Eigenvectors of a matrix in Jordan Normal Form

So, we have to find the eigenvectors of J and then use P to find the corresponding eigenvectors of A.
  • #1
Ted123
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0
Let [itex]A =\begin{bmatrix} -14 & 5 & -2 & 1 \\ -38 & 13 & -4 & 5 \\ 25 & -10 & 7 & 5 \\ -17 & 5 & -2 & 4 \end{bmatrix}[/itex] .

The Jordan Normal Form of A is [itex]J =\begin{bmatrix} 2 & 1 & 0 & 0 \\ 0 & 2 & 0 & 0 \\ 0 & 0 & 3 & 1 \\ 0 & 0 & 0 & 3 \end{bmatrix}[/itex] .

Now, I've been told that eigenvectors can be read off as the columns with no 1's on the superdiagonal.

So for the eigenvalue 2, an eigenvector is [itex]\begin{bmatrix} 1 \\ 0 \\ 0 \\ 0 \end{bmatrix}[/itex] and for the eigenvalue 3, an eigenvector is [itex]\begin{bmatrix} 0 \\ 0 \\ 1 \\ 0 \end{bmatrix}[/itex] .

But [itex]\text{Ker} (A-2I) = \left\{ \begin{bmatrix} w \\ 3w \\ 0 \\ w \end{bmatrix} : w\in\mathbb{R} \right\} = \text{span} \left\{ \begin{bmatrix} 1 \\ 3 \\ 0 \\ 1 \end{bmatrix} \right\}[/itex]

but clearly [itex]\begin{bmatrix} 1 \\ 0 \\ 0 \\ 0 \end{bmatrix} \notin \text{Ker} (A-2I)[/itex]

All eigenvectors should be in the kernel so why isn't this - isn't it an eigenvector?

Similarly [itex]\text{Ker} (A-3I) = \left\{ \begin{bmatrix} 0 \\ \frac{2}{5}z \\ z \\ 0 \end{bmatrix} : z\in\mathbb{R} \right\} = \text{span} \left\{ \begin{bmatrix} 0 \\ 2 \\ 5 \\ 0 \end{bmatrix} \right\}[/itex]

but clearly [itex]\begin{bmatrix} 0 \\ 0 \\ 1 \\ 0 \end{bmatrix} \notin \text{Ker} (A-3I)[/itex]
 
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  • #2
Ted123 said:
Let [itex]A =\begin{bmatrix} -14 & 5 & -2 & 1 \\ -38 & 13 & -4 & 5 \\ 25 & -10 & 7 & 5 \\ -17 & 5 & -2 & 4 \end{bmatrix}[/itex] .

The Jordan Normal Form of A is [itex]J =\begin{bmatrix} 2 & 1 & 0 & 0 \\ 0 & 2 & 0 & 0 \\ 0 & 0 & 3 & 1 \\ 0 & 0 & 0 & 3 \end{bmatrix}[/itex] .

Now, I've been told that eigenvectors can be read off as the columns with no 1's on the superdiagonal.

So for the eigenvalue 2, an eigenvector is [itex]\begin{bmatrix} 1 \\ 0 \\ 0 \\ 0 \end{bmatrix}[/itex] and for the eigenvalue 3, an eigenvector is [itex]\begin{bmatrix} 0 \\ 0 \\ 1 \\ 0 \end{bmatrix}[/itex] .

But [itex]\text{Ker} (A-2I) = \left\{ \begin{bmatrix} w \\ 3w \\ 0 \\ w \end{bmatrix} : w\in\mathbb{R} \right\} = \text{span} \left\{ \begin{bmatrix} 1 \\ 3 \\ 0 \\ 1 \end{bmatrix} \right\}[/itex]

but clearly [itex]\begin{bmatrix} 1 \\ 0 \\ 0 \\ 0 \end{bmatrix} \notin \text{Ker} (A-2I)[/itex]

All eigenvectors should be in the kernel so why isn't this - isn't it an eigenvector?

Similarly [itex]\text{Ker} (A-3I) = \left\{ \begin{bmatrix} 0 \\ \frac{2}{5}z \\ z \\ 0 \end{bmatrix} : z\in\mathbb{R} \right\} = \text{span} \left\{ \begin{bmatrix} 0 \\ 2 \\ 5 \\ 0 \end{bmatrix} \right\}[/itex]

but clearly [itex]\begin{bmatrix} 0 \\ 0 \\ 1 \\ 0 \end{bmatrix} \notin \text{Ker} (A-3I)[/itex]

The vectors (1,0,0,0)^T and (0,0,1,0)^T are eigenvectors of J, not of A.

RGV
 
  • #3
Ray Vickson said:
The vectors (1,0,0,0)^T and (0,0,1,0)^T are eigenvectors of J, not of A.

RGV

Of course, [itex]J=P^{-1}AP \neq A[/itex] for some change of basis matrix [itex]P[/itex].
 

FAQ: Eigenvectors of a matrix in Jordan Normal Form

What is the Jordan Normal Form of a matrix?

The Jordan Normal Form (JNF) of a matrix is a specific form that a matrix can be transformed into by a similarity transformation. It is a block diagonal matrix with Jordan blocks on the main diagonal. A Jordan block is a square matrix with a specific structure that contains eigenvalues and eigenvectors of the original matrix.

What are eigenvectors?

Eigenvectors are special vectors associated with a matrix that do not change direction when multiplied by that matrix. They represent the direction of the linear transformation of the matrix and are useful in solving systems of linear equations.

Why are eigenvectors important in the context of Jordan Normal Form?

Eigenvectors are important in the context of Jordan Normal Form because they are used to construct the Jordan blocks. The eigenvectors associated with a given eigenvalue determine the size and structure of the corresponding Jordan block in the JNF. They also allow for the simplification of complex matrices into a more manageable form.

How do you find the eigenvectors of a matrix in Jordan Normal Form?

To find the eigenvectors of a matrix in Jordan Normal Form, you first need to determine the eigenvalues of the matrix. Once you have the eigenvalues, you can use them to construct the Jordan blocks and then find the corresponding eigenvectors. You can also use the characteristic polynomial and the Cayley-Hamilton theorem to find the eigenvalues and eigenvectors of a matrix in JNF.

What is the significance of Jordan Normal Form in linear algebra and other fields of science?

Jordan Normal Form is significant in linear algebra because it simplifies the structure of a matrix and makes it easier to perform computations involving the matrix. It also allows for the determination of the geometric and algebraic multiplicities of eigenvalues, which are important concepts in linear algebra. In other fields of science, JNF is used for solving differential equations, analyzing dynamical systems, and understanding the behavior of linear transformations.

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