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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

Prove Theorem 2(b) and 2(c). Use the row-column rule. The \(\left( {i,j} \right)\)- entry in \(A\left( {B + C} \right)\) can be written as \({a_{i1}}\left( {{b_{1j}} + {c_{1j}}} \right) + ... + {a_{in}}\left( {{b_{nj}} + {c_{nj}}} \right)\) or \(\sum\limits_{k = 1}^n {{a_{ik}}\left( {{b_{kj}} + {c_{kj}}} \right)} \).

Show that block upper triangular matrix \(A\) in Example 5is invertible if and only if both \({A_{{\bf{11}}}}\) and \({A_{{\bf{12}}}}\) are invertible. [Hint: If \({A_{{\bf{11}}}}\) and \({A_{{\bf{12}}}}\) are invertible, the formula for \({A^{ - {\bf{1}}}}\) given in Example 5 actually works as the inverse of \(A\).] This fact about \(A\) is an important part of several computer algorithims that estimates eigenvalues of matrices. Eigenvalues are discussed in chapter 5.

Let \(A = \left( {\begin{aligned}{*{20}{c}}{\bf{2}}&{\bf{5}}\\{ - {\bf{3}}}&{\bf{1}}\end{aligned}} \right)\) and \(B = \left( {\begin{aligned}{*{20}{c}}{\bf{4}}&{ - {\bf{5}}}\\{\bf{3}}&k\end{aligned}} \right)\). What value(s) of \(k\), if any will make \(AB = BA\)?

In Exercise 10 mark each statement True or False. Justify each answer.

10. a. A product of invertible \(n \times n\) matrices is invertible, and the inverse of the product of their inverses in the same order.

b. If A is invertible, then the inverse of \({A^{ - {\bf{1}}}}\) is A itself.

c. If \(A = \left( {\begin{aligned}{*{20}{c}}a&b\\c&d\end{aligned}} \right)\) and \(ad = bc\), then A is not invertible.

d. If A can be row reduced to the identity matrix, then A must be invertible.

e. If A is invertible, then elementary row operations that reduce A to the identity \({I_n}\) also reduce \({A^{ - {\bf{1}}}}\) to \({I_n}\).

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

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