Eigenspace of the transformation

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SUMMARY

The discussion centers on the eigenvalues and eigenspaces associated with the transformation T, which reflects points across a line through the origin in R². The eigenvalues identified are -1 and 1, with the eigenspace defined as the set of all eigenvectors corresponding to these eigenvalues, including the zero vector. It is clarified that the basis of the eigenspace is composed of selected eigenvectors, and that the choice of eigenvectors affects the span of the eigenspace.

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with linear transformations in R²
  • Knowledge of matrix representation of transformations
  • Concept of eigenspaces and their bases
NEXT STEPS
  • Study the properties of eigenvalues and eigenvectors in linear algebra
  • Learn about reflections and their matrix representations in R²
  • Explore the concept of spanning sets and bases in vector spaces
  • Investigate the geometric interpretation of eigenspaces
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Students of linear algebra, mathematicians, and anyone studying transformations in vector spaces will benefit from this discussion.

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Homework Statement


Without writing A, find the eigenvalue of A and describe the eigenspace.

T is the transformation on R2 that reflects points across some line through the origin.




The Attempt at a Solution



The eigenvalue could either be -1 or 1. I'm not sure how to figure out the eigenspace of each of these eigenvalues though. And, just to be clear, is the basis of the eigenspace composed of the eigenvectors?
 
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The eigenspace of an eigenvalue is the set of all eigenvectors with that eigenvalue plus the zero vector.

fk378 said:
And, just to be clear, is the basis of the eigenspace composed of the eigenvectors?

Depends on which eigenvectors you choose. For example, say you have the matrix

\[ \left( \begin{array}{ccc} \lambda & 0\\ 0 & \lambda\end{array} \right)\]

This matrix has eigenvalue \lambda. Every vector in the plane is an eigenvector of this matrix. If you choose two eigenvectors lying on the same line, they obviously don't span the eigenspace.
 

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