Splitting Polynomials into Even and Odd Parts: A Unique Direct Sum Decomposition

In summary, the conversation discusses the vector subspaces of even and odd polynomials in \mathbb{R}[x]_n and how they form a direct sum that spans \mathbb{R}[x]_n. The use of projection operators is suggested as a way to prove this, with the idea that a polynomial can be split into an even and odd part, and this split is unique.
  • #1
Gregg
459
0
1. Let [tex] \mathbb{R}[x]_n^+ [/tex] and [tex] } \mathbb{R}[x]_n^- [/tex] denote the vector subspaces of even and odd polynomials in [tex] \mathbb{R}[x]_n[/tex]

Show [tex] \mathbb{R}[x]_n=\mathbb{R}[x]_n^+ \oplus\mathbb{R}[x]_n^- [/tex]

3. For every [tex] p^+(x) \in \mathbb{R}[x]_n^+ [/tex] [tex]\displaystyle p^+(x)=\sum_{m=0}^n a_m x^m=p^+(-x)[/tex]

So [tex] a_m = 0 [/tex] for [tex] m=2k+1, k=0,1,2,...[/tex] else [tex] a_m \in \mathbb{R} [/tex]. Similarly, [tex] a_m=0[/tex] for [tex] m=2k, k=0,1,2,...[/tex] if the function is odd.

[tex] p^+(x)=a_0+a_2x^2+a_4x^4+\cdots, a_m\in\mathbb{R} [/tex]

[tex] p^-(x)=a_1x+a_3x^3+a_5x^5+\cdots a_m\in\mathbb{R} [/tex]

[tex] p(x)=a_0+a_2x^2+a_4x^4+\cdots+a_1x+a_3x^3+a_5x^5+\cdots [/tex] for every [tex] p(x)\in \mathbb{R}[x]_n [/tex]. So every [tex] p(x) [/tex] is some [tex] p^+(x) [/tex] with some [tex] p^-(x) [/tex]. Is this enough? Is it better to find a basis for the two subspaces and show that the union of the two basis sets spans [tex] \mathbb{R}[x]_n [/tex] ?
 
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  • #2
All that stuff about odd and even powers is true, but it's probably easiest to prove it if you use the projection operators p+(x)=(p(x)+p(-x))/2 and p-(x)=(p(x)-p(-x))/2.
 
  • #3
Say p+(x)=(p(x)+p(-x))/2 and p-(x)=(p(x)-p(-x))/2. Then say that p(x)= p+(x)+p-(x) for all p(x) in R[x]_n?
 
  • #4
Gregg said:
Say p+(x)=(p(x)+p(-x))/2 and p-(x)=(p(x)-p(-x))/2. Then say that p(x)= p+(x)+p-(x) for all p(x) in R[x]_n?

Sure. That splits a polynomial into an even part and an odd part, which is exactly the power split you are talking about. Then I suppose you would want to show that the split is unique. That if p(x)=e(x)+o(x) where e(x) is even and o(x) is odd, then e(x)=p+(x) and o(x)=p-(x), right? Might depend on how exactly your definition of 'direct sum' is phrased.
 

Related to Splitting Polynomials into Even and Odd Parts: A Unique Direct Sum Decomposition

1. What is a vector subspace of polynomials?

A vector subspace of polynomials is a subset of the set of all polynomials, which has the properties of a vector space. This means that it contains the zero polynomial, is closed under addition and scalar multiplication, and satisfies the other axioms of a vector space.

2. How do you determine if a set of polynomials is a vector subspace?

To determine if a set of polynomials is a vector subspace, you can check if it satisfies the three conditions: contains the zero polynomial, is closed under addition, and is closed under scalar multiplication. If all three conditions are met, then the set is a vector subspace.

3. Can a vector subspace of polynomials have infinite dimensions?

Yes, a vector subspace of polynomials can have infinite dimensions. This means that the subspace contains an infinite number of linearly independent polynomials, which can span an infinite dimensional space.

4. How are vector subspaces of polynomials used in real life?

Vector subspaces of polynomials are used in various areas of science, such as physics, engineering, and computer graphics. They are used to model and solve problems related to linear systems, transformations, and optimization.

5. Are there any special properties of vector subspaces of polynomials?

Yes, there are some special properties of vector subspaces of polynomials. For example, if a vector subspace contains a basis of polynomials, then any polynomial in that subspace can be uniquely expressed as a linear combination of the basis polynomials. Additionally, the dimension of a vector subspace of polynomials is always less than or equal to the degree of the highest degree polynomial in the subspace.

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