F08YVF (ZTGSYL) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

F08YVF (ZTGSYL)

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

F08YVF (ZTGSYL) solves the generalized complex triangular Sylvester equations.

2  Specification

SUBROUTINE F08YVF ( TRANS, IJOB, M, N, A, LDA, B, LDB, C, LDC, D, LDD, E, LDE, F, LDF, SCALE, DIF, WORK, LWORK, IWORK, INFO)
INTEGER  IJOB, M, N, LDA, LDB, LDC, LDD, LDE, LDF, LWORK, IWORK(M+N+2), INFO
REAL (KIND=nag_wp)  SCALE, DIF
COMPLEX (KIND=nag_wp)  A(LDA,*), B(LDB,*), C(LDC,*), D(LDD,*), E(LDE,*), F(LDF,*), WORK(max(1,LWORK))
CHARACTER(1)  TRANS
The routine may be called by its LAPACK name ztgsyl.

3  Description

F08YVF (ZTGSYL) solves either the generalized complex Sylvester equations
AR-LB =αC DR-LE =αF , (1)
or the equations
AHR+DHL =αC RBH+LEH =-αF , (2)
where the pair A,D are given m by m matrices in generalized Schur form, B,E are given n by n matrices in generalized Schur form and C,F are given m by n matrices. The pair R,L are the m by n solution matrices, and α is an output scaling factor determined by the routine to avoid overflow in computing R,L.
Equations (1) are equivalent to equations of the form
Zx=αb ,
where
Z = IA-BHI ID-EHI
and  is the Kronecker product. Equations (2) are then equivalent to
ZHy = αb .
The pair S,T are in generalized Schur form if S and T are upper triangular as returned, for example, by F08XNF (ZGGES), or F08XSF (ZHGEQZ) with JOB='S'.
Optionally, the routine estimates DifA,D,B,E, the separation between the matrix pairs A,D and B,E, which is the smallest singular value of Z. The estimate can be based on either the Frobenius norm, or the 1-norm. The 1-norm estimate can be three to ten times more expensive than the Frobenius norm estimate, but makes the condition estimation uniform with the nonsymmetric eigenproblem. The Frobenius norm estimate provides a low cost, but equally reliable estimate. For more information see Sections 2.4.8.3 and 4.11.1.3 of Anderson et al. (1999) and Kågström and Poromaa (1996).

4  References

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 http://www.netlib.org/lapack/lug
Kågström B (1994) A perturbation analysis of the generalized Sylvester equation AR-LB,DR-LE=c,F SIAM J. Matrix Anal. Appl. 15 1045–1060
Kågström B and Poromaa P (1996) LAPACK-style algorithms and software for solving the generalized Sylvester equation and estimating the separation between regular matrix pairs ACM Trans. Math. Software 22 78–103

5  Parameters

1:     TRANS – CHARACTER(1)Input
On entry: if TRANS='N', solve the generalized Sylvester equation (1).
If TRANS='C', solve the ‘conjugate transposed’ system (2).
Constraint: TRANS='N' or 'C'.
2:     IJOB – INTEGERInput
On entry: specifies what kind of functionality is to be performed when TRANS='N'.
IJOB=0
Solve (1) only.
IJOB=1
The functionality of IJOB=0 and 3.
IJOB=2
The functionality of IJOB=0 and 4.
IJOB=3
Only an estimate of Dif A,D,B,E  is computed based on the Frobenius norm.
IJOB=4
Only an estimate of Dif A,D,B,E  is computed based on the 1-norm.
If TRANS='C', IJOB is not referenced.
3:     M – INTEGERInput
On entry: m, the order of the matrices A and D, and the row dimension of the matrices C, F, R and L.
Constraint: M0.
4:     N – INTEGERInput
On entry: n, the order of the matrices B and E, and the column dimension of the matrices C, F, R and L.
Constraint: N0.
5:     A(LDA,*) – COMPLEX (KIND=nag_wp) arrayInput
Note: the second dimension of the array A must be at least max1,M.
On entry: the upper triangular matrix A.
6:     LDA – INTEGERInput
On entry: the first dimension of the array A as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
Constraint: LDAmax1,M.
7:     B(LDB,*) – COMPLEX (KIND=nag_wp) arrayInput
Note: the second dimension of the array B must be at least max1,N.
On entry: the upper triangular matrix B.
8:     LDB – INTEGERInput
On entry: the first dimension of the array B as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
Constraint: LDBmax1,N.
9:     C(LDC,*) – COMPLEX (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array C must be at least max1,N.
On entry: contains the right-hand-side matrix C.
On exit: if TRANS='C' or 'N' and IJOB=0, 1 or 2, C is overwritten by the solution matrix R.
If TRANS='N' and IJOB=3 or 4, C holds R, the solution achieved during the computation of the Dif estimate.
10:   LDC – INTEGERInput
On entry: the first dimension of the array C as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
Constraint: LDCmax1,M.
11:   D(LDD,*) – COMPLEX (KIND=nag_wp) arrayInput
Note: the second dimension of the array D must be at least max1,M.
On entry: the upper triangular matrix D.
12:   LDD – INTEGERInput
On entry: the first dimension of the array D as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
Constraint: LDDmax1,M.
13:   E(LDE,*) – COMPLEX (KIND=nag_wp) arrayInput
Note: the second dimension of the array E must be at least max1,N.
On entry: the upper triangular matrix E.
14:   LDE – INTEGERInput
On entry: the first dimension of the array E as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
Constraint: LDEmax1,N.
15:   F(LDF,*) – COMPLEX (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array F must be at least max1,N.
On entry: contains the right-hand side matrix F.
On exit: if TRANS='C' or 'N' and IJOB=0, 1 or 2, F is overwritten by the solution matrix L.
If TRANS='N' and IJOB=3 or 4, F holds L, the solution achieved during the computation of the Dif estimate.
16:   LDF – INTEGERInput
On entry: the first dimension of the array F as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
Constraint: LDFmax1,M.
17:   SCALE – REAL (KIND=nag_wp)Output
On exit: α, the scaling factor in (1) or (2).
If 0<SCALE<1, C and F hold the solutions R and L, respectively, to a slightly perturbed system but the input arrays A, B, D and E have not been changed.
If SCALE=0, C and F hold the solutions R and L, respectively, to the homogeneous system with C=F=0. In this case DIF is not referenced.
Normally, SCALE=1.
18:   DIF – REAL (KIND=nag_wp)Output
19:   WORK(max1,LWORK) – COMPLEX (KIND=nag_wp) arrayWorkspace
20:   LWORK – INTEGERInput
On entry: the dimension of the array WORK as declared in the (sub)program from which F08YVF (ZTGSYL) is called.
If LWORK=-1, a workspace query is assumed; the routine only calculates the minimum size 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 LWORK-1,
  • if TRANS='N' and IJOB=1 or 2, LWORK2×M×N;
  • otherwise LWORK1.
.
21:   IWORK(M+N+2) – INTEGER arrayWorkspace
22:   INFO – INTEGEROutput

6  Error Indicators and Warnings

Errors or warnings detected by the routine:
INFO<0
If INFO=-i, argument i had an illegal value. An explanatory message is output, and execution of the program is terminated.
INFO>0
A,D and B,E have common or close eigenvalues and so no solution could be computed.

7  Accuracy

See Kågström (1994) for a perturbation analysis of the generalized Sylvester equation.

8  Further Comments

The total number of floating point operations needed to solve the generalized Sylvester equations is approximately 8mnn+m. The Frobenius norm estimate of Dif does not require additional significant computation, but the 1-norm estimate is typically five times more expensive.
The real analogue of this routine is F08YHF (DTGSYL).

9  Example

This example solves the generalized Sylvester equations
AR-LB =αC DR-LE =αF ,
where
A = 4.0+4.0i 1.0+1.0i 1.0+1.0i 2.0-1.0i 0.0i+0.0 2.0+1.0i 1.0+1.0i 1.0+1.0i 0.0i+0.0 0.0i+0.0 2.0-1.0i 1.0+1.0i 0.0i+0.0 0.0i+0.0 0.0i+0.0 6.0-2.0i ,
B = 2.0 1.0+1.0i 1.0+1.0i 3.0-1.0i 0.0 1.0i+0.0 2.0+1.0i 1.0+1.0i 0.0 0.0i+0.0 1.0i+0.0 1.0+1.0i 0.0 0.0i+0.0 0.0i+0.0 2.0i+0.0 ,
D = 1.0+1.0i 1.0-1.0i 1.0+1.0i 1.0-1.0i 0.0i+0.0 6.0-4.0i 1.0-1.0i 1.0+1.0i 0.0i+0.0 0.0i+0.0 2.0+4.0i 1.0-1.0i 0.0i+0.0 0.0i+0.0 0.0i+0.0 2.0+3.0i ,
E = 1.0 1.0+1.0i 1.0-1.0i 1.0+1.0i 0.0 2.0i+0.0 1.0+1.0i 1.0-1.0i 0.0 0.0i+0.0 2.0i+0.0 1.0+1.0i 0.0 0.0i+0.0 0.0i+0.0 1.0i+0.0 ,
C = -13.0+9.0i 2.0+8.0i -2.0+8.0i -2.0+5.0i -9.0-1.0i 0.0+5.0i -7.0-3.0i -6.0-0.0i -1.0+1.0i 4.0+2.0i 4.0-5.0i 9.0-5.0i -6.0+6.0i 9.0+1.0i -2.0+4.0i 22.0-8.0i
and
F = -6.0+05.0i 4.0-4.0i -3.0+11.0i 3.0-07.0i -5.0+11.0i 12.0-4.0i -2.0+02.0i 0.0+14.0i -5.0-01.0i 0.0+4.0i -2.0+10.0i 3.0-01.0i -6.0-02.0i 1.0+1.0i -7.0-03.0i 4.0+07.0i .

9.1  Program Text

Program Text (f08yvfe.f90)

9.2  Program Data

Program Data (f08yvfe.d)

9.3  Program Results

Program Results (f08yvfe.r)


F08YVF (ZTGSYL) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2011