Show HN: Rotation via Double Reflection

Bookmarked! I love the interactive diagrams! I love that you have a touch-point larger than the drag handle. And I'm impressed that the label placement takes care to avoid the axes. Some feedback:You have vector s in blue, and then vector u in teal, and then vector v in orange.In the diagram, it's "Subject", "First Reflector", "Second Reflector". I think it'd be better if these labels were "Subject s", "First Reflector u", "Second Reflector v" so that we can match up the text to the diagram even without color.Later you have "The pair of vector u and v is called a rotor". But these colors do not match the earlier colors, and it makes it hard to connect to the diagram.In the 3D diagram, I think it would be better if you used the same color scheme as for the 2D diagram. Same for the circular reflection diagram.Suggested colors:- subject s - orange in every diagram (currently blue, blue, blue)- first reflector - teal in every diagram (currently teal, magenta, pink)- second reflector - blue in every diagram (currently orange, teal, orange)This makes the rotor colors more similar to each other than to the subject.

thank you

The dimension section triggered my “vague math” spider sense:> During this zic-zac motion across the plane the vector still rotates along the plane in the except same ways as in the 2d case above.What is “the plane”? In 2D there is one single plane. In 3D every rotation rotated within a 2D plane and preserves the projection of the original vector to the orthogonal complement of the plane (which is just the distance from the plane and which side the original point is on).In 4D and up, sorry, all of our nice 3D human intuition is wrong. You can rotate in two planes at once, and that’s not equivalent to a rotation in any given plane.And indeed the article is pretty close to being a proof that the construction doesn’t work in 4+ dimensions. Reflection across a codimension-1 hyperplane (i.e. a n-1-dimension hyperplane) negates a single basis vector. Do two of these and the span of those vectors defines a 2D plane, and you get a rotation in that specific plane and no other. And this is insufficient to describe a general rotation.Of course, in 4D, there are other sorts of reflection-ish operations, like how in 3D you can negate the x and y coordinates while leaving z alone. (That specific operation is, itself, a rotation and does not change parity!) I think that, if you are willing to appropriately stretch the idea of “reflection”, then you can generate all the rotations in higher dimension.

Note that to reflect a rigid, physical model of a 2D shape, you have to rotate it around the reflection axis in 3D space. I.e. reflection is just a rotation involving a temporarily borrowed extra dimension.

Great work

There is no mystery. Imagine a huge radius of rotation. Then a small rotation is almost like a linear shift due to the large radius. Two reflections around a small angle would mean two "half roll-overs" making it a full roll-over. That means you just shifted (rotated) the thing.

To construct the two vectors spanning a given angle (well, as the article says, one of them can be chosen arbitrarily, the easiest is to just use (1, 0)), you'll of course need trigonometric functions. This is exactly equivalent to how constructing a rotation matrix from an angle requires trigonometric functions, but after that you can rotate how many vectors you like with just dot products, or how constructing e^ai = sin(a) + cos(a)*i requires trigonometric functions, but after that it's just complex multiplication.Another fun way to decompose 2D rotation is into three shears, originally given by Paeth in 1986: https://silmon.github.io/arbitrary-image-rotation-using-shea...