Understanding the Dimension of Null Space for Linear Operator T in Pn

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In summary: So, to summarize, the null space of the linear operator T is the set of all polynomials with degree less than k, which can be represented by the basis [1,x,x^{2},...,x^{k-1}]. Therefore, the dimension of the null space is k.
  • #1
Mr.Tibbs
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Define ne a linear operator T : Pn [itex]\rightarrow[/itex] Pn by
T(p(x)) = [itex]\frac{d^{k}x}{dx^{n}}[/itex]p(x)
where 1 [itex]\leq[/itex]k [itex]\leq[/itex]n. Show that dim(N(T)) = k.

i. The null space of a linear operator is all vectors v [itex]\in[/itex] V such that T(v) = 0

ii. The dimension of a vector space V, is the number of vectors in any basis of V.

My logical understanding is that the null space of T is any k derivative that gives 0 i.e. k is bigger than n. Thus the dimension has k number of possible vectors. My problem is I don't know how to write the proof. . . I'm assuming that I just have to write the null space as a summation of derivatives from 1 to k thus the dimension of the null is k (the largest possible number).
 
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  • #2
Mr.Tibbs said:
Define ne a linear operator T : Pn [itex]\rightarrow[/itex] Pn by
T(p(x)) = [itex]\frac{d^{k}x}{dx^{n}}[/itex]p(x)
where 1 [itex]\leq[/itex]k [itex]\leq[/itex]n. Show that dim(N(T)) = k.

I assume you mean ##\frac {d^k x}{dx^k}p(x)##. Or for easy display, ##D^kp(x)##.

i. The null space of a linear operator is all vectors v [itex]\in[/itex] V such that T(v) = 0

ii. The dimension of a vector space V, is the number of vectors in any basis of V.

My logical understanding is that the null space of T is any k derivative that gives 0

No. The null space isn't "any k derivative". The null space is a subspace of your nth degree polynomials.

i.e. k is bigger than n. Thus the dimension has k number of possible vectors. My problem is I don't know how to write the proof. . . I'm assuming that I just have to write the null space as a summation of derivatives from 1 to k thus the dimension of the null is k (the largest possible number).

No again, the null space is not a "summation of derivatives". For example if ##n=5## so you are considering polynomials of degree ##5##, and you operate on them with ##D^2##, which ones would map to the zero polynomial?
 
  • #3
Awesome! So I've been sitting here and had an epiphany. . . I think. . . so here is what I came up with.

Let B = {1,x,x[itex]^{2}[/itex],...,x[itex]^{n}[/itex]} be the standard basis for P[itex]_{n}[/itex]. Since p(x) is in the N(T) iff it's degree is < k, then the null space is all the polynomials with degree k-1 or less, thus [1,x,x[itex]^{2}[/itex],...,x[itex]^{k-1}[/itex]] is a basis for N(T),

and the dim(N(T)) = k


:) I think I have it what do you think?
 
  • #4
Mr.Tibbs said:
Awesome! So I've been sitting here and had an epiphany. . . I think. . . so here is what I came up with.

Let B = {1,x,x[itex]^{2}[/itex],...,x[itex]^{n}[/itex]} be the standard basis for P[itex]_{n}[/itex]. Since p(x) is in the N(T) iff it's degree is < k, then the null space is all the polynomials with degree k-1 or less, thus [1,x,x[itex]^{2}[/itex],...,x[itex]^{k-1}[/itex]] is a basis for N(T),

and the dim(N(T)) = k


:) I think I have it what do you think?

I think that's much better. :smile:
 

What is the dim(N(T))?

The dim(N(T)) refers to the dimension of the null space of a linear transformation T.

Why is the dim(N(T)) important?

The dim(N(T)) is important because it tells us the number of linearly independent vectors that are mapped to the zero vector by the linear transformation T.

How is the dim(N(T)) calculated?

The dim(N(T)) can be calculated by finding the number of free variables in the reduced row echelon form of the matrix representing the linear transformation T.

What does a larger dim(N(T)) indicate?

A larger dim(N(T)) indicates that the linear transformation T maps more vectors to the zero vector, meaning that the transformation is less injective.

How does the dim(N(T)) relate to the rank of T?

The rank-nullity theorem states that the dim(N(T)) plus the rank of T equals the dimension of the domain of T. Therefore, the dim(N(T)) and the rank are complementary and provide information about the injectivity and surjectivity of T.

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