What does this notation mean? Linear map A = [A^\mu \nu]_\mu \nu

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The notation A = [A^\mu \nu]_\mu \nu represents a linear map A from a vector space V to itself, expressed in a specific basis. The vector space is decomposed as \mathcal V = \bigoplus_\mu \mathbb C^{m_\mu} \otimes \mathcal V^\mu, allowing for a structured representation of A. Each component A^{\mu \nu} is a linear map from \mathbb C^{m_\nu} \otimes \mathcal V^\nu to \mathbb C^{m_\mu} \otimes \mathcal V^\mu, indicating a systematic way to express the matrix of A. This decomposition is applicable to any linear map without relying on special properties of A. The discussion clarifies that the notation simply reflects a matrix representation in a chosen basis, where each part of the domain is associated with a fixed codomain.
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It's used in a certain proof that I'm reading. A is a linear map from a vectorspace V onto itself.

They say they can rewrite the vector space as \mathcal V = \bigoplus_\mu \mathbb C^{m_\mu} \otimes \mathcal V^\mu and I understand this, but they then claim one can (always, as any linear map) rewrite A as A = [A^{\mu \nu}]_{\mu \nu} "where A^{\mu \nu} is a linear map of \mathbb C^{m_\nu} \otimes \mathcal V^\nu to \mathbb C^{m_\mu} \otimes \mathcal V^\mu."

I don't understand the nature of this decomposition/rewriting. Note that this rewriting has to be possible for any A, it doesn't use any special properties of A (that comes later in the proof).
 
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This seems to be an extremely obtuse way of writing the matrix of A in a given basis (indexed by \mu in the domain and by \nu in the range).
 
Writing a matrix in a given basis is possible, but they also fix the codomain for each part of the domain (it seems); I don't see why that is possible.
 
Do they explicitly state what they mean by \mathcal V^\mu?
 
Simply different vector spaces labelled by mu, it's as general as that.
 
Okay, so they are just writing A in terms of a given basis.

For simplicity, let's suppose V = V^1 \oplus V^2. Then, with respect to this decomposition, we can write
A = \begin{pmatrix} A^{11} & A^{12} \\ A^{21} & A^{22}\end{pmatrix}.
Here A^{11} will take V^1 to V^1, and A^{12} will take V^2 to V^1, etc.
 
Oh that makes sense, thank you :)
 
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