ctrsna(3P)

NAME

ctrsna - estimate reciprocal condition numbers for specified eigenvalues and/or right eigenvectors of a complex upper triangular matrix T (or of any matrix Q∗T∗Q∗∗H with Q unitary)

SYNOPSIS

SUBROUTINE CTRSNA(
JOB, HOWMNY, SELECT, N, T, LDT, VL, LDVL, VR, LDVR, S, SEP, MM, M, WORK, LDWORK, RWORK, INFO )

void ctrsna(char job, char howmny, long ∗select,
long int n, complex ∗t, long int ldt, complex ∗vl, long int ldvl, complex ∗vr, long int ldvr, float ∗s, float ∗sep, long int mm, long int ∗m, long int ∗info)

CHARACTER HOWMNY, JOB

INTEGER INFO, LDT, LDVL, LDVR, LDWORK, M, MM, N

LOGICAL SELECT( ∗ )

REAL RWORK( ∗ ), S( ∗ ), SEP( ∗ )

COMPLEX T( LDT, ∗ ), VL( LDVL, ∗ ), VR( LDVR, ∗ ), WORK( LDWORK, ∗ )

PURPOSE

CTRSNA estimates reciprocal condition numbers for specified eigenvalues and/or right eigenvectors of a complex upper triangular matrix T (or of any matrix Q∗T∗Q∗∗H with Q unitary).

ARGUMENTS

JOB (input) CHARACTER∗1
Specifies whether condition numbers are required for eigenvalues (S) or eigenvectors (SEP):
= ’E’: for eigenvalues only (S);
= ’V’: for eigenvectors only (SEP);
= ’B’: for both eigenvalues and eigenvectors (S and SEP).

HOWMNY (input) CHARACTER∗1
= ’A’: compute condition numbers for all eigenpairs;
= ’S’: compute condition numbers for selected eigenpairs specified by the array SELECT.

SELECT (input) LOGICAL array, dimension (N)
If HOWMNY = ’S’, SELECT specifies the eigenpairs for which condition numbers are required. To select condition numbers for the j-th eigenpair, SELECT(j) must be set to .TRUE.. If HOWMNY = ’A’, SELECT is not referenced.

N (input) INTEGER
The order of the matrix T. N >= 0.

T (input) COMPLEX array, dimension (LDT,N)
The upper triangular matrix T.

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

VL (input) COMPLEX array, dimension (LDVL,M)
If JOB = ’E’ or ’B’, VL must contain left eigenvectors of T (or of any Q∗T∗Q∗∗H with Q unitary), corresponding to the eigenpairs specified by HOWMNY and SELECT. The eigenvectors must be stored in consecutive columns of VL, as returned by CHSEIN or CTREVC. If JOB = ’V’, VL is not referenced.

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

VR (input) COMPLEX array, dimension (LDVR,M)
If JOB = ’E’ or ’B’, VR must contain right eigenvectors of T (or of any Q∗T∗Q∗∗H with Q unitary), corresponding to the eigenpairs specified by HOWMNY and SELECT. The eigenvectors must be stored in consecutive columns of VR, as returned by CHSEIN or CTREVC. If JOB = ’V’, VR is not referenced.

LDVR (input) INTEGER
The leading dimension of the array VR. LDVR >= 1; and if JOB = ’E’ or ’B’, LDVR >= N.

S (output) REAL array, dimension (MM)
If JOB = ’E’ or ’B’, the reciprocal condition numbers of the selected eigenvalues, stored in consecutive elements of the array. Thus S(j), SEP(j), and the j-th columns of VL and VR all correspond to the same eigenpair (but not in general the j-th eigenpair, unless all eigenpairs are selected). If JOB = ’V’, S is not referenced.

SEP (output) REAL array, dimension (MM)
If JOB = ’V’ or ’B’, the estimated reciprocal condition numbers of the selected eigenvectors, stored in consecutive elements of the array. If JOB = ’E’, SEP is not referenced.

MM (input) INTEGER
The number of elements in the arrays S (if JOB = ’E’ or ’B’) and/or SEP (if JOB = ’V’ or ’B’). MM >= M.

M (output) INTEGER
The number of elements of the arrays S and/or SEP actually used to store the estimated condition numbers. If HOWMNY = ’A’, M is set to N.

WORK (workspace) COMPLEX array, dimension (LDWORK,N+1)
If JOB = ’E’, WORK is not referenced.

LDWORK (input) INTEGER
The leading dimension of the array WORK. LDWORK >= 1; and if JOB = ’V’ or ’B’, LDWORK >= N.

RWORK (workspace) REAL array, dimension (N)
If JOB = ’E’, RWORK is not referenced.

INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value

FURTHER DETAILS

The reciprocal of the condition number of an eigenvalue lambda is defined as

        S(lambda) = |v’∗u| / (norm(u)∗norm(v))

where u and v are the right and left eigenvectors of T corresponding to lambda; v’ denotes the conjugate transpose of v, and norm(u) denotes the Euclidean norm. These reciprocal condition numbers always lie between zero (very badly conditioned) and one (very well conditioned). If n = 1, S(lambda) is defined to be 1.

An approximate error bound for a computed eigenvalue W(i) is given by

                    EPS ∗ norm(T) / S(i)

where EPS is the machine precision.

The reciprocal of the condition number of the right eigenvector u corresponding to lambda is defined as follows. Suppose

            T = ( lambda c )
                (   0    T22 )

Then the reciprocal condition number is

        SEP( lambda, T22 ) = sigma-min( T22 - lambda∗I )

where sigma-min denotes the smallest singular value. We approximate the smallest singular value by the reciprocal of an estimate of the one-norm of the inverse of T22 - lambda∗I. If n = 1, SEP(1) is defined to be abs(T(1,1)).

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

                    EPS ∗ norm(T) / SEP(i)