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In Exercises 9-18, construct the general solution of \(x' = Ax\) involving complex eigenfunctions and then obtain the general real solution. Describe the shapes of typical trajectories.

14. \(A = \left( {\begin{aligned}{ {20}{c}}{ - 2}&1\\{ - 8}&2\end{aligned}} \right)\)

Short Answer

Expert verified

The general complex solution of \(x' = Ax\) is \({c_1}\left( {\begin{aligned}{ {20}{c}}{1 - i}\\4\end{aligned}} \right){e^{\left( {2i} \right)t}} + {c_2}\left( {\begin{aligned}{ {20}{c}}{1 + i}\\4\end{aligned}} \right){e^{\left( { - 2i} \right)t}}\). The real general solution is of the form \({c_1}\left( {\begin{aligned}{ {20}{c}}{\cos 2t + \sin 2t}\\{4\cos 2t}\end{aligned}} \right) + {c_2}\left( {\begin{aligned}{ {20}{c}}{\sin 2t - \cos 2t}\\{4\sin 2t}\end{aligned}} \right)\). The trajectories are ellipse around the origin since the eigenvalues have real parts of zero.

Step by step solution

01

Determine the eigenvalues and eigenvector of the matrix

The characteristic polynomial is shown below:

\(\begin{aligned}{c}\det \left( {A - \lambda I} \right) = \left( { - 2 - \lambda } \right)\left( {2 - \lambda } \right) - \left( { - 8} \right)\left( 1 \right)\\ = - 4 + 2\lambda - 2\lambda + {\lambda ^2} + 8\\ = {\lambda ^2} + 4\end{aligned}\)

Therefore, the eigenvalues of the matrix \(A\) are \(2i\).

Construct the matrix with eigenvalue \(\lambda = 2i\) as shown below:

\(\begin{aligned}{c}A - \left( {2i} \right)I = \left( {\begin{aligned}{ {20}{c}}{ - 2}&1\\{ - 8}&2\end{aligned}} \right) - \left( {\begin{aligned}{ {20}{c}}{2i}&0\\0&{2i}\end{aligned}} \right)\\ = \left( {\begin{aligned}{ {20}{c}}{ - 2 - 2i}&1\\{ - 8}&{2 - 2i}\end{aligned}} \right)\end{aligned}\)

Write the matrix into the system of the equation as shown below:

\(\begin{aligned}{c}\left( { - 2 - 2i} \right){x_1} - {x_2} = 0\\ - 8{x_1} - \left( {2 - 2i} \right){x_2} = 0\end{aligned}\)

The equation \(A - \left( {2i} \right)I\) equals to \( - 8{x_1} - \left( {2 - 2i} \right){x_2} = 0\). Therefore, \({x_1} = - \frac{{\left( {2 - 2i} \right)}}{8}\) . The eigenvector corresponds to \(\lambda = 2i\) is \({{\mathop{\rm v}\nolimits} _1} = \left( {\begin{aligned}{ {20}{c}}{1 - i}\\4\end{aligned}} \right)\).

02

Construct the general solution of \(x' = Ax\)

The complex eigenfunctions \({\mathop{\rm v}\nolimits} {e^{\lambda t}}\) and \(\overline {\mathop{\rm v}\nolimits} {e^{\overline \lambda t}}\) provides a basis for the set of all complex solutions to \(x' = A{\mathop{\rm x}\nolimits} \). The general complex solution of \(x' = Ax\) is \({c_1}\left( {\begin{aligned}{ {20}{c}}{1 - i}\\4\end{aligned}} \right){e^{\left( {2i} \right)t}} + {c_2}\left( {\begin{aligned}{ {20}{c}}{1 + i}\\4\end{aligned}} \right){e^{\left( { - 2i} \right)t}}\) with \({c_1}\) and \({c_2}\) are arbitrary complex numbers.

03

Construct the real general solution and describe the shape of the trajectories

Rewrite \({\mathop{\rm v}\nolimits} {e^{\left( {2i} \right)t}}\) to construct the real general solution as shown below:

\(\begin{aligned}{c}{\mathop{\rm v}\nolimits} {e^{\left( {2i} \right)t}} = \left( {\begin{aligned}{ {20}{c}}{1 - i}\\4\end{aligned}} \right)\left( {\cos 2t + i\sin 2t} \right)\\ = \left( {\begin{aligned}{ {20}{c}}{\cos 2t + \sin 2t}\\{4\cos 2t}\end{aligned}} \right) + i\left( {\begin{aligned}{ {20}{c}}{\sin 2t - \cos 2t}\\{4\sin 2t}\end{aligned}} \right)\end{aligned}\)

Therefore, the real general solution is of the form \({c_1}\left( {\begin{aligned}{ {20}{c}}{\cos 2t + \sin 2t}\\{4\cos 2t}\end{aligned}} \right) + {c_2}\left( {\begin{aligned}{ {20}{c}}{\sin 2t - \cos 2t}\\{4\sin 2t}\end{aligned}} \right)\), where \({c_1}\) and \({c_2}\) are real numbers.

Therefore, the trajectories are ellipse around the origin since the eigenvalues have real parts of zero.

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Most popular questions from this chapter

Question: In Exercises \({\bf{5}}\) and \({\bf{6}}\), the matrix \(A\) is factored in the form \(PD{P^{ - {\bf{1}}}}\). Use the Diagonalization Theorem to find the eigenvalues of \(A\) and a basis for each eigenspace.

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

Question 19: Let \(A\) be an \(n \times n\) matrix, and suppose A has \(n\) real eigenvalues, \({\lambda _1},...,{\lambda _n}\), repeated according to multiplicities, so that \(\det \left( {A - \lambda I} \right) = \left( {{\lambda _1} - \lambda } \right)\left( {{\lambda _2} - \lambda } \right) \ldots \left( {{\lambda _n} - \lambda } \right)\) . Explain why \(\det A\) is the product of the n eigenvalues of A. (This result is true for any square matrix when complex eigenvalues are considered.)

Question: Let \(A = \left( {\begin{array}{*{20}{c}}{.6}&{.3}\\{.4}&{.7}\end{array}} \right)\), \({v_1} = \left( {\begin{array}{*{20}{c}}{3/7}\\{4/7}\end{array}} \right)\), \({x_0} = \left( {\begin{array}{*{20}{c}}{.5}\\{.5}\end{array}} \right)\). (Note: \(A\) is the stochastic matrix studied in Example 5 of Section 4.9.)

  1. Find a basic for \({\mathbb{R}^2}\) consisting of \({{\rm{v}}_1}\) and anther eigenvector \({{\rm{v}}_2}\) of \(A\).
  2. Verify that \({{\rm{x}}_0}\) may be written in the form \({{\rm{x}}_0} = {{\rm{v}}_1} + c{{\rm{v}}_2}\).
  3. For \(k = 1,2, \ldots \), define \({x_k} = {A^k}{x_0}\). Compute \({x_1}\) and \({x_2}\), and write a formula for \({x_k}\). Then show that \({{\bf{x}}_k} \to {{\bf{v}}_1}\) as \(k\) increases.

Define\(T:{{\rm P}_3} \to {\mathbb{R}^4}\)by\(T\left( {\bf{p}} \right) = \left( {\begin{aligned}{{\bf{p}}\left( { - 3} \right)}\\{{\bf{p}}\left( { - 1} \right)}\\{{\bf{p}}\left( 1 \right)}\\{{\bf{p}}\left( 3 \right)}\end{aligned}} \right)\).

  1. Show that \(T\) is a linear transformation.
  2. Find the matrix for \(T\) relative to the basis \(\left\{ {1,t,{t^2},{t^3}} \right\}\)for \({{\rm P}_3}\)and the standard basis for \({\mathbb{R}^4}\).

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

15. \(\left( {\begin{array}{*{20}{c}}{\bf{7}}&{\bf{4}}&{{\bf{16}}}\\{\bf{2}}&{\bf{5}}&{\bf{8}}\\{{\bf{ - 2}}}&{{\bf{ - 2}}}&{{\bf{ - 5}}}\end{array}} \right)\)

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