Dimension of a subspace of polynomials with certain coefficients

In summary, the conversation was about the dimension of a subspace of polynomials of degree 4 with certain restrictions and the dimension of a linear operator on this space. The argument revolved around whether the operator changed the dimension or not, with one party arguing that the dimension remained the same while the other argued that it increased by one. The conclusion was that the operator did indeed change the dimension, but it was not a linear operator as it did not map from the same space to itself. The conversation also touched on another operator that did change the dimension of the space.
  • #1
Zorba
77
0
Right so I've had an argument with a lecturer regarding the following:

Suppose you consider [tex]P_4[/tex] (polynomials of degree at most 4): [tex]A(t)=a_0+a_1t+a_2t^2+a_3t^3+a_4t^4[/tex]

Now if we consider the subspace of these polynomials such that [tex]a_0=0,\ a_1=0,\ a_2=0}[/tex], I propose that the dimension of of this subspace is 2 (versus the dimension of [tex]P_4[/tex] which is 5. Am I incorrect in saying this?

Based on the answer to this I have a follow up question regarding a linear operator on [tex]P_n[/tex]
 
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  • #2
Zorba said:
Right so I've had an argument with a lecturer regarding the following:

Suppose you consider [tex]P_4[/tex] (polynomials of degree at most 4): [tex]A(t)=a_0+a_1t+a_2t^2+a_3t^3+a_4t^4[/tex]

Now if we consider the subspace of these polynomials such that [tex]a_0=0,\ a_1=0,\ a_2=0}[/tex], I propose that the dimension of of this subspace is 2 (versus the dimension of [tex]P_4[/tex] which is 5. Am I incorrect in saying this?
Yes, any such polynomial can be written as [itex]0(1)+ 0(x)+ 0(x^2)+ a_3 t^3+ a_4t^4[/itex] and so [itex]\{t^3, t^4\}[/itex] is a basis.

Based on the answer to this I have a follow up question regarding a linear operator on [tex]P_n[/tex]
Fire away!
 
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  • #3
(Cheers)

Suppose we consider an operator [tex]B: A(t) \rightarrow tA(t)[/tex] where [tex]A(t) \in P_4[/tex]

Right, so my argument is that the result of this operation does not change the dimension, ie that [tex]dim(A(t))=dim(tA(t))[/tex] (basically I was trying to convince him that this was a linear operator). Am I missing something here?

He seemed to argue that since [tex]tA(t)[/tex] now belongs to [tex]P_5[/tex] it now has an extra dimension, but I argue that since [tex]tA(t)[/tex] has the form [tex]a_0t+a_1t^2+a_2t^3+a_3t^4+a_4t^5[/tex] and since a polynomial in [tex]P_5[/tex] would be [tex]A(t)=a_0+a_1t^1+a_2t^2+a_3t^3+a_4t^4+a_5t^5[/tex] that it does indeed have the same dimension... :uhh:
 
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  • #4
You are correct, the range of B has the same dimension, however, B is not a linear operator, because a linear operator is a linear transformation from a space to itself, i.e. the same space, it must take P_4 -> P_4, but tA(t) takes P_4->P_5, although to a 2 dimensional subspace in P_5 it is no longer the same space. (E.g. now we have t^5 in the range of B, but by definition that does not exist in P_4, so the spaces are different).
 
  • #5
Ahha, I had (oddly in retrospect) thought that a linear operator was one that mapped from a space to another such that both spaces had the same dimension.

One final question, I also made the argument that a polynomial acted on by the following operator "loses" a dimension: [tex]\displaystyle P: A(t) \rightarrow \frac{A(t)-A(0)}{t}[/tex]
Is that incorrect?
 
  • #6
if A(t)-A(0) is a constant then you are out of the space again...
 
  • #7
[tex]A(t)-A(0)[/tex] is never constant...

[tex]\displaystyle \frac{A(t)-A(0)}{t}=\frac{a_0+a_1t+a_2t^2+a_3t^3+a_4t^4 - a_0}{t}=a_1+a_2t+a_3t^2+a_4t^3[/tex]
 
  • #8
Oops... I don't know what i was thinking. That is correct.
 

1. What is a linear operator?

A linear operator is a mathematical function that takes in one vector as an input and produces another vector as an output. The output vector is obtained by multiplying the input vector with a fixed matrix.

2. How do you determine the dimension of a vector space?

The dimension of a vector space is the number of basis vectors needed to span the entire space. This can be determined by finding the number of linearly independent vectors in the space.

3. Can a linear operator change the dimension of a vector space?

No, a linear operator cannot change the dimension of a vector space. The dimension of the output vector space will always be the same as the dimension of the input vector space.

4. What is the relationship between the null space and the dimension of a linear operator?

The null space of a linear operator is the set of all vectors that produce a zero output when multiplied by the operator. The dimension of the null space is equal to the number of free variables in the matrix representation of the operator.

5. Can two linear operators have the same dimension?

Yes, two linear operators can have the same dimension if they operate on the same vector space and have the same number of basis vectors. However, they may not necessarily be the same operators as they can have different matrix representations.

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