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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 \(\left( {{\bf{ - 2,}}\;{\bf{1,}}\;{\bf{2}}} \right)\).

19. \(\left( {\begin{array}{*{20}{c}}{\bf{5}}&{{\bf{ - 3}}}&{\bf{0}}&{\bf{9}}\\{\bf{0}}&{\bf{3}}&{\bf{1}}&{{\bf{ - 2}}}\\{\bf{0}}&{\bf{0}}&{\bf{2}}&{\bf{0}}\\{\bf{0}}&{\bf{0}}&{\bf{0}}&{\bf{2}}\end{array}} \right)\)

Short Answer

Expert verified

The matrix \(A\) is diagonalizable with \(P = \left( {\begin{array}{*{20}{c}}1&{\frac{3}{2}}&{ - 1}&{ - 1}\\0&1&{ - 1}&2\\0&0&1&0\\0&0&0&1\end{array}} \right)\) and \(D = \left( {\begin{array}{*{20}{c}}5&0&0&0\\0&3&0&0\\0&0&2&0\\0&0&0&2\end{array}} \right)\).

Step by step solution

01

Write the Diagonalization Theorem

The Diagonalization Theorem: An \(n \times n\) matrix \(A\) is diagonalizable if and only if \(A\) has \(n\) linearly independent eigenvectors. As \(A = PD{P^{ - 1}}\) which has \(D\) a diagonal matrix if and only if the columns of \(P\) are \(n\) linearly independent eigenvectors of \(A\).

02

Find eigenvalues of the matrix

Consider the given matrix \(A = \left( {\begin{array}{*{20}{c}}5&{ - 3}&0&9\\0&3&1&{ - 2}\\0&0&2&0\\0&0&0&2\end{array}} \right)\). Since it is given the eigenvalues of the matrix are \(5\), \(3\), \(2\) and \(2\).

03

Find the eigenvector for \(\lambda   = {\bf{5}}\)

Write the matrix form for finding the eigenvector.

\(\begin{array}{c}\left( {A - 5I} \right){\bf{x}} = 0\\\left( {\begin{array}{*{20}{c}}5&{ - 3}&0&9\\0&3&1&{ - 2}\\0&0&2&0\\0&0&0&2\end{array}} \right) - \left( {\begin{array}{*{20}{c}}5&0&0&0\\0&5&0&0\\0&0&5&0\\0&0&0&5\end{array}} \right)\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right)\\\left( {\begin{array}{*{20}{c}}0&{ - 3}&0&9\\0&{ - 2}&1&{ - 2}\\0&0&{ - 3}&0\\0&0&0&{ - 3}\end{array}} \right)\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right)\end{array}\)

Therefore, the system of equations is shown below:

\(\begin{array}{c} - 3{x_2} + 9{x_4} = 0\\ - 2{x_2} + {x_3} - 2{x_4} = 0\\ - 3{x_3} = 0\\ - 3{x_4} = 0\end{array}\)

The general solution is,

\(\begin{array}{c}\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}{{x_1}}\\0\\0\\0\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}1\\0\\0\\0\end{array}} \right){x_1}\end{array}\).

Therefore, the eigenvector is \(\left\{ {{{\rm{v}}_1}} \right\} = \left\{ {\left( {\begin{array}{*{20}{c}}1\\0\\0\\0\end{array}} \right)} \right\}\).

04

Find the Eigenvector for \(\lambda   = {\bf{3}}\)

Write the matrix form for finding the eigenvector.

\(\begin{array}{c}\left( {A - 3I} \right){\bf{x}} = 0\\\left( {\begin{array}{*{20}{c}}5&{ - 3}&0&9\\0&3&1&{ - 2}\\0&0&2&0\\0&0&0&2\end{array}} \right) - \left( {\begin{array}{*{20}{c}}3&0&0&0\\0&3&0&0\\0&0&3&0\\0&0&0&3\end{array}} \right)\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right)\\\left( {\begin{array}{*{20}{c}}2&{ - 3}&0&9\\0&0&1&{ - 2}\\0&0&{ - 1}&0\\0&0&0&{ - 1}\end{array}} \right)\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right)\end{array}\)

Therefore, the system of equations is shown below:

\(\begin{array}{c} - 2{x_1} - 3{x_2} + 9{x_4} = 0\\{x_3} - 2{x_4} = 0\\ - {x_3} = 0\\ - {x_4} = 0\end{array}\)

The general solution is,

\(\begin{array}{c}\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}{\frac{3}{2}{x_2}}\\{{x_2}}\\0\\0\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}{\frac{3}{2}}\\1\\0\\0\end{array}} \right){x_2}\end{array}\).

Therefore, the eigenvector is \(\left\{ {{{\rm{v}}_2}} \right\} = \left\{ {\left( {\begin{array}{*{20}{c}}{\frac{3}{2}}\\1\\0\\0\end{array}} \right)} \right\}\).

05

Find the Eigenvector for \(\lambda   = {\bf{2}}\)

Write the matrix form for finding the eigenvector.

\(\begin{array}{c}\left( {A - 2I} \right){\bf{x}} = 0\\\left( {\begin{array}{*{20}{c}}5&{ - 3}&0&9\\0&3&1&{ - 2}\\0&0&2&0\\0&0&0&2\end{array}} \right) - \left( {\begin{array}{*{20}{c}}2&0&0&0\\0&2&0&0\\0&0&2&0\\0&0&0&2\end{array}} \right)\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right)\\\left( {\begin{array}{*{20}{c}}3&{ - 3}&0&9\\0&1&1&{ - 2}\\0&0&0&0\\0&0&0&0\end{array}} \right)\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right)\end{array}\)

Therefore, the system of equations is shown below:

\(\begin{array}{c}3{x_1} - 3{x_2} + 9{x_4} = 0\\{x_2} + {x_3} - 2{x_4} = 0\end{array}\)

The general solution is,

\(\begin{array}{c}\left( {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\\{{x_3}}\\{{x_4}}\end{array}} \right) = \left( {\begin{array}{*{20}{c}}{ - {x_3} - {x_4}}\\{ - {x_3} + 2{x_4}}\\{{x_3}}\\{{x_4}}\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}{ - 1}\\{ - 1}\\1\\0\end{array}} \right){x_3} + \left( {\begin{array}{*{20}{c}}{ - 1}\\2\\0\\1\end{array}} \right){x_4}\end{array}\).

Therefore, the eigenvectors are \(\left\{ {{{\rm{v}}_3},{{\rm{v}}_4}} \right\} = \left\{ {\left( {\begin{array}{*{20}{c}}{ - 1}\\{ - 1}\\1\\0\end{array}} \right),\left( {\begin{array}{*{20}{c}}{ - 1}\\2\\0\\1\end{array}} \right)} \right\}\).

06

Find the matrix \(P\) and \(D\)

The matrix\(P\)is formed by eigenvectors

\(P = \left( {\begin{array}{*{20}{c}}1&{\frac{3}{2}}&{ - 1}&{ - 1}\\0&1&{ - 1}&2\\0&0&1&0\\0&0&0&1\end{array}} \right)\)

The matrix\(D\)is formed by eigenvalues.

\(D = \left( {\begin{array}{*{20}{c}}5&0&0&0\\0&3&0&0\\0&0&2&0\\0&0&0&2\end{array}} \right)\)

Thus, the matrix \(A\) is diagonalizable with \(P = \left( {\begin{array}{*{20}{c}}1&{\frac{3}{2}}&{ - 1}&{ - 1}\\0&1&{ - 1}&2\\0&0&1&0\\0&0&0&1\end{array}} \right)\) and \(D = \left( {\begin{array}{*{20}{c}}5&0&0&0\\0&3&0&0\\0&0&2&0\\0&0&0&2\end{array}} \right)\).

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Most popular questions from this chapter

Question: Let \(A = \left( {\begin{array}{*{20}{c}}a&b\\c&d\end{array}} \right)\). Use formula (1) for a determinant (given before Example 2) to show that \(\det A = ad - bc\). Consider two cases: \(a \ne 0\) and \(a = 0\).

A common misconception is that if \(A\) has a strictly dominant eigenvalue, then, for any sufficiently large value of \(k\), the vector \({A^k}{\bf{x}}\) is approximately equal to an eigenvector of \(A\). For the three matrices below, study what happens to \({A^k}{\bf{x}}\) when \({\bf{x = }}\left( {{\bf{.5,}}{\bf{.5}}} \right)\), and try to draw general conclusions (for a \({\bf{2 \times 2}}\) matrix).

a. \(A{\bf{ = }}\left( {\begin{aligned}{ {20}{c}}{{\bf{.8}}}&{\bf{0}}\\{\bf{0}}&{{\bf{.2}}}\end{aligned}} \right)\) b. \(A{\bf{ = }}\left( {\begin{aligned}{ {20}{c}}{\bf{1}}&{\bf{0}}\\{\bf{0}}&{{\bf{.8}}}\end{aligned}} \right)\) c. \(A{\bf{ = }}\left( {\begin{aligned}{ {20}{c}}{\bf{8}}&{\bf{0}}\\{\bf{0}}&{\bf{2}}\end{aligned}} \right)\)

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A=[15-27]

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Consider the growth of a lilac bush. The state of this lilac bush for several years (at yearโ€™s end) is shown in the accompanying sketch. Let n(t) be the number of new branches (grown in the year t) and a(t) the number of old branches. In the sketch, the new branches are represented by shorter lines. Each old branch will grow two new branches in the following year. We assume that no branches ever die.

(a) Find the matrix A such that [nt+1at+1]=A[ntat]

(b) Verify that [11]and [2-1] are eigenvectors of A. Find the associated eigenvalues.

(c) Find closed formulas for n(t) and a(t).

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