stgsen(3S)

STGSEN - reorder the generalized real Schur decomposition of a real matrix pair (A, B) (in terms of an orthonormal equivalence trans- formation Q' * (A, B) * Z), so that a selected cluster of eigenvalues appears in the leading diagonal blocks of the upper quasi-triangular matrix A and the upper triangular B

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NAME
     STGSEN - reorder the generalized real Schur decomposition of a real
     matrix pair (A, B) (in terms of an orthonormal equivalence trans-
     formation Q' * (A, B) * Z), so that a selected cluster of eigenvalues
     appears in the leading diagonal blocks of the upper quasi-triangular
     matrix A and the upper triangular B

SYNOPSIS
     SUBROUTINE STGSEN( IJOB, WANTQ, WANTZ, SELECT, N, A, LDA, B, LDB, ALPHAR,
                        ALPHAI, BETA, Q, LDQ, Z, LDZ, M, PL, PR, DIF, WORK,
                        LWORK, IWORK, LIWORK, INFO )

         LOGICAL        WANTQ, WANTZ

         INTEGER        IJOB, INFO, LDA, LDB, LDQ, LDZ, LIWORK, LWORK, M, N

         REAL           PL, PR

         LOGICAL        SELECT( * )

         INTEGER        IWORK( * )

         REAL           A( LDA, * ), ALPHAI( * ), ALPHAR( * ), B( LDB, * ),
                        BETA( * ), DIF( * ), Q( LDQ, * ), WORK( * ), Z( LDZ, *
                        )

IMPLEMENTATION
     These routines are part of the SCSL Scientific Library and can be loaded
     using either the -lscs or the -lscs_mp option.  The -lscs_mp option
     directs the linker to use the multi-processor version of the library.

     When linking to SCSL with -lscs or -lscs_mp, the default integer size is
     4 bytes (32 bits). Another version of SCSL is available in which integers
     are 8 bytes (64 bits).  This version allows the user access to larger
     memory sizes and helps when porting legacy Cray codes.  It can be loaded
     by using the -lscs_i8 option or the -lscs_i8_mp option. A program may use
     only one of the two versions; 4-byte integer and 8-byte integer library
     calls cannot be mixed.

PURPOSE
     STGSEN reorders the generalized real Schur decomposition of a real matrix
     pair (A, B) (in terms of an orthonormal equivalence trans- formation Q' *
     (A, B) * Z), so that a selected cluster of eigenvalues appears in the
     leading diagonal blocks of the upper quasi-triangular matrix A and the
     upper triangular B. The leading columns of Q and Z form orthonormal bases
     of the corresponding left and right eigen- spaces (deflating subspaces).
     (A, B) must be in generalized real Schur canonical form (as returned by
     SGGES), i.e. A is block upper triangular with 1-by-1 and 2-by-2 diagonal
     blocks. B is upper triangular.

     STGSEN also computes the generalized eigenvalues

                 w(j) = (ALPHAR(j) + i*ALPHAI(j))/BETA(j)

     of the reordered matrix pair (A, B).

     Optionally, STGSEN computes the estimates of reciprocal condition numbers
     for eigenvalues and eigenspaces. These are Difu[(A11,B11), (A22,B22)] and
     Difl[(A11,B11), (A22,B22)], i.e. the separation(s) between the matrix
     pairs (A11, B11) and (A22,B22) that correspond to the selected cluster
     and the eigenvalues outside the cluster, resp., and norms of
     "projections" onto left and right eigenspaces w.r.t.  the selected
     cluster in the (1,1)-block.


ARGUMENTS
     IJOB    (input) INTEGER
             Specifies whether condition numbers are required for the cluster
             of eigenvalues (PL and PR) or the deflating subspaces (Difu and
             Difl):
             =0: Only reorder w.r.t. SELECT. No extras.
             =1: Reciprocal of norms of "projections" onto left and right
             eigenspaces w.r.t. the selected cluster (PL and PR).  =2: Upper
             bounds on Difu and Difl. F-norm-based estimate
             (DIF(1:2)).
             =3: Estimate of Difu and Difl. 1-norm-based estimate
             (DIF(1:2)).  About 5 times as expensive as IJOB = 2.  =4: Compute
             PL, PR and DIF (i.e. 0, 1 and 2 above): Economic version to get
             it all.  =5: Compute PL, PR and DIF (i.e. 0, 1 and 3 above)

     WANTQ   (input) LOGICAL

     WANTZ   (input) LOGICAL

     SELECT  (input) LOGICAL array, dimension (N)
             SELECT specifies the eigenvalues in the selected cluster.  To
             select a real eigenvalue w(j), SELECT(j) must be set to w(j) and
             w(j+1), corresponding to a 2-by-2 diagonal block, either
             SELECT(j) or SELECT(j+1) or both must be set to either both
             included in the cluster or both excluded.

     N       (input) INTEGER
             The order of the matrices A and B. N >= 0.

     A       (input/output) REAL array, dimension(LDA,N)
             On entry, the upper quasi-triangular matrix A, with (A, B) in
             generalized real Schur canonical form.  On exit, A is overwritten
             by the reordered matrix A.

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

     B       (input/output) REAL array, dimension(LDB,N)
             On entry, the upper triangular matrix B, with (A, B) in
             generalized real Schur canonical form.  On exit, B is overwritten
             by the reordered matrix B.

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

     ALPHAR  (output) REAL array, dimension (N)
             ALPHAI  (output) REAL array, dimension (N) BETA    (output) REAL
             array, dimension (N) On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j),
             j=1,...,N, will be the generalized eigenvalues.  ALPHAR(j) +
             ALPHAI(j)*i and BETA(j),j=1,...,N  are the diagonals of the
             complex Schur form (S,T) that would result if the 2-by-2 diagonal
             blocks of the real generalized Schur form of (A,B) were further
             reduced to triangular form using complex unitary transformations.
             If ALPHAI(j) is zero, then the j-th eigenvalue is real; if
             positive, then the j-th and (j+1)-st eigenvalues are a complex
             conjugate pair, with ALPHAI(j+1) negative.

     Q       (input/output) REAL array, dimension (LDQ,N)
             On entry, if WANTQ = .TRUE., Q is an N-by-N matrix.  On exit, Q
             has been postmultiplied by the left orthogonal transformation
             matrix which reorder (A, B); The leading M columns of Q form
             orthonormal bases for the specified pair of left eigenspaces
             (deflating subspaces).  If WANTQ = .FALSE., Q is not referenced.

     LDQ     (input) INTEGER
             The leading dimension of the array Q.  LDQ >= 1; and if WANTQ =
             .TRUE., LDQ >= N.

     Z       (input/output) REAL array, dimension (LDZ,N)
             On entry, if WANTZ = .TRUE., Z is an N-by-N matrix.  On exit, Z
             has been postmultiplied by the left orthogonal transformation
             matrix which reorder (A, B); The leading M columns of Z form
             orthonormal bases for the specified pair of left eigenspaces
             (deflating subspaces).  If WANTZ = .FALSE., Z is not referenced.

     LDZ     (input) INTEGER
             The leading dimension of the array Z. LDZ >= 1; If WANTZ =
             .TRUE., LDZ >= N.

     M       (output) INTEGER
             The dimension of the specified pair of left and right eigen-
             spaces (deflating subspaces). 0 <= M <= N.

             PL, PR  (output) REAL If IJOB = 1, 4 or 5, PL, PR are lower
             bounds on the reciprocal of the norm of "projections" onto left
             and right eigenspaces with respect to the selected cluster.  0 <
             PL, PR <= 1.  If M = 0 or M = N, PL = PR  = 1.  If IJOB = 0, 2 or
             3, PL and PR are not referenced.

     DIF     (output) REAL array, dimension (2).
             If IJOB >= 2, DIF(1:2) store the estimates of Difu and Difl.
             If IJOB = 2 or 4, DIF(1:2) are F-norm-based upper bounds on
             Difu and Difl. If IJOB = 3 or 5, DIF(1:2) are 1-norm-based
             estimates of Difu and Difl.  If M = 0 or N, DIF(1:2) = F-norm([A,
             B]).  If IJOB = 0 or 1, DIF is not referenced.

     WORK    (workspace/output) REAL array, dimension (LWORK)
             IF IJOB = 0, WORK is not referenced.  Otherwise, on exit, if INFO
             = 0, WORK(1) returns the optimal LWORK.

     LWORK   (input) INTEGER
             The dimension of the array WORK. LWORK >=  4*N+16.  If IJOB = 1,
             2 or 4, LWORK >= MAX(4*N+16, 2*M*(N-M)).  If IJOB = 3 or 5, LWORK
             >= MAX(4*N+16, 4*M*(N-M)).

             If LWORK = -1, then a workspace query is assumed; the routine
             only calculates the optimal 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 by XERBLA.

     IWORK   (workspace/output) INTEGER array, dimension (LIWORK)
             IF IJOB = 0, IWORK is not referenced.  Otherwise, on exit, if
             INFO = 0, IWORK(1) returns the optimal LIWORK.

     LIWORK  (input) INTEGER
             The dimension of the array IWORK. LIWORK >= 1.  If IJOB = 1, 2 or
             4, LIWORK >=  N+6.  If IJOB = 3 or 5, LIWORK >= MAX(2*M*(N-M),
             N+6).

             If LIWORK = -1, then a workspace query is assumed; the routine
             only calculates the optimal size of the IWORK array, returns this
             value as the first entry of the IWORK array, and no error message
             related to LIWORK is issued by XERBLA.

     INFO    (output) INTEGER
             =0: Successful exit.
             <0: If INFO = -i, the i-th argument had an illegal value.
             =1: Reordering of (A, B) failed because the transformed matrix
             pair (A, B) would be too far from generalized Schur form; the
             problem is very ill-conditioned.  (A, B) may have been partially
             reordered.  If requested, 0 is returned in DIF(*), PL and PR.

FURTHER DETAILS
     STGSEN first collects the selected eigenvalues by computing orthogonal U
     and W that move them to the top left corner of (A, B).  In other words,
     the selected eigenvalues are the eigenvalues of (A11, B11) in:

                   U'*(A, B)*W = (A11 A12) (B11 B12) n1
                                 ( 0  A22),( 0  B22) n2
                                   n1  n2    n1  n2

     where N = n1+n2 and U' means the transpose of U. The first n1 columns of
     U and W span the specified pair of left and right eigenspaces (deflating
     subspaces) of (A, B).

     If (A, B) has been obtained from the generalized real Schur decomposition
     of a matrix pair (C, D) = Q*(A, B)*Z', then the reordered generalized
     real Schur form of (C, D) is given by

              (C, D) = (Q*U)*(U'*(A, B)*W)*(Z*W)',

     and the first n1 columns of Q*U and Z*W span the corresponding deflating
     subspaces of (C, D) (Q and Z store Q*U and Z*W, resp.).

     Note that if the selected eigenvalue is sufficiently ill-conditioned,
     then its value may differ significantly from its value before reordering.

     The reciprocal condition numbers of the left and right eigenspaces
     spanned by the first n1 columns of U and W (or Q*U and Z*W) may be
     returned in DIF(1:2), corresponding to Difu and Difl, resp.

     The Difu and Difl are defined as:

          Difu[(A11, B11), (A22, B22)] = sigma-min( Zu )
     and
          Difl[(A11, B11), (A22, B22)] = Difu[(A22, B22), (A11, B11)],

     where sigma-min(Zu) is the smallest singular value of the (2*n1*n2)-by-
     (2*n1*n2) matrix

          Zu = [ kron(In2, A11)  -kron(A22', In1) ]
               [ kron(In2, B11)  -kron(B22', In1) ].

     Here, Inx is the identity matrix of size nx and A22' is the transpose of
     A22. kron(X, Y) is the Kronecker product between the matrices X and Y.

     When DIF(2) is small, small changes in (A, B) can cause large changes in
     the deflating subspace. An approximate (asymptotic) bound on the maximum
     angular error in the computed deflating subspaces is

          EPS * norm((A, B)) / DIF(2),

     where EPS is the machine precision.

     The reciprocal norm of the projectors on the left and right eigenspaces
     associated with (A11, B11) may be returned in PL and PR.  They are
     computed as follows. First we compute L and R so that P*(A, B)*Q is block
     diagonal, where

          P = ( I -L ) n1           Q = ( I R ) n1
              ( 0  I ) n2    and        ( 0 I ) n2
                n1 n2                    n1 n2

     and (L, R) is the solution to the generalized Sylvester equation

          A11*R - L*A22 = -A12
          B11*R - L*B22 = -B12

     Then PL = (F-norm(L)**2+1)**(-1/2) and PR = (F-norm(R)**2+1)**(-1/2).  An
     approximate (asymptotic) bound on the average absolute error of the
     selected eigenvalues is

          EPS * norm((A, B)) / PL.

     There are also global error bounds which valid for perturbations up to a
     certain restriction:  A lower bound (x) on the smallest F-norm(E,F) for
     which an eigenvalue of (A11, B11) may move and coalesce with an
     eigenvalue of (A22, B22) under perturbation (E,F), (i.e. (A + E, B + F),
     is

      x = min(Difu,Difl)/((1/(PL*PL)+1/(PR*PR))**(1/2)+2*max(1/PL,1/PR)).

     An approximate bound on x can be computed from DIF(1:2), PL and PR.

     If y = ( F-norm(E,F) / x) <= 1, the angles between the perturbed (L', R')
     and unperturbed (L, R) left and right deflating subspaces associated with
     the selected cluster in the (1,1)-blocks can be bounded as

      max-angle(L, L') <= arctan( y * PL / (1 - y * (1 - PL * PL)**(1/2))
      max-angle(R, R') <= arctan( y * PR / (1 - y * (1 - PR * PR)**(1/2))

     See LAPACK User's Guide section 4.11 or the following references for more
     information.

     Note that if the default method for computing the Frobenius-norm- based
     estimate DIF is not wanted (see SLATDF), then the parameter IDIFJB (see
     below) should be changed from 3 to 4 (routine SLATDF (IJOB = 2 will be
     used)). See STGSYL for more details.

     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.


SEE ALSO
     INTRO_LAPACK(3S), INTRO_SCSL(3S)

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