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In Exercises 3-6, solve the initial value problem \(x'\left( t \right) = Ax\left( t \right)\) for \(t \ge 0\), with \(x\left( 0 \right) = \left( {3,2} \right)\). Classify the nature of the origin as an attractor, repeller, or saddle point of the dynamical system described by \(x' = Ax\). Find the directions of greatest attraction and/or repulsion. When the origin is a saddle point, sketch typical trajectories.

3. \(A = \left( {\begin{aligned}{ {20}{c}}2&3\\{ - 1}&{ - 2}\end{aligned}} \right)\)

Short Answer

Expert verified

The required solution is:

\(x\left( t \right) = - \frac{5}{2}\left( {\begin{aligned}{ {20}{c}}{ - 3}\\1\end{aligned}} \right){e^t} + \frac{9}{2}\left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right){e^{ - t}}\)

The origin is a saddle point.

The direction of greatest repulsion is through the origin, and the eigenvector is\({v_1} = \left( {\begin{aligned}{ {20}{c}}{ - 3}\\1\end{aligned}} \right)\).

The direction of greatest attraction is through the origin and eigenvector is \({v_2} = \left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right)\).

Step by step solution

01

System of Differential Equations

The general solutionfor any system of differential equations withthe eigenvalues\({\lambda _1}\)and\({\lambda _2}\)with the respective eigenvectors\({v_1}\)and\({v_2}\)is given by:

\(x(t) = {c_1}{v_1}{e^{{\lambda _1}t}} + {c_2}{v_2}{e^{{\lambda _2}t}}\)

Here \({c_1}\) and \({c_2}\) are the constants from the initial condition.

02

Find the eigenvalues

As per the question, we have:

\(A = \left( {\begin{aligned}{ {20}{c}}2&3\\{ - 1}&{ - 2}\end{aligned}} \right)\)

For eigenvalues:

\(\begin{aligned}{c}det(A - \lambda I) = 0\\{\lambda ^2} - 1 = 0\\(\lambda - 1)(\lambda + 1) = 0\end{aligned}\)

The obtained eigenvalues are 1 and\( - 1\).

Hence, the origin is a saddle point.

03

Find eigenvectors for both eigenvalues

Now, we have:

\(A = \left( {\begin{aligned}{ {20}{c}}1&3&0\\{ - 1}&{ - 3}&0\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{c}}1&3&0\\0&0&0\end{aligned}} \right)\)

So,\({x_1} = - 3{x_2}\)with\({x_2}\)free.

Taking\({x_2} = 1\), we get, eigenvector:

\({v_1} = \left( {\begin{aligned}{ {20}{l}}{ - 3}\\1\end{aligned}} \right)\)

Similarly,

\(A = \left( {\begin{aligned}{ {20}{c}}3&3&0\\{ - 1}&{ - 1}&0\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{l}}1&1&0\\0&0&0\end{aligned}} \right)\)

So\({x_1} = - {x_2}\)with\({x_2}\)free.

Taking\({x_2} = 1\), we get:

\({v_2} = \left( {\begin{aligned}{ {20}{l}}{ - 1}\\1\end{aligned}} \right)\)

Using both eigenvectors, we have:

\(\left( {\begin{aligned}{ {20}{l}}{{v_1}}&{{v_2}}&{x(0)}\end{aligned}} \right) = \left( {\begin{aligned}{ {20}{c}}{ - 3}&{ - 1}&3\\1&1&2\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{c}}1&0&{ - 5/2}\\0&1&{9/2}\end{aligned}} \right)\)

Thus,\({c_1} = - 5/2,{\rm{ }}{c_2} = 9/2\).

Now, the general solution will be:

\(x(t) = - \frac{5}{2}\left( {\begin{aligned}{ {20}{c}}{ - 3}\\1\end{aligned}} \right){e^t} + \frac{9}{2}\left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right){e^{ - t}}\)

Hence, this is the required solution.

04

Find the directions of greatest attraction and/or repulsion

Since one eigenvalue is less than one and the other is greater, the origin is a saddle point of the dynamical system described by\(x\prime = Ax\).

The direction of greatest repulsion is through the origin, and the eigenvector is\({v_1} = \left( {\begin{aligned}{ {20}{c}}{ - 3}\\1\end{aligned}} \right)\).

The direction of greatest attraction is through the origin and eigenvector is \({v_2} = \left( {\begin{aligned}{ {20}{c}}{ - 1}\\1\end{aligned}} \right)\).

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Most popular questions from this chapter

Question: In Exercises 21 and 22, \(A\) and \(B\) are \(n \times n\) matrices. Mark each statement True or False. Justify each answer.

  1. The determinant of \(A\) is the product of the diagonal entries in \(A\).
  2. An elementary row operation on \(A\) does not change the determinant.
  3. \(\left( {\det A} \right)\left( {\det B} \right) = \det AB\)
  4. If \(\lambda + 5\) is a factor of the characteristic polynomial of \(A\), then 5 is an eigenvalue of \(A\).

Consider an invertiblen ร— n matrix A such that the zero state is a stable equilibrium of the dynamical system xโ†’(t+1)=Axโ†’(t)What can you say about the stability of the systems

xโ†’(t+1)=(A-2In)xโ†’(t)

Compute the quantities in Exercises 1-8 using the vectors

\({\mathop{\rm u}\nolimits} = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\2\end{aligned}} \right),{\rm{ }}{\mathop{\rm v}\nolimits} = \left( {\begin{aligned}{*{20}{c}}4\\6\end{aligned}} \right),{\rm{ }}{\mathop{\rm w}\nolimits} = \left( {\begin{aligned}{*{20}{c}}3\\{ - 1}\\{ - 5}\end{aligned}} \right),{\rm{ }}{\mathop{\rm x}\nolimits} = \left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\\3\end{aligned}} \right)\)

2. \({\mathop{\rm w}\nolimits} \cdot {\mathop{\rm w}\nolimits} ,{\mathop{\rm x}\nolimits} \cdot {\mathop{\rm w}\nolimits} ,\,\,{\mathop{\rm and}\nolimits} \,\,\frac{{{\mathop{\rm x}\nolimits} \cdot {\mathop{\rm w}\nolimits} }}{{{\mathop{\rm w}\nolimits} \cdot {\mathop{\rm w}\nolimits} }}\)

Let\(T:{{\rm P}_2} \to {{\rm P}_3}\) be a linear transformation that maps a polynomial \({\bf{p}}\left( t \right)\) into the polynomial \(\left( {t + 5} \right){\bf{p}}\left( t \right)\).

  1. Find the image of\({\bf{p}}\left( t \right) = 2 - t + {t^2}\).
  2. Show that \(T\) is a linear transformation.
  3. Find the matrix for \(T\) relative to the bases \(\left\{ {1,t,{t^2}} \right\}\) and \(\left\{ {1,t,{t^2},{t^3}} \right\}\).

Question: Let \(A = \left( {\begin{array}{*{20}{c}}{ - 6}&{28}&{21}\\4&{ - 15}&{ - 12}\\{ - 8}&a&{25}\end{array}} \right)\). For each value of \(a\) in the set \(\left\{ {32,31.9,31.8,32.1,32.2} \right\}\), compute the characteristic polynomial of \(A\) and the eigenvalues. In each case, create a graph of the characteristic polynomial \(p\left( t \right) = \det \left( {A - tI} \right)\) for \(0 \le t \le 3\). If possible, construct all graphs on one coordinate system. Describe how the graphs reveal the changes in the eigenvalues of \(a\) changes.

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