Simultaneous diagonalization while having repeated eigenvalues

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SUMMARY

Two commuting matrices can be simultaneously diagonalized if they are each diagonalizable separately, even in the presence of repeated eigenvalues. The proof involves establishing a common set of eigenvectors for both matrices, which allows for diagonalization in a shared basis. The discussion references the relationship between matrices A and B, emphasizing that if A has a single eigenvalue, the eigenvectors of A must also serve as eigenvectors for B. This conclusion is supported by the identity matrix's role in maintaining the diagonalization process.

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  • Understanding of linear algebra concepts, particularly eigenvalues and eigenvectors.
  • Familiarity with the properties of commuting matrices.
  • Knowledge of diagonalization techniques for matrices.
  • Experience with block diagonal matrices and their implications in linear transformations.
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  • Study the proof of simultaneous diagonalization of commuting matrices in detail.
  • Learn about the implications of repeated eigenvalues in matrix diagonalization.
  • Explore the concept of block diagonalization and its applications in linear algebra.
  • Investigate the role of the identity matrix in transformations and its effect on eigenvectors.
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McLaren Rulez
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Hi,

Can anyone help me prove that two commuting matrices can be simultaneously diagonalized? I can prove the case where all the eigenvalues are distinct but I'm stumped when it comes to repeated eigenvalues.

I came across this proof online but I am not sure how B'_{ab}=0 implies that B is block diagonal. Thank you.

http://www.mathematics.thetangentbundle.net/wiki/Linear_algebra/simultaneous_diagonalization_of_commuting_normal_matrices is the link for the proof.
 
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Okay I see the block diagonal bit but I still cannot see how to diagonalize those little blocks where all the diagonal elements are the same.

Basically, if v1 is an eigenvector of matrix P with eigenvalue a1 and we have PQ=QP, then PQ(v1) = QP(v1) = a1*Q(v1) which shows that Q(v1) is an eigenvector of P with eigenvalue a1. If the eigenvalues are distinct, then I can say that Q(v1) is proportional to v1 which makes v1 an eigenvector of Q as well. But this last step fails for repeated eigenvalues. So can anyone help me with this?

Thank you.
 
Erm anybody?
 
First, two matrices cannot be "simultaneously diagonalized" (i.e. A and B are simultaneously diagonalizable if and only if there exist a specific matrix P such that both P^{-1}AP and P^{-1}BP are both diagonal) unless they are each diagonalizable separately. So you must assume, even though there are repeated eigenvalues, that there exist a basis consisting entirely of eigenvectors of, say, A.
 
Ok let me try a concrete example. Say matrix A and B commute. Let's say A has only one eigenvalue, m. Let the eigenvectors be (1,0,0) (0,1,0) and (0,0,1). Now how do I know that each of these is also an eigenvector of B?

I assume that is the argument being used here i.e. the two matrices have a common set of eigenvectors. So when we change the basis to the one formed by the eigenvectors, both must be diagonalized.

Thank you
 
McLaren Rulez said:
Ok let me try a concrete example. Say matrix A and B commute. Let's say A has only one eigenvalue, m. Let the eigenvectors be (1,0,0) (0,1,0) and (0,0,1). Now how do I know that each of these is also an eigenvector of B?
Note that A=mI... (where I is the identity matrix)
 
Oh I see it now! Just diagonalize B and A is unaffected since the identity matrix doesn't change when the basis is changed. Thank you!
 

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