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ztgsna(3P)		    Sun Performance Library		    ztgsna(3P)

NAME
       ztgsna  - estimate reciprocal condition numbers for specified eigenval‐
       ues and/or eigenvectors of a matrix pair (A, B)

SYNOPSIS
       SUBROUTINE ZTGSNA(JOB, HOWMNT, SELECT, N, A, LDA, B, LDB, VL, LDVL,
	     VR, LDVR, S, DIF, MM, M, WORK, LWORK, IWORK, INFO)

       CHARACTER * 1 JOB, HOWMNT
       DOUBLE COMPLEX A(LDA,*), B(LDB,*), VL(LDVL,*), VR(LDVR,*), WORK(*)
       INTEGER N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER IWORK(*)
       LOGICAL SELECT(*)
       DOUBLE PRECISION S(*), DIF(*)

       SUBROUTINE ZTGSNA_64(JOB, HOWMNT, SELECT, N, A, LDA, B, LDB, VL,
	     LDVL, VR, LDVR, S, DIF, MM, M, WORK, LWORK, IWORK, INFO)

       CHARACTER * 1 JOB, HOWMNT
       DOUBLE COMPLEX A(LDA,*), B(LDB,*), VL(LDVL,*), VR(LDVR,*), WORK(*)
       INTEGER*8 N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER*8 IWORK(*)
       LOGICAL*8 SELECT(*)
       DOUBLE PRECISION S(*), DIF(*)

   F95 INTERFACE
       SUBROUTINE TGSNA(JOB, HOWMNT, SELECT, [N], A, [LDA], B, [LDB], VL,
	      [LDVL], VR, [LDVR], S, DIF, MM, M, [WORK], [LWORK], [IWORK],
	      [INFO])

       CHARACTER(LEN=1) :: JOB, HOWMNT
       COMPLEX(8), DIMENSION(:) :: WORK
       COMPLEX(8), DIMENSION(:,:) :: A, B, VL, VR
       INTEGER :: N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER, DIMENSION(:) :: IWORK
       LOGICAL, DIMENSION(:) :: SELECT
       REAL(8), DIMENSION(:) :: S, DIF

       SUBROUTINE TGSNA_64(JOB, HOWMNT, SELECT, [N], A, [LDA], B, [LDB], VL,
	      [LDVL], VR, [LDVR], S, DIF, MM, M, [WORK], [LWORK], [IWORK],
	      [INFO])

       CHARACTER(LEN=1) :: JOB, HOWMNT
       COMPLEX(8), DIMENSION(:) :: WORK
       COMPLEX(8), DIMENSION(:,:) :: A, B, VL, VR
       INTEGER(8) :: N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER(8), DIMENSION(:) :: IWORK
       LOGICAL(8), DIMENSION(:) :: SELECT
       REAL(8), DIMENSION(:) :: S, DIF

   C INTERFACE
       #include <sunperf.h>

       void ztgsna(char job, char howmnt, int *select,	int  n,	 doublecomplex
		 *a,  int  lda,	 doublecomplex *b, int ldb, doublecomplex *vl,
		 int ldvl, doublecomplex *vr,  int  ldvr,  double  *s,	double
		 *dif, int mm, int *m, int *info);

       void  ztgsna_64(char job, char howmnt, long *select, long n, doublecom‐
		 plex *a, long lda, doublecomplex *b, long ldb,	 doublecomplex
		 *vl, long ldvl, doublecomplex *vr, long ldvr, double *s, dou‐
		 ble *dif, long mm, long *m, long *info);

PURPOSE
       ztgsna estimates reciprocal condition numbers for specified eigenvalues
       and/or eigenvectors of a matrix pair (A, B).

       (A,  B)	must  be in generalized Schur canonical form, that is, A and B
       are both upper triangular.

ARGUMENTS
       JOB (input)
		 Specifies whether condition numbers are required  for	eigen‐
		 values (S) or eigenvectors (DIF):
		 = 'E': for eigenvalues only (S);
		 = 'V': for eigenvectors only (DIF);
		 = 'B': for both eigenvalues and eigenvectors (S and DIF).

       HOWMNT (input)
		 = 'A': compute condition numbers for all eigenpairs;
		 =  'S':  compute  condition  numbers  for selected eigenpairs
		 specified by the array SELECT.

       SELECT (input)
		 If HOWMNT = 'S', SELECT specifies the	eigenpairs  for	 which
		 condition  numbers  are required. To select condition numbers
		 for the corresponding	j-th  eigenvalue  and/or  eigenvector,
		 SELECT(j)  must be set to .TRUE..  If HOWMNT = 'A', SELECT is
		 not referenced.

       N (input) The order of the square matrix pair (A, B). N >= 0.

       A (input) The upper triangular matrix A in the pair (A,B).

       LDA (input)
		 The leading dimension of the array A. LDA >= max(1,N).

       B (input) The upper triangular matrix B in the pair (A, B).

       LDB (input)
		 The leading dimension of the array B. LDB >= max(1,N).

       VL (input)
		 If JOB = 'E' or 'B', VL must contain left eigenvectors of (A,
		 B),  corresponding  to the eigenpairs specified by HOWMNT and
		 SELECT.  The eigenvectors must be stored in consecutive  col‐
		 umns  of  VL, as returned by ZTGEVC.  If JOB = 'V', VL is not
		 referenced.

       LDVL (input)
		 The leading dimension of the array VL. LDVL >= 1; and If  JOB
		 = 'E' or 'B', LDVL >= N.

       VR (input)
		 If  JOB  =  'E' or 'B', VR must contain right eigenvectors of
		 (A, B), corresponding to the eigenpairs specified  by	HOWMNT
		 and  SELECT.	The eigenvectors must be stored in consecutive
		 columns of VR, as returned by ZTGEVC.	If JOB =  'V',	VR  is
		 not referenced.

       LDVR (input)
		 The  leading  dimension  of the array VR. LDVR >= 1; If JOB =
		 'E' or 'B', LDVR >= N.

       S (output)
		 If JOB = 'E' or 'B', the reciprocal condition numbers of  the
		 selected  eigenvalues,	 stored in consecutive elements of the
		 array.	 If JOB = 'V', S is not referenced.

       DIF (output)
		 If JOB = 'V' or 'B', the estimated reciprocal condition  num‐
		 bers of the selected eigenvectors, stored in consecutive ele‐
		 ments of the array.  If the eigenvalues cannot	 be  reordered
		 to  compute  DIF(j),  DIF(j) is set to 0; this can only occur
		 when the true value would be very small anyway.  For each ei‐
		 genvalue/vector  specified  by SELECT, DIF stores a Frobenius
		 norm-based estimate of Difl.  If JOB = 'E', DIF is not refer‐
		 enced.

       MM (input)
		 The number of elements in the arrays S and DIF. MM >= M.

       M (output)
		 The  number of elements of the arrays S and DIF used to store
		 the specified condition numbers; for each selected eigenvalue
		 one element is used. If HOWMNT = 'A', M is set to N.

       WORK (workspace)
		 If JOB = 'E', WORK is not referenced.	Otherwise, on exit, if
		 INFO = 0, WORK(1) returns the optimal LWORK.

       LWORK (input)
		 The dimension of the array WORK. LWORK >= max(1, N).  If  JOB
		 = 'V' or 'B', LWORK >= max(1, 2*N*N).

       IWORK (workspace)
		 dimension(N+2) If JOB = 'E', IWORK is not referenced.

       INFO (output)
		 = 0: Successful exit
		 < 0: If INFO = -i, the i-th argument had an illegal value

FURTHER DETAILS
       The  reciprocal	of the condition number of the i-th generalized eigen‐
       value w = (a, b) is defined as

	       S(I) = (|v'Au|**2 + |v'Bu|**2)**(1/2) / (norm(u)*norm(v))

       where u and v are the right and left eigenvectors of (A, B) correspond‐
       ing  to	w;  |z|	 denotes the absolute value of the complex number, and
       norm(u) denotes the 2-norm of the vector u. The pair (a, b) corresponds
       to  an  eigenvalue  w = a/b (= v'Au/v'Bu) of the matrix pair (A, B). If
       both a and b equal zero, then (A,B)  is	singular  and  S(I)  =	-1  is
       returned.

       An  approximate	error  bound  on the chordal distance between the i-th
       computed generalized eigenvalue w and the corresponding exact eigenval‐
       ue lambda is

	       chord(w, lambda) <=   EPS * norm(A, B) / S(I),

       where EPS is the machine precision.

       The  reciprocal	of the condition number of the right eigenvector u and
       left eigenvector v corresponding to the	generalized  eigenvalue	 w  is
       defined as follows. Suppose

			(A, B) = ( a   *  ) ( b	 *  )  1
				 ( 0  A22 ),( 0 B22 )  n-1
				   1  n-1     1 n-1

       Then the reciprocal condition number DIF(I) is

	       Difl[(a, b), (A22, B22)]	 = sigma-min( Zl )

       where sigma-min(Zl) denotes the smallest singular value of

	      Zl = [ kron(a, In-1) -kron(1, A22) ]
		   [ kron(b, In-1) -kron(1, B22) ].

       Here  In-1  is  the identity matrix of size n-1 and X' is the conjugate
       transpose of X. kron(X, Y) is the Kronecker product between the	matri‐
       ces X and Y.

       We  approximate	the smallest singular value of Zl with an upper bound.
       This is done by ZLATDF.

       An approximate error bound for a computed eigenvector VL(i) or VR(i) is
       given by

			   EPS * norm(A, B) / DIF(i).

       See ref. [2-3] for more details and further references.

       Based on contributions by
	  Bo Kagstrom and Peter Poromaa, Department of Computing Science,
	  Umea University, S-901 87 Umea, Sweden.

       References
       ==========

       [1] B. Kagstrom; A Direct Method for Reordering Eigenvalues in the
	   Generalized Real Schur Form of a Regular Matrix Pair (A, B), in
	   M.S. Moonen et al (eds), Linear Algebra for Large Scale and
	   Real-Time Applications, Kluwer Academic Publ. 1993, pp 195-218.

       [2] B. Kagstrom and P. Poromaa; Computing Eigenspaces with Specified
	   Eigenvalues of a Regular Matrix Pair (A, B) and Condition
	   Estimation: Theory, Algorithms and Software, Report
	   UMINF - 94.04, Department of Computing Science, Umea University,
	   S-901 87 Umea, Sweden, 1994. Also as LAPACK Working Note 87.
	   To appear in Numerical Algorithms, 1996.

       [3] B. Kagstrom and P. Poromaa, LAPACK-Style Algorithms and Software
	   for Solving the Generalized Sylvester Equation and Estimating the
	   Separation between Regular Matrix Pairs, Report UMINF - 93.23,
	   Department of Computing Science, Umea University, S-901 87 Umea,
	   Sweden, December 1993, Revised April 1994, Also as LAPACK Working
	   Note 75.
	   To appear in ACM Trans. on Math. Software, Vol 22, No 1, 1996.

				  6 Mar 2009			    ztgsna(3P)
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