Dimension of Eigenspace of A and A^T

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SUMMARY

The discussion focuses on the relationship between the dimensions of the eigenspaces of a matrix A and its transpose A^T, emphasizing that the rank of A and A^T are equal. The dimension of the eigenspace corresponding to an eigenvalue λ is defined as the nullity of the matrix (λI - A). The rank-nullity theorem is crucial for proving this relationship, as it connects the concepts of rank and nullity in linear algebra.

PREREQUISITES
  • Understanding of eigenvalues and eigenspaces
  • Familiarity with the rank-nullity theorem
  • Knowledge of matrix operations, specifically transpose
  • Basic linear algebra concepts
NEXT STEPS
  • Study the rank-nullity theorem in detail
  • Explore the properties of eigenvalues and eigenspaces
  • Learn about matrix transposition and its implications
  • Investigate proofs related to the equality of ranks of A and A^T
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Students and professionals in mathematics, particularly those studying linear algebra, as well as educators looking to deepen their understanding of matrix theory and eigenvalue problems.

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Homework Statement
Prove that the dimension of the eigenspace of A and dimension of eigenspace of A^T are equal
Relevant Equations
dim(E_A)=dim(E_(At))
I know that the rank of A and A^T are equal, and that the statement follows from there, but I have no idea how to prove it.
 
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The eigenspace of ##A## corresponding to an eigenvalue ##\lambda## is the nullspace of ##\lambda I - A##. So, the dimension of that eigenspace is the nullity of ##\lambda I - A##. Are you familiar with the rank-nullity theorem? (If not, then look it up: Your book may call it differently.) You can apply that theorem here.
 

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