Diagonalize Matrix, Given an Eigenvalue and Eigenvector

In summary, the homework statement is saying that the problem is to find the eigenvalues and corresponding eigenvectors of the matrix A, given that one eigenvalue is 5. The attempt at a solution is to find the eigenvalue and system of equations that the eigenvector for λ=5 has to satisfy.
  • #1
BraedenP
96
0

Homework Statement



[tex]\begin{bmatrix}
-7 && -16 && 4\\
6 && 13 && -2\\
12 && 16 && 1
\end{bmatrix}[/tex]

Diagonalize the matrix (if possible), given that one eigenvalue is 5, and that one eigenvector is {-2, 1, 2}

Homework Equations



[tex]A=PDP^{-1}[/tex]

The Attempt at a Solution



If I were allowed to simply calculate the eigenvalues and corresponding eigenvectors, I'd be able to determine if it's diagonalizable and if so, to diagonalize it. The problem here is that I have to go only on the provided information.

I'm stuck regarding how to proceed with this question. Where do I start?

Thanks!
 
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  • #2
Start by finding the eigenvalue associated with the given eigenvector and determining what system of equations the eigenvector for λ=5 has to satisfy.
 
  • #3
Oh! I just read the question wrong. I assumed that the eigenvector provided was in the eigenspace of the provided eigenvalue. That probably means there will be two eigenvalues, and one of them will have an algebraic multiplicity of 2.

I'll give it a shot and see if that works. Thanks. :)

Edit:

Well that was easy! Perhaps I should spend more time reading these questions :P

Thanks!
 
Last edited:
  • #4
BraedenP said:
Oh! I just read the question wrong. I assumed that the eigenvector provided was in the eigenspace of the provided eigenvalue.
Well, that obviously is NOT true because (-7)(-2)+ (-16)(1)+ (4)(2)= 14- 16+ 8= 6, not -10.

That probably means there will be two eigenvalues, and one of them will have an algebraic multiplicity of 2.

I'll give it a shot and see if that works. Thanks. :)

Edit:

Well that was easy! Perhaps I should spend more time reading these questions :P

Thanks!
Why did you say "If I were allowed to simply calculate the eigenvalues and corresponding eigenvectors"? There is nothing in the statement of the problem that prohibits that. The characteristic equation is cubic and knowing one solution allows you to reduce it to a quadratic.
 
  • #5
HallsofIvy said:
Well, that obviously is NOT true because (-7)(-2)+ (-16)(1)+ (4)(2)= 14- 16+ 8= 6, not -10.


Why did you say "If I were allowed to simply calculate the eigenvalues and corresponding eigenvectors"? There is nothing in the statement of the problem that prohibits that. The characteristic equation is cubic and knowing one solution allows you to reduce it to a quadratic.

Regarding your first point, I didn't actually calculate anything; I just took it by assumption (yes, bad.. I know) that the eigenvector and value were associated.

Regarding the second point, we were explicitly told not to calculate eigenvalues using the characteristic equation.

But it's all good now. Thanks :)
 

1. What is diagonalization of a matrix?

Diagonalization of a matrix is the process of transforming a square matrix into a diagonal matrix by finding a set of eigenvectors and eigenvalues that can be used to represent the original matrix.

2. What is an eigenvalue?

An eigenvalue is a scalar value that represents the scaling factor of an eigenvector when the matrix is multiplied by it. It is a special set of numbers that are associated with a matrix and help in understanding the matrix's properties.

3. What is an eigenvector?

An eigenvector is a non-zero vector that, when multiplied by a matrix, results in a scalar multiple of itself. It is a special vector that represents the direction of the transformation of the matrix.

4. How do you find the eigenvalues and eigenvectors of a matrix?

To find the eigenvalues and eigenvectors of a matrix, we first find the characteristic polynomial of the matrix, which is obtained by subtracting the identity matrix multiplied by a scalar lambda from the original matrix. The roots of this polynomial are the eigenvalues. To find the eigenvectors, we solve the system of linear equations obtained by substituting the eigenvalues in the characteristic polynomial.

5. Why is diagonalization of a matrix important?

Diagonalization of a matrix is important because it simplifies the representation of a matrix. It also helps in understanding the properties of a matrix, such as its rank, determinant, and inverse. It also makes calculations and operations on the matrix easier and more efficient.

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