T/F: Whether a matrix is diagonalizable

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In summary, the matrix ##\begin{bmatrix} 2 & 1 & 0 \\ 0 & 2 & 0 \\ 0 & 0 & 3 \end{bmatrix}## is not diagonalizable because the matrix ##A##, which is a block of the larger matrix, is not diagonalizable due to the presence of a ##1## on the superdiagonal. This is evident from the Jordan normal form of the matrix and the fact that the eigenvalues can be read from it.
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Mr Davis 97
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Homework Statement



T/F: The matrix ##\begin{bmatrix} 2 & 1 & 0 \\ 0 & 2 & 0 \\ 0 & 0 & 3 \end{bmatrix}## is diagonalizable.




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The Attempt at a Solution


Is there a quick way to tell whether the matrix is diagonalizable? Since it's a T/F question, that would seem to be the case. The matrix is not symmetric, so we can't conclude anything there. Also, even though it is triangular, the entries on the diagonal are not distinct, so that's a dead end too.
 
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You can consider it as a matrix which is built by two blocks: ##\begin{bmatrix}2&1&0\\0&2&0\\0&0&3\end{bmatrix}=\begin{bmatrix}A&0\\0&3\end{bmatrix}##. Now you only have to deal with ##A##.
 
  • #3
fresh_42 said:
You can consider it as a matrix which is built by two blocks: ##\begin{bmatrix}2&1&0\\0&2&0\\0&0&3\end{bmatrix}=\begin{bmatrix}A&0\\0&3\end{bmatrix}##. Now you only have to deal with ##A##.
So by brute force calculation I found that A is not diagonalizable. Why does this imply that the bigger matrix is not diagonalizable? Also, is there something characteristic of A that should tell me it's not diagonalizable, or do you have to brute force calculate it?
 
  • #4
Mr Davis 97 said:
So by brute force calculation I found that A is not diagonalizable. Why does this imply that the bigger matrix is not diagonalizable?
If it was diagonalizable, then ##A## would be diagonalized as well. (Edit: And the block with ##3## doesn't contribute to ##A##.)
Also, is there something characteristic of A that should tell me it's not diagonalizable, or do you have to brute force calculate it?
Yes, the ##1## beside the diagonal (on the superdiagonal) is the reason. The matrix is in the Jordan normal form. It is already almost diagonal and one can read the eigenvalues. The ##1## indicates, that there is a two-dimensional eigenspace.
 

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

Diagonalizable matrices are those that can be transformed into a diagonal matrix through a similarity transformation. This means that the matrix can be expressed as a diagonal matrix by changing its basis vectors.

2. How can I check if a matrix is diagonalizable?

A matrix is diagonalizable if it has n linearly independent eigenvectors, where n is the dimension of the matrix. To check this, you can calculate the eigenvalues and eigenvectors of the matrix and see if they are linearly independent.

3. Are all matrices diagonalizable?

No, not all matrices are diagonalizable. For a matrix to be diagonalizable, it must have n linearly independent eigenvectors, where n is the dimension of the matrix. If a matrix does not have enough eigenvectors, it cannot be diagonalizable.

4. Can a matrix be partially diagonalizable?

No, a matrix is either fully diagonalizable or not diagonalizable at all. A partially diagonalizable matrix would have some eigenvalues with multiple eigenvectors and others with none, which is not possible.

5. How is diagonalization useful in matrix computations?

Diagonalization simplifies many matrix computations, such as finding powers of a matrix and calculating the exponential of a matrix. It also allows for easier analysis of the properties of a matrix, as well as solving systems of linear equations.

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