Reminder on how to find eigenvectors

  • Thread starter eherrtelle59
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    Eigenvectors
In summary, the conversation is about finding the eigenvectors for a given matrix in linear algebra. The eigenvalues have already been found and the equations for the eigenvectors are being solved. The eigenvector for λ_1 is determined to be (0 0 1), but the conversation gets stuck when trying to find the eigenvectors for the other two eigenvalues. The paper being read provides the solution as (σ σ+λ_2 0) and (σ σ+λ_3 0), but there is confusion about the algebraic steps needed to get to this result.
  • #1
eherrtelle59
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Ok everybody, it's been awhile since I've taken linear algebra. I need some help dusting off the cobwebs. (I'm trying to follow this in a paper; this isn't a homework question, but I'll be glad to move it...)

Let's say I have a matrix M = \begin{bmatrix}
-σ & σ & 0 \\[0.3em]
ρ & -1 & 0 \\[0.3em]
0 & 0 & -1
\end{bmatrix} \

Ok, now I want to find the eigenvectors (I've already found the eigenvalues.

These are λ_1=-1 and λ_2,3 = -(σ+1)/2 +/- ( (σ+1)^2 -4σ(1-ρ))^.5

Now, to find the eigenvectors, I solve these equations:

(-σ-λ)e_1 +σ e_2 =0
ρ e_1 +(-1-λ) e_2 =0
(-1-λ) e_3 =0

Now, I see that the eigenvector for λ_1 is ( 0 0 1).

Now I'm stuck. How do I find the eigenvectors for the other two?

The result in the paper I'm reading says

λ_2,3 = (σ σ+λ_2 0 ) , (σ σ+λ_3 0 )

I forget how to do this...
 
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  • #2
Essentially, just the way you did the first part, just much messier algebra!
 
  • #3
Um...yes...

So, (-σ-λ)e_1 +σ e_2 =0

Looking at this and getting (σ+λ)e_1 =σ e_2, I would think the eigenvector is (σ+λ σ) not (σ+λ σ).
 

1. What is an eigenvector?

An eigenvector is a special type of vector that, when multiplied by a square matrix, results in a scaled version of itself. In other words, the direction of the eigenvector remains unchanged, but its length may be multiplied by a scalar value.

2. Why are eigenvectors important?

Eigenvectors are important because they help us understand the behavior of a linear transformation or a system of linear equations. They also have many practical applications in fields such as physics, engineering, and data analysis.

3. How do I find eigenvectors?

To find eigenvectors, you first need to calculate the eigenvalues of a matrix. Once you have the eigenvalues, you can use them to solve for the corresponding eigenvectors by plugging them into a specific formula, depending on the method you are using (e.g. power iteration, QR algorithm).

4. Can I have more than one eigenvector for a given eigenvalue?

Yes, it is possible to have multiple eigenvectors for a given eigenvalue. This is because an eigenvector can be multiplied by any scalar value and still remain an eigenvector. Therefore, if one eigenvector exists for a certain eigenvalue, then infinitely many eigenvectors also exist for that eigenvalue.

5. What are the applications of eigenvectors?

Eigenvectors have many applications in various fields. In physics, they are used to describe the direction and magnitude of vibrations in a system. In engineering, they are used in structural analysis and control systems. In data analysis, they are used for dimensionality reduction and feature extraction. They are also used in image and signal processing, quantum mechanics, and many other areas.

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