Finding the Jordan canonical form of a matrix

In summary: B\vec{v}_2 = \vec{v}_1## as a matrix equation, and then solve it with your favorite method (I used Gaussian elimination). Once you have ##\vec{v}_2##, you can then use it as a starting point for finding ##\vec{v}_3, \vec{v}_4, \ldots, \vec{v}_n##, where ##n## is the size of the matrix.An alternative method is to find the generalized eigenvectors from the matrix A, and then use those to form ##\vec{v}_1## and ##\vec{v}_2##.
  • #1
Mr Davis 97
1,462
44

Homework Statement


Find the Jordan canonical form of the matrix ##
\left( \begin{array}{ccc}
1 & 1 \\
-1 & 3 \\ \end{array} \right)##.

Homework Equations

The Attempt at a Solution


So my professor gave us the following procedure:

1. Find the eigenvalues for each matrix A. Your characteristic polynomial must definitely SPLIT over ##\mathbb{C}##, but mostly likely you will be able to split it already over ##\mathbb{R}##.

2. For each eigenvalue ##\lambda## of A set the matrix ##B=A-\lambda I##

3. Calculate several consecutive powers of ##B=A-\lambda I##, e.g., ##B^1##,##B^2##,##B^3##, etc., and check the ranks of these matrices. Set ##N## to be the first exponent where the rank stabilizes, i.e., ##\text{rk}(B^N)=\text{rk}(B^{N+1}).##.

4. Find a basis for the kernel of ##B^N##; i.e., a basis for the generalized eigenspace ##K_{\lambda}(T)=\text{Ker}(A-\lambda I)^N##.

5. In each part, put together the bases you found for all ##K_{\lambda}(T)##, verify that you have obtained a basis for the whole space V, and write down the matrix of T in this basis.So, we have the matrix ##
\left( \begin{array}{ccc}
1 & 1 \\
-1 & 3 \\ \end{array} \right)##. It's characteristic polynomial is ##f(\lambda) = (\lambda - 2)^2##. So we have an eigenvalue of 2 with multiplicity 2.
Now, let ##B=A - \lambda I =
\left( \begin{array}{ccc}
-1 & 1 \\
-1 & 1 \\ \end{array} \right)##. This matrix has rank 1. Now, ##B^2 =
\left( \begin{array}{ccc}
0 & 0 \\
0 & 0 \\ \end{array} \right)
##. So it has rank 0. We can see that ##\text{rk}(B^2) = \text{rk}(B^3)##, so we must find a basis for the kernel of ##B^2##.

This is where I can get confused. We got the zero matrix, so the kernel of the zero matrix is all of ##\mathbb{R}^2##. So would we just choose any two linearly independent vectors? Or am I completely off-track and making a big mistake somewhere? I feel like I am following the procedure...
 
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  • #2
Mr Davis 97 said:

Homework Statement


Find the Jordan canonical form of the matrix ##
\left( \begin{array}{ccc}
1 & 1 \\
-1 & 3 \\ \end{array} \right)##.

Homework Equations

The Attempt at a Solution


So my professor gave us the following procedure:

1. Find the eigenvalues for each matrix A. Your characteristic polynomial must definitely SPLIT over ##\mathbb{C}##, but mostly likely you will be able to split it already over ##\mathbb{R}##.

2. For each eigenvalue ##\lambda## of A set the matrix ##B=A-\lambda I##

3. Calculate several consecutive powers of ##B=A-\lambda I##, e.g., ##B^1##,##B^2##,##B^3##, etc., and check the ranks of these matrices. Set ##N## to be the first exponent where the rank stabilizes, i.e., ##\text{rk}(B^N)=\text{rk}(B^{N+1}).##.

4. Find a basis for the kernel of ##B^N##; i.e., a basis for the generalized eigenspace ##K_{\lambda}(T)=\text{Ker}(A-\lambda I)^N##.

5. In each part, put together the bases you found for all ##K_{\lambda}(T)##, verify that you have obtained a basis for the whole space V, and write down the matrix of T in this basis.So, we have the matrix ##
\left( \begin{array}{ccc}
1 & 1 \\
-1 & 3 \\ \end{array} \right)##. It's characteristic polynomial is ##f(\lambda) = (\lambda - 2)^2##. So we have an eigenvalue of 2 with multiplicity 2.
Now, let ##B=A - \lambda I =
\left( \begin{array}{ccc}
-1 & 1 \\
-1 & 1 \\ \end{array} \right)##. This matrix has rank 1. Now, ##B^2 =
\left( \begin{array}{ccc}
0 & 0 \\
0 & 0 \\ \end{array} \right)
##. So it has rank 0. We can see that ##\text{rk}(B^2) = \text{rk}(B^3)##, so we must find a basis for the kernel of ##B^2##.

This is where I can get confused. We got the zero matrix, so the kernel of the zero matrix is all of ##\mathbb{R}^2##. So would we just choose any two linearly independent vectors? Or am I completely off-track and making a big mistake somewhere? I feel like I am following the procedure...

You make it too complicated. What can be the Jordan form of a 2x2 matrix?
 
  • #3
Do take note of what your professor told you, but always start investigating simpler alternatives. What do you know about a 2x2 JCF ? Are there any necessary conditions you can think of that it must satisfy?
 
  • #4
ehild said:
You make it too complicated. What can be the Jordan form of a 2x2 matrix?
The Jordan form is ##
\left( \begin{array}{ccc}
2 & 1 \\
0 & 2 \\ \end{array} \right)##, right? But I am still confused about how this fits into the given procedure.
 
  • #5
Mr Davis 97 said:
The Jordan form is ##
\left( \begin{array}{ccc}
2 & 1 \\
0 & 2 \\ \end{array} \right)##, right? But I am still confused about how this fits into the given procedure.
The original matrix A can be transformed into the Jordan form by choosing an appropriate matrix S: S-1AS=J. The first column of S is v, the eigenvector of A(or B) , the second one is a "generalized eigenvector", eigenvector of B^2 but not eigenvector of B.
 
  • #6
ehild said:
The original matrix A can be transformed into the Jordan form by choosing an appropriate matrix S: S-1AS=J. The first column of S is v, the eigenvector of A(or B) , the second one is a base factor which is not eigenvector of A (B).
That makes sense. However, I am still confused about the method that the professor gave us. Is the method not working? Obviously, a basis for the kernel of ##B^2## does not give the correct basis vectors which yield the JCF
 
  • #7
Mr Davis 97 said:
That makes sense. However, I am still confused about the method that the professor gave us. Is the method not working? Obviously, a basis for the kernel of ##B^2## does not give the correct basis vectors which yield the JCF
As B2=0 you can choose any pair of independent vectors as basis. So this method does not work. You have to choose the other base vector so as you get the Jordan form.
Try https://math.berkeley.edu/~ogus/old/Math_54-05/webfoils/jordan.pdf
 
  • #8
Mr Davis 97 said:
That makes sense. However, I am still confused about the method that the professor gave us. Is the method not working? Obviously, a basis for the kernel of ##B^2## does not give the correct basis vectors which yield the JCF
The procedure in the original post doesn't quite work. You want to find two vectors ##\vec{v}_1## and ##\vec{v}_2## that satisfy
\begin{align*}
B\vec{v}_1 &= 0 \\
B\vec{v}_2 &= \vec{v}_1
\end{align*}
##\vec{v}_1## is just a regular eigenvector. Note that ##B^2\vec{v}_2 = B\vec{v}_1 = 0##, so ##\vec{v}_2## is in the kernel of ##B^2##.

If you want to find ##\vec{v}_2## first, it can't be any vector in the kernel of ##B^2##. It also has to satisfy ##B\vec{v}_2 \ne 0##. Let ##\vec{v}_2 = (x,y)##. Then
$$B\vec{v}_2 = \begin{pmatrix} -x + y \\ -x+y \end{pmatrix}.$$ You can choose ##x## and ##y## arbitrarily as long as ##x \ne y##. Then ##\vec{v}_1 = B\vec{v}_2##.
 
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What is the Jordan canonical form of a matrix?

The Jordan canonical form of a matrix is a specific form that a square matrix can be transformed into through a process called diagonalization. It is a useful tool for understanding the behavior of linear systems and can simplify computations involving the matrix.

How do you find the Jordan canonical form of a matrix?

The process of finding the Jordan canonical form involves finding the eigenvalues and corresponding eigenvectors of the matrix, and then arranging them in a specific way to create the Jordan canonical form. This can be done through a series of matrix operations and transformations.

Why is the Jordan canonical form important?

The Jordan canonical form is important because it provides a way to simplify complex matrix calculations and make them easier to understand. It also helps to identify the behavior of linear systems and can be used to solve differential equations and other mathematical problems.

Can any matrix be transformed into Jordan canonical form?

No, not every matrix can be transformed into Jordan canonical form. In order for a matrix to have a Jordan canonical form, it must be a square matrix and have a complete set of linearly independent eigenvectors.

Are there any applications of the Jordan canonical form in science?

Yes, the Jordan canonical form has applications in a variety of scientific fields, including physics, engineering, and computer science. It is used to solve differential equations, model physical systems, and analyze the behavior of linear systems in control theory.

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