Integer, Intent (In)	::	n, ldz
Integer, Intent (Out)	::	info
Real (Kind=nag_wp), Intent (Out)	::	w(n), rwork(3*n-2)
Complex (Kind=nag_wp), Intent (Inout)	::	ap(), z(ldz,)
Complex (Kind=nag_wp), Intent (Out)	::	work(2*n-1)
Character (1), Intent (In)	::	jobz, uplo

C Header Interface

#include <nag.h>

void	f08gnf_ (const char jobz, const char uplo, const Integer n, Complex ap[], double w[], Complex z[], const Integer ldz, Complex work[], double rwork[], Integer *info, const Charlen length_jobz, const Charlen length_uplo)

The routine may be called by the names f08gnf, nagf_lapackeig_zhpev or its LAPACK name zhpev.

3 Description

The Hermitian matrix

A

is first reduced to real tridiagonal form, using unitary similarity transformations, and then the

Q R

algorithm is applied to the tridiagonal matrix to compute the eigenvalues and (optionally) the eigenvectors.

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 https://www.netlib.org/lapack/lug

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'

'V'

2: $uplo$ – Character(1) Input

On entry: if

uplo ='U'

, the upper triangular part of

A

is stored.

uplo ='L'

, the lower triangular part of

A

is stored.

Constraint:

uplo ='U'

'L'

3: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

4: $ap (*)$ – Complex (Kind=nag_wp) array Input/Output

Note: the dimension of the array ap must be at least

\max (1, n \times (n + 1) / 2)

On entry: the upper or lower triangle of the

n

n

Hermitian matrix

A

, packed by columns.

More precisely,

if $uplo ='U'$ , the upper triangle of $A$ must be stored with element $A_{i j}$ in $ap (i + j (j - 1) / 2)$ for $i \leq j$ ;
if $uplo ='L'$ , the lower triangle of $A$ must be stored with element $A_{i j}$ in $ap (i + (2 n - j) (j - 1) / 2)$ for $i \geq j$ .

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

5: $w (n)$ – Real (Kind=nag_wp) array Output

On exit: the eigenvalues in ascending order.

6: $z (ldz *)$ – Complex (Kind=nag_wp) array Output

Note: the second dimension of the array z must be at least

\max (1, n)

jobz ='V'

, and at least

1

otherwise.

On exit: if

jobz ='V'

, z contains the orthonormal eigenvectors of the matrix

A

, with the

i

th column of

Z

holding the eigenvector associated with

w (i)

jobz ='N'

, z is not referenced.

7: $ldz$ – Integer Input

On entry: the first dimension of the array z as declared in the (sub)program from which f08gnf is called.

Constraints:

if $jobz ='V'$ , $ldz \geq \max (1, n)$ ;
otherwise $ldz \geq 1$ .

8: $work (2 \times n - 1)$ – Complex (Kind=nag_wp) array Workspace

9: $rwork (3 \times n - 2)$ – Real (Kind=nag_wp) array Workspace

10: $info$ – Integer Output

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; $〈value〉$ off-diagonal elements of an intermediate tridiagonal form did not converge to zero.

7 Accuracy

The computed eigenvalues and eigenvectors are exact for a nearby matrix

(A + E)

, where

{‖E‖}_{2} = O (ε) {‖A‖}_{2},

and

ε

is the machine precision. See Section 4.7 of Anderson et al. (1999) for further details.

8 Parallelism and Performance

f08gnf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f08gnf 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

Each eigenvector is normalized so that the element of largest absolute value is real.

The total number of floating-point operations is proportional to

n^{3}

The real analogue of this routine is f08gaf.

10 Example

This example finds all the eigenvalues of the Hermitian matrix

A = (\begin{array}{l} 1 & 2 - i & 3 - i & 4 - i \\ 2 + i & 2 & 3 - 2 i & 4 - 2 i \\ 3 + i & 3 + 2 i & 3 & 4 - 3 i \\ 4 + i & 4 + 2 i & 4 + 3 i & 4 \end{array}),

together with approximate error bounds for the computed eigenvalues.

Interfaces: FL CL AD

NAG FL Interface Introduction

F08 (Lapackeig) Chapter Contents

F08 (Lapackeig) Chapter Introduction

f08gn: FL CL AD

NAG FL Interfacef08gnf (zhpev)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
f08gnf (zhpev)