Integer, Intent (In)	::	n, m, ldb, ldb2, ldx, ldy
Integer, Intent (Inout)	::	irevcm, icomm(2*n+40), ifail
Real (Kind=nag_wp), Intent (Inout)	::	comm(3*n+14)
Complex (Kind=nag_wp), Intent (In)	::	t, tr
Complex (Kind=nag_wp), Intent (Inout)	::	b(ldb,), b2(ldb2,), x(ldx,), y(ldy,), p(n), r(n), z(n), ccomm(n*(m+2))

C Header Interface

#include <nag.h>

void

f01hbf_ (Integer *irevcm, const Integer *n, const Integer *m, Complex b[], const Integer *ldb, const Complex *t, const Complex *tr, Complex b2[], const Integer *ldb2, Complex x[], const Integer *ldx, Complex y[], const Integer *ldy, Complex p[], Complex r[], Complex z[], Complex ccomm[], double comm[], Integer icomm[], Integer *ifail)

The routine may be called by the names f01hbf or nagf_matop_complex_gen_matrix_actexp_rcomm.

3 Description

e^{t A} B

is computed using the algorithm described in Al–Mohy and Higham (2011) which uses a truncated Taylor series to compute the

e^{t A} B

without explicitly forming

e^{t A}

The algorithm does not explicity need to access the elements of

A

; it only requires the result of matrix multiplications of the form

A X

A^{H} Y

. A reverse communication interface is used, in which control is returned to the calling program whenever a matrix product is required.

4 References

Al–Mohy A H and Higham N J (2011) Computing the action of the matrix exponential, with an application to exponential integrators SIAM J. Sci. Statist. Comput. 33(2) 488-511

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

5 Arguments

Note: this routine uses reverse communication. Its use involves an initial entry, intermediate exits and re-entries, and a final exit, as indicated by the argument irevcm. Between intermediate exits and re-entries, all arguments other than b2, x, y, p and r must remain unchanged.

1: $irevcm$ – Integer Input/Output

On initial entry: must be set to

0

On intermediate exit:

irevcm = 1

2

3

4

5

. The calling program must:

(a)if $irevcm = 1$ : evaluate $B_{2} = A B$ , where $B_{2}$ is an $n$ by $m$ matrix, and store the result in b2;
if $irevcm = 2$ : evaluate $Y = A X$ , where $X$ and $Y$ are $n$ by $2$ matrices, and store the result in y;
if $irevcm = 3$ : evaluate $X = A^{H} Y$ and store the result in x;
if $irevcm = 4$ : evaluate $p = A z$ and store the result in p;
if $irevcm = 5$ : evaluate $r = A^{H} z$ and store the result in r.
(b)call f01hbf again with all other parameters unchanged.

On final exit:

irevcm = 0

Note: any values you return to f01hbf as part of the reverse communication procedure should not include floating-point NaN (Not a Number) or infinity values, since these are not handled by f01hbf. If your code does inadvertently return any NaNs or infinities, f01hbf is likely to produce unexpected results.

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $m$ – Integer Input

On entry: the number of columns of the matrix

B

Constraint:

m \geq 0

4: $b (ldb *)$ – Complex (Kind=nag_wp) array Input/Output

Note: the second dimension of the array b must be at least

m

On initial entry: the

n

m

matrix

B

On intermediate exit: if

irevcm = 1

, contains the

n

m

matrix

B

On intermediate re-entry: must not be changed.

On final exit: the

n

m

matrix

e^{t A} B

5: $ldb$ – Integer Input

On entry: the first dimension of the array b as declared in the (sub)program from which f01hbf is called.

Constraint:

ldb \geq n

6: $t$ – Complex (Kind=nag_wp) Input

On entry: the scalar

t

7: $tr$ – Complex (Kind=nag_wp) Input

On entry: the trace of

A

. If this is not available then any number can be supplied (

0.0

is a reasonable default); however, in the trivial case,

n = 1

, the result

e^{tr t} B

is immediately returned in the first row of

B

. See Section 9.

8: $b2 (ldb2 *)$ – Complex (Kind=nag_wp) array Input/Output

Note: the second dimension of the array b2 must be at least

m

On initial entry: need not be set.

On intermediate re-entry: if

irevcm = 1

, must contain

A B

On final exit: the array is undefined.

9: $ldb2$ – Integer Input

On initial entry: the first dimension of the array b2 as declared in the (sub)program from which f01hbf is called.

Constraint:

ldb2 \geq n

10: $x (ldx *)$ – Complex (Kind=nag_wp) array Input/Output

Note: the second dimension of the array x must be at least

2

On initial entry: need not be set.

On intermediate exit: if

irevcm = 2

, contains the current

n

2

matrix

X

On intermediate re-entry: if

irevcm = 3

, must contain

A^{H} Y

On final exit: the array is undefined.

11: $ldx$ – Integer Input

On entry: the first dimension of the array x as declared in the (sub)program from which f01hbf is called.

Constraint:

ldx \geq n

12: $y (ldy *)$ – Complex (Kind=nag_wp) array Input/Output

Note: the second dimension of the array y must be at least

2

On initial entry: need not be set.

On intermediate exit: if

irevcm = 3

, contains the current

n

2

matrix

Y

On intermediate re-entry: if

irevcm = 2

, must contain

A X

On final exit: the array is undefined.

13: $ldy$ – Integer Input

On entry: the first dimension of the array y as declared in the (sub)program from which f01hbf is called.

Constraint:

ldy \geq n

14: $p (n)$ – Complex (Kind=nag_wp) array Input/Output

On initial entry: need not be set.

On intermediate re-entry: if

irevcm = 4

, must contain

A z

On final exit: the array is undefined.

15: $r (n)$ – Complex (Kind=nag_wp) array Input/Output

On initial entry: need not be set.

On intermediate re-entry: if

irevcm = 5

, must contain

A^{H} z

On final exit: the array is undefined.

16: $z (n)$ – Complex (Kind=nag_wp) array Input/Output

On initial entry: need not be set.

On intermediate exit: if

irevcm = 4

5

, contains the vector

z

On intermediate re-entry: must not be changed.

On final exit: the array is undefined.

17: $ccomm (n \times (m + 2))$ – Complex (Kind=nag_wp) array Communication Array

18: $comm (3 \times n + 14)$ – Real (Kind=nag_wp) array Communication Array

19: $icomm (2 \times n + 40)$ – Integer array Communication Array

20: $ifail$ – Integer Input/Output

On entry: ifail must be set to

0

- 1 or 1

. If you are unfamiliar with this argument you should refer to Section 4 in the Introduction to the NAG Library FL Interface for details.

For environments where it might be inappropriate to halt program execution when an error is detected, the value

- 1 or 1

is recommended. If the output of error messages is undesirable, then the value

1

is recommended. Otherwise, if you are not familiar with this argument, the recommended value is

0

. When the value $- 1 or 1$ is used it is essential to test the value of ifail on exit.

On exit:

ifail = 0

unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry

ifail = 0

- 1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 2$: $e^{t A} B$ has been computed using an IEEE double precision Taylor series, although the arithmetic precision is higher than IEEE double precision.

$ifail = - 1$: On initial entry, $irevcm = 〈value〉$ .
Constraint: $irevcm = 0$ .

On intermediate re-entry, $irevcm = 〈value〉$ .
Constraint: $irevcm = 1$ , $2$ , $3$ , $4$ or $5$ .

$ifail = - 2$: On initial entry, $n = 〈value〉$ .
Constraint: $n \geq 0$ .

$ifail = - 3$: On initial entry, $m = 〈value〉$ .
Constraint: $m \geq 0$ .

$ifail = - 5$: On initial entry, $ldb = 〈value〉$ and $n = 〈value〉$ .
Constraint: $ldb \geq n$ .

$ifail = - 9$: On initial entry, $ldb2 = 〈value〉$ and $n = 〈value〉$ .
Constraint: $ldb2 \geq n$ .

$ifail = - 11$: On initial entry, $ldx = 〈value〉$ and $n = 〈value〉$ .
Constraint: $ldx \geq n$ .

$ifail = - 13$: On initial entry, $ldy = 〈value〉$ and $n = 〈value〉$ .
Constraint: $ldy \geq n$ .

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 999$: Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

For an Hermitian matrix

A

(for which

A^{H} = A

) the computed matrix

e^{t A} B

is guaranteed to be close to the exact matrix, that is, the method is forward stable. No such guarantee can be given for non-Hermitian matrices. See Section 4 of Al–Mohy and Higham (2011) for details and further discussion.

8 Parallelism and Performance

f01hbf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

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

9.1 Use of $T r (A)$

The elements of

A

are not explicitly required by f01hbf. However, the trace of

A

is used in the preprocessing phase of the algorithm. If

T r (A)

is not available to the calling subroutine then any number can be supplied (

0

is recommended). This will not affect the stability of the algorithm, but it may reduce its efficiency.

9.2 When to use f01hbf

f01hbf is designed to be used when

A

is large and sparse. Whenever a matrix multiplication is required, the routine will return control to the calling program so that the multiplication can be done in the most efficient way possible. Note that

e^{t A} B

will not, in general, be sparse even if

A

is sparse.

A

is small and dense then f01haf can be used to compute

e^{t A} B

without the use of a reverse communication interface.

The real analog of f01hbf is f01gbf.

9.3 Use in Conjunction with NAG Library Routines

To compute

e^{t A} B

, the following skeleton code can normally be used:

revcm: Do 
  Call f01hbf(irevcm,n,m,b,ldb,t,tr,b2,ldb2,x,ldx,y,ldx,p,r,z, &
             ccomm,comm,icomm,ifail)
  If (irevcm == 0) Then 
      Exit revcm 
  Else If (irevcm == 1) Then
      .. Code to compute b2=ab ..
  Else If (irevcm == 2) Then
      .. Code to compute y=ax ..
  Else If (irevcm == 3) Then
      .. Code to compute x=a^h y ..
  Else If (irevcm == 4) Then
      .. Code to compute p=az ..
  Else If (irevcm == 5) Then 
      .. Code to compute r=a^h z ..
  End If
End Do revcm

The code used to compute the matrix products will vary depending on the way

A

is stored. If all the elements of

A

are stored explicitly, then f06zaf can be used. If

A

is triangular then f06zff should be used. If

A

is Hermitian, then f06zcf should be used. If

A

is symmetric, then f06ztf should be used. For sparse

A

stored in coordinate storage format f11xnf and f11xsf can be used. For sparse

A

stored in compressed column storage format (CCS) the program text of Section 10 contains the routine matmul to perform matrix products.

10 Example

This example computes

e^{t A} B

where

A = (\begin{array}{r} 0.7 + 0.8 i & - 0.2 + 0.0 i & 1.0 + 0.0 i & 0.6 + 0.5 i \\ 0.3 + 0.7 i & 0.7 + 0.0 i & 0.9 + 3.0 i & 1.0 + 0.8 i \\ 0.3 + 3.0 i & - 0.7 + 0.0 i & 0.2 + 0.6 i & 0.7 + 0.5 i \\ 0.0 + 0.9 i & 4.0 + 0.0 i & 0.0 + 0.0 i & 0.2 + 0.0 i \end{array}),

B = (\begin{matrix} 0.1 + 0.0 i & 1.2 + 0.1 i \\ 1.3 + 0.9 i & - 0.2 + 2.0 i \\ 4.0 + 0.6 i & - 1.0 + 0.8 i \\ 0.4 + 0.0 i & - 0.9 + 0.0 i \end{matrix})

and

t = 1.1 + 0.0 i .

A

is stored in compressed column storage format (CCS) and matrix multiplications are performed using the routine matmul.

Interfaces: FL CL AD

NAG FL Interface Introduction

F01 (Matop) Chapter Contents

F01 (Matop) Chapter Introduction

f01hb: FL CL AD

NAG FL Interfacef01hbf (complex_​gen_​matrix_​actexp_​rcomm)

▸▿ 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

9.1 Use of TrA

9.2 When to use f01hbf

9.3 Use in Conjunction with NAG Library Routines

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
f01hbf (complex_gen_matrix_actexp_rcomm)

9.1 Use of $T r (A)$