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a. Let \(A\) be a diagonalizable \(n \times n\) matrix. Show that if the multiplicity of an eigenvalue \(\lambda \) is \(n\), then \(A = \lambda I\).

b. Use part (a) to show that the matrix \(A =\left({\begin{aligned}{*{20}{l}}3&1\\0&3\end{aligned}}\right)\) is not diagonalizable.

Short Answer

Expert verified

a. It is proved that if the multiplicity of an eigenvalue \(\lambda \)is \(n\), then\(A = \lambda I\).

b. By part (a), if A would be diagonalizable then A would be \(3I\). Since \(A \ne 3I\)It is not diagonalizable.

Step by step solution

01

Showing that if the multiplicity of an eigenvalue

If\(A\)is diagonalizable, then\(A = PD{P^{ - 1}}\), for some invertible matrix\(P\)and diagonal matrix\(D\), where entries in\(D\)are eigenvalues of\(A\).

Since multiplicity of\(\lambda \)is\(n\)and \(\lambda \)appears\(n\)times in every diagonal entry in\(D\).

In other words,\(D = \lambda I\), so:

\(\begin{aligned}{c}A &= PD{P^{ - 1}}\\ &= P\lambda I{P^{ - 1}}\\ &= \lambda PI{P^{ - 1}}\\ &= \lambda I\end{aligned}\)

Hence \(A = \lambda I\).

It is proved that if the multiplicity of an eigenvalue \(\lambda \)is \(n\), then\(A = \lambda I\).

02

Showing that the matrix \(A\) not diagonalizable

The matrix is triangular, so its eigenvalues are on its diagonal.

Only eigenvalue is 3 with multiplicity 2.

By part a), if\(A\)would be diagonalizable then\(A\)would be\(3I\).

Since \(A \ne 3I\), it is not diagonalizable.

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Most popular questions from this chapter

Show that if \({\bf{x}}\) is an eigenvector of the matrix product \(AB\) and \(B{\rm{x}} \ne 0\), then \(B{\rm{x}}\) is an eigenvector of\(BA\).

Question: Diagonalize the matrices in Exercises \({\bf{7--20}}\), if possible. The eigenvalues for Exercises \({\bf{11--16}}\) are as follows:\(\left( {{\bf{11}}} \right)\lambda {\bf{ = 1,2,3}}\); \(\left( {{\bf{12}}} \right)\lambda {\bf{ = 2,8}}\); \(\left( {{\bf{13}}} \right)\lambda {\bf{ = 5,1}}\); \(\left( {{\bf{14}}} \right)\lambda {\bf{ = 5,4}}\); \(\left( {{\bf{15}}} \right)\lambda {\bf{ = 3,1}}\); \(\left( {{\bf{16}}} \right)\lambda {\bf{ = 2,1}}\). For exercise \({\bf{18}}\), one eigenvalue is \(\lambda {\bf{ = 5}}\) and one eigenvector is \(\left( {{\bf{ - 2,}}\;{\bf{1,}}\;{\bf{2}}} \right)\).

9. \(\left( {\begin{array}{*{20}{c}}3&{ - 1}\\1&5\end{array}} \right)\)

Let \(B = \left\{ {{{\bf{b}}_1},{{\bf{b}}_2},{{\bf{b}}_3}} \right\}\)be a basis for a vector space \(V\) and\(T:V \to {\mathbb{R}^2}\) be a linear transformation with the property that

\(T\left( {{x_1}{{\bf{b}}_1} + {x_2}{{\bf{b}}_2} + {x_3}{{\bf{b}}_3}} \right) = \left( {\begin{aligned}{2{x_1} - 4{x_2} + 5{x_3}}\\{ - {x_2} + 3{x_3}}\end{aligned}} \right)\)

Find the matrix for \(T\) relative to \(B\) and the standard basis for \({\mathbb{R}^2}\).

For the matrix A, find real closed formulas for the trajectoryx(t+1)=Ax¯(t)where x=[01]. Draw a rough sketch

A=[15-27]

Use Exercise 12 to find the eigenvalues of the matrices in Exercises 13 and 14.

14. \(A{\bf{ = }}\left( {\begin{array}{*{20}{c}}{\bf{1}}&{\bf{5}}&{{\bf{ - 6}}}&{{\bf{ - 7}}}\\{\bf{2}}&{\bf{4}}&{\bf{5}}&{\bf{2}}\\{\bf{0}}&{\bf{0}}&{{\bf{ - 7}}}&{{\bf{ - 4}}}\\{\bf{0}}&{\bf{0}}&{\bf{3}}&{\bf{1}}\end{array}} \right)\)

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