What are the conditions for commuting linear maps?

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Since P is invertible, the new matrices PAP^{-1} and PBP^{-1} are still A and B, respectively, so A and B commute in any basis. In summary, if two linear maps are described by matrices A and B, they will commute if AB=BA. This condition also holds if the matrices are square and if the maps are endomorphisms. Additionally, commutation is independent of basis, meaning that if two maps commute in one basis, they will also commute in any other basis.
  • #1
Marin
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Hi all!

I was wondering what conditions must two linear maps obey in order to commute?

If they are described by two matrices A and B, then one condition would be:

AB-BA=0

but what if we don't know the matrices, so we cannot compute AB adn BA? How is one supposed to proceed, is there a more general condition?



And another question: Suppose A and B commute. Will they still commute if I change the basis, I mean is the commutation coordinate independent?


thanks a lot for the help,

marin
 
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  • #2
I hope this answers in part your questions:

If you have two linear maps
[tex] f: V \rightarrow W \mbox{ and } g: V' \rightarrow W' [/tex]
if you want the two maps to commute then what you are saying is you want the composition of maps to satisfy
[tex] f \circ g = g \circ f \hspace{0.3cm} \Rightarrow f(g(v)) = g(f(v)). [/tex]
If this is the case then you need that
[tex] V = W = V' = W' [/tex]
for the composition to make sense. In terms of matrices this implies that they are square.

In response to your question about changing the basis as
[tex] V = W = V' = W' [/tex]
you must perform the basis transformation on each space and if this happens then commuting matrices will still commute under a change of basis.
 
  • #3
ok, so I need my linear maps to be endomorphisms and the matrices to be square :)

but this is not enough, since there are plenty of square matrices which do not commute.

So what else do I need?
 
  • #4
The only thing you will need is
[tex] f \circ g = g \circ f \hspace{0.3cm} \Rightarrow f(g(v)) = g(f(v)). [/tex]

If the linear maps are matrices, A and B, then [itex] \circ [/itex] is just the usual matrix multiplication which gives
[tex] AB = BA. [/tex]
This is exactly what you had. I don't think that there is anything else needed and I can't think of any simpler equivalent conditions.
 
  • #5
One condition is that two linear maps commute if and only if they commute on all vectors of some basis. To see that commutation is independent of basis, note that in a new basis, the transformation A becomes PAP^{-1} and B becomes PBP^{-1} for some change of basis matrix P. If A and B commute then (PAP^{-1})(PBP^{-1}) = PABP^{-1} = PBAP^{-1} = (PBP^{-1})(PAP^{-1}).
 

FAQ: What are the conditions for commuting linear maps?

What is a commuting linear map?

A commuting linear map is a type of linear map in mathematics that satisfies the property that two linear transformations can be performed in any order without changing the result. In other words, if two linear maps commute, their composition will be the same regardless of the order in which they are applied.

How do I know if two linear maps commute?

To determine if two linear maps commute, you can check if their matrices commute. If the matrices of two linear maps commute, then the linear maps also commute. You can also check if the two linear maps share a common eigenspace, as this is another property of commuting linear maps.

What is the significance of commuting linear maps?

Commuting linear maps are significant because they allow for simplified calculations and proofs in linear algebra. They also have important applications in fields such as physics, where they are used to represent physical quantities that commute with each other.

Can a linear map commute with itself?

Yes, a linear map can commute with itself. This is known as an automorphism, where a linear map maps a vector space onto itself. In this case, the composition of the linear map with itself will always result in the same transformation.

How are commuting linear maps related to diagonalizable matrices?

Commuting linear maps are related to diagonalizable matrices in that they can both be simultaneously diagonalized. This means that if two linear maps commute, their matrices can be diagonalized at the same time, resulting in a simpler and more efficient representation of the linear maps.

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