NAG Library Routine Document

f08gpf  (zhpevx)

 Contents

    1  Purpose
    7  Accuracy

1
Purpose

f08gpf (zhpevx) computes selected eigenvalues and, optionally, eigenvectors of a complex n by n Hermitian matrix A in packed storage. Eigenvalues and eigenvectors can be selected by specifying either a range of values or a range of indices for the desired eigenvalues.

2
Specification

Fortran Interface
Subroutine f08gpf ( jobz, range, uplo, n, ap, vl, vu, il, iu, abstol, m, w, z, ldz, work, rwork, iwork, jfail, info)
Integer, Intent (In):: n, il, iu, ldz
Integer, Intent (Inout):: jfail(*)
Integer, Intent (Out):: m, iwork(5*n), info
Real (Kind=nag_wp), Intent (In):: vl, vu, abstol
Real (Kind=nag_wp), Intent (Out):: w(n), rwork(7*n)
Complex (Kind=nag_wp), Intent (Inout):: ap(*), z(ldz,*)
Complex (Kind=nag_wp), Intent (Out):: work(2*n)
Character (1), Intent (In):: jobz, range, uplo
C Header Interface
#include nagmk26.h
void  f08gpf_ ( const char *jobz, const char *range, const char *uplo, const Integer *n, Complex ap[], const double *vl, const double *vu, const Integer *il, const Integer *iu, const double *abstol, Integer *m, double w[], Complex z[], const Integer *ldz, Complex work[], double rwork[], Integer iwork[], Integer jfail[], Integer *info, const Charlen length_jobz, const Charlen length_range, const Charlen length_uplo)
The routine may be called by its LAPACK name zhpevx.

3
Description

The Hermitian matrix A is first reduced to real tridiagonal form, using unitary similarity transformations. The required eigenvalues and eigenvectors are then computed from the tridiagonal matrix; the method used depends upon whether all, or selected, eigenvalues and eigenvectors are required.

4
References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug
Demmel J W and Kahan W (1990) Accurate singular values of bidiagonal matrices SIAM J. Sci. Statist. Comput. 11 873–912
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

5
Arguments

1:     jobz – Character(1)Input
On entry: indicates whether eigenvectors are computed.
jobz='N'
Only eigenvalues are computed.
jobz='V'
Eigenvalues and eigenvectors are computed.
Constraint: jobz='N' or 'V'.
2:     range – Character(1)Input
On entry: if range='A', all eigenvalues will be found.
If range='V', all eigenvalues in the half-open interval vl,vu will be found.
If range='I', the ilth to iuth eigenvalues will be found.
Constraint: range='A', 'V' or 'I'.
3:     uplo – Character(1)Input
On entry: if uplo='U', the upper triangular part of A is stored.
If uplo='L', the lower triangular part of A is stored.
Constraint: uplo='U' or 'L'.
4:     n – IntegerInput
On entry: n, the order of the matrix A.
Constraint: n0.
5:     ap* – Complex (Kind=nag_wp) arrayInput/Output
Note: the dimension of the array ap must be at least max1,n×n+1/2.
On entry: the upper or lower triangle of the n by n Hermitian matrix A, packed by columns.
More precisely,
  • if uplo='U', the upper triangle of A must be stored with element Aij in api+jj-1/2 for ij;
  • if uplo='L', the lower triangle of A must be stored with element Aij in api+2n-jj-1/2 for ij.
On exit: ap is overwritten by the values generated during the reduction to tridiagonal form. The elements of the diagonal and the off-diagonal of the tridiagonal matrix overwrite the corresponding elements of A.
6:     vl – Real (Kind=nag_wp)Input
7:     vu – Real (Kind=nag_wp)Input
On entry: if range='V', the lower and upper bounds of the interval to be searched for eigenvalues.
If range='A' or 'I', vl and vu are not referenced.
Constraint: if range='V', vl<vu.
8:     il – IntegerInput
9:     iu – IntegerInput
On entry: if range='I', the indices (in ascending order) of the smallest and largest eigenvalues to be returned.
If range='A' or 'V', il and iu are not referenced.
Constraints:
  • if range='I' and n=0, il=1 and iu=0;
  • if range='I' and n>0, 1 il iu n .
10:   abstol – Real (Kind=nag_wp)Input
On entry: 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+ε maxa,b ,  
where ε  is the machine precision. If abstol is less than or equal to zero, then ε T1  will be used in its place, where T is the tridiagonal matrix obtained by reducing A to tridiagonal form. Eigenvalues will be computed most accurately when abstol is set to twice the underflow threshold 2 × x02amf   , not zero. If this routine returns with info>0, indicating that some eigenvectors did not converge, try setting abstol to 2 × x02amf   . See Demmel and Kahan (1990).
11:   m – IntegerOutput
On exit: the total number of eigenvalues found. 0mn.
If range='A', m=n.
If range='I', m=iu-il+1.
12:   wn – Real (Kind=nag_wp) arrayOutput
On exit: the selected eigenvalues in ascending order.
13:   zldz* – Complex (Kind=nag_wp) arrayOutput
Note: the second dimension of the array z must be at least max1,m if jobz='V', and at least 1 otherwise.
On exit: 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 ith column of Z holding the eigenvector associated with wi;
  • if an eigenvector fails to converge (info>0), then that column of Z contains the latest approximation to the eigenvector, and the index of the eigenvector is returned in jfail.
If jobz='N', z is not referenced.
Note:  you must ensure that at least max1,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 of at least n must be used.
14:   ldz – IntegerInput
On entry: the first dimension of the array z as declared in the (sub)program from which f08gpf (zhpevx) is called.
Constraints:
  • if jobz='V', ldz max1,n ;
  • otherwise ldz1.
15:   work2×n – Complex (Kind=nag_wp) arrayWorkspace
16:   rwork7×n – Real (Kind=nag_wp) arrayWorkspace
17:   iwork5×n – Integer arrayWorkspace
18:   jfail* – Integer arrayOutput
Note: the dimension of the array jfail must be at least max1,n.
On exit: if jobz='V', then
  • if info=0, the first m elements of jfail are zero;
  • if info>0, jfail contains the indices of the eigenvectors that failed to converge.
If jobz='N', jfail is not referenced.
19:   info – IntegerOutput
On exit: info=0 unless the routine detects an error (see Section 6).

6
Error Indicators and Warnings

info<0
If info=-i, argument i had an illegal value. An explanatory message is output, and execution of the program is terminated.
info>0
The algorithm failed to converge; value eigenvectors did not converge. Their indices are stored in array jfail.

7
Accuracy

The computed eigenvalues and eigenvectors are exact for a nearby matrix A+E, where
E2 = Oε A2 ,  
and ε is the machine precision. See Section 4.7 of Anderson et al. (1999) for further details.

8
Parallelism and Performance

f08gpf (zhpevx) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f08gpf (zhpevx) makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9
Further Comments

The total number of floating-point operations is proportional to n3.
The real analogue of this routine is f08gbf (dspevx).

10
Example

This example finds the eigenvalues in the half-open interval -2,2 , and the corresponding eigenvectors, of the Hermitian matrix
A = 1 2-i 3-i 4-i 2+i 2 3-2i 4-2i 3+i 3+2i 3 4-3i 4+i 4+2i 4+3i 4 .  

10.1
Program Text

Program Text (f08gpfe.f90)

10.2
Program Data

Program Data (f08gpfe.d)

10.3
Program Results

Program Results (f08gpfe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017