Page 291 - 35Linear Algebra
P. 291

16.2 Image                                                                                    291


                   Theorem 16.2.1. A function f : S → T has an inverse function g: T → S
                   if and only if f is bijective.

                   Proof. This is an “if and only if” statement so the proof has two parts.

                      1. (Existence of an inverse ⇒ bijective.)

                         Suppose that f has an inverse function g. We need to show f is bijec-
                         tive, which we break down into injective and surjective.

                                                                                      0
                           • The function f is injective: Suppose that we have s, s ∈ S such
                                              0
                              that f(s) = f(s ). We must have that g(f(s)) = s for any s ∈ S, so
                                                                 0
                                                                       0
                                                                                              0
                              in particular g(f(s)) = s and g(f(s )) = s . But since f(s) = f(s ),
                                                                  0
                                                       0
                              we have g(f(s)) = g(f(s )) so s = s . Therefore, f is injective.
                           • The function f is surjective: Let t be any element of T. We must
                              have that f(g(t)) = t. Thus, g(t) is an element of S which maps
                              to t. So f is surjective.
                      2. (Bijectivity ⇒ existence of an inverse.) Suppose that f is bijective.
                         Hence f is surjective, so every element t ∈ T has at least one pre-
                         image. Being bijective, f is also injective, so every t has no more than
                         one pre-image. Therefore, to construct an inverse function g, we simply
                         define g(t) to be the unique pre-image f  −1 (t) of t.




                      Now let us specialize to functions f that are linear maps between two
                   vector spaces. Everything we said above for arbitrary functions is exactly
                   the same for linear functions. However, the structure of vector spaces lets
                   us say much more about one-to-one and onto functions whose domains are
                   vector spaces than we can say about functions on general sets. For example,
                   we know that a linear function always sends 0 V to 0 W , i.e.,



                                                   f(0 V ) = 0 W


                   In Review Exercise 2, you will show that a linear transformation is one-to-one
                   if and only if 0 V is the only vector that is sent to 0 W . Linear functions are
                   unlike arbitrary functions between sets in that, by looking at just one (very
                   special) vector, we can figure out whether f is one-to-one!


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