Rotations in nth Dimensional Space

In summary, the conversation discusses creating a flash animation that starts with a point and gradually adds dimensions until it becomes a hypercube. The main challenge is figuring out how to rotate the cube in higher dimensions, and the conversation references a formula from Wikipedia that uses a skew-symmetric matrix. The conversation also explains how a vector can be associated with a skew-symmetric matrix in three dimensions.
  • #1
Bob65536
5
0
Let me start by saying I do not have a lot of background in linear algebra, but I'm not afraid of learning. I am working on a flash animation with action script. That does the following:
1. Start with a point.
2. Add width so it turns into a line.
3. Rotate about the x-y plane 360 deg.
4. Add height so it turns into a square.
5. Rotate about the x-y plane 360 deg.
6. Add depth so it turns into a cube.
7. Rotate about the x-z plane 360 deg.
8. Add 4 dimensional length so it turns into a hypercube.
...
I plan on going up to about 10 dimensions before the animation ends.

I have to code to:
-Create the wire frame for an nth dimensional cube.
-Orthographic projection of the verticies into 2d space for drawing.
-Animate the new "dimension being added". The last component of the vector for each vertex starts at zero and approaches the correct value over time.

Basically the only thing I am missing is rotating the cube. I am having a hard time generalizing rotations into nth dimensional space. I came across an article on Wikipedia that looks promising at http://en.wikipedia.org/wiki/Rotation_matrix#Axis_of_a_rotation. The formula is:
[tex]R = \mathbf{u}\otimes\mathbf{u} + \cos\theta(1-\mathbf{u}\otimes\mathbf{u}) + \sin\theta[\mathbf u]_{\times}[/tex]
where
R is the rotation matrix.
u is a unit vector.
[tex]\otimes[/tex] is the outer product.
[tex][\mathbf u]_{\times}[/tex] is the skew symmetric form of u.

I do not understand though how you get the skew symmetric form of u. Reading the Wikipedia page on skew symmetric matrices does not help me understand how u goes from a vector to a square matrix. Does anybody have any tips or references that might help please?

Thanks!
 
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  • #2
In three-dimensions we can associate a vector with a skew-symmetric matrix. A 3 by 3 matrix generally has 9 entries. But for skew-symmetric, [itex]a_{nm}= -a{mn}[/itex] we must have [itex]a_{nn}= -a_{nn}[/itex] so all diagonal entries are 0. That leaves 9- 3= 6 entries and, once we have set, say, the 3 above the diagonal, the other 3 are fixed. That is, 3 by 3 skew-symmetric matrix has 3 independent entries, just like a 3- vector. The standard way of associating a skew-symmetric matrix to a vector is to associate the [itex]n^{th}[/itex] basis vector with the matrix having 0s along the [itex]n^{th}[/itex] column and row, -1 above the diagonal and 1 below. (-1 below the axis and 1 above would also give rotations about the vector as axis but with reversed direction.)

Specifically, [itex]\vec{i}[/itex] maps to the matrix
[tex]\begin{bmatrix}0 & 0 & 0 \\0 & 0 & -1 \\ 0 & 1 & 0\end{bmatrix}[/tex]

[itex]\vec{j}[/itex] maps to the matrix
[tex]\begin{bmatrix}0 & 0 & -1 \\0 & 0 & 0 \\ 1 & 0 & 0\end{bmatrix}[/tex]

[itex]\vec{k}[/itex] maps to the matrix
[tex]\begin{bmatrix}0 & -1 & 0 \\ 1 & 0 & 0 \\0 & 0 & 0\end{bmatrix}[/itex]

And so a general vector, [itex]a\vec{i}+ b\vec{j}+ c\vec{k}[/itex] maps to
[tex]a\begin{bmatrix}0 & 0 & 0 \\0 & 0 & -1 \\ 0 & 1 & 0\end{bmatrix}+ b\begin{bmatrix}0 & 0 & -1 \\0 & 0 & 0 \\ 1 & 0 & 0\end{bmatrix}+ c\begin{bmatrix}0 & -1 & 0 \\ 1 & 0 & 0 \\0 & 0 & 0\end{bmatrix}[/tex][tex]= \begin{bmatrix}0 & -c & -b \\ c & 0 & -a \\ b & a & 0 \end{bmatrix}[/tex]
 

1. What is a rotation in nth dimensional space?

A rotation in nth dimensional space is a transformation that moves points in n-dimensional space around a fixed point, preserving the distance between the points and the fixed point. This can be thought of as spinning an object around a specific axis or point in space.

2. How is a rotation in nth dimensional space different from a rotation in 2 or 3 dimensional space?

A rotation in nth dimensional space follows the same principles as a rotation in 2 or 3 dimensional space, but it involves more axes and dimensions. In 2 or 3 dimensions, rotations are performed around a single axis, while in nth dimensional space, rotations can be performed around multiple axes.

3. What is the formula for calculating a rotation in nth dimensional space?

The formula for calculating a rotation in nth dimensional space uses matrices and trigonometric functions. It involves multiplying the coordinates of a point by a rotation matrix, which is determined by the angles of rotation around each axis.

4. Can rotations in nth dimensional space be visualized?

Yes, rotations in nth dimensional space can be visualized, but it can be more challenging than visualizing rotations in 2 or 3 dimensional space. Visualization techniques, such as using projections onto lower dimensional spaces, can be used to understand the rotation in nth dimensional space.

5. What are some applications of rotations in nth dimensional space?

Rotations in nth dimensional space have many applications in physics, computer graphics, and engineering. Some examples include simulating the movement of objects in 3D space, calculating the orientation of spacecraft, and performing transformations in computer graphics to create 3D animations or models.

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