Linear Algebra - Showing a Matrix is not Diagonalizable

In summary: I would guess that I need to somehow find a way to include the transpose of the matrix in my solution, but I'm not sure how to do that.
  • #1
Rockoz
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Homework Statement


Show that the matrix A is not diagonalizable. Explain your reasoning.

A=\begin{bmatrix}k&0\\0&k\\\end{bmatrix}

Homework Equations


Important theorem: A nxn matrix is diagonalizable if and only if it has n linearly independent eigenvectors.


The Attempt at a Solution


Since A is triangular, the eigenvalues are the entries on the main diagonal. In this case the only eigenvalue is k. So then I solve for B = (λI - A) where λ=k, which turns out to equal a 2x2 zero matrix. Then I solve Bx = 0 to try and find the eigenvectors. Here is where I think I'm going wrong. Since B is the zero matrix, I believe that x1 = t, x2 = s, where t and s are any real number. So I find that the vector x is equal to t(1,0) + s(0,1) which would indicate to me that the matrix has two linearly independent eigenvectors and should be diagonalizable.

But this is the opposite of which I wished to prove! So clearly my thinking must be wrong. The solution for this problem says that a basis for the eigenspace is simply {(0,0)}, so since A does not have two linearly independent eigenvectors, it does not satisfy the theorem I have above and cannot be diagonalizable.

My problem is that I don't see how you can say from Bx=0 where B is the 2x2 zero matrix that x can only be (0,0) and thus the basis for the eigenspace is only {(0,0)}. Can't x be any vector?

Thank you.

EDIT: Another point. Isn't this matrix also symmetric (A=Atranspose)? Then shouldn't it be diagonalizable (it's already diagonal anyways)?
 
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  • #2
I would go with your EDIT, this is already a diagonal matrix.

Are you sure the matrix is written correctly?
 
  • #3
Thank you for replying. Yes, it is written correctly.

There must be some idea I'm missing here in solving the problem. I have trouble believing the book is incorrect on this, since I'm usually wrong on such things.
 

FAQ: Linear Algebra - Showing a Matrix is not Diagonalizable

How do you show that a matrix is not diagonalizable?

To show that a matrix is not diagonalizable, you can use the diagonalization theorem which states that a matrix is diagonalizable if and only if it has n linearly independent eigenvectors, where n is the size of the matrix. Therefore, to prove that a matrix is not diagonalizable, you need to show that it does not have n linearly independent eigenvectors.

What is the difference between diagonalizable and non-diagonalizable matrices?

A diagonalizable matrix is a square matrix that can be written as a diagonal matrix by similarity transformation. This means that the matrix has n linearly independent eigenvectors, where n is the size of the matrix. On the other hand, a non-diagonalizable matrix is a square matrix that cannot be written as a diagonal matrix and does not have n linearly independent eigenvectors.

Can a non-diagonalizable matrix be made diagonalizable?

No, a non-diagonalizable matrix cannot be made diagonalizable. This is because the property of diagonalizability is inherent to the matrix and cannot be changed through any operations. If a matrix does not have n linearly independent eigenvectors, it will always be non-diagonalizable.

What are some methods for proving that a matrix is not diagonalizable?

Some methods for proving that a matrix is not diagonalizable include computing the eigenvalues and eigenvectors of the matrix, checking for repeated eigenvalues, and using the diagonalization theorem. Additionally, you can also use the Jordan canonical form to show that a matrix is not diagonalizable.

Why is it important to determine if a matrix is diagonalizable?

Determining if a matrix is diagonalizable is important because it can provide valuable information about the matrix. A diagonalizable matrix has many important properties and can be easily manipulated and solved, making it useful in various applications such as solving systems of linear equations and calculating exponential functions. On the other hand, a non-diagonalizable matrix can be more difficult to work with and may have limited applications.

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