Simultaneous diagonalization while having repeated eigenvalues

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Two commuting matrices can be simultaneously diagonalized if they are each diagonalizable separately, even in the presence of repeated eigenvalues. The discussion highlights the challenge of proving this when eigenvalues are not distinct, emphasizing the need for a common set of eigenvectors. An example illustrates that if matrix A has a single eigenvalue, its eigenvectors can also serve as eigenvectors for matrix B, provided they commute. The conversation concludes with the realization that diagonalizing matrix B does not affect matrix A when using the identity matrix as a basis change. Understanding this relationship is crucial for proving simultaneous diagonalization under these conditions.
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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