Why is T(1)=2 in the matrix of a linear mapping?

In summary, the problem asks to find the matrix of a linear mapping T:P_3 → P_3 defined by (Tp)(t)=p(t)+p'(t)+p(0), with respect to the basis {1,t,t^2,t^3} of P_3 and to deduce that given a polynomial q \in P_3, there exists a polynomial p \in P_3 such that q(t)=p(t)+p'(t)+p(0). The solution involves finding T(1), T(t), T(t^2), and T(t^3) which are given as T(1)=2, T(t)=t+1, T(t^2)=t^2+2
  • #1
juanma101285
5
0
Hi, I have the following problem that is solved, but I get lost at one step and cannot find how to do it in the notes. I would really appreciate it if someone could tell me where my teacher gets the result from.

The problem says:

"Find the matrix of linear mapping [itex]T:P_3 → P_3[/itex] defined by

[itex](Tp)(t)=p(t)+p'(t)+p(0)[/itex]

with respect to the basis {[itex]1,t,t^2,t^3[/itex]} of [itex]P_3[/itex]. Deduce that, given [itex]q \in P_3[/itex], there exists [itex]p \in P_3[/itex] such that
[itex]q(t)=p(t)+p'(t)+p(0)[/itex]."

And I get lost here... It says:

"We have

[itex]T(1)=2[/itex]
[itex]T(t)=1+t[/itex]
[itex]T(t^2)=2t+t^2[/itex]
[itex]T(t^3)=3t^2+t^3[/itex]"

So I don't know why it says [itex]T(1)=2[/itex]... I think [itex]T(t)=1+t[/itex] because it is the derivative of t plus t, and [itex]T(t^2)[/itex] is the derivative of [itex]t^2[/itex] plus [itex]t^2[/itex]... But why T(1)=2?

Thanks a lot!
 
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  • #2
I think this would be clearer written slightly differently.

[tex]T[p(t)] = p(0) + \frac{dp}{dt} + p(t)[/tex]

When you say [itex]T(1)[/itex], you substitute [itex]p(t) = 1[/itex] into the above. Clearly, then, [itex]p(0) = 1[/itex] because [itex]p(t) = 1[/itex] for any [itex]t[/itex]. That takes care of the first and last terms. The derivative is zero because [itex]p[/itex] is a constant.

In short, you get

[tex]T(1) = 1 + 0 + 1 = 2[/tex]
 
  • #3
T takes polynomials to polynomials, so when he writes T(1), 1 denotes a polynomial. The only polynomial that it makes sense to denote by 1 is the function that takes every real number to 1. It might be less confusing to denote it by a symbol like I instead. Then for all real numbers t, we have ##(T(I))(t)=I(t)+I'(t)+I(0)=1+0+1##, as Muphrid has already said. So T(I) is the polynomial that takes every real number t to 2. In this context, it seems to be standard to denote this polynomial by 2.

Muphrid said:
I think this would be clearer written slightly differently.

[tex]T[p(t)] = p(0) + \frac{dp}{dt} + p(t)[/tex]
I think this notation is worse, because now it looks like T is acting on the real number p(t) instead of on the polynomial p.
 
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  • #4
juanma101285 said:
I think [itex]T(t)=1+t[/itex] because it is the derivative of t plus t,
I don't understand this argument. To find T(t), you need to do something similar to what I did above.

Here t denotes the identity map on the set of real numbers, i.e. the function that takes every real number to itself. If we use this notation, then for all real numbers s, we have
##(T(t))(s)=t(s)+t'(s)+t(0)=s+1+0##. So T(t) is the polynomial that takes s to 1+s. In this notation, that polynomial is denoted by 1+t.

This problem shows how confusing it can be to use notations like t2 both for a number (the square of the number t) and a function (the function that takes every real number to its square). I would prefer to use a different notation for the basis vectors, for example ##\{e_1,e_2,e_3,e_4\}## instead of ##\{1,t,t^2,t^3\}##, where the ##e_i## are defined by
##e_1(s)=1## for all s.
##e_2(s)=s## for all s.
...and so on.

Now what the problem writes as T(1) and T(t) can be written as ##Te_0## and ##Te_1## respectively, and for all ##t\in\mathbb R##,
##Te_1(t)=e_1(t)+e_1'(0)+e_1(0)=1+0+1=2=2(e_1(t))=(2e_1)(t),##
##Te_2(t)=e_2(t)+e_2'(0)+e_2(0)=t+1+0=e_2(t)+e_1(t)=e_1(t)+e_2(t)=(e_1+e_2)(t)##.

Since this holds for all t, we have ##Te_1=2e_1## and ##Te_2=e_1+e_2##.

Can you do ##T(t^2)## and ##T(t^3)## now? You can stick to the t^something notation if it doesn't confuse you, but then you will have to write weird things like ##{t^2}'(s)=2s##.
 
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  • #5
juanma101285 said:
Hi, I have the following problem that is solved, but I get lost at one step and cannot find how to do it in the notes. I would really appreciate it if someone could tell me where my teacher gets the result from.

The problem says:

"Find the matrix of linear mapping [itex]T:P_3 → P_3[/itex] defined by

[itex](Tp)(t)=p(t)+p'(t)+p(0)[/itex]

with respect to the basis {[itex]1,t,t^2,t^3[/itex]} of [itex]P_3[/itex]. Deduce that, given [itex]q \in P_3[/itex], there exists [itex]p \in P_3[/itex] such that
[itex]q(t)=p(t)+p'(t)+p(0)[/itex]."

And I get lost here... It says:

"We have

[itex]T(1)=2[/itex]
[itex]T(t)=1+t[/itex]
[itex]T(t^2)=2t+t^2[/itex]
[itex]T(t^3)=3t^2+t^3[/itex]"

So I don't know why it says [itex]T(1)=2[/itex]
The derivative of the polynomial p(t)= 1 (for all t) is 0 so p(t)+ p'(t)+ p(0)= 1+ 0+ 1= 2.

... I think [itex]T(t)=1+t[/itex] because it is the derivative of t plus t,
More precisely p(t)+ p'(t)+ p(0)= t+ 1+ 0= t+ 1

and [itex]T(t^2)[/itex] is the derivative of [itex]t^2[/itex] plus [itex]t^2[/itex]...
Again, [itex]p(t)+ p'(t)+ p(0)= t^2+ 2t+ 0= t^2+ 2t[/itex]
But why T(1)=2?

Thanks a lot!
 

1. What is a matrix of a linear mapping?

A matrix of a linear mapping is a representation of a linear transformation between two vector spaces. It is a rectangular array of numbers that describes how the basis vectors of one vector space are transformed into the basis vectors of another vector space.

2. How is a matrix of a linear mapping related to a linear transformation?

A matrix of a linear mapping is closely related to a linear transformation as it represents the transformation in a more concise and organized way. The columns of the matrix correspond to the images of the basis vectors of the domain, and the rows correspond to the coordinates of the images of the basis vectors of the range.

3. What is the importance of a matrix of a linear mapping in linear algebra?

A matrix of a linear mapping is essential in linear algebra as it allows us to study linear transformations in a more efficient manner. It enables us to perform calculations and solve problems related to linear transformations, such as finding the image of a vector or determining if a transformation is invertible.

4. How is a matrix of a linear mapping calculated?

A matrix of a linear mapping is calculated by applying the linear transformation to each of the basis vectors of the domain and recording the coordinates of the resulting vectors. These coordinates are then placed in a matrix, with the columns representing the images of the basis vectors of the domain and the rows representing the coordinates of the images of the basis vectors of the range.

5. Can a matrix of a linear mapping be used to find the inverse of a linear transformation?

Yes, a matrix of a linear mapping can be used to find the inverse of a linear transformation. If the matrix is invertible, then its inverse will represent the inverse linear transformation. This can be useful in solving problems related to linear transformations, such as finding the pre-image of a vector.

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