Diagonalizable Matrix: How to Approach?

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In summary: If a is not equal to 6, the determinant will not be zero, and we will need to find the eigenvectors corresponding to a different eigenvalue.
  • #1
Yankel
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Hello all

I have this matrix:

\[\begin{pmatrix} 6 & 0\\ -3 & a \end{pmatrix}\]

And I am told it is diagonalizable. Therefore, the value of a is:

1) a=0
2) a not= 0
3) a not=6
4) a=6
5) a not=0,6

How should I approach this? Is there a "trick" or should I find eigenvalues and eigenvectors for both values of a?

Thank you.
 
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  • #2
Yankel said:
Hello all

I have this matrix:

\[\begin{pmatrix} 6 & 0\\ -3 & a \end{pmatrix}\]

And I am told it is diagonalizable. Therefore, the value of a is:

1) a=0
2) a not= 0
3) a not=6
4) a=6
5) a not=0,6

How should I approach this? Is there a "trick" or should I find eigenvalues and eigenvectors for both values of a?

Thank you.

Hi Yankel! ;)

Are you familiar with the Jordan normal form?
If so, what are the possibilities for the Jordan normal form?

Furthermore, a "trick" is that the trace ($6+a$) is equal to the sum of the eigenvalues, and the determinant is equal to the product of the eigenvalues.
 
  • #3
Hi,

So 6a is the product of the eigenvalues and 6+a is the sum.

if a=0, the product is 0 and the sum is 6

if a=6 the product is 36 and the sum is 12

how does that help me find a ?

what is Jordan normal form?
 
  • #4
Yankel said:
Hi,

So 6a is the product of the eigenvalues and 6+a is the sum.

if a=0, the product is 0 and the sum is 6

if a=6 the product is 36 and the sum is 12

how does that help me find a ?

what is Jordan normal form?

More specifically, the eigenvalues are $6$ and $a$.

And if you're not familiar with the Jordan normal form, you're probably supposed to indeed find the eigenvalues and the eigenvectors to do the diagonalization.

For the record, every matrix is similar to a Jordan normal form.
It tells us something about how diagonalizable a matrix is, and how to categorize matrices..
Note that a diagonalizable matrix is defined as a matrix that is similar to a diagonal matrix.

The possibilities for the Jordan normal form are:
$$\begin{pmatrix}\lambda_1 & 1 \\ 0 & \lambda_1\end{pmatrix},
\begin{pmatrix}\lambda_1 & 0 \\ 0 & \lambda_1\end{pmatrix},
\begin{pmatrix}\lambda_1 & 0 \\ 0 & \lambda_2\end{pmatrix}
$$
It means that the matrix is guaranteed to be diagonalizable if the eigenvalues are different.
And if the eigenvalues are the same, we cannot tell yet. We'll have to check further.
 
  • #5
A matrix is "diagonalizable" if and only if it has a "complete set" of eigenvectors. That is, that there exist a basis for the vector space consisting of Eigen vectors. Here, that means that there must be two independent eigenvectors.

It is obvious that the two eigenvalues are "6" and "a". If a is any number other than "6" the two eigenvectors will be independent (eigenvectors corresponding to distinct eigenvalues are always independent). Since this a "triangular" matrix, it is obvious that if a= 6, there are not two independent eignvectors.
 

FAQ: Diagonalizable Matrix: How to Approach?

What is a diagonalizable matrix?

A diagonalizable matrix is a square matrix that can be transformed into a diagonal matrix through a similarity transformation. This means that the matrix has a set of linearly independent eigenvectors, and the diagonal matrix will have the eigenvalues of the original matrix along its diagonal.

How can you tell if a matrix is diagonalizable?

A matrix is diagonalizable if it has a full set of linearly independent eigenvectors. This means that the matrix must have as many distinct eigenvectors as its dimension. It is also important to note that not all matrices are diagonalizable.

What are the steps for diagonalizing a matrix?

The process for diagonalizing a matrix involves finding the eigenvalues and corresponding eigenvectors, creating a diagonal matrix with the eigenvalues along the diagonal, and then finding the inverse of the matrix of eigenvectors. The product of these three matrices will result in the diagonalized form of the original matrix.

Can a non-square matrix be diagonalizable?

No, a non-square matrix cannot be diagonalizable because only square matrices have eigenvalues and eigenvectors. A non-square matrix does not have enough dimensions to have a full set of linearly independent eigenvectors.

What is the significance of diagonalizable matrices in linear algebra?

Diagonalizable matrices are important in linear algebra because they simplify many calculations and make it easier to understand and manipulate linear transformations. They also allow for the easy computation of powers and inverses of matrices, which is useful in various applications such as solving systems of linear equations and studying Markov chains.

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