Linear transformation. TEST today help.

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Homework Help Overview

The discussion revolves around linear transformations, specifically focusing on the transformation defined by T(A) = (A + AT)/2 for matrices in M2x2. Participants are exploring how to express transformations in matrix form and the implications of using different bases.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss how to handle matrix expressions involving fractions, with one suggesting a clearer representation. There is also a question about converting coefficient vectors into a transformation matrix, leading to a clarification about the nature of the vectors versus matrices. Another participant raises a question about finding a basis of eigenvectors and constructing a transformation matrix from them.

Discussion Status

The discussion is active, with participants providing clarifications and questioning terminology. Some guidance has been offered regarding the representation of matrices and the definition of linear transformations. There is an acknowledgment of confusion around the definitions and the need for clarity in the transformation being discussed.

Contextual Notes

Participants are navigating the complexities of linear transformations, matrix representations, and the implications of different bases. There are indications of misunderstandings regarding terminology and the definitions of transformations, which are being addressed in the discussion.

trap101
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Not too big of a question, it's more so just handling a certain presentation.

T: M2x2-->M2x2 defined by: T(A) = (A + AT)/2. So my question is, how do I handle the fraction considering it will be a matrix?
 
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trap101 said:
Not too big of a question, it's more so just handling a certain presentation.

T: M2x2-->M2x2 defined by: T(A) = (A + AT)/2. So my question is, how do I handle the fraction considering it will be a matrix?

The '2' isn't a matrix. It's a scalar. Write it as (1/2)*(A+A^(T)). Nothing complicated here.
 
Thanks. I have another quick question. I'm finding a transformation matrix [T]ββ .

The form is 2x2...I've gotten through everything including obtaining the values for the coeffcient vectors. I have two vectors:

\begin{bmatrix} 1 & 0 \\ 0 & 2 \end{bmatrix} \begin{bmatrix} 1 & 0\\ 0 & 2 \ end{bmatrix}

how do I convert these into the [T]ββ...since I know that has to be 2x2?
 
You seem to be very confused- or a little loose with your terminology. What you show is not "two vectors", it is a matrix. And before you can write a linear transformation, you will have to define the linear transformation. Then, a linear transformation, from vector space U to vector space V, can be written as a matrix given specific bases for both U and V. Of course, if U and V are both R2, it would be standard to take <1, 0> and <0, 1> but since you talk about [T]_{\beta\beta}, I take it that you are given some basis and I suspect that is what <1, 0> and <0, 2> are- you are asked to find the matrix form of linear transformation T in that basis. But that still leaves the most crucial question- what is T? How is T defined?

Or are you using the standard basis, <1, 0> and <0, 1>, and have determined that T(<1, 0>)= 1<1, 0>+ 0<0, 1> and T(<0, 1>)= 0<1, 0>+ 2<0, 1>? In that case, the matrix you give is the matrix form you are looking for.
 
Let T: C2 ! C2 be the linear transformation whose matrix with respect to the stan-
dard basis of C2 is 

(2x2) Matrix with complex numbers

Find a basis for C2 consisting of eigenvectors of T and [T]ββ .

That's the question.


So I've obtained eigenvectors and applied the eigenvectors (which resulted in 2x2 matrices) to the transformation matrix I was given. This produced a new 2x2 matrix. Now I wanted to write out this new 2x2 matrix as a linear combination of my standard basis and take those co-efficients to construct a new transformation matrix.
 
Nevermind, I figured out my mistake. It might help if I did actually get the eigenvectors, instead of the matrix A-I(lambda)
 

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