Eigenvalues/eigenvectors and linear transformation

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SUMMARY

The linear operator T defined by T(A) = transpose A on the vector space of nxn matrices has eigenvalues of +/- 1. The characteristic polynomial f(t) = det([T]b - tIn) reveals that these are the only eigenvalues, as they correspond to the roots of the polynomial. The eigenvectors associated with these eigenvalues can be described as matrices that remain unchanged or change sign upon transposition.

PREREQUISITES
  • Understanding of linear operators and their properties
  • Familiarity with eigenvalues and eigenvectors
  • Knowledge of characteristic polynomials and determinants
  • Experience with matrix transposition and its effects
NEXT STEPS
  • Study the derivation of the characteristic polynomial for linear operators
  • Explore the concept of matrix representations in different bases
  • Learn about the implications of eigenvalues in linear transformations
  • Investigate the geometric interpretation of eigenvectors in relation to linear operators
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Students of linear algebra, mathematicians studying eigenvalue problems, and educators teaching concepts of linear transformations and matrix theory.

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Homework Statement



Let T be a linear operator on the vector space of nxn matrices on the real field, defined by T(A) = transpose A.

Show that +/- 1 are the only eigenvalues of T, and describe corresponding eigenvectors.

Homework Equations



The characteristic polynomial is given by f(t) = det ( [T]b - tIn) = 0, where [T]b is the matrix representation of T on some basis b and In is the nxn identity matrix. The eigenvalues should be given by the roots to f(t).

Also, there are only eigenvalues if det ([T]b - tIn) = 0.

The Attempt at a Solution



The only thing I can really see is that for any nxn matrix A, its transpose will have the same diagonal elements as it. But since I'm talking about the matrix representation of T, not matrix A, I'm not really sure how this helps. If we were to choose a basis and write [T]b, I am also fairly sure that this wouldn't be an upper triangular matrix, so I don't see how we can figure out what the eigenvalues would be anyway. I definitely don't see why the eigenvalues should be +/- 1. Any help would be great -- I just need help in seeing how this is ever the case.
 
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