
!>        define all the wanted eigenvalues to high relative accuracy.
!>        This means that small relative changes in the entries of D and L
!>        cause only small relative changes in the eigenvalues and
!>        eigenvectors. The standard (unfactored) representation of the
!>        tridiagonal matrix T does not have this property in general.
!>    (b) Compute the eigenvalues to suitable accuracy.
!>        If the eigenvectors are desired, the algorithm attains full
!>        accuracy of the computed eigenvalues only right before
!>        the corresponding vectors have to be computed, see steps c) and d).
!>    (c) For each cluster of close eigenvalues, select a new
!>        shift close to the cluster, find a new factorization, and refine
!>        the shifted eigenvalues to suitable accuracy.
!>    (d) For each eigenvalue with a large enough relative separation compute
!>        the corresponding eigenvector by forming a rank revealing twisted
!>        factorization. Go back to (c) for any clusters that remain.
!>
!> The desired accuracy of the output can be specified by the input
!> parameter ABSTOL.
!>
!> For more details, see ZSTEMR's documentation and:
!> - Inderjit S. Dhillon and Beresford N. Parlett: 
!>   Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004.
!> - Inderjit Dhillon and Beresford Parlett:  SIAM Journal on Matrix Analysis and Applications, Vol. 25,
!>   2004.  Also LAPACK Working Note 154.
!> - Inderjit Dhillon: ,
!>   Computer Science Division Technical Report No. UCB/CSD-97-971,
!>   UC Berkeley, May 1997.
!>
!>
!> Note 1 : ZHEEVR calls ZSTEMR when the full spectrum is requested
!> on machines which conform to the ieee-754 floating point standard.
!> ZHEEVR calls DSTEBZ and ZSTEIN on non-ieee machines and
!> when partial spectrum requests are made.
!>
!> Normal execution of ZSTEMR may create NaNs and infinities and
!> hence may abort due to a floating point exception in environments
!> which do not handle NaNs and infinities in the ieee standard default
!> manner.
!>
Parameters
[in]JOBZ
!>          JOBZ is CHARACTER*1
!>          = 'N':  Compute eigenvalues only;
!>          = 'V':  Compute eigenvalues and eigenvectors.
!>
!>          This parameter influences the choice of the algorithm and
!>          may alter the computed values.
!>
[in]RANGE
!>          RANGE is 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.
!>          For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and
!>          ZSTEIN are called
!>
!>          This parameter influences the choice of the algorithm and
!>          may alter the computed values.
!>
[in]UPLO
!>          UPLO is CHARACTER*1
!>          = 'U':  Upper triangle of A is stored;
!>          = 'L':  Lower triangle of A is stored.
!>
[in]N
!>          N is INTEGER
!>          The order of the matrix A.  N >= 0.
!>
[in,out]A
!>          A is COMPLEX*16 array, dimension (LDA, N)
!>          On entry, the Hermitian matrix A.  If UPLO = 'U', the
!>          leading N-by-N upper triangular part of A contains the
!>          upper triangular part of the matrix A.  If UPLO = 'L',
!>          the leading N-by-N lower triangular part of A contains
!>          the lower triangular part of the matrix A.
!>          On exit, the lower triangle (if UPLO='L') or the upper
!>          triangle (if UPLO='U') of A, including the diagonal, is
!>          destroyed.
!>
[in]LDA
!>          LDA is INTEGER
!>          The leading dimension of the array A.  LDA >= max(1,N).
!>
[in]VL
!>          VL is DOUBLE PRECISION
!>          If RANGE='V', the lower bound of the interval to
!>          be searched for eigenvalues. VL < VU.
!>          Not referenced if RANGE = 'A' or 'I'.
!>
[in]VU
!>          VU is DOUBLE PRECISION
!>          If RANGE='V', the upper bound of the interval to
!>          be searched for eigenvalues. VL < VU.
!>          Not referenced if RANGE = 'A' or 'I'.
!>
[in]IL
!>          IL is INTEGER
!>          If RANGE='I', the index of the
!>          smallest eigenvalue 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'.
!>
[in]IU
!>          IU is INTEGER
!>          If RANGE='I', the index of the
!>          largest eigenvalue 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'.
!>
[in]ABSTOL
!>          ABSTOL is DOUBLE PRECISION
!>          The absolute error tolerance for the eigenvalues.
!>          An approximate eigenvalue is accepted as converged
!>          when it is determined to lie in an interval [a,b]
!>          of width less than or equal to
!>
!>                  ABSTOL + EPS *   max( |a|,|b| ) ,
!>
!>          where EPS is the machine precision.  If ABSTOL is less than
!>          or equal to zero, then  EPS*|T|  will be used in its place,
!>          where |T| is the 1-norm of the tridiagonal matrix obtained
!>          by reducing A to tridiagonal form.
!>
!>          See  by Demmel and
!>          Kahan, LAPACK Working Note #3.
!>
!>          If high relative accuracy is important, set ABSTOL to
!>          DLAMCH( 'Safe minimum' ).  Doing so will guarantee that
!>          eigenvalues are computed to high relative accuracy when
!>          possible in future releases.  The current code does not
!>          make any guarantees about high relative accuracy, but
!>          future releases will. See J. Barlow and J. Demmel,
!>          , LAPACK Working Note #7, for a discussion
!>          of which matrices define their eigenvalues to high relative
!>          accuracy.
!>
[out]M
!>          M is INTEGER
!>          The total number of eigenvalues found.  0 <= M <= N.
!>          If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
!>
[out]W
!>          W is DOUBLE PRECISION array, dimension (N)
!>          The first M elements contain the selected eigenvalues in
!>          ascending order.
!>
[out]Z
!>          Z is 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 A
!>          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.
!>          Supplying N columns is always safe.
!>
[in]LDZ
!>          LDZ is INTEGER
!>          The leading dimension of the array Z.  LDZ >= 1, and if
!>          JOBZ = 'V', LDZ >= max(1,N).
!>
[out]ISUPPZ
!>          ISUPPZ is 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 ). This is an output of ZSTEMR (tridiagonal
!>          matrix). The support of the eigenvectors of A is typically
!>          1:N because of the unitary transformations applied by ZUNMTR.
!>          Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1
!>
[out]WORK
!>          WORK is COMPLEX*16 array, dimension (MAX(1,LWORK))
!>          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
!>
[in]LWORK
!>          LWORK is INTEGER
!>          The length of the array WORK.
!>          If N <= 1, LWORK >= 1, else LWORK >= 2*N.
!>          For optimal efficiency, LWORK >= (NB+1)*N,
!>          where NB is the max of the blocksize for ZHETRD and for
!>          ZUNMTR as returned by ILAENV.
!>
!>          If LWORK = -1, then a workspace query is assumed; the routine
!>          only calculates the optimal sizes of the WORK, RWORK and
!>          IWORK arrays, returns these values as the first entries of
!>          the WORK, RWORK and IWORK arrays, and no error message
!>          related to LWORK or LRWORK or LIWORK is issued by XERBLA.
!>
[out]RWORK
!>          RWORK is DOUBLE PRECISION array, dimension (MAX(1,LRWORK))
!>          On exit, if INFO = 0, RWORK(1) returns the optimal
!>          (and minimal) LRWORK.
!>
[in]LRWORK
!>          LRWORK is INTEGER
!>          The length of the array RWORK.
!>          If N <= 1, LRWORK >= 1, else LRWORK >= 24*N.
!>
!>          If LRWORK = -1, then a workspace query is assumed; the
!>          routine only calculates the optimal sizes of the WORK, RWORK
!>          and IWORK arrays, returns these values as the first entries
!>          of the WORK, RWORK and IWORK arrays, and no error message
!>          related to LWORK or LRWORK or LIWORK is issued by XERBLA.
!>
[out]IWORK
!>          IWORK is INTEGER array, dimension (MAX(1,LIWORK))
!>          On exit, if INFO = 0, IWORK(1) returns the optimal
!>          (and minimal) LIWORK.
!>
[in]LIWORK
!>          LIWORK is INTEGER
!>          The dimension of the array IWORK.
!>          If N <= 1, LIWORK >= 1, else LIWORK >= 10*N.
!>
!>          If LIWORK = -1, then a workspace query is assumed; the
!>          routine only calculates the optimal sizes of the WORK, RWORK
!>          and IWORK arrays, returns these values as the first entries
!>          of the WORK, RWORK and IWORK arrays, and no error message
!>          related to LWORK or LRWORK or LIWORK is issued by XERBLA.
!>
[out]INFO
!>          INFO is INTEGER
!>          = 0:  successful exit
!>          < 0:  if INFO = -i, the i-th argument had an illegal value
!>          > 0:  Internal error
!>
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Contributors:
Inderjit Dhillon, IBM Almaden, USA
Osni Marques, LBNL/NERSC, USA
Ken Stanley, Computer Science Division, University of California at Berkeley, USA
Jason Riedy, Computer Science Division, University of California at Berkeley, USA