1DLAED4(1) LAPACK routine (version 3.1) DLAED4(1)
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6 DLAED4 - compute the I-th updated eigenvalue of a symmetric rank-one
7 modification to a diagonal matrix whose elements are given in the array
8 d, and that D(i) < D(j) for i < j and that RHO > 0
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11 SUBROUTINE DLAED4( N, I, D, Z, DELTA, RHO, DLAM, INFO )
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13 INTEGER I, INFO, N
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15 DOUBLE PRECISION DLAM, RHO
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17 DOUBLE PRECISION D( * ), DELTA( * ), Z( * )
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20 This subroutine computes the I-th updated eigenvalue of a symmetric
21 rank-one modification to a diagonal matrix whose elements are given in
22 the array d, and that no loss in generality. The rank-one modified
23 system is thus
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25 diag( D ) + RHO * Z * Z_transpose.
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27 where we assume the Euclidean norm of Z is 1.
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29 The method consists of approximating the rational functions in the sec‐
30 ular equation by simpler interpolating rational functions.
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34 N (input) INTEGER
35 The length of all arrays.
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37 I (input) INTEGER
38 The index of the eigenvalue to be computed. 1 <= I <= N.
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40 D (input) DOUBLE PRECISION array, dimension (N)
41 The original eigenvalues. It is assumed that they are in order,
42 D(I) < D(J) for I < J.
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44 Z (input) DOUBLE PRECISION array, dimension (N)
45 The components of the updating vector.
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47 DELTA (output) DOUBLE PRECISION array, dimension (N)
48 If N .GT. 2, DELTA contains (D(j) - lambda_I) in its j-th com‐
49 ponent. If N = 1, then DELTA(1) = 1. If N = 2, see DLAED5 for
50 detail. The vector DELTA contains the information necessary to
51 construct the eigenvectors by DLAED3 and DLAED9.
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53 RHO (input) DOUBLE PRECISION
54 The scalar in the symmetric updating formula.
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56 DLAM (output) DOUBLE PRECISION
57 The computed lambda_I, the I-th updated eigenvalue.
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59 INFO (output) INTEGER
60 = 0: successful exit
61 > 0: if INFO = 1, the updating process failed.
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64 Logical variable ORGATI (origin-at-i?) is used for distinguishing
65 whether D(i) or D(i+1) is treated as the origin.
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67 ORGATI = .true. origin at i ORGATI = .false. origin at i+1
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69 Logical variable SWTCH3 (switch-for-3-poles?) is for noting if we are
70 working with THREE poles!
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72 MAXIT is the maximum number of iterations allowed for each eigenvalue.
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74 Further Details ===============
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76 Based on contributions by Ren-Cang Li, Computer Science Division, Uni‐
77 versity of California at Berkeley, USA
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81 LAPACK routine (version 3.1) November 2006 DLAED4(1)