f08fqf computes all the eigenvalues and, optionally, all the eigenvectors of a complex Hermitian matrix.
If the eigenvectors are requested, then it uses a divide-and-conquer algorithm to compute eigenvalues and eigenvectors. However, if only eigenvalues are required, then it uses the Pal–Walker–Kahan variant of the or algorithm.
The routine may be called by the names f08fqf, nagf_lapackeig_zheevd or its LAPACK name zheevd.
3Description
f08fqf computes all the eigenvalues and, optionally, all the eigenvectors of a complex Hermitian matrix .
In other words, it can compute the spectral factorization of as
where is a real diagonal matrix whose diagonal elements are the eigenvalues , and is the (complex) unitary matrix whose columns are the eigenvectors . Thus
4References
Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia https://www.netlib.org/lapack/lug
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
5Arguments
1: – Character(1)Input
On entry: indicates whether eigenvectors are computed.
Only eigenvalues are computed.
Eigenvalues and eigenvectors are computed.
Constraint:
or .
2: – Character(1)Input
On entry: indicates whether the upper or lower triangular part of is stored.
The upper triangular part of is stored.
The lower triangular part of is stored.
Constraint:
or .
3: – IntegerInput
On entry: , the order of the matrix .
Constraint:
.
4: – Complex (Kind=nag_wp) arrayInput/Output
Note: the second dimension of the array a
must be at least
.
On entry: the Hermitian matrix .
If , the upper triangular part of must be stored and the elements of the array below the diagonal are not referenced.
If , the lower triangular part of must be stored and the elements of the array above the diagonal are not referenced.
On exit: if , a is overwritten by the unitary matrix which contains the eigenvectors of .
5: – IntegerInput
On entry: the first dimension of the array a as declared in the (sub)program from which f08fqf is called.
Constraint:
.
6: – Real (Kind=nag_wp) arrayOutput
Note: the dimension of the array w
must be at least
.
On exit: the eigenvalues of the matrix in ascending order.
7: – Complex (Kind=nag_wp) arrayWorkspace
On exit: if , the real part of contains the required minimal size of lwork.
8: – IntegerInput
On entry: the dimension of the array work as declared in the (sub)program from which f08fqf is called.
If , a workspace query is assumed; the routine only calculates the minimum dimension of the work array, returns this value as the first entry of the work array, and no error message related to lwork is issued.
Constraints:
if , or ;
if and , or ;
if and , or .
9: – Real (Kind=nag_wp) arrayWorkspace
On exit: if , contains the required minimal size of .
10: – IntegerInput
On entry: the dimension of the array rwork as declared in the (sub)program from which f08fqf is called.
If , a workspace query is assumed; the routine only calculates the minimum dimension of the rwork array, returns this value as the first entry of the rwork array, and no error message related to lrwork is issued.
Constraints:
if , or ;
if and , or ;
if and , or .
11: – Integer arrayWorkspace
On exit: if , contains the required minimal size of liwork.
12: – IntegerInput
On entry: the dimension of the array iwork as declared in the (sub)program from which f08fqf is called.
If , a workspace query is assumed; the routine only calculates the minimum dimension of the iwork array, returns this value as the first entry of the iwork array, and no error message related to liwork is issued.
Constraints:
if , or ;
if and , or ;
if and , or .
13: – IntegerOutput
On exit: unless the routine detects an error (see Section 6).
6Error Indicators and Warnings
If , argument had an illegal value. An explanatory message is output, and execution of the program is terminated.
If and , the algorithm failed to converge; elements of an intermediate tridiagonal form did not converge to zero; if and , then the algorithm failed to compute an eigenvalue while working on the submatrix lying in rows and column through .
7Accuracy
The computed eigenvalues and eigenvectors are exact for a nearby matrix , where
and is the machine precision. See Section 4.7 of Anderson et al. (1999) for further details.
8Parallelism and Performance
Background information to multithreading can be found in the Multithreading documentation.
f08fqf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f08fqf 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 routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.