Geometric Algebra supporters keep advertising that rotors are great since they work in any dimension, which makes me wonder: would an arbitrary n-dimensional SVD-like decomposition benefit from using rotors instead of rotation matrices, and if so how? And if not, why?
Yes, but from the canonical form of rotation matrices [1] I would expect such matrices to be represented as a sum of bi-vectors/rotors, which should take the same amount of data?
