Prove two commutative Hermitian matrices have the same eigenvectors

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Homework Help Overview

The discussion revolves around proving that two commutative Hermitian matrices share the same set of eigenvectors, specifically under the condition that their product commutes (i.e., AB - BA = 0). The context is rooted in linear algebra and quantum mechanics, focusing on properties of Hermitian matrices.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the implications of commutativity and the properties of Hermitian matrices. Some discuss the diagonalizability of the product of the matrices and the relationship between eigenvectors and eigenvalues. Others question the assumptions made regarding eigenvalues and seek clarification on the proof structure.

Discussion Status

The discussion is ongoing, with participants providing hints and prompting each other to articulate their understanding of eigenvectors and theorems related to Hermitian matrices. There is an acknowledgment of the need for attempts to be made before seeking further assistance.

Contextual Notes

Some participants note that the problem may not strictly adhere to textbook-style constraints, as it relates to a well-known theorem in quantum mechanics. There is also mention of potential complications arising from non-unique eigenvalues, which could affect the proof's structure.

xuphys
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Hi,

Does anyone know how to prove that two commutative Hermitian matrices can always have the same set of eigenvectors?

i.e.

AB - BA=0

A and B are both Hermitian matrices, how to prove A and B have the same set of eigenvectors?

Thanks!
 
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xuphys said:
Hi,

Does anyone know how to prove that two commutative Hermitian matrices can always have the same set of eigenvectors?

i.e.

AB - BA=0

A and B are both Hermitian matrices, how to prove A and B have the same set of eigenvectors?

Thanks!
Since this is a textbook-style problem, the forum rules tell us to treat it as homework (even if it's not). So we can only give you hints, and you will have to show us what you've got so far. At the very least, you're going to have to show us that you know what the statement "v is an eigenvector of A" means.
 
Fredrik said:
Since this is a textbook-style problem, the forum rules tell us to treat it as homework (even if it's not). So we can only give you hints, and you will have to show us what you've got so far. At the very least, you're going to have to show us that you know what the statement "v is an eigenvector of A" means.

Thanks for your reply.

What I would say is that this is a common mathematical theorem which is one of the mathematical basis in quantum mechanics, but not a textbook style problem. I ask here because my textbook (which is not written in English) only gives a simplified version of proof (assuming there is no duplicated eigenvalue). I am curious about a relatively more robust way to prove it.
 


Textbook problems often ask the reader to prove a theorem that wasn't proved in the text. So this certainly could be a textbook problem or a small part of a homework assignment.
 


I have moved this to homework. xuphys, please make an attempt when asking a question. What do you think of the problem? Is there something you can do?
 


micromass said:
I have moved this to homework. xuphys, please make an attempt when asking a question. What do you think of the problem? Is there something you can do?

OK. What I thought is, since A and B are commutative, and they are also hermitians, so AB is also a hermitian (easy to prove).

Then AB is diagonalizable:

Code:
AB=UDU[SUP]-1[/SUP]

i.e.

Code:
D=U[SUP]-1[/SUP]ABU=(U[SUP]-1[/SUP]AU)(U[SUP]-1[/SUP]BU)

Now I am unable to prove that both U-1AU and U-1BU are diagonal... and I am not sure whether I am on the right track. Could you help me with this?

Thanks!
 


Hermitian matrices are diagonalizable, so we have n eigenpairs (a_i, v_i) for A and eigenpairs (b_i, u_i) for B (where v_i and u_i may be chosen linearly independent).
It follows that A*v_i = a_i*v_i. This implies B*A*v_i = a_i*B*v_i. But this equals A*B*v_i, so B*v_i is an eigenvector to A with eigenvalue a_i. So B*v_i = k_i*v_i if eigenvalues are unique.
The argument is symmetric, so it follows that A and B have the same eigenvectors. The argument is more difficult if eigenvalues aren't unique, but you get invariant subspaces and block matrices, for which you can choose diagonal bases, roughly.
 
Last edited:

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