Finding Eigenvectors for Distinct Real Eigenvalues

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In summary, the matrix has an arbitrary number in the center, and the solutions to the equation (A - 1I)x = 0 are not zero vectors.
  • #1
MetalManuel
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Homework Statement


I don't know how to put matrices in, so I'll just link an http://forum.bodybuilding.com/attachment.php?attachmentid=3339921&d=1305058219"
Basically find the solution for that matrix.

Homework Equations


The Attempt at a Solution


This was the http://img560.imageshack.us/img560/9672/scr1305068624.png" I came up with. when I use an eigenvector calculator though, for c2 it gives me 0,1,0 instead of 0,0,0 which is what I got. I was wondering why I was wrong. Thanks
 
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  • #2
An eigenvector can't be the zero vector.

Here's your matrix in LaTeX. They're not hard to do.

[tex]\begin{bmatrix}1&0&1 \\ 0&1&0 \\ 1&0&1 \end{bmatrix}[/tex]

Click the matrix to see my LaTeX script.

Check your calculation for the eigenvector associated with the eigenvalue of 1.
 
  • #3
Mark44 said:
An eigenvector can't be the zero vector.

Here's your matrix in LaTeX. They're not hard to do.

[tex]\begin{bmatrix}1&0&1 \\ 0&1&0 \\ 1&0&1 \end{bmatrix}[/tex]

Click the matrix to see my LaTeX script.

Check your calculation for the eigenvector associated with the eigenvalue of 1.

I didn't know that, damnit. So the 1 in the center is an arbitrary number? The matric after you plug in 1 is
[tex]
\begin{bmatrix}0&0&1 \\ 0&0&0 \\ 1&0&0 \end{bmatrix}
[/tex]

I don't go to lectures and I learn off of textbooks. I only go to class to take the exams, i don't remember reading that it can't be the zero vector. So because it can't be the zero vector I have to make up a number that will make it work? Since the k2 for all of them is 0, i can just basically put anything in right?
 
  • #4
To find your eigenvector, which is assumed to be nonzero (I'll bet that this is in your text and was stated in class), you're going to be finding solutions to the equation (A - 1I)x = 0.

Of course, x = 0 is a solution of this equation, but we want nonzero x.

Your matrix A - 1I says that x3 = 0, x1 = 0, and x2 is arbitrary, so the vector <0, 1, 0> is an eigenvector for the eigenvalue 1.

You ought to reconsider going to class...
 
  • #5
Mark44 said:
To find your eigenvector, which is assumed to be nonzero (I'll bet that this is in your text and was stated in class), you're going to be finding solutions to the equation (A - 1I)x = 0.

Of course, x = 0 is a solution of this equation, but we want nonzero x.

Your matrix A - 1I says that x3 = 0, x1 = 0, and x2 is arbitrary, so the vector <0, 1, 0> is an eigenvector for the eigenvalue 1.

You ought to reconsider going to class...

Well now that I know that it can't be a non zero vector it all makes sense. I don't like going to lectures, it's not my thing. I prefer independent learning, which is hard for a lot of professors to understand. This was basically the only thing bothering me. Everything else is really easy. I probably skipped over that part in the text when it said it. I already knew about arbitrary numbers, but I didn't know about solutions not being able to be zero vectors. Thanks.
 

1. What are distinct real eigenvalues?

Distinct real eigenvalues are a concept in linear algebra that refers to the eigenvalues of a square matrix that are both real numbers and different from one another. Eigenvalues are numbers that, when multiplied by a specific vector, result in a scalar multiple of that vector. Distinct real eigenvalues are important because they provide information about the behavior and properties of a matrix.

2. How do you find the distinct real eigenvalues of a matrix?

To find the distinct real eigenvalues of a matrix, you can use the characteristic polynomial method. This involves taking the determinant of the matrix minus a scalar lambda, and then solving for lambda using the quadratic formula. The solutions to this equation will be the distinct real eigenvalues of the matrix.

3. What are the applications of distinct real eigenvalues?

Distinct real eigenvalues have various applications in different fields, including physics, engineering, and computer science. They can be used to solve differential equations, analyze the stability of systems, and even compress data in image and signal processing.

4. Can a matrix have more than two distinct real eigenvalues?

Yes, a matrix can have any number of distinct real eigenvalues, as long as it is a square matrix. The number of distinct real eigenvalues will always be less than or equal to the dimension of the matrix.

5. What happens when a matrix has repeated eigenvalues?

If a matrix has repeated eigenvalues, it is called a defective matrix. This means that there is not a sufficient number of linearly independent eigenvectors for the matrix. In this case, other methods, such as the Jordan canonical form, may need to be used to fully understand the matrix's properties.

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