Is a Matrix with Two Distinct Eigenvalues Always Diagonalizable?

  • Thread starter Thread starter hitmeoff
  • Start date Start date
  • Tags Tags
    Matrix
Join the discussion
Ask a follow-up here, or get your own question answered by working scientists, mathematicians and engineers — people, not an autocomplete.
Real named experts · corrections over time · the nuance an AI answer skips
3 replies · 3K views
hitmeoff
Messages
260
Reaction score
1

Homework Statement


Suppose the A [tex]\in[/tex] Mn X n(F) has two distinct eigenvalues, [tex]\lambda[/tex]1 and [tex]\lambda[/tex]2, and that dim(E[tex]\lambda[/tex]1) = n -1. Prove A is diagonalizable.

Homework Equations


The Attempt at a Solution



1. The charac poly clearly splits because we have eigenvalues.
2. need to show m = dim (E).

Ok, we are given that dim(E[tex]\lambda[/tex]1) = n - 1

we know multiplicity has to be 1 [tex]\leq[/tex] dim(E[tex]\lambda[/tex]1) [tex]\leq[/tex] m.

so: 1 [tex]\leq[/tex] n - 1 [tex]\leq[/tex] m.

But I am stuck now, not sure how to show that m = dim(E[tex]\lambda[/tex])
 
Last edited:
Physics news on Phys.org


Office_Shredder said:
We're told that [tex]dimE^{\lambda_1}[/tex] is [tex]n-1[/tex]. What is [tex]dimE^{\lambda_2}[/tex] then, and what can you say about [tex]E^{\lambda_1} \oplus E^{\lambda_2}[/tex]?

[tex]dimE^{\lambda_2}[/tex] = 1 then right?

[tex]E^{\lambda_1} \oplus E^{\lambda_2}[/tex] = V?
 


A linear operator T on a finite-dimensional vector space V is diagonalizable iff V is the direct sum of eigenspaces of T.