Eigenplane Explained

In mathematics, an eigenplane is a two-dimensional invariant subspace in a given vector space.[1] By analogy with the term eigenvector for a vector which, when operated on by a linear operator is another vector which is a scalar multiple of itself, the term eigenplane can be used to describe a two-dimensional plane (a 2-plane), such that the operation of a linear operator on a vector in the 2-plane always yields another vector in the same 2-plane.

A particular case that has been studied is that in which the linear operator is an isometry M of the hypersphere (written S3) represented within four-dimensional Euclidean space:

M [s t] = [s t]Λ\theta

where s and t are four-dimensional column vectors and Λθ is a two-dimensional eigenrotation within the eigenplane.

In the usual eigenvector problem, there is freedom to multiply an eigenvector by an arbitrary scalar; in this case there is freedom to multiply by an arbitrary non-zero rotation.

This case is potentially physically interesting in the case that the shape of the universe is a multiply connected 3-manifold, since finding the angles of the eigenrotations of a candidate isometry for topological lensing is a way to falsify such hypotheses.

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Notes and References

  1. Book: Ohno . Hiroshi . Yamamoto . Masanobu . Gesture recognition using character recognition techniques on two-dimensional eigenspace . Proceedings of the Seventh IEEE International Conference on Computer Vision . 1999 . 1 . 151–156 . 10.1109/ICCV.1999.791211 . 0-7695-0164-8 .