Integer, Intent (In)	::	n, nrhs, ldb
Integer, Intent (Out)	::	info
Complex (Kind=nag_wp), Intent (In)	::	ap(*)
Complex (Kind=nag_wp), Intent (Inout)	::	b(ldb,*)
Character (1), Intent (In)	::	uplo

C Header Interface

#include <nag.h>

void	f07gsf_ (const char uplo, const Integer n, const Integer nrhs, const Complex ap[], Complex b[], const Integer ldb, Integer *info, const Charlen length_uplo)

The routine may be called by the names f07gsf, nagf_lapacklin_zpptrs or its LAPACK name zpptrs.

3 Description

f07gsf is used to solve a complex Hermitian positive definite system of linear equations

A X = B

, the routine must be preceded by a call to f07grf which computes the Cholesky factorization of

A

, using packed storage. The solution

X

is computed by forward and backward substitution.

uplo ='U'

A = U^{H} U

, where

U

is upper triangular; the solution

X

is computed by solving

U^{H} Y = B

and then

U X = Y

uplo ='L'

A = L L^{H}

, where

L

is lower triangular; the solution

X

is computed by solving

L Y = B

and then

L^{H} X = Y

4 References

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

5 Arguments

1: $uplo$ – Character(1) Input

On entry: specifies how

A

has been factorized.

$uplo ='U'$: $A = U^{H} U$ , where $U$ is upper triangular.
$uplo ='L'$: $A = L L^{H}$ , where $L$ is lower triangular.

Constraint:

uplo ='U'

'L'

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $nrhs$ – Integer Input

On entry:

r

, the number of right-hand sides.

Constraint:

nrhs \geq 0

4: $ap (*)$ – Complex (Kind=nag_wp) array Input

Note: the dimension of the array ap must be at least

\max (1, n \times (n + 1) / 2)

On entry: the Cholesky factor of

A

stored in packed form, as returned by f07grf.

5: $b (ldb *)$ – Complex (Kind=nag_wp) array Input/Output

Note: the second dimension of the array b must be at least

\max (1, nrhs)

On entry: the

n

r

right-hand side matrix

B

On exit: the

n

r

solution matrix

X

6: $ldb$ – Integer Input

On entry: the first dimension of the array b as declared in the (sub)program from which f07gsf is called.

Constraint:

ldb \geq \max (1, n)

7: $info$ – Integer Output

On exit:

info = 0

unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

$info < 0$: If $info = - i$ , argument $i$ had an illegal value. An explanatory message is output, and execution of the program is terminated.

7 Accuracy

For each right-hand side vector

b

, the computed solution

x

is the exact solution of a perturbed system of equations

(A + E) x = b

, where

if $uplo ='U'$ , $|E| \leq c (n) ε |U^{H}| |U|$ ;
if $uplo ='L'$ , $|E| \leq c (n) ε |L| |L^{H}|$ ,

c (n)

is a modest linear function of

n

, and

ε

is the machine precision.

\hat{x}

is the true solution, then the computed solution

x

satisfies a forward error bound of the form

\frac{{‖x - \hat{x}‖}_{\infty}}{{‖x‖}_{\infty}} \leq c (n) cond (A, x) ε

where

cond (A, x) = {‖|A^{- 1}| |A| |x|‖}_{\infty} / {‖x‖}_{\infty} \leq cond (A) = {‖|A^{- 1}| |A|‖}_{\infty} \leq κ_{\infty} (A)

Note that

cond (A, x)

can be much smaller than

cond (A)

Forward and backward error bounds can be computed by calling f07gvf, and an estimate for

κ_{\infty} (A)

(

= κ_{1} (A)

) can be obtained by calling f07guf.

8 Parallelism and Performance

f07gsf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f07gsf 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.

9 Further Comments

The total number of real floating-point operations is approximately

8 n^{2} r

This routine may be followed by a call to f07gvf to refine the solution and return an error estimate.

The real analogue of this routine is f07gef.

10 Example

This example solves the system of equations

A X = B

, where

A = (\begin{array}{r} 3.23 + 0.00 i & 1.51 - 1.92 i & 1.90 + 0.84 i & 0.42 + 2.50 i \\ 1.51 + 1.92 i & 3.58 + 0.00 i & - 0.23 + 1.11 i & - 1.18 + 1.37 i \\ 1.90 - 0.84 i & - 0.23 - 1.11 i & 4.09 + 0.00 i & 2.33 - 0.14 i \\ 0.42 - 2.50 i & - 1.18 - 1.37 i & 2.33 + 0.14 i & 4.29 + 0.00 i \end{array})

and

B = (\begin{array}{r} 3.93 - 6.14 i & 1.48 + 6.58 i \\ 6.17 + 9.42 i & 4.65 - 4.75 i \\ - 7.17 - 21.83 i & - 4.91 + 2.29 i \\ 1.99 - 14.38 i & 7.64 - 10.79 i \end{array}) .

Here

A

is Hermitian positive definite, stored in packed form, and must first be factorized by f07grf.

f07gs: FL CL CPP AD

NAG FL Interfacef07gsf (zpptrs)

▸▿ 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 FL Interface
f07gsf (zpptrs)