Jordan Normal Form of Matrix: 65 Characters

In summary: This means that, for every vector v in the space, there is a corresponding column in P that satisfies the following equation: \begin{pmatrix}P^{-1}AP & -AP\\P^{-1} & AP+1\\0 & -AP\end{matrix}In summary, the two generalized eigenvalues are 1 and 2 and the method to find them is to find a vector that produces the normal vector on a plane when crossed.
  • #1
Gregg
459
0
[tex] \left(
\begin{array}{ccc}
0 & 1 & 0 \\
-1 & -1 & 1 \\
-1 & 0 & 1
\end{array}
\right) [/tex]

The answer is

[tex] \left\{\left(
\begin{array}{ccc}
1 & -1 & 0 \\
0 & 1 & -1 \\
1 & 0 & 0
\end{array}
\right),\left(
\begin{array}{ccc}
0 & 1 & 0 \\
0 & 0 & 1 \\
0 & 0 & 0
\end{array}
\right)\right\} [/tex]


The first one [tex] \left( \begin{array}{c}
1 \\
0 \\
1
\end{array} \right) [/tex] which is an eigenvector.

The eigenvalues are 0,0,0.

Looking at [tex] \text{Ker}(M-\lambda I)^2) =\text{Ker}(M^2)=\text{Ker}(\left(
\begin{array}{ccc}
-1 & -1 & 1 \\
0 & 0 & 0 \\
-1 & -1 & 1
\end{array}
\right))[/tex]

[tex]z=x+y[/tex]

For the first eigenvector [tex] \left( \begin{array}{c}
1 \\
0 \\
1
\end{array} \right) [/tex] is in this generalised eigenspace [itex] E_1 \subset E_2 [/itex] I thought about trying to find two vectors that produce the normal vector on that plane when crossed but that doesn't work and I'm not sure it's even the right thing to do. Can choose [tex] \left( \begin{array}{c}
-1 \\
1 \\
0
\end{array} \right) [/tex] for z=x+y. But [tex]\text{Ker}(M^3)=\text{Ker}(0) [/tex]

I know there is the method [itex] (M-\lambda I)\vec{v}_2=\lambda \vec{v_1} [/itex] ? Do I have to use that? I'd prefer to be able to use kernels.
 
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  • #2
I found by doing [tex] A \vec{v_i} = \vec{v_{i-1}} [/tex]. But why didn't the nullspace approach work?
 
  • #3
Yes, 0 is a triple eigenvalue. The characteristic equation is [itex]x^3= 0[/itex] and, since every matrix satisfies its own characteristic equation, [itex]A^3v= 0[/itex] for every vector. But, as you have found, only multiples of <1, 0, 1> are eigenvectors. That is, there is only a one dimensional subspace of eigevectors- that satisfy Av= 0. So we may have some vectors, u, such that Au is not 0 but [itex]A^2u= 0[/itex] which in turn means [itex]A(Au)= 0[/itex] which means Au must be a multiple of <1, 0, 1>.

We look for <x, y, z> such that
[tex]\begin{pmatrix}0 & 1 & 0 \\ -1 & -1 & 1\\ -1 & 0 & 1\end{pmatrix}\begin{pmatrix}x \\ y \\ z\end{pmatrix}= \begin{pmatrix}y \\-x- y+ z\\ -x+ z\end{pmatrix}= \begin{pmatrix}1 \\ 0 \\ 1\end{pmatrix}[/tex]
which gives y= 1, -x- y+ z= 0, x+ z= 0. Since y= 1, the other two equations reduce to z- x= 1. If we take x= 0, we get z= 1 so <0, 1, 1> is a "generalized" eigenvalue.

But we must have some vectors, v, such that neither [itex]Av[/itex] nor [itex]A^2v[/itex] is 0 but [itex]A^3v= 0[/itex] which means [itex]u= Av[/itex] must be such that [itex]A^2v= 0[/itex] which is what we just found:
[tex]\begin{pmatrix}0 & 1 & 0 \\ -1 & -1 & 1\\ -1 & 0 & 1\end{pmatrix}\begin{pmatrix}x \\ y \\ z\end{pmatrix}= \begin{pmatrix}y \\-x- y+ z\\ -x+ z\end{pmatrix}= \begin{pmatrix}0 \\ 1 \\ 1\end{pmatrix}[/tex]
which gives the equations y= 0, -x- y+ z= -x+ 0+ z= 1, and -x+ z= 1. Those are really the same as we had before- taking a different vaue for x, say 1 instead of 0, z= 2. A second "generalized" eigenvalue is <1, 0, 2>.

Form matrix P having those three vectors as columns. Then [itex]P^{-1}AP[/itex] is in "Jordan Normal Form".
 

1. What is the Jordan Normal Form of a matrix?

The Jordan Normal Form of a matrix is a special form that a matrix can be transformed into, where the matrix is made up of blocks of diagonal and upper triangular matrices. It is named after the mathematician Camille Jordan.

2. Why is the Jordan Normal Form important?

The Jordan Normal Form is important because it simplifies the structure of a matrix, making it easier to analyze and perform calculations with. It also reveals important information about the eigenvalues and eigenvectors of a matrix.

3. How is the Jordan Normal Form calculated?

The Jordan Normal Form is calculated by finding the eigenvalues and eigenvectors of a matrix, and then using these to construct a diagonal matrix with the eigenvalues on the diagonal and upper triangular matrices with the corresponding eigenvectors in the blocks.

4. What are some applications of the Jordan Normal Form?

The Jordan Normal Form has various applications in fields such as physics, engineering, and computer science. It can be used to analyze linear systems, solve differential equations, and diagonalize matrices for efficient computation.

5. Can all matrices be transformed into the Jordan Normal Form?

No, not all matrices can be transformed into the Jordan Normal Form. Only square matrices that are not defective (i.e. have a full set of eigenvectors) can be transformed into the Jordan Normal Form.

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