void	f08qvc (Nag_OrderType order, Nag_TransType trana, Nag_TransType tranb, Nag_SignType sign, Integer m, Integer n, const Complex a[], Integer pda, const Complex b[], Integer pdb, Complex c[], Integer pdc, double scal, NagError fail)

The function may be called by the names: f08qvc, nag_lapackeig_ztrsyl or nag_ztrsyl.

3 Description

f08qvc solves the complex Sylvester matrix equation

op (A) X \pm X op (B) = α C,

where

op (A) = A

A^{H}

, and the matrices

A

and

B

are upper triangular;

α

is a scale factor (

\leq 1

) determined by the function to avoid overflow in

X

;

A

m \times m

and

B

n \times n

while the right-hand side matrix

C

and the solution matrix

X

are both

m \times n

. The matrix

X

is obtained by a straightforward process of back-substitution (see Golub and Van Loan (1996)).

Note that the equation has a unique solution if and only if

α_{i} \pm β_{j} \neq 0

, where

{α_{i}}

and

{β_{j}}

are the eigenvalues of

A

and

B

respectively and the sign (

+

-

) is the same as that used in the equation to be solved.

4 References

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

Higham N J (1992) Perturbation theory and backward error for

A X - X B = C

Numerical Analysis Report University of Manchester

5 Arguments

1: $order$ – Nag_OrderType Input

On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by

order = Nag_RowMajor

. See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.

Constraint:

order = Nag_RowMajor

Nag_ColMajor

2: $trana$ – Nag_TransType Input

On entry: specifies the option

op (A)

$trana = Nag_NoTrans$: $op (A) = A$ .
$trana = Nag_ConjTrans$: $op (A) = A^{H}$ .

Constraint:

trana = Nag_NoTrans

Nag_ConjTrans

3: $tranb$ – Nag_TransType Input

On entry: specifies the option

op (B)

$tranb = Nag_NoTrans$: $op (B) = B$ .
$tranb = Nag_ConjTrans$: $op (B) = B^{H}$ .

Constraint:

tranb = Nag_NoTrans

Nag_ConjTrans

4: $sign$ – Nag_SignType Input

On entry: indicates the form of the Sylvester equation.

$sign = Nag_Plus$: The equation is of the form $op (A) X + X op (B) = α C$ .
$sign = Nag_Minus$: The equation is of the form $op (A) X - X op (B) = α C$ .

Constraint:

sign = Nag_Plus

Nag_Minus

5: $m$ – Integer Input

On entry:

m

, the order of the matrix

A

, and the number of rows in the matrices

X

and

C

Constraint:

m \geq 0

6: $n$ – Integer Input

On entry:

n

, the order of the matrix

B

, and the number of columns in the matrices

X

and

C

Constraint:

n \geq 0

7: $a [\dim]$ – const Complex Input

Note: the dimension, dim, of the array a must be at least

\max (1, pda \times m)

The

(i, j)

th element of the matrix

A

is stored in

$a [(j - 1) \times pda + i - 1]$ when $order = Nag_ColMajor$ ;
$a [(i - 1) \times pda + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the

m \times m

upper triangular matrix

A

8: $pda$ – Integer Input

On entry: the stride separating row or column elements (depending on the value of order) in the array a.

Constraint:

pda \geq \max (1, m)

9: $b [\dim]$ – const Complex Input

Note: the dimension, dim, of the array b must be at least

\max (1, pdb \times n)

The

(i, j)

th element of the matrix

B

is stored in

$b [(j - 1) \times pdb + i - 1]$ when $order = Nag_ColMajor$ ;
$b [(i - 1) \times pdb + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the

n \times n

upper triangular matrix

B

10: $pdb$ – Integer Input

On entry: the stride separating row or column elements (depending on the value of order) in the array b.

Constraint:

pdb \geq \max (1, n)

11: $c [\dim]$ – Complex Input/Output

Note: the dimension, dim, of the array c must be at least

$\max (1, pdc \times n)$ when $order = Nag_ColMajor$ ;
$\max (1, m \times pdc)$ when $order = Nag_RowMajor$ .

The

(i, j)

th element of the matrix

C

is stored in

$c [(j - 1) \times pdc + i - 1]$ when $order = Nag_ColMajor$ ;
$c [(i - 1) \times pdc + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the

m \times n

right-hand side matrix

C

On exit: c is overwritten by the solution matrix

X

12: $pdc$ – Integer Input

On entry: the stride separating row or column elements (depending on the value of order) in the array c.

Constraints:

if $order = Nag_ColMajor$ , $pdc \geq \max (1, m)$ ;
if $order = Nag_RowMajor$ , $pdc \geq \max (1, n)$ .

13: $scal$ – double * Output

On exit: the value of the scale factor

α

14: $fail$ – NagError * Input/Output

The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
NE_INT: On entry, $m = ⟨ value ⟩$ .
Constraint: $m \geq 0$ .

On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .

On entry, $pda = ⟨ value ⟩$ .
Constraint: $pda > 0$ .

On entry, $pdb = ⟨ value ⟩$ .
Constraint: $pdb > 0$ .

On entry, $pdc = ⟨ value ⟩$ .
Constraint: $pdc > 0$ .
NE_INT_2: On entry, $pda = ⟨ value ⟩$ and $m = ⟨ value ⟩$ .
Constraint: $pda \geq \max (1, m)$ .

On entry, $pdb = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $pdb \geq \max (1, n)$ .

On entry, $pdc = ⟨ value ⟩$ and $m = ⟨ value ⟩$ .
Constraint: $pdc \geq \max (1, m)$ .

On entry, $pdc = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $pdc \geq \max (1, n)$ .
NE_INTERNAL_ERROR: An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
NE_PERTURBED: $A$ and $B$ have common or close eigenvalues, perturbed values of which were used to solve the equation.

7 Accuracy

Consider the equation

A X - X B = C

. (To apply the remarks to the equation

A X + X B = C

, simply replace

B

- B

Let

\tilde{X}

be the computed solution and

R

the residual matrix:

R = C - (A \tilde{X} - \tilde{X} B) .

Then the residual is always small:

{‖ R ‖}_{F} = O (ε) ({‖ A ‖}_{F} + {‖ B ‖}_{F}) {‖ \tilde{X} ‖}_{F} .

However,

\tilde{X}

is not necessarily the exact solution of a slightly perturbed equation; in other words, the solution is not backwards stable.

For the forward error, the following bound holds:

{‖ \tilde{X} - X ‖}_{F} \leq \frac{{‖ R ‖}_{F}}{sep (A, B)}

but this may be a considerable over estimate. See Golub and Van Loan (1996) for a definition of

sep (A, B)

, and Higham (1992) for further details.

These remarks also apply to the solution of a general Sylvester equation, as described in Section 9.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

f08qvc 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 function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The total number of real floating-point operations is approximately

4 m n (m + n)

To solve the general complex Sylvester equation

A X \pm X B = C

where

A

and

B

are general matrices,

A

and

B

must first be reduced to Schur form :

A = Q_{1} \tilde{A} Q_{1}^{H} and B = Q_{2} \tilde{B} Q_{2}^{H}

where

\tilde{A}

and

\tilde{B}

are upper triangular and

Q_{1}

and

Q_{2}

are unitary. The original equation may then be transformed to:

\tilde{A} \tilde{X} \pm \tilde{X} \tilde{B} = \tilde{C}

where

\tilde{X} = Q_{1}^{H} X Q_{2}

and

\tilde{C} = Q_{1}^{H} C Q_{2}

\tilde{C}

may be computed by matrix multiplication; f08qvc may be used to solve the transformed equation; and the solution to the original equation can be obtained as

X = Q_{1} \tilde{X} Q_{2}^{H}

The real analogue of this function is f08qhc.

10 Example

This example solves the Sylvester equation

A X + X B = C

, where

A = (\begin{array}{r} - 6.00 - 7.00 i & 0.36 - 0.36 i & - 0.19 + 0.48 i & 0.88 - 0.25 i \\ 0.00 + 0.00 i & - 5.00 + 2.00 i & - 0.03 - 0.72 i & - 0.23 + 0.13 i \\ 0.00 + 0.00 i & 0.00 + 0.00 i & 8.00 - 1.00 i & 0.94 + 0.53 i \\ 0.00 + 0.00 i & 0.00 + 0.00 i & 0.00 + 0.00 i & 3.00 - 4.00 i \end{array}),

B = (\begin{array}{r} 0.50 - 0.20 i & - 0.29 - 0.16 i & - 0.37 + 0.84 i & - 0.55 + 0.73 i \\ 0.00 + 0.00 i & - 0.40 + 0.90 i & 0.06 + 0.22 i & - 0.43 + 0.17 i \\ 0.00 + 0.00 i & 0.00 + 0.00 i & - 0.90 - 0.10 i & - 0.89 - 0.42 i \\ 0.00 + 0.00 i & 0.00 + 0.00 i & 0.00 + 0.00 i & 0.30 - 0.70 i \end{array})

and

C = (\begin{array}{r} 0.63 + 0.35 i & 0.45 - 0.56 i & 0.08 - 0.14 i & - 0.17 - 0.23 i \\ - 0.17 + 0.09 i & - 0.07 - 0.31 i & 0.27 - 0.54 i & 0.35 + 1.21 i \\ - 0.93 - 0.44 i & - 0.33 - 0.35 i & 0.41 - 0.03 i & 0.57 + 0.84 i \\ 0.54 + 0.25 i & - 0.62 - 0.05 i & - 0.52 - 0.13 i & 0.11 - 0.08 i \end{array}) .

f08qv: FL CL CPP AD PY MB

NAG CL Interfacef08qvc (ztrsyl)

▸▿ 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 CL Interface
f08qvc (ztrsyl)