Let \(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) be an invertible linear transformation. Explain why T is both one-to-one and onto \({\mathbb{R}^n}\). Use equations (1) and (2). Then give a second explanation using one or more theorems.

Short Answer

Expert verified

It is proved that Tis both one-to-one and onto.

Step by step solution

01

Show that T is one-to-one

The linear transformation S,given by \[S\left( x \right) = {A^{ - 1}}{\mathop{\rm x}\nolimits} \], is a unique function satisfying the equations

  1. \(S\left( {T\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \)for all x in \({\mathbb{R}^n}\), and
  2. \(T\left( {S\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \)for all x in \({\mathbb{R}^n}\).

Let \[T\left( {\mathop{\rm u}\nolimits} \right) = T\left( {\mathop{\rm v}\nolimits} \right)\] for vectors u and v in \({\mathbb{R}^n}\). Then, \(S\left( {T\left( {\mathop{\rm u}\nolimits} \right)} \right) = S\left( {T\left( {\mathop{\rm v}\nolimits} \right)} \right)\), where Srepresents the inverse of T.

By equation (1), \({\mathop{\rm u}\nolimits} = S\left( {T\left( {\mathop{\rm u}\nolimits} \right)} \right)\) and \(S\left( {T\left( {\mathop{\rm v}\nolimits} \right)} \right) = {\mathop{\rm v}\nolimits} \). Thus, \[{\mathop{\rm u}\nolimits} = v\] and T is one-to-one.

02

Show that T is onto

Let \(y\) be an arbitrary vector in \({\mathbb{R}^n}\) and \({\mathop{\rm x}\nolimits} = S\left( y \right)\). Equation (2) shows that \(T\left( {\mathop{\rm x}\nolimits} \right) = T\left( {S\left( {\mathop{\rm y}\nolimits} \right)} \right) = {\mathop{\rm y}\nolimits} \), which indicates that Tmaps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\).

Thus, it is proved that Tmaps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\).

03

Show that T is both one-to-one and onto

Let\(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) be a linear transformation and Abe the standard matrix for T. Then, according totheorem 9, Tis invertibleif and only if Ais an invertible matrix. The linear transformation S,given by \[S\left( x \right) = {A^{ - 1}}{\mathop{\rm x}\nolimits} \], is a unique function satisfying the equations

  1. \(S\left( {T\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \)for all x in \({\mathbb{R}^n}\), and
  2. \(T\left( {S\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \)for all x in \({\mathbb{R}^n}\).

Let\(T:{\mathbb{R}^n} \to {\mathbb{R}^m}\) be a linear transformation and Abe the standard matrix for T. Then, according to theorem 12,

  1. Tmaps \({\mathbb{R}^n}\) onto \({\mathbb{R}^m}\) if and only if the columns of Aspan \({\mathbb{R}^m}\);
  2. T is one-to-one if and only if the columns of Aare linearly independent.

The standard matrix Afor T is invertible, according to theorem 9.

Following the invertible matrix theorem, the columns of Aare linearly independent, and they span \({\mathbb{R}^n}\). Therefore, T is one-to-one and it maps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\), based on theorem 12.

Thus, it is proved that Tis both one-to-one and onto.

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Most popular questions from this chapter

In exercises 11 and 12, mark each statement True or False. Justify each answer.

a. The definition of the matrix-vector product \(A{\bf{x}}\) is a special case of block multiplication.

b. If \({A_{\bf{1}}}\), \({A_{\bf{2}}}\), \({B_{\bf{1}}}\), and \({B_{\bf{2}}}\) are \(n \times n\) matrices, \[A = \left[ {\begin{array}{*{20}{c}}{{A_{\bf{1}}}}\\{{A_{\bf{2}}}}\end{array}} \right]\] and \(B = \left[ {\begin{array}{*{20}{c}}{{B_{\bf{1}}}}&{{B_{\bf{2}}}}\end{array}} \right]\), then the product \(BA\) is defined, but \(AB\) is not.

Let T be a linear transformation that maps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\). Is \({T^{ - 1}}\) also one-to-one?

How many rows does \(B\) have if \(BC\) is a \({\bf{3}} \times {\bf{4}}\) matrix?

The inverse of \(\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\C&I&{\bf{0}}\\A&B&I\end{array}} \right]\) is \(\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\Z&I&{\bf{0}}\\X&Y&I\end{array}} \right]\). Find X, Y, and Z.

Exercises 15 and 16 concern arbitrary matrices A, B, and Cfor which the indicated sums and products are defined. Mark each statement True or False. Justify each answer.

16. a. If A and B are \({\bf{3}} \times {\bf{3}}\) and \(B = \left( {\begin{aligned}{*{20}{c}}{{{\bf{b}}_1}}&{{{\bf{b}}_2}}&{{{\bf{b}}_3}}\end{aligned}} \right)\), then \(AB = \left( {A{{\bf{b}}_1} + A{{\bf{b}}_2} + A{{\bf{b}}_3}} \right)\).

b. The second row of ABis the second row of Amultiplied on the right by B.

c. \(\left( {AB} \right)C = \left( {AC} \right)B\)

d. \({\left( {AB} \right)^T} = {A^T}{B^T}\)

e. The transpose of a sum of matrices equals the sum of their transposes.

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