Notation used in matrix representation of linear transformation

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The discussion revolves around understanding the notation ##[T]_{B,B'}## in the context of linear transformations between bases in ##\mathbb{R}^2##. It clarifies that this notation indicates using basis ##B'## for the domain and basis ##B## for the codomain. To find the matrix representation, one must express the transformation of basis vectors ##v_1## and ##v_2## in terms of the basis vectors ##u_1## and ##u_2##. The resulting matrix is constructed from the coefficients of these expressions. The confusion arose from a text that incorrectly used the notation, leading to a transposed matrix representation.
Seydlitz
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Hello guys,

Let ##T: \mathbb{R^2} \to \mathbb{R^2}##. Suppose I have standard basis ##B = \{u_1, u_2\}## and another basis ##B^{\prime} = \{v_1, v_2\}## The linear transformation is described say as such ##T(v_1) = v_1 + v_2, T(v_2) = v_1##

If I want to write the matrix representing ##T## with respect to basis ##B^{\prime}## then I'll just find ##[T]_{B'}##. I can also find ##[T]_{B}## rather straightforward using similarity transformation if I know the transition matrix between those two bases.

But suddenly I encounter this notation ##[T]_{B,B'}##. I don't know exactly what this notation represents. Do you guys know what this notation mean? What other matrix should I provide in this case? Normally I use that comma subscript to denote transition matrix between bases, but never for linear transformation matrix.

Thank You
 
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It means that you take the basis ##B^\prime## on the domain and ##B## on the codomain (both are ##\mathbb{R}^2##). Or the other way around, depending on who is using the notation.

So the idea is to see what happens to ##v_i##. So look at ##T(v_1)## and ##T(v_2)## and express these in the ##\{u_1,u_2\}## basis. So you write ##T(v_1) = \alpha u_1 + \beta u_2## and ##T(v_2) = \gamma u_1 + \delta u_2##. The the matrix you seek is

\left(\begin{array}{cc}<br /> \alpha &amp; \gamma\\<br /> \beta &amp; \delta<br /> \end{array}\right)
 
micromass said:
It means that you take the basis ##B^\prime## on the domain and ##B## on the codomain (both are ##\mathbb{R}^2##). Or the other way around, depending on who is using the notation.

So the idea is to see what happens to ##v_i##. So look at ##T(v_1)## and ##T(v_2)## and express these in the ##\{u_1,u_2\}## basis. So you write ##T(v_1) = \alpha u_1 + \beta u_2## and ##T(v_2) = \gamma u_1 + \delta u_2##. The the matrix you seek is

\left(\begin{array}{cc}<br /> \alpha &amp; \gamma\\<br /> \beta &amp; \delta<br /> \end{array}\right)

Thanks micromass for the help. It makes sense. I managed to get that matrix by post-multiplying ##[T]_b## with the transition matrix ##P_{B' \to B}##. I was just really confused because one of the text that I'm reading apparently got the matrix wrong. (Not considering the fact that they use comma and arrow notation interchangeably)
 
Seydlitz said:
Thanks micromass for the help. It makes sense. I managed to get that matrix by post-multiplying ##[T]_b## with the transition matrix ##P_{B' \to B}##.

That works too.

I was just really confused because one of the text that I'm reading apparently got the matrix wrong. (Not considering the fact that they use comma and arrow notation interchangeably)

What did the text say?
 
micromass said:
That works too.

What did the text say?

It's an example problem. The desired matrix is just the same with my own work, but somehow transposed.
 
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