NAG Library Function Document

nag_zhetrs (f07msc)

void	nag_zhetrs (Nag_OrderType order, Nag_UploType uplo, Integer n, Integer nrhs, const Complex a[], Integer pda, const Integer ipiv[], Complex b[], Integer pdb, NagError *fail)

3 Description

nag_zhetrs (f07msc) is used to solve a complex Hermitian indefinite system of linear equations

A X = B

, this function must be preceded by a call to nag_zhetrf (f07mrc) which computes the Bunch–Kaufman factorization of

A

uplo = Nag_Upper

A = P U D U^{H} P^{T}

, where

P

is a permutation matrix,

U

is an upper triangular matrix and

D

is an Hermitian block diagonal matrix with

1

1

and

2

2

blocks; the solution

X

is computed by solving

P U D Y = B

and then

U^{H} P^{T} X = Y

uplo = Nag_Lower

A = P L D L^{H} P^{T}

, where

L

is a lower triangular matrix; the solution

X

is computed by solving

P L D Y = B

and then

L^{H} P^{T} 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: order – Nag_OrderTypeInput

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 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.

Constraint:

order = Nag_RowMajor

Nag_ColMajor

2: uplo – Nag_UploTypeInput

On entry: specifies how

A

has been factorized.

$uplo = Nag_Upper$: $A = P U D U^{H} P^{T}$ , where $U$ is upper triangular.
$uplo = Nag_Lower$: $A = P L D L^{H} P^{T}$ , where $L$ is lower triangular.

Constraint:

uplo = Nag_Upper

Nag_Lower

3: n – IntegerInput

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

4: nrhs – IntegerInput

On entry:

r

, the number of right-hand sides.

Constraint:

nrhs \geq 0

5: a[ $\dim$ ] – const ComplexInput

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

\max (1, pda \times n)

On entry: details of the factorization of

A

, as returned by nag_zhetrf (f07mrc).

6: pda – IntegerInput

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

Constraint:

pda \geq \max (1, n)

7: ipiv[ $\dim$ ] – const IntegerInput

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

\max (1, n)

On entry: details of the interchanges and the block structure of

D

, as returned by nag_zhetrf (f07mrc).

8: b[ $\dim$ ] – ComplexInput/Output

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

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

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

r

right-hand side matrix

B

On exit: the

n

r

solution matrix

X

9: pdb – IntegerInput

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

Constraints:

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

10: fail – NagError *Input/Output

The NAG error argument (see Section 3.6 in the Essential Introduction).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
NE_BAD_PARAM: On entry, argument $⟨value⟩$ had an illegal value.
NE_INT: On entry, $n = ⟨value⟩$ .
Constraint: $n \geq 0$ .
On entry, $nrhs = ⟨value⟩$ .
Constraint: $nrhs \geq 0$ .
On entry, $pda = ⟨value⟩$ .
Constraint: $pda > 0$ .
On entry, $pdb = ⟨value⟩$ .
Constraint: $pdb > 0$ .
NE_INT_2: On entry, $pda = ⟨value⟩$ and $n = ⟨value⟩$ .
Constraint: $pda \geq \max (1, n)$ .
On entry, $pdb = ⟨value⟩$ and $n = ⟨value⟩$ .
Constraint: $pdb \geq \max (1, n)$ .
On entry, $pdb = ⟨value⟩$ and $nrhs = ⟨value⟩$ .
Constraint: $pdb \geq \max (1, nrhs)$ .
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.

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 $uplo = Nag_Upper$ , $|E| \leq c (n) ε P |U| |D| |U^{H}| P^{T}$ ;
if $uplo = Nag_Lower$ , $|E| \leq c (n) ε P |L| |D| |L^{H}| P^{T}$ ,

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 nag_zherfs (f07mvc), and an estimate for

κ_{\infty} (A)

(

= κ_{1} (A)

) can be obtained by calling nag_zhecon (f07muc).

8 Parallelism and Performance

nag_zhetrs (f07msc) is not threaded by NAG in any implementation.

nag_zhetrs (f07msc) 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 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 function may be followed by a call to nag_zherfs (f07mvc) to refine the solution and return an error estimate.

The real analogue of this function is nag_dsytrs (f07mec).

10 Example

This example solves the system of equations

A X = B

, where

A = (\begin{array}{r} - 1.36 + 0.00 i & 1.58 + 0.90 i & 2.21 - 0.21 i & 3.91 + 1.50 i \\ 1.58 - 0.90 i & - 8.87 + 0.00 i & - 1.84 - 0.03 i & - 1.78 + 1.18 i \\ 2.21 + 0.21 i & - 1.84 + 0.03 i & - 4.63 + 0.00 i & 0.11 + 0.11 i \\ 3.91 - 1.50 i & - 1.78 - 1.18 i & 0.11 - 0.11 i & - 1.84 + 0.00 i \end{array})

and

B = (\begin{array}{r} 7.79 + 5.48 i & - 35.39 + 18.01 i \\ - 0.77 - 16.05 i & 4.23 - 70.02 i \\ - 9.58 + 3.88 i & - 24.79 - 8.40 i \\ 2.98 - 10.18 i & 28.68 - 39.89 i \end{array}) .

Here

A

is Hermitian indefinite and must first be factorized by nag_zhetrf (f07mrc).

NAG Library Function Documentnag_zhetrs (f07msc)

+− 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 Library Function Document

nag_zhetrs (f07msc)