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Chapter Contents
Chapter Introduction
NAG Toolbox

# NAG Toolbox: nag_linsys_real_symm_solve (f04bh)

## Purpose

nag_linsys_real_symm_solve (f04bh) computes the solution to a real system of linear equations $AX=B$, where $A$ is an $n$ by $n$ symmetric matrix and $X$ and $B$ are $n$ by $r$ matrices. An estimate of the condition number of $A$ and an error bound for the computed solution are also returned.

## Syntax

[a, ipiv, b, rcond, errbnd, ifail] = f04bh(uplo, a, b, 'n', n, 'nrhs_p', nrhs_p)
[a, ipiv, b, rcond, errbnd, ifail] = nag_linsys_real_symm_solve(uplo, a, b, 'n', n, 'nrhs_p', nrhs_p)

## Description

The diagonal pivoting method is used to factor $A$ as $A=UD{U}^{\mathrm{T}}$, if ${\mathbf{uplo}}=\text{'U'}$, or $A=LD{L}^{\mathrm{T}}$, if ${\mathbf{uplo}}=\text{'L'}$, where $U$ (or $L$) is a product of permutation and unit upper (lower) triangular matrices, and $D$ is symmetric and block diagonal with $1$ by $1$ and $2$ by $2$ diagonal blocks. The factored form of $A$ is then used to solve the system of equations $AX=B$.

## 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
Higham N J (2002) Accuracy and Stability of Numerical Algorithms (2nd Edition) SIAM, Philadelphia

## Parameters

### Compulsory Input Parameters

1:     $\mathrm{uplo}$ – string (length ≥ 1)
If ${\mathbf{uplo}}=\text{'U'}$, the upper triangle of the matrix $A$ is stored.
If ${\mathbf{uplo}}=\text{'L'}$, the lower triangle of the matrix $A$ is stored.
Constraint: ${\mathbf{uplo}}=\text{'U'}$ or $\text{'L'}$.
2:     $\mathrm{a}\left(\mathit{lda},:\right)$ – double array
The first dimension of the array a must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
The second dimension of the array a must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
The $n$ by $n$ symmetric matrix $A$.
If ${\mathbf{uplo}}=\text{'U'}$, the leading n by n upper triangular part of the array a contains the upper triangular part of the matrix $A$, and the strictly lower triangular part of a is not referenced.
If ${\mathbf{uplo}}=\text{'L'}$, the leading n by n lower triangular part of the array a contains the lower triangular part of the matrix $A$, and the strictly upper triangular part of a is not referenced.
3:     $\mathrm{b}\left(\mathit{ldb},:\right)$ – double array
The first dimension of the array b must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
The second dimension of the array b must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{nrhs_p}}\right)$.
The $n$ by $r$ matrix of right-hand sides $B$.

### Optional Input Parameters

1:     $\mathrm{n}$int64int32nag_int scalar
Default: the first dimension of the arrays a, b and the second dimension of the array a.
The number of linear equations $n$, i.e., the order of the matrix $A$.
Constraint: ${\mathbf{n}}\ge 0$.
2:     $\mathrm{nrhs_p}$int64int32nag_int scalar
Default: the second dimension of the array b.
The number of right-hand sides $r$, i.e., the number of columns of the matrix $B$.
Constraint: ${\mathbf{nrhs_p}}\ge 0$.

### Output Parameters

1:     $\mathrm{a}\left(\mathit{lda},:\right)$ – double array
The first dimension of the array a will be $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
The second dimension of the array a will be $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
If ${\mathbf{ifail}}\ge {\mathbf{0}}$, the block diagonal matrix $D$ and the multipliers used to obtain the factor $U$ or $L$ from the factorization $A=UD{U}^{\mathrm{T}}$ or $A=LD{L}^{\mathrm{T}}$ as computed by nag_lapack_dsytrf (f07md).
2:     $\mathrm{ipiv}\left({\mathbf{n}}\right)$int64int32nag_int array
If ${\mathbf{ifail}}\ge {\mathbf{0}}$, details of the interchanges and the block structure of $D$, as determined by nag_lapack_dsytrf (f07md).
${\mathbf{ipiv}}\left(k\right)>0$
Rows and columns $k$ and ${\mathbf{ipiv}}\left(k\right)$ were interchanged, and ${d}_{kk}$ is a $1$ by $1$ diagonal block.
${\mathbf{uplo}}=\text{'U'}$ and ${\mathbf{ipiv}}\left(k\right)={\mathbf{ipiv}}\left(k-1\right)<0$
Rows and columns $k-1$ and $-{\mathbf{ipiv}}\left(k\right)$ were interchanged and ${d}_{k-1:k,k-1:k}$ is a $2$ by $2$ diagonal block.
${\mathbf{uplo}}=\text{'L'}$ and ${\mathbf{ipiv}}\left(k\right)={\mathbf{ipiv}}\left(k+1\right)<0$
Rows and columns $k+1$ and $-{\mathbf{ipiv}}\left(k\right)$ were interchanged and ${d}_{k:k+1,k:k+1}$ is a $2$ by $2$ diagonal block.
3:     $\mathrm{b}\left(\mathit{ldb},:\right)$ – double array
The first dimension of the array b will be $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
The second dimension of the array b will be $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{nrhs_p}}\right)$.
If ${\mathbf{ifail}}={\mathbf{0}}$ or $\mathbf{n}+{\mathbf{1}}$, the $n$ by $r$ solution matrix $X$.
4:     $\mathrm{rcond}$ – double scalar
If no constraints are violated, an estimate of the reciprocal of the condition number of the matrix $A$, computed as ${\mathbf{rcond}}=1/\left({‖A‖}_{1}{‖{A}^{-1}‖}_{1}\right)$.
5:     $\mathrm{errbnd}$ – double scalar
If ${\mathbf{ifail}}={\mathbf{0}}$ or $\mathbf{n}+{\mathbf{1}}$, an estimate of the forward error bound for a computed solution $\stackrel{^}{x}$, such that ${‖\stackrel{^}{x}-x‖}_{1}/{‖x‖}_{1}\le {\mathbf{errbnd}}$, where $\stackrel{^}{x}$ is a column of the computed solution returned in the array b and $x$ is the corresponding column of the exact solution $X$. If rcond is less than machine precision, then errbnd is returned as unity.
6:     $\mathrm{ifail}$int64int32nag_int scalar
${\mathbf{ifail}}={\mathbf{0}}$ unless the function detects an error (see Error Indicators and Warnings).

## Error Indicators and Warnings

Errors or warnings detected by the function:

Cases prefixed with W are classified as warnings and do not generate an error of type NAG:error_n. See nag_issue_warnings.

${\mathbf{ifail}}>0 \text{and} {\mathbf{ifail}}\le {\mathbf{n}}$
Diagonal block $_$ of the block diagonal matrix is zero. The factorization has been completed, but the solution could not be computed.
W  ${\mathbf{ifail}}={\mathbf{n}}+1$
A solution has been computed, but rcond is less than machine precision so that the matrix $A$ is numerically singular.
${\mathbf{ifail}}=-1$
On entry, uplo not one of 'U' or 'u' or 'L' or 'l'.
${\mathbf{ifail}}=-2$
Constraint: ${\mathbf{n}}\ge 0$.
${\mathbf{ifail}}=-3$
Constraint: ${\mathbf{nrhs_p}}\ge 0$.
${\mathbf{ifail}}=-5$
Constraint: $\mathit{lda}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
${\mathbf{ifail}}=-8$
Constraint: $\mathit{ldb}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
${\mathbf{ifail}}=-99$
${\mathbf{ifail}}=-399$
Your licence key may have expired or may not have been installed correctly.
${\mathbf{ifail}}=-999$
Dynamic memory allocation failed.
The integer allocatable memory required is n, and the double allocatable memory required is $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(2×{\mathbf{n}},{\mathbf{lwork}}\right)$, where lwork is the optimum workspace required by nag_lapack_dsysv (f07ma). If this failure occurs it may be possible to solve the equations by calling the packed storage version of nag_linsys_real_symm_solve (f04bh), nag_linsys_real_symm_packed_solve (f04bj), or by calling nag_lapack_dsysv (f07ma) directly with less than the optimum workspace (see Chapter F07).

## Accuracy

The computed solution for a single right-hand side, $\stackrel{^}{x}$, satisfies an equation of the form
 $A+E x^ = b ,$
where
 $E1 = Oε A1$
and $\epsilon$ is the machine precision. An approximate error bound for the computed solution is given by
 $x^-x1 x1 ≤ κA E1 A1 ,$
where $\kappa \left(A\right)={‖{A}^{-1}‖}_{1}{‖A‖}_{1}$, the condition number of $A$ with respect to the solution of the linear equations. nag_linsys_real_symm_solve (f04bh) uses the approximation ${‖E‖}_{1}=\epsilon {‖A‖}_{1}$ to estimate errbnd. See Section 4.4 of Anderson et al. (1999) for further details.

The total number of floating-point operations required to solve the equations $AX=B$ is proportional to $\left(\frac{1}{3}{n}^{3}+2{n}^{2}r\right)$. The condition number estimation typically requires between four and five solves and never more than eleven solves, following the factorization.
In practice the condition number estimator is very reliable, but it can underestimate the true condition number; see Section 15.3 of Higham (2002) for further details.
The complex analogues of nag_linsys_real_symm_solve (f04bh) are nag_linsys_complex_herm_solve (f04ch) for complex Hermitian matrices, and nag_linsys_complex_symm_solve (f04dh) for complex symmetric matrices.

## Example

This example solves the equations
 $AX=B,$
where $A$ is the symmetric indefinite matrix
 $A= -1.81 2.06 0.63 -1.15 2.06 1.15 1.87 4.20 0.63 1.87 -0.21 3.87 -1.15 4.20 3.87 2.07 and B= 0.96 3.93 6.07 19.25 8.38 9.90 9.50 27.85 .$
An estimate of the condition number of $A$ and an approximate error bound for the computed solutions are also printed.
```function f04bh_example

fprintf('f04bh example results\n\n');

% Solve Ax = b for symmetric A with error bound and condition number
uplo = 'Upper';
a = [-1.81,  2.06,  0.63, -1.15;
0,     1.15,  1.87,  4.20;
0,     0,    -0.21,  3.87;
0,     0,     0,     2.07];
b = [ 0.96,  3.93;
6.07, 19.25;
8.38,  9.90;
9.50, 27.85];

[a, ipiv, x, rcond, errbnd, ifail] = ...
f04bh(uplo, a, b);

disp('Solution');
disp(x);
disp('Estimate of condition number');
fprintf('%10.1f\n\n',1/rcond);
disp('Estimate of error bound for computed solutions');
fprintf('%10.1e\n\n',errbnd);

```
```f04bh example results

Solution
-5.0000    2.0000
-2.0000    3.0000
1.0000    4.0000
4.0000    1.0000

Estimate of condition number
75.7

Estimate of error bound for computed solutions
8.4e-15

```