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

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 \({\mathbb{R}^2}\).

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.

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

Question: In Exercises \({\bf{1}}\) and \({\bf{2}}\), let \(A = PD{P^{ - {\bf{1}}}}\) and compute \({A^{\bf{4}}}\).

1. \(P{\bf{ = }}\left( {\begin{array}{*{20}{c}}{\bf{5}}&{\bf{7}}\\{\bf{2}}&{\bf{3}}\end{array}} \right)\), \(D{\bf{ = }}\left( {\begin{array}{*{20}{c}}{\bf{2}}&{\bf{0}}\\{\bf{0}}&{\bf{1}}\end{array}} \right)\)

Question: Construct a random integer-valued \(4 \times 4\) matrix \(A\).

  1. Reduce \(A\) to echelon form \(U\) with no row scaling, and use \(U\) in formula (1) (before Example 2) to compute \(\det A\). (If \(A\) happens to be singular, start over with a new random matrix.)
  2. Compute the eigenvalues of \(A\) and the product of these eigenvalues (as accurately as possible).
  3. List the matrix \(A\), and, to four decimal places, list the pivots in \(U\) and the eigenvalues of \(A\). Compute \(\det A\) with your matrix program, and compare it with the products you found in (a) and (b).

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 \(A\).
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