. A nonsingular matrix has multiple square roots. For a matrix with no eigenvalues on the closed negative real line, the principal square root, denoted by

A^{1 / 2}

, is the unique square root whose eigenvalues lie in the open right half-plane.

A^{1 / 2}

is computed using the algorithm described in Higham (1987). This is a real arithmetic version of the algorithm of Björck and Hammarling (1983). In addition a blocking scheme described in Deadman et al. (2013) is used.

4 References

Björck Å and Hammarling S (1983) A Schur method for the square root of a matrix Linear Algebra Appl. 52/53 127–140

Deadman E, Higham N J and Ralha R (2013) Blocked Schur Algorithms for Computing the Matrix Square Root Applied Parallel and Scientific Computing: 11th International Conference, (PARA 2012, Helsinki, Finland) P. Manninen and P. Öster, Eds Lecture Notes in Computer Science 7782 171–181 Springer–Verlag

Higham N J (1987) Computing real square roots of a real matrix Linear Algebra Appl. 88/89 405–430

Higham N J (2008) Functions of Matrices: Theory and Computation SIAM, Philadelphia, PA, USA

5 Arguments

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

Constraint: $n \geq 0$ .
2: $a [\dim]$ – double Input/Output: Note: the dimension, dim, of the array a must be at least $pda \times n$ .

The $(i, j)$ th element of the matrix $A$ is stored in $a [(j - 1) \times pda + i - 1]$ .

On entry: the $n \times n$ matrix $A$ .

On exit: contains, if $fail . code =$ NE_NOERROR, the $n \times n$ principal matrix square root, $A^{1 / 2}$ . Alternatively, if $fail . code =$ NE_EIGENVALUES, contains an $n \times n$ non-principal square root of $A$ .
3: $pda$ – Integer Input: On entry: the stride separating matrix row elements in the array a.

Constraint: $pda \geq n$ .
4: $fail$ – NagError * Input/Output: The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
NE_EIGENVALUES: $A$ has a semisimple vanishing eigenvalue. A non-principal square root is returned.
NE_INT: On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .
NE_INT_2: On entry, $pda = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $pda \geq n$ .
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.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NEGATIVE_EIGVAL: $A$ has a negative real eigenvalue. The principal square root is not defined. f01fnc can be used to return a complex, non-principal square root.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
NE_SINGULAR: $A$ has a defective vanishing eigenvalue. The square root cannot be found in this case.

7 Accuracy

The computed square root

\hat{X}

satisfies

{\hat{X}}^{2} = A + Δ A

, where

{‖ Δ A ‖}_{F} \approx O (ε) n^{3} {‖ \hat{X} ‖}_{F}^{2}

, where

ε

is machine precision.

For further discussion of the condition of the matrix square root see Section 6.1 of Higham (2008).

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

f01enc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f01enc 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 function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The cost of the algorithm is

85 n^{3} / 3

floating-point operations; see Algorithm 6.7 of Higham (2008).

O (2 \times n^{2})

of real allocatable memory is required by the function.

If condition number and residual bound estimates are required, then f01jdc should be used.

10 Example

This example finds the principal matrix square root of the matrix

A = (\begin{array}{r} 507 & 622 & 300 & −202 \\ 237 & 352 & 126 & −60 \\ 751 & 950 & 440 & −286 \\ −286 & −326 & −192 & 150 \end{array}) .

f01en: FL CL CPP AD PY MB

NAG CL Interfacef01enc (real_​gen_​matrix_​sqrt)

▸▿ 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 CL Interface
f01enc (real_gen_matrix_sqrt)