All Eigenvalues Lie on the Unit Circle

In summary, the conversation discusses a 2x2 partitioned matrix and the certainty that all of its eigenvalues are on the unit circle. However, there is no known proof for this and an example is given where the eigenvalue is not on the unit circle. It is also mentioned that there is no special condition on the matrix and that the key to understanding the relationship between orthogonality of A and B1...B4 lies in the interrelations of the block matrices. The question of whether or not the matrix is normal is also brought up as potentially relevant to finding a solution.
  • #1
ali987
9
0
Hi everyone

Consider a 2x2 partitioned matrix as follow:

A = [ B1 B2 ; B3 B4 ]

I'm sure that all eigenvalues of A are on the unit circle (i.e., abs
(all eig) = 1 ). but, I don't know how to prove it. Is there any
theorem?
 
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  • #2
Is it, by chance, a unitary matrix: [tex]AA^\dag=I[/tex]?
 
  • #3
[tex]\begin{pmatrix}2 & 0\\ 0 & 1\end{pmatrix}\begin{pmatrix}1 \\ 0\end{pmatrix}=2\begin{pmatrix}1\\ 0\end{pmatrix}[/tex]
 
  • #4
ali987 said:
Hi everyone

Consider a 2x2 partitioned matrix as follow:

A = [ B1 B2 ; B3 B4 ]

I'm sure that all eigenvalues of A are on the unit circle (i.e., abs
(all eig) = 1 ). but, I don't know how to prove it. Is there any
theorem?
You can't prove it- it's not true! Fredrik gave an example in which the eigenvalue is 2, not on the unit circle.

Now, is there some condition on A, such as [tex]AA^\dag=I[/tex], as arkajad suggests, that you haven't told us?
 
  • #5
Unfortunately, there is no special condition on A.
B1, B2, B3 and B4 are constructed from several matrices themselves, some of those matrices are symmetric and positive definite.
Is there any theorem which relate orthogonality of the A to orthogonality (or sth like that) of B1...B4?
 
  • #6
ali987 said:
Is there any theorem which relate orthogonality of the A to orthogonality (or sth like that) of B1...B4?

No. What is important are the interrelations of your block matrices. Write [tex]AA^\dag[/tex] in the block matrix form and you will see. Is your matrix normal: [tex]AA^\dag=A^\dag A[/tex]? If you do not know even this - then what do you know about your B matrices and relations between them? The key to your question is there.
 

FAQ: All Eigenvalues Lie on the Unit Circle

1. What does it mean for all eigenvalues to lie on the unit circle?

When all eigenvalues of a matrix lie on the unit circle, it means that the magnitude of each eigenvalue is equal to 1. This indicates that the matrix has a special property known as unitary or orthogonal, which is often associated with symmetry and rotation.

2. Is it possible for a matrix to have all eigenvalues on the unit circle?

Yes, it is possible for a matrix to have all eigenvalues on the unit circle. This is often the case for matrices that have certain symmetries or are related to rotations, such as the rotation matrix in 2D or the complex conjugate matrix in 3D.

3. What are the implications of having all eigenvalues on the unit circle?

Having all eigenvalues on the unit circle can provide useful information about the properties of a matrix. For example, it can indicate that the matrix is normal, which means it commutes with its adjoint. This property can be useful in solving systems of linear equations and in numerical algorithms.

4. How can you determine if a matrix has all eigenvalues on the unit circle?

To determine if a matrix has all eigenvalues on the unit circle, you can calculate the eigenvalues of the matrix and check their magnitudes. If all eigenvalues have a magnitude of 1, then they lie on the unit circle. Another way is to check if the matrix is normal, as mentioned earlier.

5. Are there any real-world applications of matrices with all eigenvalues on the unit circle?

Yes, there are several real-world applications of matrices with all eigenvalues on the unit circle. One example is in control systems engineering, where these matrices can represent stable systems that do not have any unstable modes. They are also used in signal processing, specifically in Fourier analysis, where they can represent sinusoidal signals with constant amplitude and phase.

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