Finding eigenvalues of matrix

In summary: Thanks for the explanation!In summary, the eigenvalues of the given matrix are 4, -2, and 2. When finding the eigenvalues, it is important to factor and consider all possible cases, as dividing by a term to cancel it can result in losing a solution.
  • #1
DanielFaraday
87
0

Homework Statement



Find the eigenvalues of the following matrix:

[tex]
\left(
\begin{array}{ccc}
1 & 0 & -3 \\
1 & 2 & 1 \\
-3 & 0 & 1
\end{array}
\right)
[/tex]

Homework Equations


The Attempt at a Solution



I think I'm forgetting a basic algebra rule or something. I know there are supposed to be 3 eigenvalues, but I am only getting 2.

[tex]
0=\det (\lambda I-A)=\left|
\begin{array}{ccc}
\lambda -1 & 0 & 3 \\
-1 & \lambda -2 & -1 \\
3 & 0 & \lambda -1
\end{array}
\right|
[/tex]
[tex]
=\frac{(\lambda -1)(\lambda -2)(\lambda -1)-3(3)(\lambda -2)}{(\lambda -2)}
[/tex]
[tex]
=(\lambda -1)(\lambda -1)-9
[/tex]
[tex]
=(\lambda -1)^2-9
[/tex]
[tex]
(\lambda -1)^2=9
[/tex]
[tex]
\lambda =\pm 3+1
[/tex]
 
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  • #2


Where you cancel the (lambda - 2) term, you lose one solution: lambda = 2.

Remember, you have to factor. By canceling the term (lambda - 2), you're basically saying "lambda cannot under any circumstances equal 2". If you want to do that, you have to consider two separate cases: lambda=2 and lambda!=2.

So the three eigenvalues are 3+1=4, -3+1=-2, and 2.
 
  • #3


Why did you divide by (lambda - 2) in the first place?
 
  • #4


Thanks for your help.

So let me get this straight. Whenever I divide by a term to cancel it, I count that term as one of my solutions, right? Does this always work? I didn't quite understand what you meant by testing two separate cases.
 
  • #5


Pengwuino said:
Why did you divide by (lambda - 2) in the first place?

Because it was much easier to do that than it was to multiply everything out and try to factor a third-degree polynomial.
 
  • #6


Why did you divide by lambda-2 in the second line of your equations? Do you remember the formulas for a determinant of a 3x3 matrix?
 
  • #7


Oh, duh. Since there are two terms on the RHS and they are constants then the must both be equal to zero separately. Haha.
 
  • #8


DanielFaraday said:
Because it was much easier to do that than it was to multiply everything out and try to factor a third-degree polynomial.

You can just factor (x-2) to get an easily solvable equation
 
  • #9


VeeEight said:
Why did you divide by lambda-2 in the second line of your equations? Do you remember the formulas for a determinant of a 3x3 matrix?

I was just doing two steps at once. Bad form on my part.
 
  • #10


DanielFaraday said:
Thanks for your help.

So let me get this straight. Whenever I divide by a term to cancel it, I count that term as one of my solutions, right? Does this always work? I didn't quite understand what you meant by testing two separate cases.

Yes. Think of it this way, let's say you're trying to find the solutions of x for (x-1)(x-2)(x-3)=0. Obviously your solutions are x=1,2, and 3. If you divide out (x-1), you lose a solution and are left with (x-2)(x-3)=0.
 
  • #11


Pengwuino said:
Yes. Think of it this way, let's say you're trying to find the solutions of x for (x-1)(x-2)(x-3)=0. Obviously your solutions are x=1,2, and 3. If you divide out (x-1), you lose a solution and are left with (x-2)(x-3)=0.

Very good point. Thanks!
 
  • #12


DanielFaraday said:
Very good point. Thanks!

Your welcome. Also, to clarify AU's point, when you divide by (lambda-2), your left with that (lambda-2) in the denominator of the left hand side (the 0). Now for any number other then 2, it's going to be 0 divided by some finite number which is 0. However, with lambda = 2, you get 0/0 which is undefined, not 0.
 
  • #13


Pengwuino said:
Your welcome. Also, to clarify AU's point, when you divide by (lambda-2), your left with that (lambda-2) in the denominator of the left hand side (the 0). Now for any number other then 2, it's going to be 0 divided by some finite number which is 0. However, with lambda = 2, you get 0/0 which is undefined, not 0.

Aha. That makes sense now.
 

What is an eigenvalue?

An eigenvalue of a matrix is a scalar value that represents the magnitude of the matrix's transformation on a particular eigenvector. It essentially describes the stretching or shrinking effect of the matrix on that vector.

How do you find the eigenvalues of a matrix?

To find the eigenvalues of a matrix, you need to solve the characteristic equation det(A - λI) = 0, where A is the matrix and λ is the eigenvalue. This equation is obtained by setting the determinant of the matrix minus the identity matrix multiplied by the eigenvalue equal to 0. The solutions to this equation are the eigenvalues of the matrix.

Why are eigenvalues important in linear algebra?

Eigenvalues are important in linear algebra because they allow us to understand the behavior of a matrix and its effect on vectors. They also help in solving systems of linear equations and finding important properties of a matrix, such as determinant and trace.

Can a matrix have more than one eigenvalue?

Yes, a matrix can have multiple eigenvalues. In fact, every square matrix has at least one eigenvalue. However, the number of eigenvalues a matrix can have is limited by its size - a 2x2 matrix can have at most 2 eigenvalues, a 3x3 matrix can have at most 3 eigenvalues, and so on.

What is the relationship between eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are closely related - every eigenvalue has a corresponding eigenvector that describes the direction of the transformation of the matrix. The eigenvectors associated with a particular eigenvalue form a subspace of the vector space, known as the eigenspace.

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