CTGSEN(3)

📦 version 3.12.0, in opensuse-leap 16.0

💅 CTGSEN(3) 💅

This is the CTGSEN(3) page from the Library Functions Manual, and it’s all about /home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/ctgsen.f. Bestie, we are in LAPACK girlie territory now — upper triangular matrix pairs, generalized Schur forms, the whole iconic mess. 💖

🌸 NAME 🌸

/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/ctgsen.f

✨ SYNOPSIS ✨

Functions/Subroutines

subroutine CTGSEN (ijob, wantq, wantz, select, n, a, lda, b, ldb, alpha,
    beta, q, ldq, z, ldz, m, pl, pr, dif, work, lwork, iwork, liwork,
    info)

CTGSEN

🦋 Function/Subroutine Documentation 🦋

subroutine CTGSEN (integer ijob, logical wantq, logical wantz, logical,
    dimension( * ) select, integer n, complex, dimension( lda, * ) a,
    integer lda, complex, dimension( ldb, * ) b, integer ldb, complex,
    dimension( * ) alpha, complex, dimension( * ) beta, complex, dimension(
    ldq, * ) q, integer ldq, complex, dimension( ldz, * ) z, integer ldz,
    integer m, real pl, real pr, real, dimension( * ) dif, complex,
    dimension( * ) work, integer lwork, integer, dimension( * ) iwork,
    integer liwork, integer info)

CTGSEN

🎯 Purpose 🎯

Okay so CTGSEN reorders the generalized Schur decomposition of a complex matrix pair (A, B) — and we’re talking in terms of a unitary equivalence transformation Q**H * (A, B) * Z — so that a selected cluster of eigenvalues appears in the leading diagonal blocks of the pair (A,B). The leading columns of Q and Z form unitary bases of the corresponding left and right eigenspaces (deflating subspaces). (A, B) must be in generalized Schur canonical form, that is, A and B are both upper triangular. Slay. 💅

CTGSEN also computes the generalized eigenvalues

w(j)= ALPHA(j) / BETA(j)

of the reordered matrix pair (A, B).

Optionally, the routine computes 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 onto left and right eigenspaces w.r.t. the selected cluster in the (1,1)-block. 🫶

🌈 Parameters 🌈

IJOB

IJOB is 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 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

WANTQ is LOGICAL.

  • .TRUE.: update the left transformation matrix Q;
  • .FALSE.: do not update Q.

WANTZ

WANTZ is LOGICAL.

  • .TRUE.: update the right transformation matrix Z;
  • .FALSE.: do not update Z.

SELECT

SELECT is LOGICAL array, dimension (N).

SELECT specifies the eigenvalues in the selected cluster. To select an eigenvalue w(j), SELECT(j) must be set to .TRUE..

N

N is INTEGER.

The order of the matrices A and B. N >= 0.

A

A is COMPLEX array, dimension (LDA,N).

On entry, the upper triangular matrix A, in generalized Schur canonical form. On exit, A is overwritten by the reordered matrix A.

LDA

LDA is INTEGER.

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

B

B is COMPLEX array, dimension (LDB,N).

On entry, the upper triangular matrix B, in generalized Schur canonical form. On exit, B is overwritten by the reordered matrix B.

LDB

LDB is INTEGER.

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

ALPHA

ALPHA is COMPLEX array, dimension (N).

BETA

BETA is COMPLEX array, dimension (N).

The diagonal elements of A and B, respectively, when the pair (A,B) has been reduced to generalized Schur form. ALPHA(i)/BETA(i) i=1,...,N are the generalized eigenvalues.

Q

Q is COMPLEX 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 unitary 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

LDQ is INTEGER.

The leading dimension of the array Q. LDQ >= 1. If WANTQ = .TRUE., LDQ >= N.

Z

Z is COMPLEX 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 unitary 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

LDZ is INTEGER.

The leading dimension of the array Z. LDZ >= 1. If WANTZ = .TRUE., LDZ >= N.

M

M is INTEGER.

The dimension of the specified pair of left and right eigenspaces, (deflating subspaces) 0 <= M <= N.

PL

PL is REAL.

PR

PR is REAL.

If IJOB = 1, 4 or 5, PL, PR are lower bounds on the reciprocal of the norm of onto left and right eigenspace 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, PR are not referenced.

DIF

DIF is 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, computed using reversed communication with CLACN2. If M = 0 or N, DIF(1:2) = F-norm([A, B]). If IJOB = 0 or 1, DIF is not referenced.

WORK

WORK is COMPLEX array, dimension (MAX(1,LWORK)).

On exit, if INFO = 0, WORK(1) returns the optimal LWORK.

LWORK

LWORK is INTEGER.

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

IWORK is INTEGER array, dimension (MAX(1,LIWORK)).

On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.

LIWORK

LIWORK is INTEGER.

The dimension of the array IWORK. LIWORK >= 1. If IJOB = 1, 2 or 4, LIWORK >= N+2; If IJOB = 3 or 5, LIWORK >= MAX(N+2, 2*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

INFO is 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.

👑 Author 👑

Univ. of Tennessee

Univ. of California Berkeley

Univ. of Colorado Denver

NAG Ltd.

💜 Further Details 💜

The original page has this section heading, but no further details are filled in here. More parts follow. 🦋

okay so CTGSEN starts by collecting the selected eigenvalues — it computes unitary 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 this whole situation:

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

where N = n1+n2 and U**H means the conjugate 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). bestie, that’s the whole vibe of the opening move 💅✨

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 Schur form of (C, D) is given by

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

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.). lowkey iconic, highkey important 🦋

⚠️ ngl, if the selected eigenvalue is sufficiently ill-conditioned, then its value may differ significantly from its value before reordering. That’s not a drill, bestie — it’s giving “handle with care” energy 😭

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**H, In1) ]
            [ kron(In2, B11)  -kron(B22**H, In1) ].

Here, Inx is the identity matrix of size nx and A22**H is the conjugate transpose of A22. kron(X, Y) is the Kronecker product between the matrices X and Y. math girlies, we love to see it 🧚💜

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. so yeah, when DIF(2) gets tiny, the drama gets big 💀

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 are 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 CLATDF), then the parameter IDIFJB (see below) should be changed from 3 to 4 (routine CLATDF (IJOB = 2 will be used)). See CTGSYL for more details. iykyk 🫶

💖 Contributors

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

🌈 References

  1. [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. [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. [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.

Definition at line 430 of file ctgsen.f.

🫶 Author

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okay bestie, that’s the CTGSEN lore — math, bounds, references, and all 💅✨ Footer vibe check: source /home/abui...RC/ctgsen.f(3), LAPACK Version 3.12.0, plus the date stamp that lives in that official footer. Periodt 🎀🦋

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