Finding the dimension of a subspace

  • Thread starter Thread starter fishturtle1
  • Start date Start date
  • Tags Tags
    Dimension Subspace
Click For Summary

Homework Help Overview

The discussion revolves around finding the dimension of a subspace defined by a linear functional on an n-dimensional vector space. Participants explore the properties of the subspace W, which consists of vectors x such that [x, y] = 0, and the implications of the rank-nullity theorem in this context.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the proof of W being a subspace and the challenge of determining its dimension. There are suggestions to utilize the rank-nullity theorem and questions about the notation used for the linear functional. Some participants express uncertainty about the implications of the rank of the functional on the dimension of W.

Discussion Status

The discussion is active, with participants offering guidance on using the rank-nullity theorem and questioning the notation for the linear functional. There is acknowledgment of the need for clarity in definitions and notation, and some participants are considering alternative approaches to the problem.

Contextual Notes

There are discussions about the appropriateness of the notation used for the linear functional, with some participants suggesting more standard forms. The implications of the rank of the functional on the dimension of the subspace are also under consideration.

fishturtle1
Messages
393
Reaction score
82
Homework Statement
Prove that if ##y## is a linear functional on an ##n##-dimensional vector space ##V##, then the set of all those vectors ##x## such that ##[x, y] = 0## is a subspace of ##V##; what is the dimension of this subspace?
Relevant Equations
A function ##y : V \rightarrow \mathbb{R}## is a linear functional on ##V## if for all ##u, v \in V## and ##\alpha, \beta \in F##, we have ##[\alpha u + \beta v , y] = \alpha [u, y] + \beta [v, y]##.

We have the notation ##[v, y]## to mean ##y(v)##.
I am stuck on finding the dimension of the subspace. Here's what I have so far.

Proof: Let ##W = \lbrace x \in V : [x, y] = 0\rbrace##. We see ##[0, y] = 0##, so ##W## is non empty. Let ##u, v \in W## and ##\alpha, \beta## be scalars. Then ##[\alpha u + \beta v, y] = \alpha [u, y] + \beta [v, y] = \alpha \cdot 0 + \beta \cdot 0 = 0##. So, ##\alpha u + \beta v \in W##. This shows ##W## is a subspace of ##V##.

Next, we will find the dimension of ##W##. Let ##x_1, x_2, \dots, x_n## be a basis of ##V##. We can find a maximal subset of this basis ##z_1, \dots, z_k## such that ##[z_i, y] = 0## for all ##i##. We claim this is a basis for ##W##. Since ##u \in V##, there exists scalars ##\alpha_1, \dots, \alpha_n## such that ##u = \alpha_1 z_1 + \dots + \alpha_k z_k + \alpha_{k+1}x_{k+1} + \dots + \alpha_n x_n##. Then,
$$[u, y] = [\alpha_1 z_1 + \dots + \alpha_k z_k + \alpha_{k+1}x_{k+1} + \dots + \alpha_n x_n, y] = \alpha_{k+1} [x_{k+1}, y] + \dots + \alpha_n [x_n, y] = 0$$.
We want to somehow conclude ##\alpha_{k+1} = \dots = \alpha_n = 0##, but I'm not sure how to proceed. Can I have a hint, please?
 
Physics news on Phys.org
I don't see what you are trying to do with the dimension proof. Do you know the rank formula for linear functions ##\varphi : V\longrightarrow W##?
 
  • Informative
Likes   Reactions: fishturtle1
fishturtle1 said:
Homework Statement:: Prove that if ##y## is a linear functional on an ##n##-dimensional vector space ##V##, then the set of all those vectors ##x## such that ##[x, y] = 0## is a subspace of ##V##; what is the dimension of this subspace?
Relevant Equations:: A function ##y : V \rightarrow \mathbb{R}## is a linear functional on ##V## if for all ##u, v \in V## and ##\alpha, \beta \in F##, we have ##[\alpha u + \beta v , y] = \alpha [u, y] + \beta [v, y]##.

We have the notation ##[v, y]## to mean ##y(v)##.
Why not use a more standard notation?
I.e., ##f: V \rightarrow \mathbb{R}##
and ##f(v)## instead of [v, y]
fishturtle1 said:
I am stuck on finding the dimension of the subspace. Here's what I have so far.
I don't think the work below is going to get you anywhere. You're not going to be able to find the dimension of the nullspace directly, because you don't know how many vectors are in a basis for the nullspace. A better option is to use the rank-nullity theorem - see Rank–nullity theorem - Wikipedia .
fishturtle1 said:
Proof: Let ##W = \lbrace x \in V : [x, y] = 0\rbrace##. We see ##[0, y] = 0##, so ##W## is non empty. Let ##u, v \in W## and ##\alpha, \beta## be scalars. Then ##[\alpha u + \beta v, y] = \alpha [u, y] + \beta [v, y] = \alpha \cdot 0 + \beta \cdot 0 = 0##. So, ##\alpha u + \beta v \in W##. This shows ##W## is a subspace of ##V##.

Next, we will find the dimension of ##W##. Let ##x_1, x_2, \dots, x_n## be a basis of ##V##. We can find a maximal subset of this basis ##z_1, \dots, z_k## such that ##[z_i, y] = 0## for all ##i##. We claim this is a basis for ##W##. Since ##u \in V##, there exists scalars ##\alpha_1, \dots, \alpha_n## such that ##u = \alpha_1 z_1 + \dots + \alpha_k z_k + \alpha_{k+1}x_{k+1} + \dots + \alpha_n x_n##. Then,
$$[u, y] = [\alpha_1 z_1 + \dots + \alpha_k z_k + \alpha_{k+1}x_{k+1} + \dots + \alpha_n x_n, y] = \alpha_{k+1} [x_{k+1}, y] + \dots + \alpha_n [x_n, y] = 0$$.
We want to somehow conclude ##\alpha_{k+1} = \dots = \alpha_n = 0##, but I'm not sure how to proceed. Can I have a hint, please?
 
  • Informative
Likes   Reactions: fishturtle1
Thank you for your replies. Yes, I think we can use Rank-Nullity theorem, I will try it.

And yeah, I'm happy to use a more standard notation if that's better; I was trying to mimic the textbook.
 
fishturtle1 said:
Thank you for your replies. Yes, I think we can use Rank-Nullity theorem, I will try it.

And yeah, I'm happy to use a more standard notation if that's better; I was trying to mimic the textbook.
You could also use ##\langle y, .\rangle\, : \,v\longmapsto \langle y,v\rangle## in case it is an inner product space.
 
  • Informative
Likes   Reactions: fishturtle1
fresh_42 said:
You could also use ##\langle y, .\rangle\, : \,v\longmapsto \langle y,v\rangle## in case it is an inner product space.
I don't think that's applicable here, about an inner product space. My objection to the notation [x, y] was that it hinted at being an inner product, but wasn't.
 
  • Informative
Likes   Reactions: fishturtle1
We know ##y : V \rightarrow \mathbb{R}## is a linear transformation. By Rank-Nullity theorem we have ##\dim V = rank(y) + null(y)##. We note that ##null(y) = \dim W##. If ##rank(y) = 0##, then ##\dim V = \dim W## and so ##\dim W = n##.

If ##rank(y) \neq 0##, then ##rank(y) = 1##. And so ##\dim W = n - 1##.
 
Mark44 said:
I don't think that's applicable here, about an inner product space. My objection to the notation [x, y] was that it hinted at being an inner product, but wasn't.
In case we have finite dimensional vector space, there is a one-to-one correspondence between ##V## and ##V^*##, and if it is a real vector space, then any ##v\in V^*## can be written as some ##\langle y_v,-\rangle##, i.e. the bijection can be realized by the inner product. This should even hold for other fields of characteristic zero.

However, you were right that the brackets were problematic. They are usually used for commutators, in group as well as in algebra theory.
 
  • Like
Likes   Reactions: etotheipi

Similar threads

  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 10 ·
Replies
10
Views
3K
Replies
4
Views
2K
  • · Replies 15 ·
Replies
15
Views
2K
Replies
15
Views
2K
  • · Replies 10 ·
Replies
10
Views
2K
Replies
8
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K