I can't seem to find an eigenvector for this 2x2 matrix

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    Eigenvector Matrix
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Homework Help Overview

The discussion revolves around finding eigenvectors for a given 2x2 matrix in the context of ordinary differential equations (ODEs). Participants explore the definitions and relationships between matrices and their eigenvectors.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • The original poster attempts to find eigenvectors by setting up equations based on the matrix but questions the validity of their results when they arrive at a zero vector. Other participants suggest alternative formulations of the eigenvector equation and clarify the relationship between eigenvalues and eigenvectors.

Discussion Status

Some participants have identified mistakes in the setup of the matrix and equations, leading to a more productive exploration of the correct eigenvector relationships. There is an ongoing examination of the definitions and methods related to eigenvalues and eigenvectors.

Contextual Notes

Participants note the importance of correctly applying the characteristic equation and the potential for errors in matrix manipulation. The discussion reflects a learning environment where assumptions and definitions are being critically evaluated.

Hercuflea
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Homework Statement



I'm doing an ODE for homework and I can't find the eigenvector for this matrix (sorry, I don't know how to make matrices on here. Consider these as one matrix.):

[ 2 0] [v[itex]_{1}[/itex]] = [0]
[ 1 1] [v[itex]_{2}[/itex]] = [0]

Homework Equations



The only way he has taught us to find eigenvectors seems mostly like guesswork to me.

The Attempt at a Solution



2v[itex]_{1}[/itex] + 0v[itex]_{2}[/itex] = 0

v[itex]_{1}[/itex] + v[itex]_{2}[/itex] = 0

So 2v[itex]_{1}[/itex] = 0 =====> v[itex]_{1}[/itex] = 0

But v[itex]_{1}[/itex] + v[itex]_{2}[/itex] = 0, so v[itex]_{2}[/itex] = 0 as well. But eigenvectors cannot consist of all zeros?
 
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wouldnt your eqn be more like

M * v = k * v where M is your matrix and k is some constant and v is your vector

2*v1 + 0*v2 = k * v1

v1 + v2 = k*v2
 
Sorry maybe I didn't give the full background. (A-rI)v = 0

A =

[3 1]
[2 2]

one of the roots of the characteristic equation is r[itex]_{2}[/itex] = 1

Since r[itex]_{2}[/itex] = 1, (A-I)v=0

So

[ 2 0]
[ 1 1] v = 0
 
!

Just found my mistake, I copied the matrix wrong!

This is embarrasseing...
 
isn't that just Av = Iv which is Av = v ?
 
Found my mistake, I accidentally subtracted 1 from ALL the elements in the original matrix A, when I should have only subtracted 1 from a11 and a22
 
Since you have found your error, expanding on jedishrfu's suggestion that you solve Av= v, that would be [tex]\begin{bmatrix}3 & 1 \\ 2 & 2\end{bmatrix}\begin{bmatrix}x \\ y\end{bmatrix}= \begin{bmatrix}x \\ y\end{bmatrix}[/tex].
which gives the equations 3x+ y= x and 2x+ 2y= y, both of which are equivalent to y= -2x. That is, any eigenvector, corresponding to eigenvalue 1, is of the form <x, y>= <x, -2x>= x<1, -2>.

For the other eigenvalue, 4, we have [tex]\begin{bmatrix}3 & 1 \\ 2 & 2\end{bmatrix}\begin{bmatrix}x \\ y\end{bmatrix}= 4\begin{bmatrix}x \\ y\end{bmatrix}[/tex]
which gives the equations 3x+ y= 4x and 2x+ 2y= 4y, both of which are equivalent to y= x. That is, any eigenvector, corresponding to eigenvalue 4, is of the form <x, y>=<x, x>= x<1, 1>.

Of course, solving [itex](A- \lambda)v= 0[/itex] is equivalent to solving [itex]Av= \lambda v[/itex] but the latter is more closely connected to the definitions of "eigenvalue" and "eigenvector".
 

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