Integer, Intent (In)	::	n, kl, ku, nrhs, ldab, ipiv(*), ldb
Integer, Intent (Out)	::	info
Complex (Kind=nag_wp), Intent (In)	::	ab(ldab,*)
Complex (Kind=nag_wp), Intent (Inout)	::	b(ldb,*)
Character (1), Intent (In)	::	trans

C Header Interface

#include nagmk26.h

void	f07bsf_ ( const char trans, const Integer n, const Integer kl, const Integer ku, const Integer nrhs, const Complex ab[], const Integer ldab, const Integer ipiv[], Complex b[], const Integer ldb, Integer info, const Charlen length_trans)

The routine may be called by its LAPACK name zgbtrs.

3

Description

f07bsf (zgbtrs) is used to solve a complex band system of linear equations

A X = B

A^{T} X = B

A^{H} X = B

, the routine must be preceded by a call to f07brf (zgbtrf) which computes the

L U

factorization of

A

A = P L U

. The solution is computed by forward and backward substitution.

trans ='N'

, the solution is computed by solving

P L Y = B

and then

U X = Y

trans ='T'

, the solution is computed by solving

U^{T} Y = B

and then

L^{T} P^{T} X = Y

trans ='C'

, the solution is computed by solving

U^{H} 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: $trans$ – Character(1)Input

On entry: indicates the form of the equations.

$trans ='N'$: $A X = B$ is solved for $X$ .
$trans ='T'$: $A^{T} X = B$ is solved for $X$ .
$trans ='C'$: $A^{H} X = B$ is solved for $X$ .

Constraint:

trans ='N'

'T'

'C'

2: $n$ – IntegerInput

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $kl$ – IntegerInput

On entry:

k_{l}

, the number of subdiagonals within the band of the matrix

A

Constraint:

kl \geq 0

4: $ku$ – IntegerInput

On entry:

k_{u}

, the number of superdiagonals within the band of the matrix

A

Constraint:

ku \geq 0

5: $nrhs$ – IntegerInput

On entry:

r

, the number of right-hand sides.

Constraint:

nrhs \geq 0

6: $ab (ldab *)$ – Complex (Kind=nag_wp) arrayInput

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

\max (1, n)

On entry: the

L U

factorization of

A

, as returned by f07brf (zgbtrf).

7: $ldab$ – IntegerInput

On entry: the first dimension of the array ab as declared in the (sub)program from which f07bsf (zgbtrs) is called.

Constraint:

ldab \geq 2 \times kl + ku + 1

8: $ipiv (*)$ – Integer arrayInput

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

\max (1, n)

On entry: the pivot indices, as returned by f07brf (zgbtrf).

9: $b (ldb *)$ – Complex (Kind=nag_wp) arrayInput/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

10: $ldb$ – IntegerInput

On entry: the first dimension of the array b as declared in the (sub)program from which f07bsf (zgbtrs) is called.

Constraint:

ldb \geq \max (1, n)

11: $info$ – IntegerOutput

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

|E| \leq c (k) ε |L| |U|,

c (k)

is a modest linear function of

k = k_{l} + k_{u} + 1

, and

ε

is the machine precision. This assumes

k ≪ n

\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 (k) 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)

, and

cond (A^{H})

(which is the same as

cond (A^{T})

) can be much larger (or smaller) than

cond (A)

Forward and backward error bounds can be computed by calling f07bvf (zgbrfs), and an estimate for

κ_{\infty} (A)

can be obtained by calling f07buf (zgbcon) with

norm ='I'

8

Parallelism and Performance

f07bsf (zgbtrs) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f07bsf (zgbtrs) 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 k_{l} + k_{u}) r

, assuming

n ≫ k_{l}

and

n ≫ k_{u}

This routine may be followed by a call to f07bvf (zgbrfs) to refine the solution and return an error estimate.

The real analogue of this routine is f07bef (dgbtrs).

10

Example

This example solves the system of equations

A X = B

, where

A = (\begin{array}{r} - 1.65 + 2.26 i & - 2.05 - 0.85 i & 0.97 - 2.84 i & 0.00 + 0.00 i \\ 0.00 + 6.30 i & - 1.48 - 1.75 i & - 3.99 + 4.01 i & 0.59 - 0.48 i \\ 0.00 + 0.00 i & - 0.77 + 2.83 i & - 1.06 + 1.94 i & 3.33 - 1.04 i \\ 0.00 + 0.00 i & 0.00 + 0.00 i & 4.48 - 1.09 i & - 0.46 - 1.72 i \end{array})

and

B = (\begin{array}{r} - 1.06 + 21.50 i & 12.85 + 2.84 i \\ - 22.72 - 53.90 i & - 70.22 + 21.57 i \\ 28.24 - 38.60 i & - 20.7 - 31.23 i \\ - 34.56 + 16.73 i & 26.01 + 31.97 i \end{array}) .

Here

A

is nonsymmetric and is treated as a band matrix, which must first be factorized by f07brf (zgbtrf).

NAG Library Routine Document

f07bsf (zgbtrs)

▸▿ 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

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