NAG FL Interface
f08hpf (zhbevx)

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

1: $\mathbf{jobz}$ – Character(1) Input

On entry: indicates whether eigenvectors are computed.

$\mathbf{jobz}=\text{'N'}$

Only eigenvalues are computed.

$\mathbf{jobz}=\text{'V'}$

Eigenvalues and eigenvectors are computed.

Constraint: $\mathbf{jobz}=\text{'N'}$ or $\text{'V'}$.

2: $\mathbf{range}$ – Character(1) Input

On entry: if $\mathbf{range}=\text{'A'}$, all eigenvalues will be found.

If $\mathbf{range}=\text{'V'}$, all eigenvalues in the half-open interval $(\mathbf{vl},\mathbf{vu}]$ will be found.

If $\mathbf{range}=\text{'I'}$, the ilth to iuth eigenvalues will be found.

Constraint: $\mathbf{range}=\text{'A'}$, $\text{'V'}$ or $\text{'I'}$.

3: $\mathbf{uplo}$ – Character(1) Input

On entry: if $\mathbf{uplo}=\text{'U'}$, the upper triangular part of $A$ is stored.

If $\mathbf{uplo}=\text{'L'}$, the lower triangular part of $A$ is stored.

Constraint: $\mathbf{uplo}=\text{'U'}$ or $\text{'L'}$.

4: $\mathbf{n}$ – Integer Input

On entry: $n$, the order of the matrix $A$.

Constraint: $\mathbf{n}\ge 0$.

5: $\mathbf{kd}$ – Integer Input

On entry: if $\mathbf{uplo}=\text{'U'}$, the number of superdiagonals, $k_d$, of the matrix $A$.

If $\mathbf{uplo}=\text{'L'}$, the number of subdiagonals, $k_d$, of the matrix $A$.

Constraint: $\mathbf{kd}\ge 0$.

6: $\mathbf{ab}(\mathbf{ldab},*)$ – Complex (Kind=nag_wp) array Input/Output

Note: the second dimension of the array ab must be at least $\max (1,\mathbf{n})$.

On entry: the upper or lower triangle of the $n\times n$ Hermitian band matrix $A$.

The matrix is stored in rows $1$ to $k_d+1$, more precisely,

• if $\mathbf{uplo}=\text{'U'}$, the elements of the upper triangle of $A$ within the band must be stored with element $A_{ij}$ in $\mathbf{ab}(k_d+1+i-j,j)\text{ for }\max (1,j-k_d)\le i\le j$;
• if $\mathbf{uplo}=\text{'L'}$, the elements of the lower triangle of $A$ within the band must be stored with element $A_{ij}$ in $\mathbf{ab}(1+i-j,j)\text{ for }j\le i\le \min (n,j+k_d)\text{.}$

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: $\mathbf{ldab}$ – Integer Input

On entry: the first dimension of the array ab as declared in the (sub)program from which f08hpf is called.

Constraint: $\mathbf{ldab}\ge \mathbf{kd}+1$.

8: $\mathbf{q}(\mathbf{ldq},*)$ – Complex (Kind=nag_wp) array Output

Note: the second dimension of the array q must be at least $\max (1,\mathbf{n})$ if $\mathbf{jobz}=\text{'V'}$, and at least $1$ otherwise.

On exit: if $\mathbf{jobz}=\text{'V'}$, the $n\times n$ unitary matrix used in the reduction to tridiagonal form.

If $\mathbf{jobz}=\text{'N'}$, q is not referenced.

9: $\mathbf{ldq}$ – Integer Input

On entry: the first dimension of the array q as declared in the (sub)program from which f08hpf is called.

Constraints:

• if $\mathbf{jobz}=\text{'V'}$, $\mathbf{ldq}\ge \max (1,\mathbf{n})$;
• otherwise $\mathbf{ldq}\ge 1$.

10: $\mathbf{vl}$ – Real (Kind=nag_wp) Input

11: $\mathbf{vu}$ – Real (Kind=nag_wp) Input

On entry: if $\mathbf{range}=\text{'V'}$, the lower and upper bounds of the interval to be searched for eigenvalues.

If $\mathbf{range}=\text{'A'}$ or $\text{'I'}$, vl and vu are not referenced.

Constraint: if $\mathbf{range}=\text{'V'}$, $\mathbf{vl}<\mathbf{vu}$.

12: $\mathbf{il}$ – Integer Input

13: $\mathbf{iu}$ – Integer Input

On entry: if $\mathbf{range}=\text{'I'}$, il and iu specify the indices (in ascending order) of the smallest and largest eigenvalues to be returned, respectively.

If $\mathbf{range}=\text{'A'}$ or $\text{'V'}$, il and iu are not referenced.

Constraints:

• if $\mathbf{range}=\text{'I'}$ and $\mathbf{n}=0$, $\mathbf{il}=1$ and $\mathbf{iu}=0$;
• if $\mathbf{range}=\text{'I'}$ and $\mathbf{n}>0$, $1\le \mathbf{il}\le \mathbf{iu}\le \mathbf{n}$.

14: $\mathbf{abstol}$ – Real (Kind=nag_wp) Input

On entry: the absolute error tolerance for the eigenvalues. An approximate eigenvalue is accepted as converged when it is determined to lie in an interval $[a,b]$ of width less than or equal to

$$\mathbf{abstol}+\epsilon \max (\left|a\right|,\left|b\right|)\text{,}$$

where $\epsilon$ is the machine precision. If abstol is less than or equal to zero, then $\epsilon {\Vert T\Vert }_1$ will be used in its place, where $T$ is the tridiagonal matrix obtained by reducing $A$ to tridiagonal form. Eigenvalues will be computed most accurately when abstol is set to twice the underflow threshold $2\times \mathbf{x02amf}( )$, not zero. If this routine returns with $\mathbf{info}>\mathbf{0}$, indicating that some eigenvectors did not converge, try setting abstol to $2\times \mathbf{x02amf}( )$. See Demmel and Kahan (1990).

15: $\mathbf{m}$ – Integer Output

On exit: the total number of eigenvalues found. $0\le \mathbf{m}\le \mathbf{n}$.

If $\mathbf{range}=\text{'A'}$, $\mathbf{m}=\mathbf{n}$.

If $\mathbf{range}=\text{'I'}$, $\mathbf{m}=\mathbf{iu}-\mathbf{il}+1$.

16: $\mathbf{w}\left(\mathbf{n}\right)$ – Real (Kind=nag_wp) array Output

On exit: the first m elements contain the selected eigenvalues in ascending order.

17: $\mathbf{z}(\mathbf{ldz},*)$ – Complex (Kind=nag_wp) array Output

Note: the second dimension of the array z must be at least $\max (1,\mathbf{m})$ if $\mathbf{jobz}=\text{'V'}$, and at least $1$ otherwise.

On exit: if $\mathbf{jobz}=\text{'V'}$, then

• if $\mathbf{info}=\mathbf{0}$, the first m columns of $Z$ contain the orthonormal eigenvectors of the matrix $A$ corresponding to the selected eigenvalues, with the $i$th column of $Z$ holding the eigenvector associated with $\mathbf{w}\left(i\right)$;
• if an eigenvector fails to converge ($\mathbf{info}>\mathbf{0}$), then that column of $Z$ contains the latest approximation to the eigenvector, and the index of the eigenvector is returned in jfail.

If $\mathbf{jobz}=\text{'N'}$, z is not referenced.

Note:  you must ensure that at least $\max (1,\mathbf{m})$ columns are supplied in the array z; if $\mathbf{range}=\text{'V'}$, the exact value of m is not known in advance and an upper bound of at least n must be used.

18: $\mathbf{ldz}$ – Integer Input

On entry: the first dimension of the array z as declared in the (sub)program from which f08hpf is called.

Constraints:

• if $\mathbf{jobz}=\text{'V'}$, $\mathbf{ldz}\ge \max (1,\mathbf{n})$;
• otherwise $\mathbf{ldz}\ge 1$.

19: $\mathbf{work}\left(\mathbf{n}\right)$ – Complex (Kind=nag_wp) array Workspace

20: $\mathbf{rwork}\left(7\times \mathbf{n}\right)$ – Real (Kind=nag_wp) array Workspace

21: $\mathbf{iwork}\left(5\times \mathbf{n}\right)$ – Integer array Workspace

22: $\mathbf{jfail}\left(*\right)$ – Integer array Output

Note: the dimension of the array jfail must be at least $\max (1,\mathbf{n})$.

On exit: if $\mathbf{jobz}=\text{'V'}$, then

• if $\mathbf{info}=\mathbf{0}$, the first m elements of jfail are zero;
• if $\mathbf{info}>\mathbf{0}$, jfail contains the indices of the eigenvectors that failed to converge.

If $\mathbf{jobz}=\text{'N'}$, jfail is not referenced.

23: $\mathbf{info}$ – Integer Output

On exit: $\mathbf{info}=0$ unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

$\mathbf{info}<0$

If $\mathbf{info}=-i$, argument $i$ had an illegal value. An explanatory message is output, and execution of the program is terminated.

$\mathbf{info}>0$

The algorithm failed to converge; $⟨\mathit{\text{value}}⟩$ eigenvectors did not converge. Their indices are stored in array jfail.

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results