Linear transformation. TEST today help.

In summary: I got.If you are given a transformation matrix [T], you can find the eigenvalues and eigenvectors by solving the equation \det[T] = eigenvalues \lambda_1 + eigenvalues \lambda_2The eigenvalues are the solutions to this equation in which the coefficients are the corresponding eigenvectors.
  • #1
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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  • #2
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.
 
  • #3
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?
 
  • #4
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 [itex][T]_{\beta\beta}[/itex], 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.
 
  • #5
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.
 
  • #6
Nevermind, I figured out my mistake. It might help if I did actually get the eigenvectors, instead of the matrix A-I(lambda)
 

What is a linear transformation?

A linear transformation is a mathematical operation that maps one vector space to another in a linear manner. This means that the transformation preserves the properties of vector addition and scalar multiplication.

What are the key properties of a linear transformation?

There are three key properties that define a linear transformation:

  1. Additivity: T(u + v) = T(u) + T(v)
  2. Scalar multiplication: T(cu) = cT(u)
  3. Preservation of zero vector: T(0) = 0

How can I visualize a linear transformation?

A linear transformation can be visualized using a transformation matrix, which maps the original vector to the transformed vector. This can also be represented graphically as a transformation of points in a coordinate system.

What is the importance of linear transformations in science?

Linear transformations are a fundamental concept in mathematics and have numerous applications in science, including physics, engineering, and computer science. They are used to model and solve problems involving relationships between variables and to analyze data.

How can I prepare for a linear transformation test?

To prepare for a linear transformation test, it is important to review the key properties and concepts, practice with transformation matrices and graphical representations, and work through sample problems. It may also be helpful to seek assistance from a tutor or study group.

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