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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.

6. \(A = \left( {\begin{aligned}{ {20}{c}}1&{ - 2}\\3&{ - 4}\end{aligned}} \right)\)

Short Answer

Expert verified

The required solution is:

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

The origin is an attractor.

The direction of the greatest attraction is through the origin and eigenvector \({v_1} = \left( {\begin{aligned}{ {20}{c}}2\\3\end{aligned}} \right)\).

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:

\(A = \left( {\begin{aligned}{ {20}{c}}1&{ - 2}\\3&{ - 4}\end{aligned}} \right)\)

For eigenvalues:

\(\begin{aligned}{c}\det (A - \lambda I) = 0\\(1 - \lambda )( - 4 - \lambda ) + 6 = 0\\2 + 3\lambda + {\lambda ^2} = 0\\{\lambda _1} = - 2,{\lambda _2} = - 1\end{aligned}\)

The obtained eigenvalues are:\( - 2\)and\( - 1\).

Hence, the origin is an attractor.

03

Find eigenvectors for both eigenvalues

Now, for\({\lambda _1} = - 2\),we have:

\(A = \left( {\begin{aligned}{ {20}{c}}3&{ - 2}&0\\3&{ - 2}&0\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{c}}1&{ - \frac{2}{3}}&0\\0&0&0\end{aligned}} \right)\)

So,\({x_1} = \frac{2}{3}{x_2}\)with\({x_2}\)free.

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

\({v_1} = \left( {\begin{aligned}{ {20}{l}}2\\3\end{aligned}} \right)\)

Similarly,for\({\lambda _2} = - 1\)we have:

\(A = \left( {\begin{aligned}{ {20}{c}}2&{ - 2}&0\\3&{ - 3}&0\end{aligned}} \right)\~\left( {\begin{aligned}{ {20}{l}}1&{ - 1}&0\\0&0&0\end{aligned}} \right)\)

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:

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

Thus,\({c_1} = - 1\)and\({c_2} = 5\),

Now, the general solution will be:

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

Hence, this is the required solution.

04

Find the directions of greatest attraction and/or repulsion

Since both eigenvalues are less than 1, so the origin is an attractor of the dynamical system described by\(x\prime = Ax\).

The direction of greatest repulsion is through the origin, and the eigenvector is \({v_1} = \left( {\begin{aligned}{ {20}{c}}2\\3\end{aligned}} \right)\).

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Most popular questions from this chapter

Suppose \({\bf{x}}\) is an eigenvector of \(A\) corresponding to an eigenvalue \(\lambda \).

a. Show that \(x\) is an eigenvector of \(5I - A\). What is the corresponding eigenvalue?

b. Show that \(x\) is an eigenvector of \(5I - 3A + {A^2}\). What is the corresponding eigenvalue?

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 \(a = 0\).

Question: Exercises 9-14 require techniques section 3.1. Find the characteristic polynomial of each matrix, using either a cofactor expansion or the special formula for \(3 \times 3\) determinants described prior to Exercise 15-18 in Section 3.1. [Note: Finding the characteristic polynomial of a \(3 \times 3\) matrix is not easy to do with just row operations, because the variable \(\lambda \) is involved.

13. \(\left[ {\begin{array}{*{20}{c}}6&- 2&0\\- 2&9&0\\5&8&3\end{array}} \right]\)

Exercises 19โ€“23 concern the polynomial \(p\left( t \right) = {a_{\bf{0}}} + {a_{\bf{1}}}t + ... + {a_{n - {\bf{1}}}}{t^{n - {\bf{1}}}} + {t^n}\) and \(n \times n\) matrix \({C_p}\) called the companion matrix of \(p\): \({C_p} = \left[ {\begin{aligned}{*{20}{c}}{\bf{0}}&{\bf{1}}&{\bf{0}}&{...}&{\bf{0}}\\{\bf{0}}&{\bf{0}}&{\bf{1}}&{}&{\bf{0}}\\:&{}&{}&{}&:\\{\bf{0}}&{\bf{0}}&{\bf{0}}&{}&{\bf{1}}\\{ - {a_{\bf{0}}}}&{ - {a_{\bf{1}}}}&{ - {a_{\bf{2}}}}&{...}&{ - {a_{n - {\bf{1}}}}}\end{aligned}} \right]\).

22. Let \(p\left( t \right) = {a_{\bf{0}}} + {a_{\bf{1}}}t + {a_{\bf{2}}}{t^{\bf{2}}} + {t^{\bf{3}}}\), and let \(\lambda \) be a zero of \(p\).

  1. Write the companion matrix for \(p\).
  2. Explain why \({\lambda ^{\bf{3}}} = - {a_{\bf{0}}} - {a_{\bf{1}}}\lambda - {a_{\bf{2}}}{\lambda ^{\bf{2}}}\), and show that \(\left( {{\bf{1}},\lambda ,{\lambda ^2}} \right)\) is an eigenvector of the companion matrix for \(p\).

In Exercises \({\bf{3}}\) and \({\bf{4}}\), use the factorization \(A = PD{P^{ - {\bf{1}}}}\) to compute \({A^k}\) where \(k\) represents an arbitrary positive integer.

4. \(\left( {\begin{array}{*{20}{c}}{ - 2}&{12}\\{ - 1}&5\end{array}} \right) = \left( {\begin{array}{*{20}{c}}3&4\\1&1\end{array}} \right)\left( {\begin{array}{*{20}{c}}2&0\\0&1\end{array}} \right)\left( {\begin{array}{*{20}{c}}{ - 1}&4\\1&{ - 3}\end{array}} \right)\)

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