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In Exercises \(1-4\), without the aid of technology, using only your algebra skills, sketch the nullclines and find the equilibrium point(s) of the assigned system. Indicate the flow of the the vector field along each nullcline, similar to that shown in Figure 13.1. Check your result with pplane6. If the Symbolic Toolbox is available, use the solve command to find the equilibrium point(s). $$ \begin{aligned} &x^{\prime}=x+2 y \\ &y^{\prime}=2 x-y \end{aligned} $$

Short Answer

Expert verified
The equilibrium point is (0,0).

Step by step solution

01

Define the Nullclines

Identify the nullclines by setting each derivative in the system to zero:1. For the nullcline associated with \(x'\), set \(x' = x + 2y = 0\) to find the equation defining the nullcline.2. For the nullcline associated with \(y'\), set \(y' = 2x - y = 0\) to find the equation defining the nullcline.
02

Solve for Nullclines Equations

For each equation, solve for one variable in terms of the other:1. From \(x + 2y = 0\), solve for \(y\) to get \(y = -\frac{x}{2}\).2. From \(2x - y = 0\), solve for \(y\) to get \(y = 2x\).These are the equations of the nullclines.
03

Find Intersection of Nullclines

Solve the equations of the nullclines to find the equilibrium point(s):- Set \(y = -\frac{x}{2}\) equal to \(y = 2x\): \[-\frac{x}{2} = 2x\] Solving this gives \(x = 0\).- Substitute \(x = 0\) into \(y = -\frac{x}{2}\) to find \(y = 0\).Thus, the equilibrium point is \((0,0)\).
04

Sketch Nullclines and Indicate Flow

Draw the nullclines on a coordinate plane:- The line \(y = -\frac{x}{2}\) is a nullcline where \(x' = 0\).- The line \(y = 2x\) is a nullcline where \(y' = 0\).To indicate the flow of the vector field, consider the sign of the derivatives:- Above the line \(y = -\frac{x}{2}\), \(x' = x + 2y > 0\); flow is to the right.- Below the line \(y = -\frac{x}{2}\), \(x' = x + 2y < 0\); flow is to the left.- To the right of the line \(y = 2x\), \(y' = 2x - y > 0\); flow is upward.- To the left of the line \(y = 2x\), \(y' = 2x - y < 0\); flow is downward.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Nullclines
Nullclines are a vital tool used in analyzing systems of differential equations. They are lines in the plane where either the rate of change of the first variable or the second variable is zero. This entails that on a nullcline, the variables are not changing. In other words, they provide pathways along which the solution to the differential equation remains constant in one dimension. To find the nullclines in a given system of equations, we set each derivative to zero and solve for the variables involved. For example, given the system:- \( x' = x + 2y \)- \( y' = 2x - y \)We can derive the nullclines by:- Setting \( x' = 0 \) and solving \( x + 2y = 0 \), resulting in the nullcline equation \( y = -\frac{x}{2} \)- Setting \( y' = 0 \) and solving \( 2x - y = 0 \), resulting in the nullcline equation \( y = 2x \)Nullclines intersect at equilibrium points, playing a crucial role in visualizing the nature of the system's behavior.
Equilibrium Points
Equilibrium points in a differential equation system are locations where the system does not change over time. At these points, both derivatives, typically represented as \( x' \) and \( y' \), are equal to zero. This means the entire system reaches a balance, creating a resting spot within the vector field. To find equilibrium points, you need to solve for the intersection of the nullclines. Using the earlier derived nullclines, we find the point of intersection by:- Equating \( y = -\frac{x}{2} \) and \( y = 2x \)- Solving \( -\frac{x}{2} = 2x \), leading to \( x = 0 \)- Substituting \( x = 0 \) back into either nullcline equation, such as \( y = -\frac{x}{2} \), gives \( y = 0 \)Thus, the equilibrium point is found to be \((0,0)\). At this point, for small disturbances, the system's behavior can be further determined, whether stable or unstable, often using other analytical techniques like linearization.
Vector Field
A vector field provides a graphical depiction of how solutions to a differential equation system evolve over time within the phase plane. It consists of arrows indicating direction and velocity of the system's state variables, \( x \) and \( y \), at each point in that space.Understanding the vector field involves interpreting the behavior of solutions along the nullclines - Above and below the nullcline \( y = -\frac{x}{2} \), the vector field points to the right and left, respectively, as \( x' \) changes sign.- Likewise, to the right and left of the nullcline \( y = 2x \), the vector field points upward and downward as \( y' \) changes sign.This visualization helps to predict behavior of real physical systems, allowing to see how dynamic conditions might stabilize or change, guiding qualitative understanding of the system's kinematics.

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Most popular questions from this chapter

It is a nice exercise to classify linear systems based on their position in the trace-determinant plane. Consider the matrix $$ A=\left[\begin{array}{ll} a & b \\ c & d \end{array}\right] $$ a) Show that the characteristic polynomial of the matrix \(A\) is \(p(\lambda)=\lambda^{2}-T \lambda+D\), where \(T=a+d\) is the trace of \(A\) and \(D=\operatorname{det}(A)=a d-b c\) is the determinant of \(A\). b) We know that the characteristic polynomial factors as \(p(\lambda)=\left(\lambda-\lambda_{1}\right)\left(\lambda-\lambda_{2}\right)\), where \(\lambda_{1}\) and \(\lambda_{2}\) are the eigenvalues. Use this and the result of part (a) to show that the product of the eigenvalues is equal to the determinant of matrix A. Note: This is a useful fact. For example, if the determinant is negative, then you must have one positive and one negative eigenvalue, indicating a saddle equilibrium point. Also, show that the sum of the eigenvalues equals the trace of matrix \(A\). c) Show that the eigenvalues of matrix \(A\) are given by the formula $$ \lambda=\frac{T \pm \sqrt{T^{2}-4 D}}{2} $$ Note that there are three possible scenarios. If \(T^{2}-4 D<0\), then there are two complex eigenvalues. If \(T^{2}-4 D>0\), there are two real eigenvalues. Finally, if \(T^{2}-4 D=0\), then there is one repeated eigenvalue of algebraic multiplicity two. d) Draw a pair of axes on a piece of poster board. Label the vertical axis \(D\) and the horizontal axis \(T\). Sketch the graph of \(T^{2}-4 D=0\) on your poster board. The axes and the parabola defined by \(T^{2}-4 D=0\) divide the trace- determinant plane into six distinct regions, as shown in Figure 13.17. e) You can classify any matrix \(A\) by its location in the trace-determinant plane. For example, if $$ A=\left[\begin{array}{rr} 1 & 2 \\ -3 & 2 \end{array}\right] $$ then \(T=3\) and \(D=8\), so the point \((T, D)\) is located in the first quadrant. Furthermore, \((3)^{2}-4(8)<\) 0 , placing the point \((3,8)\) above the parabola \(T^{2}-4 D=0\). Finally, if you substitute \(T=3\) and \(D=8\) into the formula \(\lambda=\left(T \pm \sqrt{T^{2}-4 D}\right) / 2\), then you get eigenvalues that are complex with a positive real part, making the equilibrium point of the system \(\mathbf{x}^{\prime}=A \mathbf{x}\) a spiral source. Use pplane6 to generate a phase portrait of this particular system and attach the printout to the poster board at the point \((3,8)\). f) Linear systems possess a small number of distinctive phase portraits. Each of these is graphically different from the others, but each corresponds to the pair of eigenvalues and their multiplicities. For each case, use pplane 6 to construct a phase portrait, and attach a printout at its appropriate point \((T, D)\) in your poster board trace-determinant plane. Hint: There are degenerate cases on the axes and the parabola. For example, you can find degenerate cases on the parabola in the first quadrant that separate nodal sources from spiral sources. There are also a number of interesting degenerate cases at the origin of the trace-determinant plane. One final note: We have intentionally used the words "small number of distinctive cases"' so as to spur argument amongst our readers when working on this activity. What do you think is the correct number?

Consider the nonlinear system $$ \begin{aligned} &x^{\prime}=x(1-x)-x y, \\ &y^{\prime}=y(2-y)+2 x y . \end{aligned} $$ Show that \((-1 / 3,4 / 3)\) is an equilibrium point of the system. a) Without the use of technology, calculate the Jacobian of the system at the equilibrium point \((-1 / 3\), \(4 / 3)\). What is the equation of the linearization at this equilibrium point? Use [v,e]=eig( \(\mathrm{J})\) to find the eigenvalues and eigenvectors of this Jacobian. b) Enter the system in pplane6. Find the equilibrium point at \((-1 / 3,4 / 3)\). Does the data in the Equilibrium point data window agree with your findings in part (a)? Note: The eigenvalues of the Jacobian predict classification of the equilibrium point. In this case, the point \((-1 / 3,4 / 3)\) is a saddle because the eigenvalues are real and opposite in sign. c) Display the linearization. Does the equation of the linearization agree with your findings in part (a)?

Duffing 's equation is $$ m x^{\prime \prime}+c x^{\prime}+k x+l x^{3}=F(t) $$ When \(k>0\) this equation models a vibrating spring, which could be soft \((l<0)\) or hard \((l>0)\) (See Student Project #1 in Chapter 8). When \(k<0\) the equation arises as a model of the motion of a long thin elastic steel beam that has its top end embedded in a pulsating frame (the \(F(t)\) term), and its lower end hanging just above two magnets which are slightly displaced from what would be the equilibrium position. We will be looking at the unforced case (i.e. \(F(t)=0\) ), with \(m=1\). The system corresponding to Duffing's equation is available in the Gallery menu. a) This is the case of a hard spring with \(k=16\), and \(l=4\). Use pplane 6 to plot the phase planes of some solutions with the damping constant \(c=0,1\), and 4. In particular, find all equilibrium points. b) Do the same for the soft spring with \(k=16\) and \(l=-4\). Now there will be a pair of saddle points. Find them and plot the stable/unstable orbits. c) Now consider the case when \(k=-1\), and \(l=1\). For each of the cases \(c=0, c=0.2\), and \(c=1\), use pplane6 to analyze the system. In particular, find all equilibrium points and determine their types. Plot stable/unstable orbits where appropriate, and plot typical orbits. d) With \(c=0.2\) in part c), there are two sinks. Determine the basins of attraction of each of these sinks. Indicate these regions on a print out of the phase plane.

What condition on \(\lambda\) will ensure that the straight line solution \(\mathbf{x}(t)=e^{\lambda t} \mathbf{v}\) moves toward the equilibrium point at the origin as time increases? What condition ensures that the straight line solution will move away from the equilibrium point as time increases?

In Exercises \(21-30\), perform steps i) and ii) for the linear system $$ \mathbf{x}^{\prime}=\mathbf{A x}, $$ where \(\mathbf{A}\) is the given matrix. i) Find the type of the equilibrium point at the origin. Do this without the aid of any technology or pplane6. You may, of course, check your answer using pplane. ii) Use pplane6 to plot several solution curves - enough to fully illustrate the behavior of the system. You will find it convenient to use the "linear system" choice from the Gallery menu. If the eigenvalues are real, use the "Keyboard input" option to include straight line solutions starting at \(\pm 10\) times the eigenvectors. If the equilibrium point is a saddle point, compute and plot the separatrices. $$ \left[\begin{array}{rr} -1 & 0 \\ 0 & -1 \end{array}\right] $$

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