naginterfaces.library.matop.real_​gen_​matrix_​frcht_​pow

naginterfaces.library.matop.real_gen_matrix_frcht_pow(a, e, p)

real_gen_matrix_frcht_pow computes the Fréchet derivative $L(A,E)$ of the $p$th power (where $p$ is real) of the real $n\times n$ matrix $A$ applied to the real $n\times n$ matrix $E$. The principal matrix power $A^p$ is also returned.

For full information please refer to the NAG Library document for f01jf

https://www.nag.com/numeric/nl/nagdoc_29.3/flhtml/f01/f01jff.html

Parameters

afloat, array-like, shape $(n,n)$

The $n\times n$ matrix $A$.

efloat, array-like, shape $(n,n)$

The $n\times n$ matrix $E$.

pfloat

The required power of $A$.

Returns

afloat, ndarray, shape $(n,n)$

The $n\times n$ principal matrix $p$th power, $A^p$.

efloat, ndarray, shape $(n,n)$

The Fréchet derivative $L(A,E)$.

Raises

NagValueError

(errno $-1$)

On entry, $n=⟨value⟩$.

Constraint: $n\ge 0$.

(errno $1$)

$A$ has eigenvalues on the negative real line. The principal $p$th power is not defined in this case; complex_gen_matrix_frcht_pow() can be used to find a complex, non-principal $p$th power.

(errno $2$)

$A$ is singular so the $p$th power cannot be computed.

(errno $4$)

An unexpected internal error occurred. This failure should not occur and suggests that the function has been called incorrectly.

Warns

NagAlgorithmicWarning

(errno $3$)

$A^p$ has been computed using an IEEE double precision Padé approximant, although the arithmetic precision is higher than IEEE double precision.

Notes

For a matrix $A$ with no eigenvalues on the closed negative real line, $A^p$ ($p\in R$) can be defined as

$$A^p=exp\left(p\log \left(A\right)\right)$$

where $\log \left(A\right)$ is the principal logarithm of $A$ (the unique logarithm whose spectrum lies in the strip $\{z:-\pi <Im\left(z\right)<\pi \}$).

The Fréchet derivative of the matrix $p$th power of $A$ is the unique linear mapping $E⟼L(A,E)$ such that for any matrix $E$

$${(A+E)}^p-A^p-L(A,E)=o\left(\parallel E\parallel \right)\text{.}$$

The derivative describes the first-order effect of perturbations in $A$ on the matrix power $A^p$.

real_gen_matrix_frcht_pow uses the algorithms of Higham and Lin (2011) and Higham and Lin (2013) to compute $A^p$ and $L(A,E)$. The real number $p$ is expressed as $p=q+r$ where $q\in (-1,1)$ and $r\in Z$. Then $A^p=A^q{A}^r$. The integer power $A^r$ is found using a combination of binary powering and, if necessary, matrix inversion. The fractional power $A^q$ 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 $A^q$ and $L(A,E)$ is then computed using a combination of the chain rule and the product rule for Fréchet derivatives.

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, SIAM J. Matrix Anal. Appl. (34(3)), 1341–1360