Page 160 - Linear Algebra Done Right
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Chapter 7. Operators on Inner-Product Spaces
                       148
                                              where we have used 6.17. Applying S to both sides of 7.33 gives
                                                            Sv = v, e 1  Se 1 +· · ·+Pv, e n  Se n
                                                                = λ 1  v, e 1  e 1 + ··· + λ n  v, e n  e n .
                                              The last equation, along with the equation |λ j |= 1, shows that
                                                                                             2
                                                                             2
                                                                  2
                                              7.35            Sv  =| v, e 1  | + ··· + | v, e n  | .
                                              Comparing 7.34 and 7.35 shows that  v = Sv . In other words, S is
                                              an isometry.
                                                                                                     2
                        An isometry on a real   For another example, let θ ∈ R. Then the operator on R of coun-
                        inner-product space is  terclockwise rotation (centered at the origin) by an angle of θ is an
                              often called an  isometry (you should find the matrix of this operator with respect to
                                                                   2
                         orthogonal operator.  the standard basis of R ).
                            An isometry on a    If S ∈L(V) is an isometry, then S is injective (because if Sv = 0,
                       complex inner-product  then  v = Sv = 0, and hence v = 0). Thus every isometry is
                        space is often called a  invertible (by 3.21).
                         unitary operator. We   The next theorem provides several conditions that are equivalent
                            will use the term  to being an isometry. These equivalences have several important in-
                         isometry so that our  terpretations. In particular, the equivalence of (a) and (b) shows that
                          results can apply to  an isometry preserves inner products. Because (a) implies (d), we see
                        both real and complex  that if S is an isometry and (e 1 ,...,e n ) is an orthonormal basis of V,
                        inner-product spaces.  then the columns of the matrix of S (with respect to this basis) are or-
                                              thonormal; because (e) implies (a), we see that the converse also holds.
                                              Because (a) is equivalent to conditions (i) and (j), we see that in the last
                                              sentence we can replace “columns” with “rows”.

                                              7.36  Theorem: Suppose S ∈L(V). Then the following are equiva-
                                              lent:

                                              (a)  S is an isometry;
                                              (b)   Su, Sv = u, v  for all u, v ∈ V;
                                              (c)  S S = I;
                                                     ∗
                                              (d)  (Se 1 ,...,Se n ) is orthonormal whenever (e 1 ,...,e n ) is an ortho-
                                                   normal list of vectors in V;
                                              (e)  there exists an orthonormal basis (e 1 ,...,e n ) of V such that
                                                   (Se 1 ,...,Se n ) is orthonormal;
                                              (f)  S  ∗  is an isometry;
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