Image and nullspace bases of a linear transformation

In summary, the conversation discusses finding bases for the image and nullspace of a linear transformation T: M2x2-->M2x2, defined as T([a,b;c,d]) = [b,b;d,d]. The standard basis of a 2x2 matrix is given, and the rank-nullity theorem is mentioned. The attempt at a solution involved multiplying the standard basis by T and finding a basis for the image by taking the columns with leading entries. However, the correct basis for the image is {[0,0;1,0],[0,0;0,1]}, and the basis for the nullspace is {[0,0;0,0]}. The conversation also discusses the importance of considering non-zero
  • #1
featheredteap
4
0

Homework Statement



Let T be the linear transformation T: M2x2-->M2x2 given by

T([a,b;c,d]) = [a,b;c,d][0,0;1,1] = [b,b;d,d]

Find bases (consisting of 2x2 matrices) for the image of T and the nullspace of T.

Homework Equations



Standard basis of a 2x2 matrix: {[1,0;0,0],[0,1;0,0],[0,0;1,0],[0,0;0,1]}

rank(T) + nullity (T) = n (number of columns of T)

The Attempt at a Solution



I multiplied the elements of the standard basis by T to find the image points of the transformation. I then put those image points in the form [a,b;c,d] in a matrix, which equalled the matrix T relative to the standard basis S:

[T]S=[0,0,0,0;0,1,0,0;0,0,0,1;0,0,0,0]

To find a basis for the image, I took the columns with leading entries, but I'm not completely sure it's correct:

basis: {[0,1;0,0],[0,0;1,0]}

As for the basis for the nullspace, wouldn't it just be {0} because there is only one solution to the system of equations (i.e. they are linearly independent)? Or is it [0,0;0,0]? However, rank + nullity = 4 and (assuming I got the basis for the image right) rank = 2, so nullity should = 2. Does the nullity of a 2x2 matrix = 2?
 
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  • #2
woops looked at it again - ok, so
[tex] \begin{pmatrix} a & b \\ c & d \end{pmatrix} \begin{pmatrix} 0 & 0 \\ 1 & 1 \end{pmatrix} = \begin{pmatrix} b & b\\ d & d \end{pmatrix}[/tex]

as you have sort of done, you can imagine the matricies as vectors in [tex] \mathbb{R}^4 [/tex]

if should be clear that any matrix with b=d=0, will be mapped to the zero matrix, giving the null space

if either b or d is non-zero, then the resultant transformation will be non-zero, giving the basis of vectors that will be mapped to non-zero vectors. input these individulaly to find a basis for the image space... (i think the one you presented is incorrect)
 
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1. What is a linear transformation?

A linear transformation is a mathematical function that maps a vector space to another vector space, while preserving the linear relationships between its elements.

2. What is an image of a linear transformation?

The image of a linear transformation is the set of all possible outputs that can be obtained by applying the transformation to every element in the input vector space.

3. What is a nullspace of a linear transformation?

The nullspace of a linear transformation is the set of all vectors in the input vector space that are mapped to the zero vector in the output vector space.

4. How are image and nullspace bases of a linear transformation related?

The image and nullspace bases of a linear transformation are related in that they both form a basis for the respective vector spaces. This means that they span the entire space and are linearly independent.

5. Why are image and nullspace bases important in linear algebra?

Image and nullspace bases are important in linear algebra because they provide a way to represent and understand the behavior of a linear transformation. They also allow for the computation of important properties such as dimension, rank, and nullity.

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