What is the Eigenvalue and Eigenvector for a Complex Matrix Equation?

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In summary, Dave found the eigenvalue of an equation involving invertible matrices A and B, but wasn't able to find the corresponding eigenvector.
  • #1
dkotschessaa
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Homework Statement



If invertible matrices A and B have eigenvalues α and β resp. wrt to a common eigenvector x, what is the eigenvalue of

4A3B-4-17AB2 + ∏I

(We'll call this equation (1))

Homework Equations



Ax = αx
Bx = βx

The Attempt at a Solution



I think I'm ok for the actual eigenvalue. Basically we "exchange" α for A and β for B in the equation above, since Ax = αx implies A2x = α2x and so on and so forth. ∏I is just an identity matrix multiplied by ∏, so it's eigenvalue is ∏ (with multiplicity two).

So I get 4α24 - 17αβ2 + ∏

But I can't seem to figure out how to approach getting the corresponding Eigenvector. I know the characteristic equation

det(A - λI) = 0

may tell me something, but if I plug in (1) for A and the eigenvalue above for λ I just get a complete mess.

-Dave K
 
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  • #2
dkotschessaa said:

Homework Statement



If invertible matrices A and B have eigenvalues α and β resp. wrt to a common eigenvector x, what is the eigenvalue of

4A3B-4-17AB2 + ∏I

(We'll call this equation (1))

Homework Equations



Ax = αx
Bx = βx


The Attempt at a Solution



I think I'm ok for the actual eigenvalue. Basically we "exchange" α for A and β for B in the equation above, since Ax = αx implies A2x = α2x and so on and so forth. ∏I is just an identity matrix multiplied by ∏, so it's eigenvalue is ∏ (with multiplicity two).

So I get 4α24 - 17αβ2 + ∏

But I can't seem to figure out how to approach getting the corresponding Eigenvector. I know the characteristic equation

det(A - λI) = 0

may tell me something, but if I plug in (1) for A and the eigenvalue above for λ I just get a complete mess.

-Dave K

You can't really find the eigenvector unless you have actual values for the A and B matrices. Do you?
 
  • #3
Hi Dave!

Let's call C = 4A3B-4-17AB2 + ∏I
Then, as you said, Cx = (4α24 - 17αβ2 + ∏)x

Let's call λ=4α24 - 17αβ2 + ∏.
Then Cxx.

You had already found the eigenvalue λ.
What do you think the corresponding eigenvector is? :wink:
 
  • #4
I like Serena said:
Hi Dave!

Let's call C = 4A3B-4-17AB2 + ∏I
Then, as you said, Cx = (4α24 - 17αβ2 + ∏)x

Let's call λ=4α24 - 17αβ2 + ∏.
Then Cxx.

You had already found the eigenvalue λ.
What do you think the corresponding eigenvector is? :wink:

I did try that but I'm not sure how to "solve" for x. As the other poster pointed out, I don't even know what the values of C are... I don't even know what dimension so I can't use some identity matrix and use λ (the mess) as a scalar... Not sure what I'm supposed to do.
 
  • #5
dkotschessaa said:
I did try that but I'm not sure how to "solve" for x. As the other poster pointed out, I don't even know what the values of C are... I don't even know what dimension so I can't use some identity matrix and use λ (the mess) as a scalar... Not sure what I'm supposed to do.

You can't solve for x any more than you can solve for α and β. x is the eigenvector. I think you are done.
 
  • #6
dkotschessaa said:
I did try that but I'm not sure how to "solve" for x. As the other poster pointed out, I don't even know what the values of C are... I don't even know what dimension so I can't use some identity matrix and use λ (the mess) as a scalar... Not sure what I'm supposed to do.

The vector x is given as the common eigenvector of A and B.
None of them is specified other than that they are given to exist.
C has the same common eigenvector x as A and B.
 
  • #7
Dick said:
You can't solve for x any more than you can solve for α and β. x is the eigenvector. I think you are done.

Yeah, we went over this in class, and the eigenvector is just x. Ok then. Thanks everyone.
 

1. What is an Eigenvalue/Eigenvector?

An eigenvalue is a scalar value that represents how an eigenvector is stretched or compressed by a linear transformation. An eigenvector is a vector that remains in the same direction after being transformed by a linear transformation.

2. Why is finding eigenvalues and eigenvectors important?

Finding eigenvalues and eigenvectors is important in many areas of mathematics and science, including linear algebra, differential equations, and physics. They are used to simplify complex systems and can reveal important information about the behavior of a system.

3. How do you find eigenvalues and eigenvectors?

To find eigenvalues and eigenvectors, you must first set up and solve a characteristic equation. This equation is formed by subtracting the eigenvalue from the main diagonal of a matrix and finding the determinant of the resulting matrix. The eigenvalues are then the solutions to this equation. Once the eigenvalues are found, the corresponding eigenvectors can be found by solving a system of linear equations.

4. Can a matrix have multiple eigenvalues and eigenvectors?

Yes, a matrix can have multiple eigenvalues and eigenvectors. In fact, most matrices have multiple eigenvalues and eigenvectors. The number of eigenvalues and eigenvectors a matrix has is equal to its dimensions.

5. How are eigenvalues and eigenvectors used in data analysis?

Eigenvalues and eigenvectors are used in data analysis to reduce the dimensionality of a dataset. This means that they can help simplify complex datasets and make it easier to understand and analyze. They are also used in techniques such as principal component analysis, which is used to identify patterns and relationships within a dataset.

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