Finding rotation axis and angle, using eigenvalues

In summary, the book does not teach how to find the eigenvectors of a 3×3 matrix. You can solve simultaneous equations to find the eigenvalue of interest.
  • #1
ahmed markhoos
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http://im54.gulfup.com/ZtJZd5.png

http://im54.gulfup.com/SJgJXh.png Till now compared with other subjects that I studied by my self, linear algebra is really the toughest one :bow:

Anyway, here I found a plane using characteristic eq. which really surprised me since det(M)=1, M is the matrix I've posted.

##-2x+y+z=0## , how is that? a rotation around plane! in which dimension that's possible!, as the book did I took a vector satisfy the plane that's ##(1,1,1)##, then I found ##\theta = π##

Everything is correct according to book solution. But I'm not convinced yet! a plane has a lot of vectors in many directions nevertheless we derived the axis of rotation from plane eq.?! that's really weird.

Thanks a lot guys.
 
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  • #2
There is no rotation around a plane. It is reflection in a plane followed by (or preceded by, as the two operations commute) a rotation around the normal to the plane (a plane only has one normal). The axis of rotation is the straight line through the origin in the direction of that normal.
 
  • #3
andrewkirk said:
There is no rotation around a plane. It is reflection in a plane followed by (or preceded by, as the two operations commute) a rotation around the normal to the plane (a plane only has one normal). The axis of rotation is the straight line through the origin in the direction of that normal.

But the determinant shows no reflection ?
 
  • #4
ahmed markhoos said:
But the determinant shows no reflection ?
Then in that case you don't need to bother with a plane. Just find the axis of rotation. It will be the line through the origin in the direction of the eigenvector with an associated eigenvalue of 1.
 
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  • #5
andrewkirk said:
Then in that case you don't need to bother with a plane. Just find the axis of rotation. It will be the line through the origin in the direction of the eigenvector with an associated eigenvalue of 1.

I did what you exactly said, but as you can see from the matrix in the question: "using first row"

##-x+2y+2z=\frac{1}{3}λx##

λ=1, that gives me ##-2x+y+z=0##

there is more than one vector satisfy the conditions you said "through the origin and eigenvector with an associated eigenvalue of 1"

what am I really missing?, I am supposed to have a line not a plane!
 
  • #6
What eigenvector(s) have you found that has an eigenvalue of 1?

Have they taught you how to find eigenvectors?
 
  • #7
andrewkirk said:
What eigenvector(s) have you found that has an eigenvalue of 1?

Have they taught you how to find eigenvectors?

I'm frustrated now by your question ><.

I know how to find eigenvalues and eigenvectors for 2×2 matrix with no doubt. Maybe I'm really not getting the idea of 3×3 matrices?! The book I read didn't point out clearly how to find the eigenvectors (of 3×3), just degeneracy in 3×3 matrices by Grand-Schmidt method.

Now I'm afraid that's the answer might be NO .
"Mathematical Methods in the physical sciences, by Mary Boas"
 
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  • #8
Do you know how to solve simultaneous equations then? Because once you have an eigenvalue of ##\lambda## you can find an eigenvector as follows, where M is the matrix you wrote above and ##\vec{v}## is the eigenvector:

$$M\vec{v}=\lambda \vec{v}=\lambda I\vec{v}$$
Hence
$$M'\vec{v}=0$$
where ##M'=M-\lambda I## - that is, M' is the original matrix M, with ##\lambda## subtracted from each of the diagonal elements.

So just solve that second equation and you're done.

Here of course, you have ##\lambda = 1## for the eigenvalue of interest.
 
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  • #9
andrewkirk said:
Do you know how to solve simultaneous equations then? Because once you have an eigenvalue of ##\lambda## you can find an eigenvector as follows, where M is the matrix you wrote above and ##\vec{v}## is the eigenvector:

$$M\vec{v}=\lambda \vec{v}=\lambda I\vec{v}$$
Hence
$$M'\vec{v}=0$$
where ##M'=M-\lambda I## - that is, M' is the original matrix M, with ##\lambda## subtracted from each of the diagonal elements.

So just solve that second equation and you're done.

Here of course, you have ##\lambda = 1## for the eigenvalue of interest.
andrewkirk said:
Do you know how to solve simultaneous equations then? Because once you have an eigenvalue of ##\lambda## you can find an eigenvector as follows, where M is the matrix you wrote above and ##\vec{v}## is the eigenvector:

$$M\vec{v}=\lambda \vec{v}=\lambda I\vec{v}$$
Hence
$$M'\vec{v}=0$$
where ##M'=M-\lambda I## - that is, M' is the original matrix M, with ##\lambda## subtracted from each of the diagonal elements.

So just solve that second equation and you're done.

Here of course, you have ##\lambda = 1## for the eigenvalue of interest.

Thanks a lot,

I was blind from seeing that obvious thing !
 

Related to Finding rotation axis and angle, using eigenvalues

1. What are eigenvalues and why are they important in finding rotation axis and angle?

Eigenvalues are a set of special numbers that represent how a matrix or transformation affects a vector. In the context of finding rotation axis and angle, eigenvalues are important because they can help us determine the direction and magnitude of the rotation.

2. How do you find the eigenvalues of a matrix?

To find the eigenvalues of a matrix, we first need to subtract the identity matrix from the original matrix. Then, we use the determinant to solve for the eigenvalues. The resulting eigenvalues will be the values that satisfy the equation (A - I)x = 0, where A is the original matrix and x is the eigenvector.

3. Can you explain the process of finding rotation axis and angle using eigenvalues?

To find the rotation axis and angle using eigenvalues, we first find the eigenvalues of the rotation matrix. Then, we use the eigenvalues to calculate the rotation angle. Next, we find the eigenvector corresponding to the largest eigenvalue, which will represent the rotation axis. Finally, we use the cross product of the original vector and the rotation axis to determine the direction of rotation.

4. Are there any limitations to using eigenvalues to find rotation axis and angle?

Yes, there are limitations to using eigenvalues. One limitation is that it only works for square matrices, meaning the number of rows and columns must be equal. Additionally, if the matrix is not a rotation matrix, the eigenvalues and eigenvectors may not accurately represent the rotation axis and angle.

5. How is this method of finding rotation axis and angle used in real-world applications?

Finding rotation axis and angle using eigenvalues is commonly used in computer graphics and computer vision. It is also used in robotics and physics to analyze the rotation of objects and systems. This method can also be applied in engineering for designing and analyzing mechanical systems that involve rotation.

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