# NAG FL Interfacef08gqf (zhpevd)

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## 1Purpose

f08gqf computes all the eigenvalues and, optionally, all the eigenvectors of a complex Hermitian matrix held in packed storage. If the eigenvectors are requested, then it uses a divide-and-conquer algorithm to compute eigenvalues and eigenvectors. However, if only eigenvalues are required, then it uses the Pal–Walker–Kahan variant of the $QL$ or $QR$ algorithm.

## 2Specification

Fortran Interface
 Subroutine f08gqf ( job, uplo, n, ap, w, z, ldz, work, info)
 Integer, Intent (In) :: n, ldz, lwork, lrwork, liwork Integer, Intent (Out) :: iwork(max(1,liwork)), info Real (Kind=nag_wp), Intent (Inout) :: w(*) Real (Kind=nag_wp), Intent (Out) :: rwork(max(1,lrwork)) Complex (Kind=nag_wp), Intent (Inout) :: ap(*), z(ldz,*) Complex (Kind=nag_wp), Intent (Out) :: work(max(1,lwork)) Character (1), Intent (In) :: job, uplo
#include <nag.h>
 void f08gqf_ (const char *job, const char *uplo, const Integer *n, Complex ap[], double w[], Complex z[], const Integer *ldz, Complex work[], const Integer *lwork, double rwork[], const Integer *lrwork, Integer iwork[], const Integer *liwork, Integer *info, const Charlen length_job, const Charlen length_uplo)
The routine may be called by the names f08gqf, nagf_lapackeig_zhpevd or its LAPACK name zhpevd.

## 3Description

f08gqf computes all the eigenvalues and, optionally, all the eigenvectors of a complex Hermitian matrix $A$ (held in packed storage). In other words, it can compute the spectral factorization of $A$ as
 $A=ZΛZH,$
where $\Lambda$ is a real diagonal matrix whose diagonal elements are the eigenvalues ${\lambda }_{i}$, and $Z$ is the (complex) unitary matrix whose columns are the eigenvectors ${z}_{i}$. Thus
 $Azi=λizi, i=1,2,…,n.$

## 4References

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

## 5Arguments

1: $\mathbf{job}$Character(1) Input
On entry: indicates whether eigenvectors are computed.
${\mathbf{job}}=\text{'N'}$
Only eigenvalues are computed.
${\mathbf{job}}=\text{'V'}$
Eigenvalues and eigenvectors are computed.
Constraint: ${\mathbf{job}}=\text{'N'}$ or $\text{'V'}$.
2: $\mathbf{uplo}$Character(1) Input
On entry: indicates whether the upper or lower triangular part of $A$ is stored.
${\mathbf{uplo}}=\text{'U'}$
The upper triangular part of $A$ is stored.
${\mathbf{uplo}}=\text{'L'}$
The lower triangular part of $A$ is stored.
Constraint: ${\mathbf{uplo}}=\text{'U'}$ or $\text{'L'}$.
3: $\mathbf{n}$Integer Input
On entry: $n$, the order of the matrix $A$.
Constraint: ${\mathbf{n}}\ge 0$.
4: $\mathbf{ap}\left(*\right)$Complex (Kind=nag_wp) array Input/Output
Note: the dimension of the array ap must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}×\left({\mathbf{n}}+1\right)/2\right)$.
On entry: the upper or lower triangle of the $n×n$ Hermitian matrix $A$, packed by columns.
More precisely,
• if ${\mathbf{uplo}}=\text{'U'}$, the upper triangle of $A$ must be stored with element ${A}_{ij}$ in ${\mathbf{ap}}\left(i+j\left(j-1\right)/2\right)$ for $i\le j$;
• if ${\mathbf{uplo}}=\text{'L'}$, the lower triangle of $A$ must be stored with element ${A}_{ij}$ in ${\mathbf{ap}}\left(i+\left(2n-j\right)\left(j-1\right)/2\right)$ for $i\ge j$.
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: $\mathbf{w}\left(*\right)$Real (Kind=nag_wp) array Output
Note: the dimension of the array w must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
On exit: the eigenvalues of the matrix $A$ in ascending order.
6: $\mathbf{z}\left({\mathbf{ldz}},*\right)$Complex (Kind=nag_wp) array Output
Note: the second dimension of the array z must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$ if ${\mathbf{job}}=\text{'V'}$ and at least $1$ if ${\mathbf{job}}=\text{'N'}$.
On exit: if ${\mathbf{job}}=\text{'V'}$, z is overwritten by the unitary matrix $Z$ which contains the eigenvectors of $A$.
If ${\mathbf{job}}=\text{'N'}$, z is not referenced.
7: $\mathbf{ldz}$Integer Input
On entry: the first dimension of the array z as declared in the (sub)program from which f08gqf is called.
Constraints:
• if ${\mathbf{job}}=\text{'V'}$, ${\mathbf{ldz}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
• if ${\mathbf{job}}=\text{'N'}$, ${\mathbf{ldz}}\ge 1$.
8: $\mathbf{work}\left(\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{lwork}}\right)\right)$Complex (Kind=nag_wp) array Workspace
On exit: if ${\mathbf{info}}={\mathbf{0}}$, ${\mathbf{work}}\left(1\right)$ contains the required minimal size of lwork.
9: $\mathbf{lwork}$Integer Input
On entry: the dimension of the array work as declared in the (sub)program from which f08gqf is called.
If ${\mathbf{lwork}}=-1$, a workspace query is assumed; the routine only calculates the minimum dimension of the work array, returns this value as the first entry of the work array, and no error message related to lwork is issued.
Constraints:
• if ${\mathbf{n}}\le 1$, ${\mathbf{lwork}}\ge 1$ or ${\mathbf{lwork}}=-1$;
• if ${\mathbf{job}}=\text{'N'}$ and ${\mathbf{n}}>1$, ${\mathbf{lwork}}\ge {\mathbf{n}}$ or ${\mathbf{lwork}}=-1$;
• if ${\mathbf{job}}=\text{'V'}$ and ${\mathbf{n}}>1$, ${\mathbf{lwork}}\ge 2×{\mathbf{n}}$ or ${\mathbf{lwork}}=-1$.
10: $\mathbf{rwork}\left(\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{lrwork}}\right)\right)$Real (Kind=nag_wp) array Workspace
On exit: if ${\mathbf{info}}={\mathbf{0}}$, ${\mathbf{rwork}}\left(1\right)$ contains the required minimal size of ${\mathbf{lrwork}}$.
11: $\mathbf{lrwork}$Integer Input
On entry: the dimension of the array rwork as declared in the (sub)program from which f08gqf is called.
If ${\mathbf{lrwork}}=-1$, a workspace query is assumed; the routine only calculates the minimum dimension of the rwork array, returns this value as the first entry of the rwork array, and no error message related to lrwork is issued.
Constraints:
• if ${\mathbf{n}}\le 1$, ${\mathbf{lrwork}}\ge 1$ or ${\mathbf{lrwork}}=-1$;
• if ${\mathbf{job}}=\text{'N'}$ and ${\mathbf{n}}>1$, ${\mathbf{lrwork}}\ge {\mathbf{n}}$ or ${\mathbf{lrwork}}=-1$;
• if ${\mathbf{job}}=\text{'V'}$ and ${\mathbf{n}}>1$, ${\mathbf{lrwork}}\ge 2×{{\mathbf{n}}}^{2}+5×{\mathbf{n}}+1$ or ${\mathbf{lrwork}}=-1$.
12: $\mathbf{iwork}\left(\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{liwork}}\right)\right)$Integer array Workspace
On exit: if ${\mathbf{info}}={\mathbf{0}}$, ${\mathbf{iwork}}\left(1\right)$ contains the required minimal size of liwork.
13: $\mathbf{liwork}$Integer Input
On entry: the dimension of the array iwork as declared in the (sub)program from which f08gqf is called.
If ${\mathbf{liwork}}=-1$, a workspace query is assumed; the routine only calculates the minimum dimension of the iwork array, returns this value as the first entry of the iwork array, and no error message related to liwork is issued.
Constraints:
• if ${\mathbf{job}}=\text{'N'}$ or ${\mathbf{n}}\le 1$, ${\mathbf{liwork}}\ge 1$ or ${\mathbf{liwork}}=-1$;
• if ${\mathbf{job}}=\text{'V'}$ and ${\mathbf{n}}>1$, ${\mathbf{liwork}}\ge 5×{\mathbf{n}}+3$ or ${\mathbf{liwork}}=-1$.
14: $\mathbf{info}$Integer Output
On exit: ${\mathbf{info}}=0$ unless the routine detects an error (see Section 6).

## 6Error Indicators and Warnings

${\mathbf{info}}<0$
If ${\mathbf{info}}=-i$, argument $i$ had an illegal value. An explanatory message is output, and execution of the program is terminated.
${\mathbf{info}}>0$
If ${\mathbf{info}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{job}}=\text{'N'}$, the algorithm failed to converge; $⟨\mathit{\text{value}}⟩$ elements of an intermediate tridiagonal form did not converge to zero; if ${\mathbf{info}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{job}}=\text{'V'}$, then the algorithm failed to compute an eigenvalue while working on the submatrix lying in rows and column $⟨\mathit{\text{value}}⟩/\left({\mathbf{n}}+1\right)$ through .

## 7Accuracy

The computed eigenvalues and eigenvectors are exact for a nearby matrix $\left(A+E\right)$, where
 $‖E‖2 = O(ε) ‖A‖2 ,$
and $\epsilon$ is the machine precision. See Section 4.7 of Anderson et al. (1999) for further details.

## 8Parallelism and Performance

f08gqf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f08gqf 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.

The real analogue of this routine is f08gcf.

## 10Example

This example computes all the eigenvalues and eigenvectors of the Hermitian matrix $A$, where
 $A = ( 1.0+0.0i 2.0-1.0i 3.0-1.0i 4.0-1.0i 2.0+1.0i 2.0+0.0i 3.0-2.0i 4.0-2.0i 3.0+1.0i 3.0+2.0i 3.0+0.0i 4.0-3.0i 4.0+1.0i 4.0+2.0i 4.0+3.0i 4.0+0.0i ) .$

### 10.1Program Text

Program Text (f08gqfe.f90)

### 10.2Program Data

Program Data (f08gqfe.d)

### 10.3Program Results

Program Results (f08gqfe.r)