NAG Library Routine Document
f08awf (zunglq)
1
Purpose
f08awf (zunglq) generates all or part of the complex unitary matrix
$Q$ from an
$LQ$ factorization computed by
f08avf (zgelqf).
2
Specification
Fortran Interface
Integer, Intent (In)  ::  m, n, k, lda, lwork  Integer, Intent (Out)  ::  info  Complex (Kind=nag_wp), Intent (In)  ::  tau(*)  Complex (Kind=nag_wp), Intent (Inout)  ::  a(lda,*)  Complex (Kind=nag_wp), Intent (Out)  ::  work(max(1,lwork)) 

C Header Interface
#include nagmk26.h
void 
f08awf_ (const Integer *m, const Integer *n, const Integer *k, Complex a[], const Integer *lda, const Complex tau[], Complex work[], const Integer *lwork, Integer *info) 

The routine may be called by its
LAPACK
name zunglq.
3
Description
f08awf (zunglq) is intended to be used after a call to
f08avf (zgelqf), which performs an
$LQ$ factorization of a complex matrix
$A$. The unitary matrix
$Q$ is represented as a product of elementary reflectors.
This routine may be used to generate $Q$ explicitly as a square matrix, or to form only its leading rows.
Usually
$Q$ is determined from the
$LQ$ factorization of a
$p$ by
$n$ matrix
$A$ with
$p\le n$. The whole of
$Q$ may be computed by:
Call zunglq(n,n,p,a,lda,tau,work,lwork,info)
(note that the array
a must have at least
$n$ rows) or its leading
$p$ rows by:
Call zunglq(p,n,p,a,lda,tau,work,lwork,info)
The rows of
$Q$ returned by the last call form an orthonormal basis for the space spanned by the rows of
$A$; thus
f08avf (zgelqf) followed by
f08awf (zunglq) can be used to orthogonalize the rows of
$A$.
The information returned by the
$LQ$ factorization routines also yields the
$LQ$ factorization of the leading
$k$ rows of
$A$, where
$k<p$. The unitary matrix arising from this factorization can be computed by:
Call zunglq(n,n,k,a,lda,tau,work,lwork,info)
or its leading
$k$ rows by:
Call zunglq(k,n,k,a,lda,tau,work,lwork,info)
4
References
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
5
Arguments
 1: $\mathbf{m}$ – IntegerInput

On entry: $m$, the number of rows of the matrix $Q$.
Constraint:
${\mathbf{m}}\ge 0$.
 2: $\mathbf{n}$ – IntegerInput

On entry: $n$, the number of columns of the matrix $Q$.
Constraint:
${\mathbf{n}}\ge {\mathbf{m}}$.
 3: $\mathbf{k}$ – IntegerInput

On entry: $k$, the number of elementary reflectors whose product defines the matrix $Q$.
Constraint:
${\mathbf{m}}\ge {\mathbf{k}}\ge 0$.
 4: $\mathbf{a}\left({\mathbf{lda}},*\right)$ – Complex (Kind=nag_wp) arrayInput/Output

Note: the second dimension of the array
a
must be at least
$\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
On entry: details of the vectors which define the elementary reflectors, as returned by
f08avf (zgelqf).
On exit: the $m$ by $n$ matrix $Q$.
 5: $\mathbf{lda}$ – IntegerInput

On entry: the first dimension of the array
a as declared in the (sub)program from which
f08awf (zunglq) is called.
Constraint:
${\mathbf{lda}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{m}}\right)$.
 6: $\mathbf{tau}\left(*\right)$ – Complex (Kind=nag_wp) arrayInput

Note: the dimension of the array
tau
must be at least
$\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{k}}\right)$.
On entry: further details of the elementary reflectors, as returned by
f08avf (zgelqf).
 7: $\mathbf{work}\left(\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{lwork}}\right)\right)$ – Complex (Kind=nag_wp) arrayWorkspace

On exit: if
${\mathbf{info}}={\mathbf{0}}$, the real part of
${\mathbf{work}}\left(1\right)$ contains the minimum value of
lwork required for optimal performance.
 8: $\mathbf{lwork}$ – IntegerInput

On entry: the dimension of the array
work as declared in the (sub)program from which
f08awf (zunglq) is called.
If
${\mathbf{lwork}}=1$, a workspace query is assumed; the routine only calculates the optimal size of the
work array, returns this value as the first entry of the
work array, and no error message related to
lwork is issued.
Suggested value:
for optimal performance, ${\mathbf{lwork}}\ge {\mathbf{m}}\times \mathit{nb}$, where $\mathit{nb}$ is the optimal block size.
Constraint:
${\mathbf{lwork}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{m}}\right)$ or ${\mathbf{lwork}}=1$.
 9: $\mathbf{info}$ – 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 matrix
$Q$ differs from an exactly unitary matrix by a matrix
$E$ such that
where
$\epsilon $ is the
machine precision.
8
Parallelism and Performance
f08awf (zunglq) 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 implementationspecific information.
The total number of real floatingpoint operations is approximately $16mnk8\left(m+n\right){k}^{2}+\frac{16}{3}{k}^{3}$; when $m=k$, the number is approximately $\frac{8}{3}{m}^{2}\left(3nm\right)$.
The real analogue of this routine is
f08ajf (dorglq).
10
Example
This example forms the leading
$4$ rows of the unitary matrix
$Q$ from the
$LQ$ factorization of the matrix
$A$, where
The rows of
$Q$ form an orthonormal basis for the space spanned by the rows of
$A$.
10.1
Program Text
Program Text (f08awfe.f90)
10.2
Program Data
Program Data (f08awfe.d)
10.3
Program Results
Program Results (f08awfe.r)