Proofs of dimensions and subspaces check

I see the problem. The code isn't processing my line-breaks. I'll try to do it slightly differently:DefineW' = Sp\left\{u_1, u_2, ... , u_k, v_{l+1}, v_{l+2}, ... , v_n\right\}Since W' \subseteq V can be written as the span of a subset of the vectors forming the basis of V, it is a subspace of V.
  • #1
harvesl
9
0
Hi, I'd be grateful if someone could tell me whether these proofs I've done are correct or not. Thanks in advanced.

Let [itex]V[/itex] be an [itex]n[/itex]-dimensional vector space over [itex]\mathbb{R}[/itex]

Prove that [itex]V[/itex] contains a subspace of dimension [itex]r[/itex] for each [itex]r[/itex] such that [itex]0 \leq r \leq n[/itex]



Since [itex]V[/itex] is n-dimensional, there exists [itex]v_1, v_2,...,v_n \in V[/itex] such that [itex]\left\{v_1,v_2,...,v_n\right\}[/itex] is a basis for [itex]V[/itex].

For an element [itex] x \in V[/itex], we can write [itex]x[/itex] as

[itex]x = \lambda_1 v_1 + \lambda_2 v_2 + ... + \lambda_n v_n[/itex] for [itex]\lambda_i \in \mathbb{R}[/itex]

Since [itex]Sp\left\{v_1,v_2,...,v_n\right\} = V[/itex]

Therefore we can also say that

[itex] V = \left\{\lambda_1 v_1 + \lambda_2 v_2 + ... + \lambda_n v_n\right\}[/itex]

Since [itex]V[/itex] is a vector space [itex]\left\{(0)\right\} \in V[/itex] and [itex]\left\{(0)\right\}[/itex] is clearly a 0-dimension subspace of [itex]V[/itex] as it is closed under both addition and multiplication.

Since any non-empty subset of a linearly independent set of vectors is also linearly independent we have that for [itex]q[/itex], where [itex] 1 \leq q \leq n[/itex]

[itex]\left\{v_1, v_2,..., v_q\right\} = \left\{\mu_1 v_1 + \mu_2 v_2 + ... + \mu_q v_q : \mu_i \in \mathbb{R}\right\}

\subseteq \left\{\lambda_1 v_1 + \lambda_2 v_2 + ... + \lambda_n v_n\right\} = V[/itex]




---
Second question
---

Let [itex]U,W[/itex] be subspaces of [itex]V[/itex] with [itex]U \subseteq W[/itex]. Show that there is some subspace [itex]W'[/itex] of [itex]V[/itex] such that [itex]W \cap W' = U[/itex] and [itex]W +W' = V[/itex]


Firstly, since [itex]W \cap W' = U[/itex],[itex]\ \ \ U \subseteq W'[/itex] because if [itex]x \in U[/itex] then [itex]x \in W'[/itex]

Therefore we can write that

[itex]W' = U \cup \left\{v_1, v_2, ... , v_m\right\}[/itex]

For some vectors [itex](v_1, v_2, ... , v_m) \in V \backslash U[/itex] but [itex](v_1, v_2, ... , v_m) \notin W[/itex] because if any [itex]v_i \in W[/itex] then [itex]v_i \in W \cap W'[/itex] and we would have that [itex]W \cap W' \neq U[/itex]

Since [itex]dim(V) = n[/itex], if we set [itex]dim(W) = x[/itex] we get that

[itex]dim(\left\{v_1, v_2, ... , v_m\right\}) = m = n-x[/itex]

Hence we can find [itex]m[/itex] linearly independent [itex]\left\{v_1, v_2, ... , v_m\right\} \notin Sp(W)[/itex] to give

[itex]W \cap W' = W \cap (U \cup \left\{v_1, v_2, ... , v_m\right\}) = U[/itex]

and

[itex] W + W' = \left\{w + w' : w \in W, w' \in W'\right\} = Sp(W \cup W') = V[/itex]

As [itex]dim(W \cup W') = x + n-x = n[/itex]


Again, thanks to anyone who helps!
 
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  • #2
Your first answer sounds a bit ... confused, if I may call it that. You correctly noticed that V is spanned by n basis vectors, and that taking the first r of these should give you a subspace of dimension r. So what I would do, is write that down as a claim, rather than a conclusion. Proving the claim should then be straightforward.

For the second exercise, you seem to be using the conclusion as the first step of the proof. You need to show that a W' satisfying those conditions exists. Until you've done that, you cannot assume it. However, just like I said before: you can make a claim ("define W' as ...") and then prove that it satisfies the conditions. That proof will be very similar to what you've already got (just make sure you don't use the conclusion, i.e. don't use that [itex]W cap W' = U[/itex]).
 
  • #3
CompuChip said:
Your first answer sounds a bit ... confused, if I may call it that. You correctly noticed that V is spanned by n basis vectors, and that taking the first r of these should give you a subspace of dimension r. So what I would do, is write that down as a claim, rather than a conclusion. Proving the claim should then be straightforward.

For the second exercise, you seem to be using the conclusion as the first step of the proof. You need to show that a W' satisfying those conditions exists. Until you've done that, you cannot assume it. However, just like I said before: you can make a claim ("define W' as ...") and then prove that it satisfies the conditions. That proof will be very similar to what you've already got (just make sure you don't use the conclusion, i.e. don't use that [itex]W cap W' = U[/itex]).

Yeah, I've redone the second proof - currently working on the first.

[itex]U = Sp\left\{u_1, u_2, ... , u_k\right\}[/itex]

Where [itex]\left\{u_1, u_2, ... , u_k\right\}[/itex] is linearly independent

We can extend this to a basis of [itex]W[/itex] as [itex]U \subseteq W[/itex]

So for [itex]w_{k+1}, w_{k+2}, ... , w_l \in W \backslash U[/itex]

We have that

[itex]W = Sp\left\{u_1, u_2, ... , u_k, w_{k+1}, w_{k+2}, ... , w_l\right\}[/itex]

Which we can, again, extend to a basis of [itex]V[/itex] as [itex]W \subseteq V[/itex].

So for [itex]v_{l+1}, v_{l+2}, ... , v_n \notin W[/itex]

We have that

[itex] V = Sp\left\{u_1, u_2, ... , u_k, w_{k+1}, w_{k+2}, ... , w_l, v_{l+1}, v_{l+2}, ... , v_n\right\}[/itex]

Since [itex]W' \subseteq V[/itex] is a subspace it can be written as the span of a subset of the vectors forming the basis of [itex]V[/itex]

If we define

[itex]W' = Sp\left\{u_1, u_2, ... , u_k, v_{l+1}, v_{l+2}, ... , v_n\right\}[/itex]

[itex]W \cap W' = Sp[\left\{u_1, u_2, ... , u_k, w_{k+1}, w_{k+2}, ... , w_l\right\} \cap \left\{u_1, u_2, ... , u_k, v_{l+1}, v_{l+2}, ... , v_n\right\}] = Sp\left\{u_1, u_2, ... , u_k\right\} = U[/itex]

and

[itex]W + W' = Sp[\left\{u_1, u_2, ... , u_k, w_{k+1}, w_{k+2}, ... , w_l\right\} \cup \left\{u_1, u_2, ... , u_k, v_{l+1}, v_{l+2}, ... , v_n\right\}]

\

= Sp\left\{u_1, u_2, ... , u_k, w_{k+1}, w_{k+2}, ... , w_l, v_{l+1}, v_{l+2}, ... , v_n\right\} = V[/itex]
 
  • #4
harvesl said:
Since [itex]W' \subseteq V[/itex] is a subspace it can be written as the span of a subset of the vectors forming the basis of [itex]V[/itex]

If we define

[itex]W' = Sp\left\{u_1, u_2, ... , u_k, v_{l+1}, v_{l+2}, ... , v_n\right\}[/itex]

I would switch those statements:

Define
[itex]W' = Sp\left\{u_1, u_2, ... , u_k, v_{l+1}, v_{l+2}, ... , v_n\right\}[/itex]

Since [itex]W' \subseteq V[/itex] can be written as the span of a subset of the vectors forming the basis of [itex]V[/itex], it is a subspace of V.

This shows that W' is a subspace, which is one of the things that you are trying to prove.
 
  • #5
CompuChip said:
I would switch those statements:



This shows that W' is a subspace, which is one of the things that you are trying to prove.

Ah yeah, that makes more sense - define W' and then state it clearly is a subspace. Also, for the first question regarding showing there is a subspace of dimension r for each r between 0 and n - can this also be best done by extending the basis n times from the 0-dimensional subspace S = Sp{0}?

So say we can add some vector in V giving S1 = Sp{0, v1} which is 1-dimensional and linearly independent.

Then add another vector v2 in V\S1 to give S2 = Sp{0, v1, v2} which is 2-dimensional and linearly independent

We can continue this all the way until Sn = Sp{0, v1, v2, ..., vn} which is an n-dimensional linearly independent subspace?
 
  • #6
Yep. A common way of writing that down is starting with "Let [itex]0 \le r \le n[/itex]. Then define [itex]V_r := \cdots[/itex]" and proceed to show that it is the required subspace. Just like before, really.
 
  • #7
Thanks!
 

1. What is a proof of dimensions and subspaces check?

A proof of dimensions and subspaces check is a mathematical method used to determine the dimensions of a vector space and its subspaces. It involves showing that the dimensions of the vector space and its subspaces follow certain properties and are consistent with each other.

2. Why is it important to prove dimensions and subspaces?

Proving dimensions and subspaces is important because it allows us to understand the structure of a vector space and its subspaces. It also helps us to identify the basis vectors and the number of linearly independent vectors in a vector space, which are crucial in many applications of linear algebra.

3. What are the key properties used in proofs of dimensions and subspaces?

The key properties used in proofs of dimensions and subspaces include the dimension theorem, which states that the dimensions of a vector space and its subspace must add up to the dimension of the original vector space. Another important property is the rank-nullity theorem, which relates the dimensions of the null space and the range of a linear transformation.

4. Can proofs of dimensions and subspaces be applied to any vector space?

Yes, proofs of dimensions and subspaces can be applied to any vector space. However, the techniques used may vary depending on the specific properties of the vector space and its subspaces.

5. How can I improve my understanding of proofs of dimensions and subspaces?

To improve your understanding of proofs of dimensions and subspaces, it is important to have a strong foundation in linear algebra and understand the basic concepts of vector spaces, subspaces, and linear transformations. It is also helpful to practice solving problems and working through proofs to gain hands-on experience.

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