Linear maps: finding matrix

T In summary, we define T:R[x]^2->R[x]^3 as T(P(x))=xP(x) and compute the matrix of T with respect to bases {1,x,x^2} and {1,x,x^2,x^3}. The resulting matrix is ((0,0,0),(1,0,0),(0,1,0),(0,0,1)), with the kernel being the zero vector and the image being a subspace spanned by the basis vectors (0,1,0,0), (0,0,1,0), and (0,0,0,1).
  • #1
jiles-smith
7
0

Homework Statement



Let T:R[x]2->R[x]3 be defined by T(P(x))=xP(x). Compute the matrix of T with respect to bases {1,x,x^2} and {1,x,x^2,x^3}. Find the kernel and image of T.


The Attempt at a Solution


I genuinely have no idea where to start on this, any pointers you can give me would be greatly appreciated.
 
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  • #2
i would start be computing the action of T on each basis vector of R2 & write in terms of basis of R3

then use that to make a matrix

notice the polynomials are considered as vectors, so for example ax2 +b x + c in the basis of R2 could just be written (c,b,a)
 
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  • #3
so would the basis in R^2 in vector form be: {1,0,0},{0,1,0},{0,0,1}? If so, how would you get this in terms of the R^3 basis?
 
  • #4
jiles-smith said:
so would the basis in R^2 in vector form be: {1,0,0},{0,1,0},{0,0,1}? If so, how would you get this in terms of the R^3 basis?
What you give, since they are in R3, form a basis for R3, not R2. A basis for R2 is {(1, 0), (0,1)}. (Don't use "{" and "}" for individual vectors. Those are set delimiters.)
 
  • #5
jiles-smith said:
so would the basis in R^2 in vector form be: {1,0,0},{0,1,0},{0,0,1}? If so, how would you get this in terms of the R^3 basis?

as halls points out its not R^2, I'm not too sure what the proper notation is, but as there are 3 independent basis vectors, it much more like R^3

so for the space, like R^3 with the basis {1,x,x2}, i think you're correct that you identify
(1,0,0) with 1
(0,1,0) with x & so on

simarlarly for the space where the image resides, with the basis {1,x,x2,x^3}, I would identify
(1,0,0,0) with 1
(0,1,0,0) with x & so on

is what you wrote exactly how the question is written?
 
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  • #6
okay, so i have used the basis for R^3 and got a diagonal matrix with the elements x. Given the equation T(P(x))=x P(x) it looks like it could work. Is this correct? cheers
 
  • #7
what matrix do you get, the way I'm thinking there shoudn't be any x's in the matrix?

if its from a 3 dimensional space to a 4 dimensional space, i think it should be a 4x3 matrix

Also i think it should have constant entries... consider what multiplying by x does, it shifts you from one basis vector to another... (similar to 90degree rotation in normal R^3)
 
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  • #8
well i have just changed direction a bit but here is what i have so:
T(1,0,0)=(0,1,0,0); T(0,1,0)=(0,0,1,0); T(0,0,1)=(0,0,0,1)
So the matrix would be:
((0,0,0),(1,0,0),(0,1,0),(0,0,1))

(Each sub-bracket is a row)
 
  • #9
sounds reasonable to me & all lines up with the initial definition
 

1. What is a linear map?

A linear map, also known as a linear transformation or linear function, is a mathematical function that maps one vector space to another in a way that preserves the vector space operations of addition and scalar multiplication.

2. How do you find the matrix representation of a linear map?

To find the matrix representation of a linear map, you first need to determine the basis vectors for the domain and codomain of the map. Then, the columns of the matrix will correspond to the image of each basis vector under the linear map. The entries in each column will be the coefficients of the basis vectors in the image.

3. What is the importance of finding the matrix representation of a linear map?

Finding the matrix representation of a linear map allows us to easily perform calculations and transformations on the map. It also allows us to compare and analyze different linear maps, and to determine properties such as invertibility and rank.

4. How is the matrix representation of a linear map related to its transformation properties?

The matrix representation of a linear map reflects its transformation properties. For example, the size and shape of the matrix will depend on the dimensions of the domain and codomain, and the entries in the matrix will correspond to the coefficients of the linear transformation.

5. Can you find the matrix representation of any linear map?

Yes, it is possible to find the matrix representation of any linear map as long as the vector spaces involved have finite dimensions. The process may become more complex for higher dimensions, but the concept remains the same.

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