The vector space of matrices that commute with A

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The discussion focuses on determining the dimension of the vector space V of matrices that commute with a given n x n matrix A. Participants explore the challenge of constructing a basis for V and derive a system of linear equations from the commutation condition AB = BA. It is noted that the dimension of V can vary depending on A, with specific cases like A being the zero matrix leading to a dimension of n^2. Additionally, it is mentioned that matrices B will commute with A if they share the same eigenvectors, and that both matrices can be upper triangular in a suitable basis. The conversation highlights the complexity of the problem while suggesting that additional constraints on A and B could yield further insights.
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Suppose ##A## is a ## n \times n## matrix.

Define the set ## V = \{ B | AB = BA, B \in M_{n \times n}( \mathbb{F}) \} ##
I know that ##V## is a subspace of ##M_{n \times n}( \mathbb{F}) ## but how might I go about finding the dimension of ##V##? Is this even possible? It seems like an interesting problem, but constructing a basis for ##V## seems to me challenging enough. Any tips for me?

Thanks!

P.S. Not a homework problem, I made it myself and not sure if it has a simple answer.

BiP
 
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Let's demonstrate this with 2X2 matrices...

Let A = \left( \begin{array}{cc}<br /> 1 &amp; 2 \\<br /> 3 &amp; 4 \\ \end{array} \right) . Multiplying this from either side with the general 2X2 matrix \left( \begin{array}{cc}<br /> a &amp; b \\<br /> c &amp; d \\ \end{array} \right) and requiring that the matrix elements of these products are equal, we get a system of linear equations:

a + 2c - a - 3b = 0
b + 2d - 2a - 4b = 0
3a + 4c - c - 3d = 0
3b + 4d - 2c - 4d = 0

Now we get the dimensionality of the space of matrices commuting with A as the dimensionality of the kernel of the coefficient matrix of this linear system.
 
The answer is going to depend upon A. For example, if A= 0, AB= BA= 0 for all B so the space of all matrices that commute with A has dimension n^2.
 
In general you would have n^2 equations
\sum_{m=1}^n A_{im} B_{mj} - A_{mj}B_{im} = 0
The dimension of V will be a most n^2 and at least 2 (providing n &gt; 1), since all n\times n matrices commute with scalar multiples of the identity, as well as scalar multiples of themselves. Perhaps it is interesting to consider additional constraints on \mathbf{A} and \mathbf{B}. For example, what if \mathbf{A} and \mathbf{B} are Hermitian?
 
I'm not a very mathy person, so I'll just drop my 2 cents. If B has the same eigenvectors as A, then it commutes with A.
 
HasuChObe said:
I'm not a very mathy person, so I'll just drop my 2 cents. If B has the same eigenvectors as A, then it commutes with A.

This almost cuts out the full heart of the matter. The matrices will commute if and only if there is a basis where they are both upper triangular.

There's even a wikipedia article about it:

http://en.wikipedia.org/wiki/Commuting_matrices
 
I am studying the mathematical formalism behind non-commutative geometry approach to quantum gravity. I was reading about Hopf algebras and their Drinfeld twist with a specific example of the Moyal-Weyl twist defined as F=exp(-iλ/2θ^(μν)∂_μ⊗∂_ν) where λ is a constant parametar and θ antisymmetric constant tensor. {∂_μ} is the basis of the tangent vector space over the underlying spacetime Now, from my understanding the enveloping algebra which appears in the definition of the Hopf algebra...

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