nag_matop_complex_gen_matrix_frcht_pow (f01kfc) (PDF version)
f01 Chapter Contents
f01 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_matop_complex_gen_matrix_frcht_pow (f01kfc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_matop_complex_gen_matrix_frcht_pow (f01kfc) computes the Fréchet derivative LA,E of the pth power (where p is real) of the complex n by n matrix A applied to the complex n by n matrix E. The principal matrix power Ap is also returned.

2  Specification

#include <nag.h>
#include <nagf01.h>
void  nag_matop_complex_gen_matrix_frcht_pow (Integer n, Complex a[], Integer pda, Complex e[], Integer pde, double p, NagError *fail)

3  Description

For a matrix A with no eigenvalues on the closed negative real line, Ap (p) can be defined as
Ap= expplogA
where logA is the principal logarithm of A (the unique logarithm whose spectrum lies in the strip z:-π<Imz<π). If A is nonsingular but has negative real eigenvalues, the principal logarithm is not defined, but a non-principal pth power can be defined by using a non-principal logarithm.
The Fréchet derivative of the matrix pth power of A is the unique linear mapping ELA,E such that for any matrix E 
A+Ep - Ap - LA,E = oE .
The derivative describes the first-order effect of perturbations in A on the matrix power Ap.
nag_matop_complex_gen_matrix_frcht_pow (f01kfc) uses the algorithms of Higham and Lin (2011) and Higham and Lin (2013) to compute Ap and LA,E. The real number p is expressed as p=q+r where q-1,1 and r. Then Ap=AqAr. The integer power Ar is found using a combination of binary powering and, if necessary, matrix inversion. The fractional power Aq is computed using a Schur decomposition, a Padé approximant and the scaling and squaring method. The Padé approximant is differentiated in order to obtain the Fréchet derivative of Aq and LA,E is then computed using a combination of the chain rule and the product rule for Fréchet derivatives.

4  References

Higham N J (2008) Functions of Matrices: Theory and Computation SIAM, Philadelphia, PA, USA
Higham N J and Lin L (2011) A Schur–Padé algorithm for fractional powers of a matrix SIAM J. Matrix Anal. Appl. 32(3) 1056–1078
Higham N J and Lin L (2013) An improved Schur–Padé algorithm for fractional powers of a matrix and their Fréchet derivatives MIMS Eprint 2013.1 Manchester Institute for Mathematical Sciences, School of Mathematics, University of Manchester http://eprints.ma.man.ac.uk/

5  Arguments

1:     nIntegerInput
On entry: n, the order of the matrix A.
Constraint: n0.
2:     a[dim]ComplexInput/Output
Note: the dimension, dim, of the array a must be at least pda×n.
The i,jth element of the matrix A is stored in a[j-1×pda+i-1].
On entry: the n by n matrix A.
On exit: the n by n principal matrix pth power, Ap. Alternatively if fail.code= NE_NEGATIVE_EIGVAL, a non-principal pth power is returned.
3:     pdaIntegerInput
On entry: the stride separating matrix row elements in the array a.
Constraint: pdan.
4:     e[dim]ComplexInput/Output
Note: the dimension, dim, of the array e must be at least pde×n.
The i,jth element of the matrix E is stored in e[j-1×pde+i-1].
On entry: the n by n matrix E.
On exit: the Fréchet derivative LA,E.
5:     pdeIntegerInput
On entry: the stride separating matrix row elements in the array e.
Constraint: pden.
6:     pdoubleInput
On entry: the required power of A.
7:     failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INT
On entry, n=value.
Constraint: n0.
NE_INT_2
On entry, pda=value and n=value.
Constraint: pdan.
On entry, pde=value and n=value.
Constraint: pden.
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.
NE_NEGATIVE_EIGVAL
A has eigenvalues on the negative real line. The principal pth power is not defined in this case, so a non-principal power was returned.
NE_SINGULAR
A is singular so the pth power cannot be computed.
NW_SOME_PRECISION_LOSS
Ap has been computed using an IEEE double precision Padé approximant, although the arithmetic precision is higher than IEEE double precision.

7  Accuracy

For a normal matrix A (for which AHA=AAH), the Schur decomposition is diagonal and the computation of the fractional part of the matrix power reduces to evaluating powers of the eigenvalues of A and then constructing Ap using the Schur vectors. This should give a very accurate result. In general, however, no error bounds are available for the algorithm. See Higham and Lin (2011) and Higham and Lin (2013) for details and further discussion.
If the condition number of the matrix power is required then nag_matop_complex_gen_matrix_cond_pow (f01kec) should be used.

8  Parallelism and Performance

nag_matop_complex_gen_matrix_frcht_pow (f01kfc) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
nag_matop_complex_gen_matrix_frcht_pow (f01kfc) 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 Users' Note for your implementation for any additional implementation-specific information.

9  Further Comments

The complex allocatable memory required by the algorithm is approximately 6×n2.
The cost of the algorithm is On3 floating-point operations; see Higham and Lin (2011) and Higham and Lin (2013).
If the matrix pth power alone is required, without the Fréchet derivative, then nag_matop_complex_gen_matrix_pow (f01fqc) should be used. If the condition number of the matrix power is required then nag_matop_complex_gen_matrix_cond_pow (f01kec) should be used. The real analogue of this function is nag_matop_real_gen_matrix_frcht_pow (f01jfc).

10  Example

This example finds Ap and the Fréchet derivative of the matrix power LA,E, where p=0.2,
A = 2i+ 3i+0 2i+0 1+3i 2+i 1i+0 1i+0 2+0i 0+i 2+2i 0+2i 0+4i 3i+ 0+0i 3i+0 1i+0   and   E = 0+i 3i+0 2i+0 1+3i 0+i 1i+0 3+3i 0+0i 0+i 2+2i 0+2i 0i+0 2i+ 0+0i 1i+0 1i+0 .

10.1  Program Text

Program Text (f01kfce.c)

10.2  Program Data

Program Data (f01kfce.d)

10.3  Program Results

Program Results (f01kfce.r)


nag_matop_complex_gen_matrix_frcht_pow (f01kfc) (PDF version)
f01 Chapter Contents
f01 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2014