Transforming Vectors from Basis B to C: A Confusing Matter

In summary: No trouble.In summary, we discussed the representation of linear transformations and eigenvectors in different bases and came to the conclusion that the representation of a vector in basis ##C## is given by ##v^C_i=Sv^B_i##. This is because the transformation matrix ##S## takes vectors from basis ##B## to basis ##C##, and the inverse transformation matrix takes vectors from basis ##C## to basis ##B##.
  • #1
devd
47
1
Suppose a change of basis from basis ##B## to basis ##C## is represented by the matrix ##S##.
That is, ##S## is the transformation matrix from ##B## to ##C##.

Now if ##t## is a given linear transformation, ##t:~V\rightarrow V##, with eigenvectors ##\epsilon_i##, say, and ##T## is the representation of ##t## in ##B##, then, the representation of t in ##C## is ##STS^{-1}##.

Now, if the representation of ##\epsilon_i## in basis ##B## be ##v^B_i##, then the representation of ##\epsilon_i## in basis ##C##, ##v^C_i=Sv^B_i##.

But shouldn't the vectors themselves transform in an opposite sense to the transformation of the basis, that is, shouldn't it be that ##v^C_i=S^{-1}v^B_i## ? I'm getting really confused. Please, can someone clarify?
 
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  • #2
devd said:
Suppose a change of basis from basis ##B## to basis ##C## is represented by the matrix ##S##.
That is, ##S## is the transformation matrix from ##B## to ##C##.

Now if ##t## is a given linear transformation, ##t:~V\rightarrow V##, with eigenvectors ##\epsilon_i##, say, and ##T## is the representation of ##t## in ##B##, then, the representation of t in ##C## is ##STS^{-1}##.

Now, if the representation of ##\epsilon_i## in basis ##B## be ##v^B_i##, then the representation of ##\epsilon_i## in basis ##C##, ##v^C_i=Sv^B_i##.
I agree with what you have here.
But shouldn't the vectors themselves transform in an opposite sense to the transformation of the basis, that is, shouldn't it be that ##v^C_i=S^{-1}v^B_i## ? I'm getting really confused. Please, can someone clarify?
Remember that S:B-->C. So what would it mean to take the inverse on something in B? As in:
##v^C_i=S^{-1}v^B_i##.
 
  • #3
Let's write ##B=(e_1,\dots,e_n)##, ##C=(f_1,\dots,f_n)##. Let ##T## be the linear operator such that ##Te_i=f_i## for all ##i##. I won't be writing any summation sigmas. There's always a sum over the index or indices that appear exactly twice. We have
\begin{align}
([x]_B)_j e_j =x=([x]_C)_i f_i =([x]_C)_i Te_i = ([x]_C)_i (Te_i)_j e_j =([x]_C)_i ([T]_B)_{ji} e_j=([T]_B[x]_C)_j e_j.
\end{align} This implies that ##[x]_B=[T]_B[x]_C##. If we define ##S=([T]_B)^{-1}##, we can write this as ##[x]_C=S[x]_B##, or equivalently as
$$([x]_C)_i =S_{ij} ([x]_B)_j.$$ We also have
$$f_i=Te_i =(Te_i)_j e_j =([T]_B)_{ji} e_j =(S^{-1})_{ji} e_j.$$
 
  • #4
You know it's all about the base, about the base.
 

FAQ: Transforming Vectors from Basis B to C: A Confusing Matter

What is the purpose of transforming vectors from basis B to C?

Transforming vectors from basis B to C allows us to express a vector in different coordinate systems or bases. This is useful in many areas of mathematics and science, such as linear algebra, physics, and computer graphics.

How do you perform a transformation of vectors from basis B to C?

To transform a vector from basis B to C, we use a transformation matrix that maps the coordinates of the vector from basis B to the coordinates in basis C. This matrix is typically represented by a square matrix with the basis vectors of B as its columns and the basis vectors of C as its rows.

What is the difference between a basis and a coordinate system?

A basis is a set of linearly independent vectors that span a vector space, while a coordinate system is a way of representing vectors using coordinates. A basis is used to define a coordinate system, but a coordinate system can be defined without the use of a basis.

Can you give an example of transforming vectors from basis B to C?

Imagine we have a vector (2, 3) in the standard basis, which consists of the unit vectors (1, 0) and (0, 1). If we want to transform this vector to the basis (1, 1) and (2, 1), we would use a transformation matrix with the columns (1, 1) and (2, 1). Multiplying this matrix by our original vector gives us the coordinates (5, 1) in the new basis.

Why is transforming vectors from basis B to C sometimes confusing?

Transforming vectors from basis B to C can be confusing because it involves multiple concepts such as linear transformations, matrices, and coordinate systems. It also requires a good understanding of linear algebra and the properties of vector spaces. Additionally, it can be challenging to visualize the transformation in higher dimensions.

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