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Encyclopedia > Eigenplane


In mathematics, an eigenplane is a two-dimensional invariant subspace in a given vector space. 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:

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.


See also

External links

  • possible relevance of eigenplanes (http://arxiv.org/abs/astro-ph/0409694) in cosmology
  • GNU GPL software for calculating eigenplanes (http://cosmo.torun.pl/GPLdownload/eigen/)

  Results from FactBites:
 
SULI Log 2003 (1736 words)
BPM data along a given axis (x or y) may be represented as an n x m matrix where n is the number of consecutive-turn measurements and m is the number of BPMs.
By exciting the beam’s two eigenplanes and extracting sine-like and cosine-like orbits for each excitation, one collects four linearly-independent orbits which completely determine the linear optics of the system.
For example, the data from the excitation of the beam’s first eigenplane results in two data matrices, one representing the x position of the beam at each x-sensitive BPM and the other representing the corresponding y position at each y-sensitive BPM.
  More results at FactBites »


 

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