Jordan Normal Form of Unitary Transformation

In summary, the conversation discusses finding the Jordan normal form of a unitary linear transformation. The solution is to diagonalize the matrix, with the Jordan normal form being a diagonal matrix with eigenvalues as its diagonal elements. The conversation also mentions the difficulty being hidden in the statement that a unitary matrix can be diagonalized, and suggests adding that the diagonal elements of the Jordan form must have an absolute value of 1.
  • #1
Sudharaka
Gold Member
MHB
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Hi everyone, :)

Recently I encountered the following problem. Hope you can confirm whether my method is correct. My answer seems so trivial and I have doubts whether it is correct.

Problem:

Find the Jordan normal form of a unitary linear transformation.

My Solution:

Now if we take the matrix of a unitary linear transformation (say \(A\)) it could be diagonalized; \(A=VDV^*\), where \(D\) is a diagonal unitary matrix and \(V\) is a unitary matrix. So therefore the Jordan normal form is obviously \(D\), where the diagonal elements consist of the eigenvalues of \(A\).
 
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  • #2
Sudharaka said:
Hi everyone, :)

Recently I encountered the following problem. Hope you can confirm whether my method is correct. My answer seems so trivial and I have doubts whether it is correct.

Problem:

Find the Jordan normal form of a unitary linear transformation.

My Solution:

Now if we take the matrix of a unitary linear transformation (say \(A\)) it could be diagonalized; \(A=VDV^*\), where \(D\) is a diagonal unitary matrix and \(V\) is a unitary matrix. So therefore the Jordan normal form is obviously \(D\), where the diagonal elements consist of the eigenvalues of \(A\).
Yes, that is absolutely correct. The result is not trivial, but all the difficulty is hidden in the statement that a unitary matrix can be diagonalised. If you are allowed to quote that, then the rest is easy. (You could add that the diagonal elements of the Jordan form must all have absolute value $1$.)
 
  • #3
Opalg said:
Yes, that is absolutely correct. The result is not trivial, but all the difficulty is hidden in the statement that a unitary matrix can be diagonalised. If you are allowed to quote that, then the rest is easy. (You could add that the diagonal elements of the Jordan form must all have absolute value $1$.)

Thanks very much for the detailed explanation. I really appreciate it. :)
 

FAQ: Jordan Normal Form of Unitary Transformation

What is the Jordan Normal Form of Unitary Transformation?

The Jordan Normal Form of Unitary Transformation is a mathematical concept that describes the form of a unitary transformation matrix. It is used to diagonalize a square matrix with complex eigenvalues and is named after the mathematician Camille Jordan.

How is the Jordan Normal Form of Unitary Transformation calculated?

The Jordan Normal Form of Unitary Transformation is calculated by finding the eigenvalues and eigenvectors of a matrix and then using them to construct a diagonal matrix. The eigenvectors form the columns of a transformation matrix, and the diagonal matrix contains the eigenvalues on its diagonal.

What is the significance of the Jordan Normal Form of Unitary Transformation in mathematics?

The Jordan Normal Form of Unitary Transformation is significant because it simplifies the representation of a matrix and makes it easier to perform calculations. It also allows for a better understanding of the structure and behavior of a matrix, making it a useful tool in many areas of mathematics and science.

Can any matrix be transformed into Jordan Normal Form of Unitary Transformation?

Yes, any square matrix with complex eigenvalues can be transformed into Jordan Normal Form of Unitary Transformation. However, not all matrices have a unique Jordan Normal Form, and some may not have a Jordan Normal Form at all.

What are the practical applications of the Jordan Normal Form of Unitary Transformation?

The Jordan Normal Form of Unitary Transformation is used in various fields, such as quantum mechanics, signal processing, and control theory. It is also helpful in solving systems of differential equations, analyzing the stability of dynamical systems, and studying the behavior of linear systems.

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