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9.1 Eigenvalues and Eigenvectors  271

                                                                          √
                                           For eigenvectors associated with (1 −  15i)/2, solve the 2 × 2system
                                                                       √
                                                                  (((1 −  15i)/2)I 2 − A)X = O
                                        to obtain
                                                                              1

                                                                      β      √        .
                                                                         (1 +  15i)/4
                                                                          √
                                        This is an eigenvector associated with (1 −  15i)/2 for any β  = 0.
                                           If A has real numbers as elements and λ = α + iβ is an eigenvalue, then the conjugate λ =
                                        α − iβ is also an eigenvalue. This is because the characteristic polynomial of A has real coeffi-
                                        cients in this case, so complex roots (eigenvalues of A) occur in conjugate pairs. Furthermore, if
                                        E is an eigenvector corresponding to λ, then E is an eigenvector corresponding to λ, where we
                                        take the conjugate of a matrix by taking the conjugate of each of its elements. This can be seen
                                        by taking the conjugate of AE = λE to obtain
                                                                          AE = λE.
                                        Because A has real elements, A = A so
                                                                          AE = λE.

                                        This observation can be seen in Example 9.4.
                                           There is a general expression for the eigenvalues of a matrix that will be used soon to draw
                                        conclusions about eigenvalues of matrices having special properties.

                                  LEMMA 9.1

                                        Let A be an n × n matrix of numbers. Let λ be an eigenvalue of A, with eigenvector E. Then
                                                                             t
                                                                            E AE
                                                                        λ =   t  .                               (9.2)
                                                                             E E
                                           Before giving the one line proof of this expression, examine what the right side means. Let

                                                                             ⎛ ⎞
                                                                               e 1
                                                                             ⎜ ⎟
                                                                               e 2
                                                                          E = ⎜ . ⎟.
                                                                             ⎜ ⎟
                                                                               .
                                                                             ⎝ . ⎠
                                                                               e n
                                        Then
                                                                             ⎛                ⎞⎛ ⎞
                                                                              a 11  a 12  ···  a 1n  e 1
                                                                                                 e 2
                                                                             ⎜
                                                        t     
               a 21  a 22  ···  a 2n  ⎟⎜ ⎟
                                                                                              ⎟⎜ ⎟
                                                                             ⎜
                                                       E AE = e 1  e 2  ··· e n ⎜ .  .  .   . ⎟⎜ . ⎟.
                                                                             ⎝ . .  . .  . .  . . ⎠⎝ . ⎠
                                                                                                  .
                                                                              a n1  a n2  ··· a nn  e n
                                        This is a product of a 1 × n matrix with an n × n matrix, then an n × 1 matrix, hence is a 1 × 1
                                        matrix, which we think of as a number. If we carry out this matrix product we obtain the number
                                                                             n  n
                                                                      t
                                                                     E AE =       a ij e i e j .
                                                                            i=1  j=1
                                        For the denominator of equation (9.2) we have a 1 × n matrix multiplied by an n × 1 matrix,
                                        which is also a 1 × 1 matrix, or number. Specifically,

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