void	f08hsc (Nag_OrderType order, Nag_VectType vect, Nag_UploType uplo, Integer n, Integer kd, Complex ab[], Integer pdab, double d[], double e[], Complex q[], Integer pdq, NagError *fail)

The function may be called by the names: f08hsc, nag_lapackeig_zhbtrd or nag_zhbtrd.

3 Description

f08hsc reduces a Hermitian band matrix

A

to real symmetric tridiagonal form

T

by a unitary similarity transformation:

T = Q^{H} A Q .

The unitary matrix

Q

is determined as a product of Givens rotation matrices, and may be formed explicitly by the function if required.

The function uses a vectorizable form of the reduction, due to Kaufman (1984).

4 References

Kaufman L (1984) Banded eigenvalue solvers on vector machines ACM Trans. Math. Software 10 73–86

Parlett B N (1998) The Symmetric Eigenvalue Problem SIAM, Philadelphia

5 Arguments

1: $order$ – Nag_OrderType Input

On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by

order = Nag_RowMajor

. See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.

Constraint:

order = Nag_RowMajor

Nag_ColMajor

2: $vect$ – Nag_VectType Input

On entry: indicates whether

Q

is to be returned.

$vect = Nag_FormQ$: $Q$ is returned.
$vect = Nag_UpdateQ$: $Q$ is updated (and the array q must contain a matrix on entry).
$vect = Nag_DoNotForm$: $Q$ is not required.

Constraint:

vect = Nag_FormQ

Nag_UpdateQ

Nag_DoNotForm

3: $uplo$ – Nag_UploType Input

On entry: indicates whether the upper or lower triangular part of

A

is stored.

$uplo = Nag_Upper$: The upper triangular part of $A$ is stored.
$uplo = Nag_Lower$: The lower triangular part of $A$ is stored.

Constraint:

uplo = Nag_Upper

Nag_Lower

4: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

5: $kd$ – Integer Input

On entry: if

uplo = Nag_Upper

, the number of superdiagonals,

k_{d}

, of the matrix

A

uplo = Nag_Lower

, the number of subdiagonals,

k_{d}

, of the matrix

A

Constraint:

kd \geq 0

6: $ab [\dim]$ – Complex Input/Output

Note: the dimension, dim, of the array ab must be at least

\max (1, pdab \times n)

On entry: the upper or lower triangle of the

n \times n

Hermitian band matrix

A

This is stored as a notional two-dimensional array with row elements or column elements stored contiguously. The storage of elements of

A_{i j}

, depends on the order and uplo arguments as follows:

if $order = Nag_ColMajor$ and $uplo = Nag_Upper$ ,: $A_{i j}$ is stored in $ab [k_{d} + i - j + (j - 1) \times pdab]$ , for $j = 1, \dots, n$ and $i = \max (1, j - k_{d}), \dots, j$ ;
if $order = Nag_ColMajor$ and $uplo = Nag_Lower$ ,: $A_{i j}$ is stored in $ab [i - j + (j - 1) \times pdab]$ , for $j = 1, \dots, n$ and $i = j, \dots, \min (n, j + k_{d})$ ;
if $order = Nag_RowMajor$ and $uplo = Nag_Upper$ ,: $A_{i j}$ is stored in $ab [j - i + (i - 1) \times pdab]$ , for $i = 1, \dots, n$ and $j = i, \dots, \min (n, i + k_{d})$ ;
if $order = Nag_RowMajor$ and $uplo = Nag_Lower$ ,: $A_{i j}$ is stored in $ab [k_{d} + j - i + (i - 1) \times pdab]$ , for $i = 1, \dots, n$ and $j = \max (1, i - k_{d}), \dots, i$ .

On exit: ab is overwritten by values generated during the reduction to tridiagonal form.

The first superdiagonal or subdiagonal and the diagonal of the tridiagonal matrix

T

are returned in ab using the same storage format as described above.

7: $pdab$ – Integer Input

On entry: the stride separating row or column elements (depending on the value of order) of the matrix

A

in the array ab.

Constraint:

pdab \geq \max (1, kd + 1)

8: $d [n]$ – double Output

On exit: the diagonal elements of the tridiagonal matrix

T

9: $e [\dim]$ – double Output

Note: the dimension, dim, of the array e must be at least

\max (1, n - 1)

On exit: the off-diagonal elements of the tridiagonal matrix

T

10: $q [\dim]$ – Complex Input/Output

Note: the dimension, dim, of the array q must be at least

$\max (1, pdq \times n)$ when $vect = Nag_FormQ$ or $Nag_UpdateQ$ ;
$1$ when $vect = Nag_DoNotForm$ .

The

(i, j)

th element of the matrix

Q

is stored in

$q [(j - 1) \times pdq + i - 1]$ when $order = Nag_ColMajor$ ;
$q [(i - 1) \times pdq + j - 1]$ when $order = Nag_RowMajor$ .

On entry: if

vect = Nag_UpdateQ

, q must contain the matrix formed in a previous stage of the reduction (for example, the reduction of a banded Hermitian-definite generalized eigenproblem); otherwise q need not be set.

On exit: if

vect = Nag_FormQ

Nag_UpdateQ

, the

n \times n

matrix

Q

vect = Nag_DoNotForm

, q is not referenced.

11: $pdq$ – Integer Input

On entry: the stride separating row or column elements (depending on the value of order) in the array q.

Constraints:

if $vect = Nag_FormQ$ or $Nag_UpdateQ$ , $pdq \geq \max (1, n)$ ;
if $vect = Nag_DoNotForm$ , $pdq \geq 1$ .

12: $fail$ – 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_ENUM_INT_2: On entry, $vect = ⟨ value ⟩$ , $pdq = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: if $vect = Nag_FormQ$ or $Nag_UpdateQ$ , $pdq \geq \max (1, n)$ ;
if $vect = Nag_DoNotForm$ , $pdq \geq 1$ .
NE_INT: On entry, $kd = ⟨ value ⟩$ .
Constraint: $kd \geq 0$ .

On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .

On entry, $pdab = ⟨ value ⟩$ .
Constraint: $pdab > 0$ .

On entry, $pdq = ⟨ value ⟩$ .
Constraint: $pdq > 0$ .
NE_INT_2: On entry, $pdab = ⟨ value ⟩$ and $kd = ⟨ value ⟩$ .
Constraint: $pdab \geq \max (1, kd + 1)$ .
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_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.

7 Accuracy

The computed tridiagonal matrix

T

is exactly similar to a nearby matrix

(A + E)

, where

{‖ E ‖}_{2} \leq c (n) ε {‖ A ‖}_{2},

c (n)

is a modestly increasing function of

n

, and

ε

is the machine precision.

The elements of

T

themselves may be sensitive to small perturbations in

A

or to rounding errors in the computation, but this does not affect the stability of the eigenvalues and eigenvectors.

The computed matrix

Q

differs from an exactly unitary matrix by a matrix

E

such that

{‖ E ‖}_{2} = O (ε),

where

ε

is the machine precision.

8 Parallelism and Performance

f08hsc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f08hsc 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 total number of real floating-point operations is approximately

20 n^{2} k

vect = Nag_DoNotForm

with

10 n^{3} (k - 1) / k

additional operations if

vect = Nag_FormQ

The real analogue of this function is f08hec.

10 Example

This example computes all the eigenvalues and eigenvectors of the matrix

A

, where

A = (\begin{array}{r} - 3.13 + 0.00 i & 1.94 - 2.10 i & - 3.40 + 0.25 i & 0.00 + 0.00 i \\ 1.94 + 2.10 i & - 1.91 + 0.00 i & - 0.82 - 0.89 i & - 0.67 + 0.34 i \\ - 3.40 - 0.25 i & - 0.82 + 0.89 i & - 2.87 + 0.00 i & - 2.10 - 0.16 i \\ 0.00 + 0.00 i & - 0.67 - 0.34 i & - 2.10 + 0.16 i & 0.50 + 0.00 i \end{array}) .

Here

A

is Hermitian and is treated as a band matrix. The program first calls f08hsc to reduce

A

to tridiagonal form

T

, and to form the unitary matrix

Q

; the results are then passed to f08jsc which computes the eigenvalues and eigenvectors of

A

f08hs: FL CL CPP AD

NAG CL Interfacef08hsc (zhbtrd)

▸▿ 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
f08hsc (zhbtrd)