Relation between complex eigenvalues and rotations

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Homework Help Overview

The discussion revolves around a matrix A and its relationship with complex eigenvalues and rotations. The original poster presents a matrix and a vector, exploring the effects of repeated multiplication of the vector by the matrix, leading to a cyclical pattern reminiscent of rotations on the unit circle. The professor's connection between the eigenvalues and geometric interpretations of rotations is a focal point.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the cyclical nature of the matrix's effect on the vector, questioning how this relates to rotations and eigenvalues. Some explore the geometric interpretation of the matrix's action and its implications for understanding eigenvalues. Others inquire about the representation of eigenvectors in terms of real and imaginary components.

Discussion Status

The discussion is ongoing, with various interpretations being explored. Some participants have offered geometric insights and connections to symmetry, while others are seeking clarification on the underlying principles and relationships between the matrix, eigenvalues, and rotations.

Contextual Notes

Participants are navigating the complexities of eigenvalues and their geometric interpretations, with references to specific properties of the matrix, such as orthogonality and symmetry. There is an emphasis on understanding the implications of the matrix's structure and behavior in relation to the unit circle and rotations.

TheMathNoob
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Homework Statement


I have the following matrix:
0 0 0 1
1 0 0 0 = A
0 1 0 0
0 0 1 0
and the vector
v = (1,0,0,0)

If I perform Av, this gives:
Av=(0,1,0,0)
And If I keep multiplying the result by A like A*A*(Av), the outcome will be something like
j= (0,0,1,0)
k=(0,0,0,1)
l=(1,0,0,0)

The professor made a relation between these outcomes and the unit circle. In the unit circle the positive x axes is labelled with 1, the -x axes with-1, the positive y axes with i and negative y axes with -i. Then, He said that the eigen values are 1,-1,i,-1 because something rotates 90 degrees. He also related e^(pi*i) with rotations. I am just wondering if you can explain me all that or the exact place where I can find information.

Homework Equations

The Attempt at a Solution

 
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TheMathNoob said:

Homework Statement


I have the following matrix:
0 0 0 1
1 0 0 0 = A
0 1 0 0
0 0 1 0
and the vector
v = (1,0,0,0)

If I perform Av, this gives:
Av=(0,1,0,0)
And If I keep multiplying the result by A like A*A*(Av), the outcome will be something like
j= (0,0,1,0)
k=(0,0,0,1)
l=(1,0,0,0)

The professor made a relation between these outcomes and the unit circle.
The connection, possibly, is that for the matrix A above, ##Iv, Av, A^2v, A^3v## is a cycle that starts repeating again with ##A^4v##, similar to the way that a rotation of a vector by ##\pi/2## repeats.

The matrix ##\begin{bmatrix} 0 & -1 \\ 1 & 0 \end{bmatrix}## rotates a vector by ##\pi/2## counterclockwise. The two eigenvalues are ##\lambda = \pm i##, and the corresponding eigenvectors are ##\vec{v} = \begin{bmatrix} \pm i \\ 1 \end{bmatrix}##.
TheMathNoob said:
In the unit circle the positive x axes is labelled with 1, the -x axes with-1, the positive y axes with i and negative y axes with -i. Then, He said that the eigen values are 1,-1,i,-1 because something rotates 90 degrees. He also related e^(pi*i) with rotations. I am just wondering if you can explain me all that or the exact place where I can find information.

Homework Equations

The Attempt at a Solution

 
Mark44 said:
The connection, possibly, is that for the matrix A above, ##Iv, Av, A^2v, A^3v## is a cycle that starts repeating again with ##A^4v##, similar to the way that a rotation of a vector by ##\pi/2## repeats.

The matrix ##\begin{bmatrix} 0 & -1 \\ 1 & 0 \end{bmatrix}## rotates a vector by ##\pi/2## counterclockwise. The two eigenvalues are ##\lambda = \pm i##, and the corresponding eigenvectors are ##\vec{v} = \begin{bmatrix} \pm i \\ 1 \end{bmatrix}##.
Right, I have been reading and watching videos about this issue. The hard thing to understand are the vectors that multiply A. In this case
you can represent your an eigen vector by an imaginary and real part. In this case, your first eigen vector, let's call it v, can be represented as following:
v=(0,1)+i(1,0)
so the multiplicand vectors that get this behavior when multiplied by A are the basis (0,1) and (1,0), my question now would be how can I know what the eigen values are if I know that a pattern like that emerges.

Example
v=(1,0,0)
r=(0,1,0)
s=(0,0,1)
 
I don't know if this help but I have a geometric interpretation of your problem.
You can notice that ##A^2## is a symmetry since ##A## is orthogonal and ##A^4 = I##.
You can find the plane of symmetry by solving ## A^2 X = X ## and it's orthogonal by solving ##A^2 X = -X ##.
The plane of symmetry is the span of ##\{(1,0,1,0),(0,1,0,1)\}## and it's orthogonal the span of ##\{(1,0,-1,0),(0,1,0,-1)\}##. By the way these vectors form a nice orthogonal family 2 by 2 in the planes, and also as a whole. Therefore, as a whole, they form an orthogonal basis of ##\mathbb{R}^4##, and 2 by 2, an orthogonal basis of the each planes.
You will notice that in these planes, ##A## performs 90 degrees rotations of the basis vectors since it transforms one basis vector into plus or minus the other depending on the plane.
I hope this will help.
 
geoffrey159 said:
You will notice that in these planes, ##A## performs 90 degrees rotations of the basis vectors since it transforms one basis vector into plus or minus the other depending on the plane.

Sorry I realize this is very unclear. What's going on is that if ##P## is the plane of symmetry of ##A^2##, then ##A## is a ##\pi/2## rotation in ##P^\perp## but a reflection about the axis directed by ##(1,1,1,1)## in ##P##.

This is because orthogonal endomorphisms in the plane are either rotations or reflections. If ##(e_1,e_2)## is the orthogonal basis of ##P## mentioned above, ##(e_3,e_4)## the orthogonal basis of ##P^\perp##, then you get that ##Ae_1 = e_2##, ## Ae_2 = e_1##. So clearly A is a reflection in ##P## about the axis at half angle between ##e_1## and ##e_2##. This axis is directed by ##e_1 + e_2 = (1,1,1,1)##.
Also ##Ae_3 = e_4##, ##A^2e_3 = -e_3##, ##A^3 e_3 = -e_4##, ##A^4 e_3 = e_3##. So ##A## is a ##\pi / 2 ## rotation in ##P^\perp##.

I think this is correct this time
 

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