Solving System of ODEs: Matrix Form, Eigenvalues/Vectors

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Discussion Overview

The discussion revolves around solving a system of ordinary differential equations (ODEs) represented in matrix form. Participants explore the process of finding eigenvalues and eigenvectors, as well as expressing the general solution in both matrix and scalar forms. The conversation includes algebraic manipulations and interpretations of results.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant presents a system of ODEs and attempts to express it in matrix form, identifying the matrix A as \begin{bmatrix} -2 & 1 \\ 2 & -3 \end{bmatrix}.
  • The same participant calculates eigenvalues, proposing $\lambda_1 = -1$ and $\lambda_2 = -4$.
  • There is a discussion about finding an eigenvector for the smallest eigenvalue, with one participant expressing uncertainty about the algebraic steps and the implications of a repeated root.
  • Another participant confirms the eigenvector for the eigenvalue -1 can be represented as $\binom {-1}{-1}$ or $\binom 11$.
  • Further questions arise regarding the general solution in matrix form, with one participant providing an expression and seeking clarification on how to convert it into scalar form.
  • Participants discuss the need to rewrite the vector solution into a set of scalar equations, with one participant questioning the coefficients in the proposed equations.
  • There is a correction regarding a coefficient in one of the scalar equations, indicating a collaborative effort to refine the solution.

Areas of Agreement / Disagreement

Participants generally agree on the process of finding eigenvalues and eigenvectors, but there are uncertainties regarding specific algebraic steps and interpretations of the results. The discussion remains unresolved on some aspects, particularly the conversion to scalar form and the coefficients involved.

Contextual Notes

Some participants express confusion about the implications of repeated roots and the correct representation of eigenvectors. There are also unresolved questions about the coefficients in the scalar equations derived from the vector solution.

shamieh
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Getting stuck on something I think that could be trivial. Maybe someone can see my mistake.

consider the system: $x' = -2x + y$ and $y' = 2x - 3y$

a) Write the system in matrix form
my solution

$\overrightarrow{X} = (^x_y)$

so: $X' = (^{x'}_{y'})$

so $A = $ \begin{bmatrix} -2 & 1 \\ 2 & -3 \end{bmatrix}

b) Find the eigenvalues for the system.
my solution
$\lambda_1 = -1$ and $\lambda_2 = -4$

c) Find an eigenvector for the smallest eigenvalue.
my solution ( Here is where I have either made a algebra mistake or I don't know how to proceed)
$(I-A)X \rightarrow (-I-A)X =$ (\begin{bmatrix} -1 & 0 \\ 0 & - 1 \end{bmatrix} $-$ \begin{bmatrix} -2 & 1 \\ 2 & - 3 \end{bmatrix} ) $X$

Then I am getting: $v_1 - v_2 = 0$ and $-2v_1 + 2v_2 = 0 $ which can be rewritten as one equation $\rightarrow -2v_1+2v_2=0$ so it seems the only numbers I can plug in are: $v_1 = v_2 = -1$ ? But then won't I have like $(^{-1}_{-1})$ and I thought you couldn't do that? Is this the repeated root thing and if so how do I proceed? Or have i made a algebra mistake.

Thanks in advance.
 
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Hi shamieh,

You are correct. The eigenvector for -1 is $\binom {-1}{-1}$. Or alternatively $\binom 11$. If you multiply A with it, you'll get its negative equivalent, as expected.
What do you mean with a repeated root?
 
Ignore my comment about the repeated root, I'm thinking too hard :rolleyes: .. So similarly would the eigenvector for the largest value be $(^1_{-2})$ ?

- - - Updated - - -

so I have two more questions with regards to this problem.

e) Write the general solution to the system in matrix form.
I got: $X(t) = C_1(^1_1)e^{-t} + C_2 (^1_{-2})e^{-4t}$but part f) says : Write the general solution to the system in scalar form.. What exactly does that mean? How do I do that?
 
shamieh said:
Ignore my comment about the repeated root, I'm thinking too hard :rolleyes: .. So similarly would the eigenvector for the largest value be $(^1_{-2})$ ?

Yup. (Nod)

so I have two more questions with regards to this problem.

e) Write the general solution to the system in matrix form.
I got: $X(t) = C_1(^1_1)e^{-t} + C_2 (^1_{-2})e^{-4t}$

Did you check if it fits into the original DE?
If it fits, it must be right.
but part f) says : Write the general solution to the system in scalar form.. What exactly does that mean? How do I do that?

The solution you have in e) is an equation containing vectors.
So I believe you're supposed to rewrite it into a set of equations that do not contain vectors:
\begin{cases}
x_1(t) = C_1 e^{-t} + C_2 e^{-4t}\\
x_2(t) = C_1 e^{-t} -4 C_2 e^{-4t}
\end{cases}
See? Only scalars.
 
I like Serena said:
Yup. (Nod)
Did you check if it fits into the original DE?
If it fits, it must be right.

The solution you have in e) is an equation containing vectors.
So I believe you're supposed to rewrite it into a set of equations that do not contain vectors:
\begin{cases}
x_1(t) = C_1 e^{-t} + C_2 e^{-4t}\\
x_2(t) = C_1 e^{-t} -4 C_2 e^{-4t}
\end{cases}
See? Only scalars.

But do you think I should write it as: $X(t) = 2C_1 e^{-t} - C_2 e^{-4t}$ ? Also why do you have a 4 in front of the $C_2$ in your $x_2(t)$ eqn ?
 
shamieh said:
But do you think I should write it as: $X(t) = 2C_1 e^{-t} - C_2 e^{-4t}$ ?

Huh? :confused:
X(t) is a vector while the right hand side is a scalar. That can't be right.
And where do you coefficients come from?

Also why do you have a 4 in front of the $C_2$ in your $x_2(t)$ eqn ?

Sorry. That should be a 2.
 

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