# NAG FL Interfacef08cvf (zgerqf)

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## 1Purpose

f08cvf computes an $RQ$ factorization of a complex $m×n$ matrix $A$.

## 2Specification

Fortran Interface
 Subroutine f08cvf ( m, n, a, lda, tau, work, info)
 Integer, Intent (In) :: m, n, lda, lwork Integer, Intent (Out) :: info Complex (Kind=nag_wp), Intent (Inout) :: a(lda,*), tau(*) Complex (Kind=nag_wp), Intent (Out) :: work(max(1,lwork))
#include <nag.h>
 void f08cvf_ (const Integer *m, const Integer *n, Complex a[], const Integer *lda, Complex tau[], Complex work[], const Integer *lwork, Integer *info)
The routine may be called by the names f08cvf, nagf_lapackeig_zgerqf or its LAPACK name zgerqf.

## 3Description

f08cvf forms the $RQ$ factorization of an arbitrary rectangular real $m×n$ matrix. If $m\le n$, the factorization is given by
 $A = ( 0 R ) Q ,$
where $R$ is an $m×m$ lower triangular matrix and $Q$ is an $n×n$ unitary matrix. If $m>n$ the factorization is given by
 $A =RQ ,$
where $R$ is an $m×n$ upper trapezoidal matrix and $Q$ is again an $n×n$ unitary matrix. In the case where $m the factorization can be expressed as
 $A = ( 0 R ) ( Q1 Q2 ) =RQ2 ,$
where ${Q}_{1}$ consists of the first $\left(n-m\right)$ rows of $Q$ and ${Q}_{2}$ the remaining $m$ rows.
The matrix $Q$ is not formed explicitly, but is represented as a product of $\mathrm{min}\phantom{\rule{0.125em}{0ex}}\left(m,n\right)$ elementary reflectors (see the F08 Chapter Introduction for details). Routines are provided to work with $Q$ in this representation (see Section 9).

## 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: $\mathbf{m}$Integer Input
On entry: $m$, the number of rows of the matrix $A$.
Constraint: ${\mathbf{m}}\ge 0$.
2: $\mathbf{n}$Integer Input
On entry: $n$, the number of columns of the matrix $A$.
Constraint: ${\mathbf{n}}\ge 0$.
3: $\mathbf{a}\left({\mathbf{lda}},*\right)$Complex (Kind=nag_wp) array Input/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: the $m×n$ matrix $A$.
On exit: if $m\le n$, the upper triangle of the subarray ${\mathbf{a}}\left(1:m,n-m+1:n\right)$ contains the $m×m$ upper triangular matrix $R$.
If $m\ge n$, the elements on and above the $\left(m-n\right)$th subdiagonal contain the $m×n$ upper trapezoidal matrix $R$; the remaining elements, with the array tau, represent the unitary matrix $Q$ as a product of $\mathrm{min}\phantom{\rule{0.125em}{0ex}}\left(m,n\right)$ elementary reflectors (see Section 3.3.6 in the F08 Chapter Introduction).
4: $\mathbf{lda}$Integer Input
On entry: the first dimension of the array a as declared in the (sub)program from which f08cvf is called.
Constraint: ${\mathbf{lda}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{m}}\right)$.
5: $\mathbf{tau}\left(*\right)$Complex (Kind=nag_wp) array Output
Note: the dimension of the array tau must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,\mathrm{min}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{m}},{\mathbf{n}}\right)\right)$.
On exit: the scalar factors of the elementary reflectors.
6: $\mathbf{work}\left(\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{lwork}}\right)\right)$Complex (Kind=nag_wp) array Workspace
On exit: if ${\mathbf{info}}={\mathbf{0}}$, the real part of ${\mathbf{work}}\left(1\right)$ contains the minimum value of lwork required for optimal performance.
7: $\mathbf{lwork}$Integer Input
On entry: the dimension of the array work as declared in the (sub)program from which f08cvf 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, ${\mathbf{lwork}}\ge {\mathbf{m}}×\mathit{nb}$, 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 ${\mathbf{lwork}}=-1$.
8: $\mathbf{info}$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.

## 7Accuracy

The computed factorization is the exact factorization of a nearby matrix $A+E$, where
 $‖E‖2 = O⁡ε ‖A‖2$
and $\epsilon$ is the machine precision.

## 8Parallelism and Performance

f08cvf 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 floating-point operations is approximately $\frac{2}{3}{m}^{2}\left(3n-m\right)$ if $m\le n$, or $\frac{2}{3}{n}^{2}\left(3m-n\right)$ if $m>n$.
To form the unitary matrix $Q$ f08cvf may be followed by a call to f08cwf :
`Call zungrq(n,n,min(m,n),a,lda,tau,work,lwork,info)`
but note that the first dimension of the array a must be at least n, which may be larger than was required by f08cvf. When $m\le n$, it is often only the first $m$ rows of $Q$ that are required and they may be formed by the call:
`Call zungrq(m,n,m,a,lda,tau,work,lwork,info)`
To apply $Q$ to an arbitrary $n×p$ real rectangular matrix $C$, f08cvf may be followed by a call to f08cxf . For example:
```Call zunmrq('Left','C',n,p,min(m,n),a,lda,tau,c,ldc, &
work,lwork,info)```
forms the matrix product $C={Q}^{\mathrm{H}}C$.
The real analogue of this routine is f08chf.

## 10Example

This example finds the minimum norm solution to the underdetermined equations
 $Ax=b$
where
 $A = ( 0.28-0.36i 0.50-0.86i -0.77-0.48i 1.58+0.66i -0.50-1.10i -1.21+0.76i -0.32-0.24i -0.27-1.15i 0.36-0.51i -0.07+1.33i -0.75+0.47i -0.08+1.01i )$
and
 $b = ( -1.35+0.19i 9.41-3.56i -7.57+6.93i ) .$
The solution is obtained by first obtaining an $RQ$ factorization of the matrix $A$.
Note that the block size (NB) of $64$ assumed in this example is not realistic for such a small problem, but should be suitable for large problems.

### 10.1Program Text

Program Text (f08cvfe.f90)

### 10.2Program Data

Program Data (f08cvfe.d)

### 10.3Program Results

Program Results (f08cvfe.r)