Let [itex]V= \mathbb{R}_3[x][/itex] be the vector space of polynomials

In summary: Yes, the Rank-nullity formula holds in this case. The basis for Im(D) you provided is correct, but it can also be written as \{x,x^2,x^3\} to make it clear that these are all polynomials of degree at most 2.
  • #1
Ted123
446
0
Let [itex]V= \mathbb{R}_3[x][/itex] be the vector space of polynomials with real coefficients with degree at most 3 and let [itex]D:V\to V[/itex] be the linear operator of taking derivatives, [itex]D(f)=f'[/itex].

I'm trying to check the Rank-nullity theorem for this example but it doesn't seem to hold:

Since [itex]D[/itex] is not injective (e.g. images of [itex]x^2[/itex] and [itex]x^2+1[/itex] are both [itex]2x[/itex]), [itex]\text{Ker}(D)\neq \{ \bf{0} \}[/itex]. (The kernel is actually all the constant polynomials).

Since [itex]D[/itex] is surjective (as every polynomial is the derivative of some other polynomial), [itex]\text{Im}(D)=V=\mathbb{R}_3[x][/itex].

Now the Rank-nullity formula is:

[itex]\text{dim}(\text{Ker}(D)) + \text{dim}(\text{Im}(D)) = \text{dim}(V)[/itex].

But [itex]\text{dim}(\text{Im}(D)) = \text{dim}(\mathbb{R}_3[x]) = 4 = \text{dim}(V)[/itex]

so if the Rank-nullity formula holds this would imply [itex]\text{dim}(\text{Ker}(D))=0[/itex] but it doesn't as [itex]D[/itex] is not injective, so what's going on?

EDIT: D is not surjective! How do I find a basis for the Kernel and Image?
 
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  • #2


Ted123 said:
Let [itex]V= \mathbb{R}_3[x][/itex] be the vector space of polynomials with real coefficients with degree at most 3 and let [itex]D:V\to V[/itex] be the linear operator of taking derivatives, [itex]D(f)=f'[/itex].

I'm trying to check the Rank-nullity theorem for this example but it doesn't seem to hold:

Since [itex]D[/itex] is not injective (e.g. images of [itex]x^2[/itex] and [itex]x^2+1[/itex] are both [itex]2x[/itex]), [itex]\text{Ker}(D)\neq \{ \bf{0} \}[/itex]. (The kernel is actually all the constant polynomials).

Since [itex]D[/itex] is surjective (as every polynomial is the derivative of some other polynomial), [itex]\text{Im}(D)=V=\mathbb{R}_3[x][/itex].
Your mistake is here. Im(D) != R3. The image of a polynomial of degree 3 is a polynomial of degree 2, so Im(D) does not contain 3rd degree polynomials, hence D is not onto (surjective).

BTW, the notation used in this problem seems nonstandard to me. The space of real polynomials of degree less than n is often called Pn. So your space would normally be called P4. At least, that's the notation I've seen most often.
Ted123 said:
Now the Rank-nullity formula is:

[itex]\text{dim}(\text{Ker}(D)) + \text{dim}(\text{Im}(D)) = \text{dim}(V)[/itex].

But [itex]\text{dim}(\text{Im}(D)) = \text{dim}(\mathbb{R}_3[x]) = 4 = \text{dim}(V)[/itex]

so if the Rank-nullity formula holds this would imply [itex]\text{dim}(\text{Ker}(D))=0[/itex] but it doesn't as [itex]D[/itex] is not injective, so what's going on?

EDIT: D is not surjective! How do I find a basis for the Kernel and Image?
 
  • #3


Mark44 said:
Your mistake is here. Im(D) != R3. The image of a polynomial of degree 3 is a polynomial of degree 2, so Im(D) does not contain 3rd degree polynomials, hence D is not onto (surjective).

BTW, the notation used in this problem seems nonstandard to me. The space of real polynomials of degree less than n is often called Pn. So your space would normally be called P4. At least, that's the notation I've seen most often.

Yeah I realized that restricting the degrees of the polynomials made D not surjective.

So with this notation does [itex]\text{Im}(D) = \mathbb{R}_2[x][/itex] (i.e. Polynomials in x with real coefficients with degree at most 2)?

We know [itex]\text{Ker}(D)=\{ \text{constant polynomials} \}[/itex] so to describe all the bases of [itex]\text{Ker}(D)[/itex] can I just say the set of singletons [itex]\{k\}[/itex] where [itex]k\in\mathbb{R} \setminus \{0\}[/itex] ? So [itex]\text{Ker}(D)[/itex] has dimension 1.

And [itex]\text{Im}(D) = \mathbb{R}_2[x][/itex] so a basis for the image is [itex]\{1,x,x^2 \}[/itex] with dimension 3. Then 1+3=4=dim(V) so the Rank-nullity formula is satisfied.
 
  • #4


Ted123 said:
Yeah I realized that restricting the degrees of the polynomials made D not surjective.

So with this notation does [itex]\text{Im}(D) = \mathbb{R}_2[x][/itex] (i.e. Polynomials in x with real coefficients with degree at most 2)?
Yes.
Ted123 said:
We know [itex]\text{Ker}(D)=\{ \text{constant polynomials} \}[/itex] so to describe all the bases of [itex]\text{Ker}(D)[/itex] can I just say the set of singletons [itex]\{k\}[/itex] where [itex]k\in\mathbb{R} \setminus \{0\}[/itex] ? So [itex]\text{Ker}(D)[/itex] has dimension 1.
Yes, Ker(D) has dimension 1. You don't need to (and shouldn't) exclude the 0 polynomial.
Ted123 said:
And [itex]\text{Im}(D) = \mathbb{R}_2[x][/itex] so a basis for the image is [itex]\{1,x,x^2 \}[/itex] with dimension 3. Then 1+3=4=dim(V) so the Rank-nullity formula is satisfied.
 

1. What is the dimension of V?

The dimension of V is 4, as it is a vector space of polynomials with degree up to 3.

2. What are the basis vectors for V?

The basis vectors for V are {1, x, x^2, x^3}.

3. How do I find the span of a set of polynomials in V?

To find the span of a set of polynomials in V, you can use the span formula: span{p1, p2, ..., pn} = {a1p1 + a2p2 + ... + anpn | a1, a2, ..., an ∈ R}.

4. Is V a finite or infinite dimensional vector space?

V is a finite dimensional vector space, as it has a finite basis of 4 vectors.

5. Can I perform scalar multiplication and vector addition on polynomials in V?

Yes, as V is a vector space, scalar multiplication and vector addition are defined for polynomials in V.

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