F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

# NAG Library Routine DocumentF08GSF (ZHPTRD)

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

## 1  Purpose

F08GSF (ZHPTRD) reduces a complex Hermitian matrix to tridiagonal form, using packed storage.

## 2  Specification

 SUBROUTINE F08GSF ( UPLO, N, AP, D, E, TAU, INFO)
 INTEGER N, INFO REAL (KIND=nag_wp) D(N), E(N-1) COMPLEX (KIND=nag_wp) AP(*), TAU(N-1) CHARACTER(1) UPLO
The routine may be called by its LAPACK name zhptrd.

## 3  Description

F08GSF (ZHPTRD) reduces a complex Hermitian matrix $A$, held in packed storage, to real symmetric tridiagonal form $T$ by a unitary similarity transformation: $A=QT{Q}^{\mathrm{H}}$.
The matrix $Q$ is not formed explicitly but is represented as a product of $n-1$ elementary reflectors (see the F08 Chapter Introduction for details). Routines are provided to work with $Q$ in this representation (see Section 9).

## 4  References

Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

## 5  Arguments

1:     $\mathrm{UPLO}$ – 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 $\text{'L'}$.
2:     $\mathrm{N}$ – INTEGERInput
On entry: $n$, the order of the matrix $A$.
Constraint: ${\mathbf{N}}\ge 0$.
3:     $\mathrm{AP}\left(*\right)$ – COMPLEX (KIND=nag_wp) arrayInput/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 $n$ by $n$ 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 tridiagonal matrix $T$ and details of the unitary matrix $Q$.
4:     $\mathrm{D}\left({\mathbf{N}}\right)$ – REAL (KIND=nag_wp) arrayOutput
On exit: the diagonal elements of the tridiagonal matrix $T$.
5:     $\mathrm{E}\left({\mathbf{N}}-1\right)$ – REAL (KIND=nag_wp) arrayOutput
On exit: the off-diagonal elements of the tridiagonal matrix $T$.
6:     $\mathrm{TAU}\left({\mathbf{N}}-1\right)$ – COMPLEX (KIND=nag_wp) arrayOutput
On exit: further details of the unitary matrix $Q$.
7:     $\mathrm{INFO}$ – INTEGEROutput
On exit: ${\mathbf{INFO}}=0$ unless the routine detects an error (see Section 6).

## 6  Error 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.

## 7  Accuracy

The computed tridiagonal matrix $T$ is exactly similar to a nearby matrix $\left(A+E\right)$, where
 $E2≤ cn ε A2 ,$
$c\left(n\right)$ is a modestly increasing function of $n$, and $\epsilon$ is the machine precision.
The elements of $T$ themselves may be sensitive to small perturbations in $A$ or to rounding errors in the computation, but this does not affect the stability of the eigenvalues and eigenvectors.

## 8  Parallelism and Performance

F08GSF (ZHPTRD) 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 total number of real floating-point operations is approximately $\frac{16}{3}{n}^{3}$.
To form the unitary matrix $Q$ F08GSF (ZHPTRD) may be followed by a call to F08GTF (ZUPGTR):
```CALL ZUPGTR(UPLO,N,AP,TAU,Q,LDQ,WORK,INFO)
```
To apply $Q$ to an $n$ by $p$ complex matrix $C$ F08GSF (ZHPTRD) may be followed by a call to F08GUF (ZUPMTR). For example,
```CALL ZUPMTR('Left',UPLO,'No Transpose',N,P,AP,TAU,C,LDC,WORK, &
INFO)```
forms the matrix product $QC$.
The real analogue of this routine is F08GEF (DSPTRD).

## 10  Example

This example reduces the matrix $A$ to tridiagonal form, where
 $A = -2.28+0.00i 1.78-2.03i 2.26+0.10i -0.12+2.53i 1.78+2.03i -1.12+0.00i 0.01+0.43i -1.07+0.86i 2.26-0.10i 0.01-0.43i -0.37+0.00i 2.31-0.92i -0.12-2.53i -1.07-0.86i 2.31+0.92i -0.73+0.00i ,$
using packed storage.

### 10.1  Program Text

Program Text (f08gsfe.f90)

### 10.2  Program Data

Program Data (f08gsfe.d)

### 10.3  Program Results

Program Results (f08gsfe.r)