Determining if a matrix is diagonalizable with explanation

In summary: However, it appears that the matrix is not diagonalizable, as all the eigenvectors are zero vectors except for one, which has only one nonzero entry. Therefore, the eigenspace is only one-dimensional, rather than the required five dimensions for a diagonalizable matrix.In summary, the given matrix is not diagonalizable due to the fact that all the eigenvectors are zero vectors except for one, which has only one nonzero entry. Therefore, the eigenspace is only one-dimensional, rather than the required five dimensions for a diagonalizable matrix.
  • #1
LinAlgStudent
5
0

Homework Statement



Determine if this matrix is diagonalizable and explain why or why not.

[ 2 1 0 0 0 ]
[ 0 2 1 0 0 ]
[ 0 0 2 1 0 ]
[ 0 0 0 2 1 ]
[ 0 0 0 0 2 ]




Homework Equations



No equations provided and the use of a calculator will be prohibited on the test, so that's out of the question. I can find the determinant via expansion, but that doesn't help really.



The Attempt at a Solution



So I'm pretty confident that this is not diagonalizable because the only eigenvalue seems to be 2 with multiplicity 5, although I'm not sure that actually proves anything. Additionally, I'm fairly certain that because the study guide has this as a 5x5 matrix with calculator use prohibited, there must be a way, just from the shape, to determine whether it's diagonalizable. Does anyone have any tips?

Thank you so much for any help!
 
Physics news on Phys.org
  • #2
One trick is to just take the matrix you have and row reduce it until you have only diagonal entries left. If you can do that, you have a diagonalizable matrix.
 
  • #3
Muphrid said:
One trick is to just take the matrix you have and row reduce it until you have only diagonal entries left. If you can do that, you have a diagonalizable matrix.

it row reduces to the identity matrix. Is that indicative of anything specific?
 
Last edited:
  • #4
Muphrid said:
One trick is to just take the matrix you have and row reduce it until you have only diagonal entries left. If you can do that, you have a diagonalizable matrix.

Got a reference for that?? I don't think what you say is true...

The best way to do this exercise is find the eigenvectors and see if they span the space.
 
  • #5
micromass said:
Got a reference for that?? I don't think what you say is true...

The best way to do this exercise is find the eigenvectors and see if they span the space.

So I've found all eigenvalues to be equal to 2, the first eigenvector i think is:

[1]
[0]
[0]
[0]
[0]

and the other four all all 5x1 zero vectors.

But what does that mean in the context of the question?
 
  • #6
LinAlgStudent said:

Homework Statement



Determine if this matrix is diagonalizable and explain why or why not.

[ 2 1 0 0 0 ]
[ 0 2 1 0 0 ]
[ 0 0 2 1 0 ]
[ 0 0 0 2 1 ]
[ 0 0 0 0 2 ]




Homework Equations



No equations provided and the use of a calculator will be prohibited on the test, so that's out of the question. I can find the determinant via expansion, but that doesn't help really.



The Attempt at a Solution



So I'm pretty confident that this is not diagonalizable because the only eigenvalue seems to be 2 with multiplicity 5, although I'm not sure that actually proves anything. Additionally, I'm fairly certain that because the study guide has this as a 5x5 matrix with calculator use prohibited, there must be a way, just from the shape, to determine whether it's diagonalizable. Does anyone have any tips?

Thank you so much for any help!

The matrix (A) above is the matrix representation of a linear transformation T with respect to the basis e_1=(1,0,0,0,0),...,e_5 = (0,0,0,0,1). If a transformation (i.e., a matrix) is diagonalizable, its matrix becomes diagonal when re-expressed in some other basis f_1, f_2, f_3, f_4, f_5. Since two similar matrices have the same eigenvalues, the "diagonal" would need to be 5 times the identity matrix, and that means that the f_i would have to be eigenvectors of T (i.e., of the matrix A). In turn, that means that there must be 5 linearly independent eigenvectors. You can determine the eigenspace of A and check whether its dimensionality is 5.

RGV
 
  • #7
Ray Vickson said:
The matrix (A) above is the matrix representation of a linear transformation T with respect to the basis e_1=(1,0,0,0,0),...,e_5 = (0,0,0,0,1). If a transformation (i.e., a matrix) is diagonalizable, its matrix becomes diagonal when re-expressed in some other basis f_1, f_2, f_3, f_4, f_5. Since two similar matrices have the same eigenvalues, the "diagonal" would need to be 5 times the identity matrix, and that means that the f_i would have to be eigenvectors of T (i.e., of the matrix A). In turn, that means that there must be 5 linearly independent eigenvectors. You can determine the eigenspace of A and check whether its dimensionality is 5.

RGV

Provided that all the eigenvectors of A are zero vectors save for one of them which has only one nonzero entry, wouldn't that suggest that the eigenspace of A is only 1 dimensional? So, in order for A to be diagonalizable, the eigenspace would have to be of dimension 5, but it is of dimension 1 so it is not diagonalizable?
 
  • #8
For further exploration, research Jordan matrix and generalized eigenvector.

Yes, because of what I know, I see that it is in Jordan form, and so it is "as close to diagonal" as it will ever be.

I also like the method explained above, find the eigenvectors for the sole eigenvalue, "in the end there will be only one."

(The zero vector is never called an eigenvector, otherwise it would always be one, A0=λ0, though eigenvalues can be zero. )
 
  • #9
LinAlgStudent said:
Provided that all the eigenvectors of A are zero vectors save for one of them which has only one nonzero entry, wouldn't that suggest that the eigenspace of A is only 1 dimensional? So, in order for A to be diagonalizable, the eigenspace would have to be of dimension 5, but it is of dimension 1 so it is not diagonalizable?

Zero vectors do not count as eigenvectors (essentially by definition), so the eigenspace is, indeed, one-dimensional. So, YES: the matrix is not diagonalizable.

In fact, the matrix is already in its Jordan Canonical Form, and that consists of a single Jordan block of dimension 5. A diagonalizable matrix would have to have a diagonal Jordan Form.

RGV
 
  • #10
Yes, I was mistaken; I thought I'd uncovered a quick way to work the problem.
 

FAQ: Determining if a matrix is diagonalizable with explanation

1. What does it mean for a matrix to be diagonalizable?

Diagonalizable matrices are those that can be transformed into a diagonal matrix through similarity transformations. This means that the matrix can be written as a product of three matrices: A = PDP^-1, where D is a diagonal matrix and P is an invertible matrix.

2. How do you determine if a matrix is diagonalizable?

A matrix is diagonalizable if it has n linearly independent eigenvectors, where n is the size of the matrix. To determine this, we can use the diagonalization theorem which states that a matrix is diagonalizable if and only if it has n distinct eigenvalues. We can also use the characteristic polynomial and eigenvalues to check for diagonalizability.

3. Can a non-square matrix be diagonalizable?

No, diagonalizable matrices must be square. This is because the diagonal matrix D in the diagonalization equation must have the same dimensions as the original matrix A.

4. What is the significance of diagonalizable matrices?

Diagonalizable matrices are important in many applications, such as in solving systems of differential equations and computing powers of matrices. They also have special properties that make them easier to work with, such as being invertible and having simpler matrix operations.

5. What are some methods for diagonalizing a matrix?

There are a few methods for diagonalizing a matrix, such as finding the eigendecomposition, Jordan canonical form, and Schur decomposition. These methods involve finding the eigenvalues and eigenvectors of the matrix and using them to construct the diagonal matrix D and invertible matrix P in the diagonalization equation.

Similar threads

Replies
3
Views
1K
Replies
7
Views
1K
Replies
1
Views
1K
Replies
2
Views
671
Replies
2
Views
2K
Replies
14
Views
3K
Replies
2
Views
1K
Replies
1
Views
2K
Back
Top