Setting up linear systems in a matrix

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Homework Help Overview

The discussion revolves around setting up and analyzing a linear system represented by a matrix. Participants are tasked with determining the stability of the critical point (0,0) for the system defined by the equations dx/dt = -2x and dy/dt = -2y, using matrix methods as instructed by their professor.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the correct formulation of the matrix and the identification of eigenvalues and eigenvectors. There are attempts to derive the characteristic equation and concerns about obtaining non-zero eigenvectors. Questions arise regarding the setup of the general solution and the implications of having a null matrix in the eigenvalue calculations.

Discussion Status

The discussion is ongoing, with participants exploring different interpretations of the matrix and its properties. Some have provided insights into the nature of eigenvalues for diagonal matrices, while others are clarifying the implications of their findings on the general solution. There is no explicit consensus yet, but productive guidance has been shared regarding the identification of eigenvalues and eigenvectors.

Contextual Notes

Participants are operating under the constraints of using matrix methods as specified by their professor, which has led to confusion regarding the application of eigenvalue theory and the setup of the general solution. The discussion reflects a mix of correct and incorrect assumptions about the matrix and its properties.

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I am getting stuck on the very beginning of these homework problems.

Solve the linear system to determine whether the critical point (0,0) is stable, asymtotically stable, or unstable.

[tex]dx/dt = -2x, dy/dt = -2y[/tex]

The book uses separation of variables, but the professor has instructed us to use matrices to do these homework problems.
[tex]x= \left(\begin{array}{c} -2 \ 0\\ 0 \ -2 \end{array}\right)[/tex]
[tex]\lambda_1 = 0, \lambda_2 = 4[/tex]

Is this the right matrix? When I use lambda = 0 in the eigenvalue method (A - (lambda)I)=0 on that matrix, the vector entries a and b both = 0 because it's just a diagonal matrix. I need to find a general solution such that
x = c1v1e^((lambda)t) + c2v2e^((lambda)t). Then determine the stability of x. But first I need to know how to set it up.
 
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You have your function x equal to a 2x2 matrix? That matrix does equal something important, but its certainly not x. And the numbers you found are not the eigenvalues of that matrix. Looking at the matrix, it should be very obvious what the eigenvalue(s) is/are. To help you get started:

[tex]\left(\begin{array}{c}x'\\y'\end{array}\right)=\left(\begin{array}{cc}-2&0\\0&-2\end{array}\right)\left(\begin{array}{c}x\\y\end{array}\right)[/tex]
 
I got the eigenvalues with the characteristic equation.
[tex](-2 - \lambda)(-2 - \lambda) -4 = 0[/tex]
[tex]\lambda^2 + 4\lambda = 0[/tex]
[tex]\lambda_1 = 0, \lambda_2 = -4[/tex]

Case 1:
[tex](A - \lambda I = 0)[/tex]
[tex]-2x + 0y = 0[/tex]
[tex]0x - 2y = 0[/tex]
[tex]x = 0, y =0[/tex]
v_1 = [0,0]

Case 2:
[tex]2x + 0y = 0[/tex]
[tex]0x + 2y = 0[/tex]
v_2 = [0,0]

Both eigenvectors equal 0? How can I set up a general solution without eigenvectors = 0? The general solution should be of the form [tex]x(t) = c_1v_1e^(lambda_1 t) + c_2v_2e^(lambda_2 t)[/tex]

[tex]\lambda t[/tex] should be in the exponent of e in the equation above, but I don't know how to make the code do that.
 
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That's not the characteristic equation.
 
Oops.
[tex]\lambda ^2 + 4\lambda + 4 = 0[/tex]
[tex]\lambda_1 = \lambda_2 = -2[/tex]

Find v_1: [tex](A - \lambda I = 0)[/tex]
[tex]\left(\begin{array}{c} 0 \ 0\\ 0 \ 0 \end{array}\right)[/tex]

How can I get an eigenvector when (A - lambda) = 0?

Since the eigenvalues are equal and less than zero, I know it is a stable proper node. So the graphing part is done. But I need a general solution.
 
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substitute back in your eigenvalues (this doesn't give the null matrix) and satisfy:

[tex]A{\bf v}=\lambda {\bf v}[/tex]

or

[tex](A-\lambda I){\bf v}=0[/tex]

where the eigenvector [tex]{\bf v}=(v_1; v_2)[/tex]
 
It might be worth your time to notice that if the matrix is
[tex]\left(\begin{array}{c} a \ 0\\ b \ c \end{array}\right)[/tex]
then the eigenvalue equation is
[tex]\left|\begin{array}{c}a-\lambda \ 0\\ b\ c-\lambda\end{array}\right|= (a- \lambda)(c-\lambda)= 0[/tex]
In other words for any triangular (which include diagonal) matrix, the numbers on the main diagonal are the eigenvalues.
 
[tex](A-\lambda I){\bf v}=0[/tex]
[tex]\left(\begin{array}{c} -2 \ 0\\ 0 \ -2 \end{array}\right)[/tex]
[tex]\left(\begin{array}{c} -2-(-2) \ 0\\ 0 \ -2-(-2) \end{array}\right)[/tex]
[tex]\left(\begin{array}{c} 0 \ 0\\ 0 \ 0 \end{array}\right)[/tex]

or

[tex](-2 - (-2)){\bf v}=0[/tex]
[tex]0v = 0[/tex]

What am I missing?
 
After asking the professor about this, it turns out the matrix is
[tex]\left(\begin{array}{c} 0 \ 0\\ 0 \ 0 \end{array}\right)[/tex]
after
[tex](A-\lambda I){\bf v}=0[/tex]

This means any vector will work.
[tex]v_1 = \left(\begin{array}{c} 1 \\ 0 \end{array}\right)[/tex]
[tex]v_2 = \left(\begin{array}{c} 0 \\ 1 \end{array}\right)[/tex]

General Solution:
x(t) = c_1(1)e^-2t + c_2(0)e^-2t = c_1e^-2t
y(t) = c_1(0)e^-2t + c_2(1)e^-2t = c_2e^-2t
 
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  • #10
That's correct. Note you should be able to look at your matrix, and recognize that it's -2I, where I is the identity matrix. If you know what eigenvectors and eigenvalues are (and not just how to compute them) then you should be able to see immediately that the only eigenvalue is -2, and that every vector is an eigenvector.
 
  • #11
The linear algebra explanation of this is the easiest way for me to understand it. Since [tex](A - \lambda I = 0)[/tex] is -2a - 0b = 0, a is a free variable. So a could be anything, which leads to an eigenvector that could be anything. Thanks everyone!
 

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