Transformation Matrix T in Terms of β1, β2 with Row Reduction Explained

In summary, the solution has calculated the matrix of T relative to the basis B and the standard basis, but in order to get the matrix with respect to B and B', the rows of the matrix need to be swapped. Row reduction may be necessary if B' is not a straightforward transformation of the standard basis.
  • #1
jolly_math
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Homework Statement
Let T be the linear transformation from R3 into R2 defined by T(x1, x2, x3) = (x1 + x2, 2x3 - x1).
B={α1,α2,α3} and B′ ={β1,β2}, where α1 = (1,0,−1), α2 = (1,1,1), α3 = (1,0,0), β1 = (0,1), β2 = (1,0). What is the matrix of T relative to the pair B, B′?
Relevant Equations
transformation
T(α1), T(α2), T(α3) written in terms of β1, β2:
Tα1 =(1,−3)
Tα2 =(2,1)
Tα3 =(1,0).
Then there is row reduction:
1667976594734.png

Therefore, the matrix of T relative to the pair B, B' is
1667976607260.png

I don't understand why the row reduction takes place? Also, how do these steps relate to ## B = S^{-1}AS ##? Thank you.
 
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  • #2
The solution has calculated the matrix of [itex]T[/itex] relative to the basis [itex]B[/itex] and the standard basis of [itex]\mathbb{R}^2[/itex], [itex]\{ e_1 = (1,0), e_2 = (0,1) \}[/itex]. But [itex]\beta_1 = e_2[/itex] and [itex]\beta_2 = e_1[/itex] so the rows of that matrix need to be swapped to give the matrix with respect to [itex]B[/itex] and [itex]B'[/itex], But you really don't need row reduction to do that; you can just swap the rows.

If [itex]B'[/itex] depended on the standard basis in a less straightforward manner, then the row reduction may have been necessary to get to the required matrix.
 
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FAQ: Transformation Matrix T in Terms of β1, β2 with Row Reduction Explained

What is a transformation matrix T in terms of β1, β2?

A transformation matrix T in terms of β1, β2 is a mathematical representation of how a set of coordinates is transformed from one coordinate system (defined by β1 and β2) to another coordinate system. It is used in linear algebra and geometry to describe transformations such as rotation, scaling, and translation.

How is the transformation matrix T related to row reduction?

The transformation matrix T can be obtained through a process called row reduction, which involves manipulating the rows of a matrix to simplify it and determine its properties. The resulting matrix will be in the form of T, with the coefficients representing the transformation in terms of β1, β2.

Why is it important to express the transformation matrix T in terms of β1, β2?

Expressing the transformation matrix T in terms of β1, β2 allows for a more intuitive understanding of the transformation. It also makes it easier to apply the transformation to different sets of coordinates, as the coefficients can be easily adjusted based on the chosen coordinate system.

What is the significance of row reduction in understanding transformations?

Row reduction is a powerful tool in linear algebra, as it allows us to determine the properties of a matrix and its relationship to other matrices. In the context of transformations, row reduction helps us to understand how a set of coordinates is transformed from one coordinate system to another, and how the transformation can be represented by a matrix.

Are there any limitations to using a transformation matrix T in terms of β1, β2?

One limitation to using a transformation matrix T in terms of β1, β2 is that it only applies to linear transformations. Non-linear transformations, such as those involving curves or surfaces, cannot be represented by a transformation matrix. Additionally, the transformation matrix T may not be unique, as there can be different matrices that represent the same transformation in terms of β1, β2.

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