Determinant of matrix of linear transformation

In summary, the problem involves finding the determinant of a linear transformation T, which maps polynomials of degree 2 to themselves. T is represented by a matrix A, which is obtained by considering the basis of P2 and the transformation of the basis vectors. In the first problem, there was a mistake in the calculation of A, resulting in an incorrect determinant. In the second problem, the vectors V1 and V2 represent the basis of R2, and by considering their transformation under T, A can be calculated and the determinant can be found.
  • #1
freetonik
10
0

Homework Statement


Linear transformation T: P2->P2
T(f) = -5f + 8f'
Need to find detA (A is a matrix of T)

Homework Equations



T(f) = Af

The Attempt at a Solution


The basis of P2 is B={1, x, x2}. Some polynomial f with respect to B looks like this in general:

(a, b, c)T

right? So, T(f) = -(a, b, c)T + 8 (0, b, 2c)T = (-a, 7b, c)T.

So, A*(a, b, c)T = (-a, 7b, c)T, therefore A =

1 0 0
0 7 0
0 0 1

And detA = -7. This is how I was thinking about it, but the answer is wrong and I am confused :(
 
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  • #2
freetonik said:
So, T(f) = -(a, b, c)T + 8 (0, b, 2c)T

What happened to the factor of 5 from T(f)=-5f+8f'?
 
  • #3
Oh!
Thanks!
It always happens to me.

So, fixing that mistake, T(f)=

-5a
3b
11c

And A becomes:

-5 0 0
0 3 0
0 0 11

and detA = -165 and it is still wrong :(
 
  • #4
Well, if [itex]f(x)=a+bx+cx^2[/itex], then [itex]f'(x)=b+2cx[/itex]

So, if you are representing your basis functions as

[tex]x^0\to\begin{pmatrix}1 \\ 0 \\ 0 \end{pmatrix} \;\;\;\;\text{and}\;\;\;\; x^1\to\begin{pmatrix}0 \\ 1 \\ 0 \end{pmatrix} \;\;\;\text{and}\;\;\;\; x^2\to\begin{pmatrix}0 \\ 0 \\ 1 \end{pmatrix}[/tex]

Then you have [tex]f(x)\to\begin{pmatrix}a \\ b \\ c \end{pmatrix}[/tex] and [tex]f'(x)\to\begin{pmatrix}b \\ 2c \\ 0 \end{pmatrix}[/tex]
 
  • #5
Okay, thank you again!
Now I have:

-5(a, b, c)T + 8 (b, 2c, 0)T =

-5a+8b
-5a+16c
-5a

And:

A(a, b, c)T = (-5a+8b, -5a+16c, -5a)T, so A=

-5 8 0
-5 0 16
-5 0 0

detA = -640 and it is still wrong :(((
 
  • #6
freetonik said:
Okay, thank you again!
Now I have:

-5(a, b, c)T + 8 (b, 2c, 0)T =

-5a+8b
-5a+16c
-5a

Errm...

[tex]-5\begin{pmatrix}a \\ b \\ c \end{pmatrix}+8\begin{pmatrix}b \\ 2c \\ 0 \end{pmatrix}=\begin{pmatrix}-5a+8b \\ -5b+16c \\ -5c \end{pmatrix}[/tex]
 
  • #7
Oh, I'm dumb! Thank you very much!
 
  • #8
There is a similar problem I cannot figure out..

T(f(t)) = f(2t) - 3f(t)

Again need to find detA.

In this case I don't even know how to start...
 
  • #9
Is T again a mapping from P2 to P2?

If so, do it in the same way, just with [itex]t[/itex] as the variable instead of [itex]x[/itex]... if [itex]f(t)=a+bt+ct^2[/itex], what is [itex]f(2t)[/itex]?
 
  • #10
f(2t) = a + b2t = c2t2?
 
  • #11
freetonik said:
f(2t) = a + b2t = c2t2?
No. If f(t) = a + bt + ct2, then f(2t) = a + b*2t + c(2t)2. This can be simplified.
 
  • #12
Thank you very much!
 
  • #13
Sorry, I've faced one more problem...
There is T: R2->R2, s.t. T(V1)=8V2, and T(V2)=-4V1.

Need to find detA.

This is how I started thinking:
AV1=8V2 => A=8V2 / V1
AV2=-4V1 => A=-4V1 / V2

Don't know how to think further...
 
  • #14
freetonik said:
Sorry, I've faced one more problem...
There is T: R2->R2, s.t. T(V1)=8V2, and T(V2)=-4V1.

Okay, and what are [itex]V_1[/itex] and [itex]V_2[/itex]?
 
  • #15
They are just some vectors in R2, they're not given.
 
  • #16
freetonik said:
They are just some vectors in R2, they're not given.

I don't believe that. If this was true for all [itex]V_1[/itex] and [itex]V_2[/itex] in [itex]\mathbf{R}^2[/itex], then the matrix [itex]A[/itex] would have to be full of zeroes. You'd need only look at some case where [itex]V_2=V_1[/itex] to prove that to yourself.

I suspect that they are supposed to represent the basis vectors of [itex]\mathbf{R}^2[/itex]. In which case, you might as well look at two orthogonal basis vectors

[tex]V_1\to\begin{pmatrix}1 \\ 0 \end{pmatrix} \;\;\;\;\text{and}\;\;\;\; V_2\to\begin{pmatrix}0 \\ 1 \end{pmatrix}[/tex]
 
  • #18
freetonik said:
This is how the problem stated:
http://imgur.com/bU4b7.png

Okay, so they are some specific vectors, you just aren't told exactly what they are.

In that case, just say

[tex]V_1\to\begin{pmatrix}a_1 \\ b_1\end{pmatrix} \;\;\;\;\text{and}\;\;\;\; V_2\to\begin{pmatrix}a_2 \\ b_2\end{pmatrix}[/tex]

and go from there.
 

FAQ: Determinant of matrix of linear transformation

What is a determinant of a matrix?

The determinant of a matrix is a numerical value that can be calculated from the elements of the matrix. It is commonly used to determine whether a matrix is invertible or singular, and it also has applications in solving systems of linear equations and computing areas and volumes in geometry.

How is the determinant of a matrix calculated?

The determinant of a matrix is calculated by using the expansion method, where the matrix is expanded along a row or column and the determinants of smaller matrices are calculated until a scalar value is obtained. Another method is the cofactor method, which involves using the cofactor matrix and multiplying it with the original matrix to obtain the determinant.

What is the significance of the determinant of a matrix in linear transformations?

The determinant of a matrix in linear transformations represents the scaling factor of the transformation. It determines whether the transformation will stretch, shrink, or flip the original shape. Additionally, the determinant also determines whether the transformation preserves the orientation of the shape.

Can the determinant of a matrix be negative?

Yes, the determinant of a matrix can be negative. A negative determinant indicates that the linear transformation has flipped the orientation of the original shape. This is often seen in transformations involving reflections or rotations.

How does the determinant of a matrix affect the solution of a system of linear equations?

The determinant of a matrix is used to determine whether a system of linear equations has a unique solution, no solution, or infinitely many solutions. If the determinant is non-zero, then the system has a unique solution. If the determinant is zero, then the system either has no solution or infinitely many solutions, depending on other factors such as consistency and linear independence.

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