.TH SLAR1V 1 "November 2006" " LAPACK auxiliary routine (version 3.1) " " LAPACK auxiliary routine (version 3.1) " .SH NAME SLAR1V - the (scaled) r-th column of the inverse of the sumbmatrix in rows B1 through BN of the tridiagonal matrix L D L^T - sigma I .SH SYNOPSIS .TP 19 SUBROUTINE SLAR1V( N, B1, BN, LAMBDA, D, L, LD, LLD, PIVMIN, GAPTOL, Z, WANTNC, NEGCNT, ZTZ, MINGMA, R, ISUPPZ, NRMINV, RESID, RQCORR, WORK ) .TP 19 .ti +4 LOGICAL WANTNC .TP 19 .ti +4 INTEGER B1, BN, N, NEGCNT, R .TP 19 .ti +4 REAL GAPTOL, LAMBDA, MINGMA, NRMINV, PIVMIN, RESID, RQCORR, ZTZ .TP 19 .ti +4 INTEGER ISUPPZ( * ) .TP 19 .ti +4 REAL D( * ), L( * ), LD( * ), LLD( * ), WORK( * ) .TP 19 .ti +4 REAL Z( * ) .SH PURPOSE SLAR1V computes the (scaled) r-th column of the inverse of the sumbmatrix in rows B1 through BN of the tridiagonal matrix L D L^T - sigma I. When sigma is close to an eigenvalue, the computed vector is an accurate eigenvector. Usually, r corresponds to the index where the eigenvector is largest in magnitude. The following steps accomplish this computation : .br (a) Stationary qd transform, L D L^T - sigma I = L(+) D(+) L(+)^T, (b) Progressive qd transform, L D L^T - sigma I = U(-) D(-) U(-)^T, (c) Computation of the diagonal elements of the inverse of L D L^T - sigma I by combining the above transforms, and choosing r as the index where the diagonal of the inverse is (one of the) largest in magnitude. .br (d) Computation of the (scaled) r-th column of the inverse using the twisted factorization obtained by combining the top part of the the stationary and the bottom part of the progressive transform. .SH ARGUMENTS .TP 9 N (input) INTEGER The order of the matrix L D L^T. .TP 9 B1 (input) INTEGER First index of the submatrix of L D L^T. .TP 9 BN (input) INTEGER Last index of the submatrix of L D L^T. .TP 10 LAMBDA (input) REAL The shift. In order to compute an accurate eigenvector, LAMBDA should be a good approximation to an eigenvalue of L D L^T. .TP 9 L (input) REAL array, dimension (N-1) The (n-1) subdiagonal elements of the unit bidiagonal matrix L, in elements 1 to N-1. .TP 9 D (input) REAL array, dimension (N) The n diagonal elements of the diagonal matrix D. .TP 9 LD (input) REAL array, dimension (N-1) The n-1 elements L(i)*D(i). .TP 9 LLD (input) REAL array, dimension (N-1) The n-1 elements L(i)*L(i)*D(i). .TP 9 PIVMIN (input) REAL The minimum pivot in the Sturm sequence. .TP 9 GAPTOL (input) REAL Tolerance that indicates when eigenvector entries are negligible w.r.t. their contribution to the residual. .TP 9 Z (input/output) REAL array, dimension (N) On input, all entries of Z must be set to 0. On output, Z contains the (scaled) r-th column of the inverse. The scaling is such that Z(R) equals 1. .TP 9 WANTNC (input) LOGICAL Specifies whether NEGCNT has to be computed. .TP 9 NEGCNT (output) INTEGER If WANTNC is .TRUE. then NEGCNT = the number of pivots < pivmin in the matrix factorization L D L^T, and NEGCNT = -1 otherwise. .TP 9 ZTZ (output) REAL The square of the 2-norm of Z. .TP 9 MINGMA (output) REAL The reciprocal of the largest (in magnitude) diagonal element of the inverse of L D L^T - sigma I. .TP 9 R (input/output) INTEGER The twist index for the twisted factorization used to compute Z. On input, 0 <= R <= N. If R is input as 0, R is set to the index where (L D L^T - sigma I)^{-1} is largest in magnitude. If 1 <= R <= N, R is unchanged. On output, R contains the twist index used to compute Z. Ideally, R designates the position of the maximum entry in the eigenvector. .TP 9 ISUPPZ (output) INTEGER array, dimension (2) The support of the vector in Z, i.e., the vector Z is nonzero only in elements ISUPPZ(1) through ISUPPZ( 2 ). .TP 9 NRMINV (output) REAL NRMINV = 1/SQRT( ZTZ ) .TP 9 RESID (output) REAL The residual of the FP vector. RESID = ABS( MINGMA )/SQRT( ZTZ ) .TP 9 RQCORR (output) REAL The Rayleigh Quotient correction to LAMBDA. RQCORR = MINGMA*TMP .TP 9 WORK (workspace) REAL array, dimension (4*N) .SH FURTHER DETAILS Based on contributions by .br Beresford Parlett, University of California, Berkeley, USA Jim Demmel, University of California, Berkeley, USA .br Inderjit Dhillon, University of Texas, Austin, USA .br Osni Marques, LBNL/NERSC, USA .br Christof Voemel, University of California, Berkeley, USA