STRSEN(3)                  MathKeisan LAPACK routine                 STRSEN(3)



NAME
       STRSEN - the real Schur factorization of a real matrix A = Q*T*Q**T, so
       that a selected cluster of eigenvalues appears in the leading  diagonal
       blocks of the upper quasi-triangular matrix T,

SYNOPSIS
       SUBROUTINE STRSEN( JOB, COMPQ, SELECT, N, T, LDT, Q, LDQ, WR, WI, M, S,
                          SEP, WORK, LWORK, IWORK, LIWORK, INFO )

           CHARACTER      COMPQ, JOB

           INTEGER        INFO, LDQ, LDT, LIWORK, LWORK, M, N

           REAL           S, SEP

           LOGICAL        SELECT( * )

           INTEGER        IWORK( * )

           REAL           Q( LDQ, * ), T( LDT, * ), WI( * ), WORK( * ), WR(  *
                          )

PURPOSE
       STRSEN  reorders  the  real  Schur  factorization  of a real matrix A =
       Q*T*Q**T, so that a selected cluster  of  eigenvalues  appears  in  the
       leading diagonal blocks of the upper quasi-triangular matrix T, and the
       leading columns of Q form an orthonormal  basis  of  the  corresponding
       right invariant subspace.

       Optionally the routine computes the reciprocal condition numbers of the
       cluster of eigenvalues and/or the invariant subspace.

       T must be in Schur canonical form (as returned  by  SHSEQR),  that  is,
       block  upper  triangular  with  1-by-1 and 2-by-2 diagonal blocks; each
       2-by-2 diagonal block has its diagonal elemnts equal and its off-diago-
       nal elements of opposite sign.


ARGUMENTS
       JOB     (input) CHARACTER*1
               Specifies  whether condition numbers are required for the clus-
               ter of eigenvalues (S) or the invariant subspace (SEP):
               = 'N': none;
               = 'E': for eigenvalues only (S);
               = 'V': for invariant subspace only (SEP);
               = 'B': for both eigenvalues and invariant subspace (S and SEP).

       COMPQ   (input) CHARACTER*1
               = 'V': update the matrix Q of Schur vectors;
               = 'N': do not update Q.

       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 matrix T. N >= 0.

       T       (input/output) REAL array, dimension (LDT,N)
               On entry, the upper quasi-triangular matrix T, in Schur canoni-
               cal form.  On exit, T is overwritten by the reordered matrix T,
               again in Schur canonical form, with the selected eigenvalues in
               the leading diagonal blocks.

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

       Q       (input/output) REAL array, dimension (LDQ,N)
               On entry, if COMPQ = 'V', the matrix Q of  Schur  vectors.   On
               exit, if COMPQ = 'V', Q has been postmultiplied by the orthogo-
               nal transformation matrix  which  reorders  T;  the  leading  M
               columns  of  Q  form  an  orthonormal  basis  for the specified
               invariant subspace.  If COMPQ = 'N', Q is not referenced.

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

       WR      (output) REAL array, dimension (N)
               WI       (output) REAL array, dimension (N) The real and imagi-
               nary parts, respectively, of the reordered  eigenvalues  of  T.
               The eigenvalues are stored in the same order as on the diagonal
               of T, with WR(i) = T(i,i) and, if T(i:i+1,i:i+1)  is  a  2-by-2
               diagonal  block, WI(i) > 0 and WI(i+1) = -WI(i). Note that if a
               complex eigenvalue is sufficiently  ill-conditioned,  then  its
               value  may  differ significantly from its value before reorder-
               ing.

       M       (output) INTEGER
               The dimension of the specified invariant subspace.  0 < = M  <=
               N.

       S       (output) REAL
               If  JOB = 'E' or 'B', S is a lower bound on the reciprocal con-
               dition number for the selected cluster of eigenvalues.  S  can-
               not  underestimate the true reciprocal condition number by more
               than a factor of sqrt(N). If M = 0 or N, S = 1.  If JOB  =  'N'
               or 'V', S is not referenced.

       SEP     (output) REAL
               If  JOB = 'V' or 'B', SEP is the estimated reciprocal condition
               number of the specified invariant subspace. If M = 0 or N,  SEP
               = norm(T).  If JOB = 'N' or 'E', SEP is not referenced.

       WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
               On exit, if INFO = 0, WORK(1) returns the optimal LWORK.

       LWORK   (input) INTEGER
               The  dimension  of  the  array  WORK.   If  JOB = 'N', LWORK >=
               max(1,N); if JOB = 'E', LWORK >= max(1,M*(N-M)); if JOB  =  'V'
               or 'B', LWORK >= max(1,2*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) INTEGER array, dimension (MAX(1,LIWORK))
               On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.

       LIWORK  (input) INTEGER
               The dimension of the array IWORK.  If JOB = 'N' or 'E',  LIWORK
               >= 1; if JOB = 'V' or 'B', LIWORK >= max(1,M*(N-M)).

               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 T failed because some  eigenvalues  are  too
               close  to separate (the problem is very ill-conditioned); T may
               have been partially reordered, and WR and WI contain the eigen-
               values  in the same order as in T; S and SEP (if requested) are
               set to zero.

FURTHER DETAILS
       STRSEN first collects the selected eigenvalues by computing an orthogo-
       nal  transformation  Z  to  move  them to the top left corner of T.  In
       other words, the selected eigenvalues are the eigenvalues of T11 in:

                     Z'*T*Z = ( T11 T12 ) n1
                              (  0  T22 ) n2
                                 n1  n2

       where N = n1+n2 and Z' means the transpose of Z. The first  n1  columns
       of Z span the specified invariant subspace of T.

       If  T has been obtained from the real Schur factorization of a matrix A
       = Q*T*Q', then the reordered real Schur factorization of A is given  by
       A  =  (Q*Z)*(Z'*T*Z)*(Q*Z)',  and  the first n1 columns of Q*Z span the
       corresponding invariant subspace of A.

       The reciprocal condition number of the average of  the  eigenvalues  of
       T11 may be returned in S. S lies between 0 (very badly conditioned) and
       1 (very well conditioned). It is computed as follows. First we  compute
       R so that

                              P = ( I  R ) n1
                                  ( 0  0 ) n2
                                    n1 n2

       is  the  projector on the invariant subspace associated with T11.  R is
       the solution of the Sylvester equation:

                             T11*R - R*T22 = T12.

       Let F-norm(M) denote the Frobenius-norm of M and 2-norm(M)  denote  the
       two-norm of M. Then S is computed as the lower bound

                           (1 + F-norm(R)**2)**(-1/2)

       on  the  reciprocal of 2-norm(P), the true reciprocal condition number.
       S cannot underestimate 1 / 2-norm(P) by more than a factor of  sqrt(N).

       An  approximate error bound for the computed average of the eigenvalues
       of T11 is

                              EPS * norm(T) / S

       where EPS is the machine precision.

       The reciprocal condition number of the right invariant subspace spanned
       by  the  first  n1 columns of Z (or of Q*Z) is returned in SEP.  SEP is
       defined as the separation of T11 and T22:

                          sep( T11, T22 ) = sigma-min( C )

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

          C  = kprod( I(n2), T11 ) - kprod( transpose(T22), I(n1) )

       I(m) is an m by m identity matrix,  and  kprod  denotes  the  Kronecker
       product.  We  estimate sigma-min(C) by the reciprocal of an estimate of
       the 1-norm of inverse(C). The true reciprocal 1-norm of inverse(C) can-
       not differ from sigma-min(C) by more than a factor of sqrt(n1*n2).

       When  SEP  is  small, small changes in T can cause large changes in the
       invariant subspace. An approximate bound on the maximum  angular  error
       in the computed right invariant subspace is

                           EPS * norm(T) / SEP




 LAPACK routine (version 3.1)    November 2006                       STRSEN(3)