Matrix of Linear Transformation T with P2: Find, Ker, Im & Inverse

In summary, we have found that the matrix for the transformation T with respect to the standard basis B={1,x,x^2} for P2 is [-1 1 0] [0 0 2] [0 0 1]. We also found that the basis for ker(T) is {1+x} and the basis for Im(T) is {-1, 2x+x^2}, with dimensions of 1 and 2 respectively. Finally, we determined that the transformation does not have an inverse.
  • #1
Kaspelek
26
0
Where T(p(x)) = (x+1)p'(x) - p(x) and p'(x) is derivative of p(x).

a) Find the matrix of T with respect to the standard basis B={1,x,x^2} for P2.

T(1) = (x+1) * 0 - 1 = -1 = -1 + 0x + 0x^2
T(x) = (x+1) * 1 - x = 1 = 1 + 0x + 0x^2
T(x^2) = (x+1) * 2x - x^2 = 2x + x^2 = 0 + 2x + x^2

So, the matrix for T with respect to B equals
[-1 1 0]
[0 0 2]
[0 0 1].b) Find a basis for kerT and hence write down dim(kerT).

c) Find a basis for ImT and hence write down dim(ImT).

d) Does the transformation have an inverse?I've done part a, so any guidance on the rest would be greatly appreciated.
 
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  • #2
Kaspelek said:
Where T(p(x)) = (x+1)p'(x) - p(x) and p'(x) is derivative of p(x).

a) Find the matrix of T with respect to the standard basis B={1,x,x^2} for P2.

T(1) = (x+1) * 0 - 1 = -1 = -1 + 0x + 0x^2
T(x) = (x+1) * 1 - x = 1 = 1 + 0x + 0x^2
T(x^2) = (x+1) * 2x - x^2 = 2x + x^2 = 0 + 2x + x^2

So, the matrix for T with respect to B equals
[-1 1 0]
[0 0 2]
[0 0 1].b) Find a basis for kerT and hence write down dim(kerT).

As you've correctly stated, we may express the transformation in the form
\(\displaystyle
A_T=\left[ \begin{array}{ccc}
-1 & 1 & 0 \\
0 & 0 & 2 \\
0 & 0 & 1 \end{array} \right]
\)

Now as for \(\displaystyle ker(T)\), we proceed to find the kernel of this transformation in the same way as we would for any other transformation. That is, we would like to solve \(\displaystyle A_T x=\left[ \begin{array}{ccc}0 & 0 & 0\end{array} \right]^T\), which requires we put the augmented matrix
\(\displaystyle \left( A_T|0 \right) =
\left[ \begin{array}{ccc}
-1 & 1 & 0 & | & 0 \\
0 & 0 & 2 & | & 0 \\
0 & 0 & 1 & | & 0 \end{array} \right]
\)
in its reduced row echelon form (of course, this problem could be solved with a little intuition instead of row reduction, but the upshot of this method is that it works where your intuition might fail). You should end up with
\(\displaystyle \left[ \begin{array}{ccc}
1 & -1 & 0 & | & 0 \\
0 & 0 & 1 & | & 0 \\
0 & 0 & 0 & | & 0 \end{array} \right]
\)
Which tells you that the kernel of the transformation is the set of all polynomials \(\displaystyle a+bx+cx^2\) such that \(\displaystyle a-b=0\) and \(\displaystyle c=0\). Thus, we may state that the kernel of \(\displaystyle T\) is spanned by the vector
\(\displaystyle \left[ \begin{array}{ccc}1 & 1 & 0\end{array} \right]^T\), which is thus the basis of the kernel of T. Since there is one vector in the basis, the dimension of the kernel is 1.

Any questions about the process so far?
 
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  • #3
Kaspelek said:
c) Find a basis for ImT and hence write down dim(ImT).

d) Does the transformation have an inverse?

For c), what we need to do is find the largest possible set of linearly independent column-vectors. If you wanted to use the rref (reduced row echelon form) that we computed previously, you simply choose the column vectors corresponding to the 1's (i.e. the "pivots") of the reduced matrix. That is, choosing the first and third columns, we find that \(\displaystyle \left[ \begin{array}{ccc}-1 & 0 & 0\end{array} \right]^T\) and \(\displaystyle \left[ \begin{array}{ccc}0 & 2 & 1\end{array} \right]^T\) form a basis of the image. It follows that \(\displaystyle dim(Im(T))=2\).

For d), we simply note that the kernel of this transformation is not of dimension 0. This is enough to state that the transformation does not have an inverse.
 
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  • #4
Something better to express the solutions as vectors of $P_2$ instead of coordinates. That is, $B_{\ker T}=\{1+x\}$ and $B_{\mbox{Im }T}=\{-1,2x+x^2\}$.
 
  • #5
That helped a lot guys, thanks a lot.
 

FAQ: Matrix of Linear Transformation T with P2: Find, Ker, Im & Inverse

What is a matrix of linear transformation?

A matrix of linear transformation is a representation of a linear transformation using a matrix. It is a way to describe how a linear transformation affects points in a vector space.

How do you find the matrix of linear transformation T with P2?

To find the matrix of linear transformation T with P2, we first need to determine the standard basis for P2. This basis consists of the vectors (1,0,0), (0,1,0), and (0,0,1). Then, we apply the linear transformation T to each of these basis vectors and record the resulting vectors as columns in a matrix. This matrix is the matrix of linear transformation T with P2.

What is the kernel (Ker) of a matrix of linear transformation T with P2?

The kernel, or null space, of a matrix of linear transformation T with P2 is the set of all vectors in the vector space P2 that are mapped to the zero vector by the linear transformation T. In other words, it is the set of all vectors that are "collapsed" by the transformation.

What is the image (Im) of a matrix of linear transformation T with P2?

The image, or range, of a matrix of linear transformation T with P2 is the set of all vectors in the vector space P2 that are mapped to by the linear transformation T. In other words, it is the set of all vectors that are "reached" by the transformation.

How do you find the inverse of a matrix of linear transformation T with P2?

To find the inverse of a matrix of linear transformation T with P2, we first need to find the standard basis for P2 and apply the linear transformation T to each basis vector. This will give us a new set of vectors, which can be used to construct a new matrix. This new matrix is the inverse of the original matrix of linear transformation T with P2.

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