Integer, Intent (In)	::	n, nrhs, ldb
Integer, Intent (Out)	::	info
Real (Kind=nag_wp), Intent (Inout)	::	d(*)
Complex (Kind=nag_wp), Intent (Inout)	::	e(), b(ldb,)

C Header Interface

#include <nag.h>

void	f07jnf_ (const Integer n, const Integer nrhs, double d[], Complex e[], Complex b[], const Integer ldb, Integer info)

The routine may be called by the names f07jnf, nagf_lapacklin_zptsv or its LAPACK name zptsv.

3 Description

f07jnf factors

A

A = L D L^{H}

. The factored form of

A

is then used to solve the system of equations.

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 https://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: $n$ – Integer Input: On entry: $n$ , the order of the matrix $A$ .

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

Constraint: $nrhs \geq 0$ .
3: $d (*)$ – Real (Kind=nag_wp) array Input/Output: Note: the dimension of the array d must be at least $\max (1, n)$ .

On entry: the $n$ diagonal elements of the tridiagonal matrix $A$ .

On exit: the $n$ diagonal elements of the diagonal matrix $D$ from the factorization $A = L D L^{H}$ .
4: $e (*)$ – Complex (Kind=nag_wp) array Input/Output: Note: the dimension of the array e must be at least $\max (1, n - 1)$ .

On entry: the $(n - 1)$ subdiagonal elements of the tridiagonal matrix $A$ .

On exit: the $(n - 1)$ subdiagonal elements of the unit bidiagonal factor $L$ from the $L D L^{H}$ factorization of $A$ . (e can also be regarded as the superdiagonal of the unit bidiagonal factor $U$ from the $U^{H} D U$ factorization of $A$ .)
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 $n \times r$ right-hand side matrix $B$ .

On exit: if $info = 0$ , the $n \times r$ solution matrix $X$ .
6: $ldb$ – Integer Input: On entry: the first dimension of the array b as declared in the (sub)program from which f07jnf 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.

$info > 0$: The leading minor of order $⟨ value ⟩$ is not positive definite, and the solution has not been computed. The factorization has not been completed unless $n = ⟨ value ⟩$ .

7 Accuracy

The computed solution for a single right-hand side,

\hat{x}

, satisfies an 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.

f07jpf is a comprehensive LAPACK driver that returns forward and backward error bounds and an estimate of the condition number. Alternatively, f04cgf solves

A x = b

and returns a forward error bound and condition estimate. f04cgf calls f07jnf to solve the equations.

8 Parallelism and Performance

f07jnf 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 number of floating-point operations required for the factorization of

A

is proportional to

n

, and the number of floating-point operations required for the solution of the equations is proportional to

n r

, where

r

is the number of right-hand sides.

The real analogue of this routine is f07jaf.

10 Example

This example solves the equations

A x = b,

where

A

is the Hermitian positive definite tridiagonal matrix

A = (\begin{array}{r} 16.0 & 16.0 - 16.0 i & 0 & 0 \\ 16.0 + 16.0 i & 41.0 & 18.0 + 9.0 i & 0 \\ 0 & 18.0 - 9.0 i & 46.0 & 1.0 + 4.0 i \\ 0 & 0 & 1.0 - 4.0 i & 21.0 \end{array})

and

b = (\begin{array}{r} 64.0 + 16.0 i \\ 93.0 + 62.0 i \\ 78.0 - 80.0 i \\ 14.0 - 27.0 i \end{array}) .

Details of the

L D L^{H}

factorization of

A

are also output.

f07jn: FL CL CPP AD

NAG FL Interfacef07jnf (zptsv)

▸▿ 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
f07jnf (zptsv)