Finding the eigenvalues of a 3x3

The eigenvalues are 0, 3, 10.In summary, the conversation discusses finding the eigenvalues of a given matrix using the equation det(A-λI)=0 and the cofactor expansion method. The correct eigenvalues are determined to be 0, 3, and 10.
  • #1
stryker105
4
1

Homework Statement


Find the eigenvalues of:
|13 -30 0|
|1 0 0|
|0 1 0|

Homework Equations



Equation for the eigenvalues: det(A-λI)=0

Cofactor expansion = det A = a11(a22a33-a23a32)+a12(a23a31-a21a33)+a13(a21a32-a22a31)

The Attempt at a Solution



|13-λ -30 0 |
| 1 -λ 0 |
| 0 1 -λ|

(13 -λ)(λ[itex]^{2}[/itex])-30(-λ)+0 = 0
13λ[itex]^{2}[/itex]-λ[itex]^{3}[/itex]+30
-λ[itex]^{3}[/itex]+13λ[itex]^{2}[/itex]+ 30λ
-λ(λ[itex]^{2}[/itex]-13λ-30)
(λ+2)(λ-15)

Eigenvalues = 0, 2, 15

However, this not the correct answer according the the software I'm using. Can anyone see what I'm doing wrong?
 
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  • #2
The -λ in bold should be just λ

stryker105 said:
(13 -λ)(λ[itex]^{2}[/itex])-30()+0 = 0
 
  • #3
Hmm, I'd say that the -30(-λ) should really be --30(-λ).
 
  • #4
I like Serena said:
Hmm, I'd say that the -30(-λ) should really be --30(-λ).

Yes, I agree that that is the most common way of seeing it. But I guess that the OP wanted to follow his formula:

Cofactor expansion = det A = a11(a22a33-a23a32)+a12(a23a31-a21a33)+a13(a21a32-a22a31)

In that case, it is [itex]-30\lambda[/itex]. But it is a weird way of doing things, agreed.
 
  • #5
Expanding on the last column gives [itex]-\lambda(\lambda^2- 13\lambda+ 30)[/itex], as I Like Serena and micromass are saying, not [itex]-\lambda(\lambda^2- 13\lambda- 30)[/itex].

That factors as [itex]-\lambda(\lambda- 10)(\lambda- 3)= 0[/itex].
 

FAQ: Finding the eigenvalues of a 3x3

What are eigenvalues?

The eigenvalues of a matrix represent the numbers that, when multiplied by the corresponding eigenvectors, result in the same vector. They are essentially the scaling factors of the eigenvectors.

Why is it important to find the eigenvalues of a 3x3 matrix?

Finding the eigenvalues of a 3x3 matrix allows us to understand the behavior of the matrix, such as how it will transform a vector and whether it is invertible or not. It also has applications in fields such as physics, engineering, and computer graphics.

How do you find the eigenvalues of a 3x3 matrix?

The eigenvalues of a 3x3 matrix can be found by solving the characteristic polynomial, which is obtained by subtracting the identity matrix multiplied by the variable lambda from the original matrix and setting the determinant equal to 0. This results in a cubic equation, which can be solved using various methods such as factoring or the quadratic formula.

Can a 3x3 matrix have complex eigenvalues?

Yes, a 3x3 matrix can have complex eigenvalues, which can be represented in the form of a+bi. This often occurs when the matrix has complex numbers as its elements or when it represents a rotation or reflection in the complex plane.

What are the properties of eigenvalues?

Some properties of eigenvalues include: they are invariant under similarity transformations, the sum of the eigenvalues is equal to the trace of the matrix, and the product of the eigenvalues is equal to the determinant of the matrix. Additionally, all eigenvalues must be real for a matrix to be diagonalizable.

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