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NAG Library Routine Document

f07anf (zgesv)

▸▿ 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

f07anf (zgesv) computes the solution to a complex system of linear equations

A X = B,

where

A

is an

n

n

matrix and

X

and

B

are

n

r

matrices.

2

Specification

Fortran Interface

Subroutine f07anf (

n, nrhs, a, lda, ipiv, b, ldb, info)

Integer, Intent (In)	::	n, nrhs, lda, ldb
Integer, Intent (Out)	::	ipiv(n), info
Complex (Kind=nag_wp), Intent (Inout)	::	a(lda,), b(ldb,)

C Header Interface

#include nagmk26.h

void	f07anf_ ( const Integer n, const Integer nrhs, Complex a[], const Integer lda, Integer ipiv[], Complex b[], const Integer ldb, Integer *info)

The routine may be called by its LAPACK name zgesv.

3

Description

f07anf (zgesv) uses the

L U

decomposition with partial pivoting and row interchanges to factor

A

A = P L U,

where

P

is a permutation matrix,

L

is unit lower triangular, and

U

is upper triangular. The factored form of

A

is then used to solve the system of equations

A X = B

4

References

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 http://www.netlib.org/lapack/lug

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

5

Arguments

1: $n$ – IntegerInput: On entry: $n$ , the number of linear equations, i.e., the order of the matrix $A$ .

Constraint: $n \geq 0$ .
2: $nrhs$ – IntegerInput: On entry: $r$ , the number of right-hand sides, i.e., the number of columns of the matrix $B$ .

Constraint: $nrhs \geq 0$ .
3: $a (lda *)$ – Complex (Kind=nag_wp) arrayInput/Output: Note: the second dimension of the array a must be at least $\max (1, n)$ .

On entry: the $n$ by $n$ coefficient matrix $A$ .

On exit: the factors $L$ and $U$ from the factorization $A = P L U$ ; the unit diagonal elements of $L$ are not stored.
4: $lda$ – IntegerInput: On entry: the first dimension of the array a as declared in the (sub)program from which f07anf (zgesv) is called.

Constraint: $lda \geq \max (1, n)$ .
5: $ipiv (n)$ – Integer arrayOutput: On exit: if no constraints are violated, the pivot indices that define the permutation matrix $P$ ; at the $i$ th step row $i$ of the matrix was interchanged with row $ipiv (i)$ . $ipiv (i) = i$ indicates a row interchange was not required.
6: $b (ldb *)$ – Complex (Kind=nag_wp) arrayInput/Output: Note: the second dimension of the array b must be at least $\max (1, nrhs)$ .

On entry: the $n$ by $r$ right-hand side matrix $B$ .

On exit: if $info = 0$ , the $n$ by $r$ solution matrix $X$ .
7: $ldb$ – IntegerInput: On entry: the first dimension of the array b as declared in the (sub)program from which f07anf (zgesv) is called.

Constraint: $ldb \geq \max (1, n)$ .
8: $info$ – 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.

$info > 0$: Element $〈value〉$ of the diagonal is exactly zero. The factorization has been completed, but the factor $U$ is exactly singular, so the solution could not be computed.

7

Accuracy

The computed solution for a single right-hand side,

\hat{x}

, satisfies the equation of the form

(A + E) \hat{x} = b,

where

{‖E‖}_{1} = O (ε) {‖A‖}_{1}

and

ε

is the machine precision. An approximate error bound for the computed solution is given by

\frac{{‖\hat{x} - x‖}_{1}}{{‖x‖}_{1}} \leq κ (A) \frac{{‖E‖}_{1}}{{‖A‖}_{1}}

where

κ (A) = {‖A^{- 1}‖}_{1} {‖A‖}_{1}

, the condition number of

A

with respect to the solution of the linear equations. See Section 4.4 of Anderson et al. (1999) for further details.

Following the use of f07anf (zgesv), f07auf (zgecon) can be used to estimate the condition number of

A

and f07avf (zgerfs) can be used to obtain approximate error bounds. Alternatives to f07anf (zgesv), which return condition and error estimates directly are f04caf and f07apf (zgesvx).

8

Parallelism and Performance

f07anf (zgesv) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f07anf (zgesv) 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 floating-point operations is approximately

\frac{8}{3} n^{3} + 8 n^{2} r

, where

r

is the number of right-hand sides.

The real analogue of this routine is f07aaf (dgesv).

10

Example

This example solves the equations

A x = b,

where

A

is the general matrix

A = (\begin{array}{r} - 1.34 + 2.55 i & 0.28 + 3.17 i & - 6.39 - 2.20 i & 0.72 - 0.92 i \\ - 0.17 - 1.41 i & 3.31 - 0.15 i & - 0.15 + 1.34 i & 1.29 + 1.38 i \\ - 3.29 - 2.39 i & - 1.91 + 4.42 i & - 0.14 - 1.35 i & 1.72 + 1.35 i \\ 2.41 + 0.39 i & - 0.56 + 1.47 i & - 0.83 - 0.69 i & - 1.96 + 0.67 i \end{array}) and b = (\begin{array}{r} 26.26 + 51.78 i \\ 6.43 - 8.68 i \\ - 5.75 + 25.31 i \\ 1.16 + 2.57 i \end{array}) .

Details of the

L U

factorization of

A

are also output.

NAG Library Routine Document

f07anf (zgesv)

▸▿ 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