Find th Jordan canonical form of a matrix

In summary: The non-diagonal numbers are there because the dimension of the eigenspace is 2 and in the standard basis, the matrix is not diagonal. The Jordan Block for this eigenvalue is 2 by 2 and only has one eigenvector. The "dimension" of its eigenspace is 1. The only eigenvector is <1, 0> so that Jordan Block is just\left[\begin{matrix} -1 & 0 \\ 1 & -1\end{array}\right] The "diagonal entries are -1" because that is the eigenvalue. In this case, that is the only eigenvalue so the Jordan form is just that block.In summary
  • #1
Antti
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I've followed and understood this small example of calculating jordan forms all the way to the last line where they say "Therefore, the jordan form is...". When they say "therefore", it's NEVER obvious :smile:

Anyway, I get why the diagonal entries are -1. And that a minimal polynomial (t+1)^2 means I have two Jordan blocks with dimensions 1 and 2. But why is (3,2) in the final answer one? Or perhaps I should ask: how do you know what "non-diagonal" numbers to put where, when you get to this point of the calculation. Thanks in advance!

http://www.math.umn.edu/~jpeters/Prelims/F96/Problem5.pdf
 
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  • #2
When you mean by "the diagonal entries are -1", you mean for this particular problem, which you hadn't shown us yet. The diagonal entries are the eigenvalues of the matrix which may or may not be "-1". By the way, some texts define the Jordan Normal Form to have "1"s above the diagonal, not below. In the url you give, the Jordan normal form for a matrix consists of "blocks" in which the diagonal numbers are the same number- an eigenvalue, and the numbers must below the diagonal are 1. Such a single block might be
[tex]\left[\begin{matrix} \lambda & 0 & 0 & 0 \\ 1 & \lambda & 0 & 0 \\ 0 & 1 & \lambda & 0 \\0 & 0 & 1 & \lambda\end{array}\right][/tex]

A general "Jordan form" might consist of a number of those: if a 4 by 4 matrix has eigenvalues 2 and 3, each of multiplicity 2, then its Jordan form might be
[tex]\left[\begin{matrix} 2 & 0 & 0 & 0 \\ 1 & 2 & 0 & 0 \\ 0 & 0 & 3 & 0\\0 & 0 & 1 & 3 \end{array}\right][/tex]

A complicating factor is that the same eigenvalue may give rise to more than one "Jordan block" depending on how many independent eigenvecotrs it has.

The particular matrix given here is 3 by 3 but its characteristic polynomial is [itex](1+ \lambda)^3[/itex] so it has only -1 as an eigenvalue, of multiplicity 3. In order to determine whether this matrix is diagonalizable, or how many "Jordan blocks" it has, we must determine the corresponding eigenvectors. It turns out that any eigenvector <x, y, z> must satisfy x+ 2y-5z so any eigenvector is a linear combination of <-2, 1, 0> and <-5, 0, 1>. That means that the eigenspace is of dimension 2 so there will be a 2 by 2 "Jordan block" and a single separate eigenvalue:
[tex]\left[\begin{matrix} -1 & 0 & 0 & 0 \\ 0 & -1 & 0 & 0 \\ 0 & 1 & -1 & 0 \\0 & 0 & 1 & -1 \end{array}\right][/tex]
Where the separate eigenvalue -1 is in the first row and the rest is the "Jordan block".
 

1. What is the Jordan canonical form of a matrix?

The Jordan canonical form of a matrix is a specific representation of a square matrix that is similar to a diagonal matrix, but with blocks along the diagonal instead of individual elements. It is useful for understanding the structure and properties of a matrix.

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

To find the Jordan canonical form of a matrix, you need to first find its eigenvalues and corresponding eigenspaces. Then, for each eigenvalue, you need to find a basis for the corresponding eigenspace. Finally, you can use these bases to construct the Jordan canonical form of the matrix.

3. What is the significance of the Jordan canonical form?

The Jordan canonical form is significant because it allows us to simplify and understand the structure of a matrix. It also provides important information about the matrix's eigenvalues, eigenvectors, and their relationships. This can be useful in solving various problems in linear algebra and other fields.

4. Can any matrix be transformed into its Jordan canonical form?

Yes, any square matrix can be transformed into its Jordan canonical form. However, the resulting form may not always be unique. It depends on the matrix's eigenvalues and how they are distributed.

5. What are some applications of the Jordan canonical form?

The Jordan canonical form has various applications in fields such as physics, engineering, and computer science. It can be used to analyze dynamical systems, study the behavior of linear systems, and solve differential equations. In addition, it is also used in data compression, signal processing, and image processing.

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