When is a subset a subspace in a vector space?

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In summary: W}~ \text{(as they share the same operations between}~ \mathbb{V}~ \text{and}~ \mathbb{W}. ~\text{so,}~ \vec 0~ \epsilon ~ \mathbb{W}) $$In summary, if ##\mathbb{W}## is a non-empty subset of a vector space ##\mathbb{V}##, and it is closed under addition and scalar multiplication, then ##\mathbb{W}## is a subspace of ##\mathbb{V}##, as it satisfies the 10 properties of a vector space. This includes commutativity and associativity under
  • #1
Kaguro
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Let ##\mathbb{V}## be a vector space and ##\mathbb{W}## be a subset of ##\mathbb{V}##, with the same operations.

Claim:
If ##\mathbb{W}## is non-empty, closed under addition and scalar multiplication, then ##\mathbb{W}## is a subspace of ##\mathbb{V}##.

A set is a vector space if it satisfies 10 properties:

  1. Closure under addition
  2. Closure under scalar multiplication
  3. Commutativity under addition
  4. Associativity under addition
  5. Existence of additive identity
  6. Existence of additive inverse
  7. Distributivity for scalar multiplication over addition in scalars
  8. Distributivity for scalar multiplication over addition in vectors
  9. Associativity under scalar multiplication
  10. Identity for scalar multiplication

The properties 1 and 2 are given. 3,4,7,8,9,10 are easily verified as ##\mathbb{W}## and ##\mathbb{V}## share same operations. For example 3:

Let ##\vec u , \vec v \epsilon \mathbb{W}##
$$ \vec u + \vec v (in~ \mathbb{W}) \\
= \vec u + \vec v (in~ \mathbb{V}) \text{(same operation)} \\
= \vec v + \vec u (in~ \mathbb{V}) (\mathbb{V} \text{is a vector space.)} \\
= \vec v + \vec u (in~ \mathbb{W}) ~\text{(same operation)} \\
$$

The problem is 5 and 6.
The book I'm using ( S. Andrilli and D. Hecker) says:-

Let ##\vec u~ \epsilon ~\mathbb{W}##
$$ \Rightarrow~~ 0\vec u ~ \epsilon ~\mathbb{W} ~\text{(closed under scalar multiplication.)}\\
\Rightarrow ~~ 0\vec u ~ \epsilon ~ \mathbb{V} ~\text{(property of subset)}\\
\Rightarrow ~~ \vec 0 ~\epsilon ~ \mathbb{V} ~\text{(property of vector space. Which we proved earlier.)}\\
\Rightarrow ~~ \vec 0 ~ \epsilon ~ \mathbb{W}~ \text{(as they share the same operations)}$$

what??

How can same operations imply that if ##\vec 0## is in ##\mathbb{V}## it also must be in ##\mathbb{W}## ??
 
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  • #2
Kaguro said:
Let ##\mathbb{V}## be a vector space and ##\mathbb{W}## be a subset of ##\mathbb{V}##, with the same operations.

Claim:
If ##\mathbb{W}## is non-empty, closed under addition and scalar multiplication, then ##\mathbb{W}## is a subspace of ##\mathbb{V}##.

A set is a vector space if it satisfies 10 properties:

  1. Closure under addition
  2. Closure under scalar multiplication
  3. Commutativity under addition
  4. Associativity under addition
  5. Existence of additive identity
  6. Existence of additive inverse
  7. Distributivity for scalar multiplication over addition in scalars
  8. Distributivity for scalar multiplication over addition in vectors
  9. Associativity under scalar multiplication
  10. Identity for scalar multiplication

The properties 1 and 2 are given. 3,4,7,8,9,10 are easily verified as ##\mathbb{W}## and ##\mathbb{V}## share same operations. For example 3:

Let ##\vec u , \vec v \epsilon \mathbb{W}##
$$ \vec u + \vec v (in~ \mathbb{W}) \\
= \vec u + \vec v (in~ \mathbb{V}) \text{(same operation)} \\
= \vec v + \vec u (in~ \mathbb{V}) (\mathbb{V} \text{is a vector space.)} \\
= \vec v + \vec u (in~ \mathbb{W}) ~\text{(same operation)} \\
$$

The problem is 5 and 6.
The book I'm using ( S. Andrilli and D. Hecker) says:-

Let ##\vec u~ \epsilon ~\mathbb{W}##
$$ \Rightarrow~~ 0\vec u ~ \epsilon ~\mathbb{W} ~\text{(closed under scalar multiplication.)}\\
\Rightarrow ~~ 0\vec u ~ \epsilon ~ \mathbb{V} ~\text{(property of subset)}\\
\Rightarrow ~~ \vec 0 ~\epsilon ~ \mathbb{V} ~\text{(property of vector space. Which we proved earlier.)}\\
\Rightarrow ~~ \vec 0 ~ \epsilon ~ \mathbb{W}~ \text{(as they share the same operations)}$$

what??

How can same operations imply that if ##\vec 0## is in ##\mathbb{V}## it also must be in ##\mathbb{W}## ??

If ##W## is closed under scalar multiplication and it is non-empty then ##\exists \ \vec{w} \in W## and ##0 \vec{w} = \vec{0} \in W##.

An important subtlety is that you know that ##0 \vec{w} = \vec{0}## because ##W \subset V## and this property holds for all vectors in ##V##, hence all vectors in ##W##.

You can show that ##-\vec{w} \in W## by a similar argument with the scalar ##-1##.
 
  • #3
PeroK said:
If WW is closed under scalar multiplication, and it is non-empty then ∃ →w∈W\exists \ \vec{w} \in W and 0→w=→0∈W0 \vec{w} = \vec{0} \in W.

That's the problem, I don't know that 0##\vec w = \vec 0## in W because it is not a Vector Space yet.
 
  • #4
Kaguro said:
The problem is 5 and 6.
The book I'm using ( S. Andrilli and D. Hecker) says:-

Let ##\vec u~ \epsilon ~\mathbb{W}##
$$ \Rightarrow~~ 0\vec u ~ \epsilon ~\mathbb{W} ~\text{(closed under scalar multiplication.)}\\
\Rightarrow ~~ 0\vec u ~ \epsilon ~ \mathbb{V} ~\text{(property of subset)}\\
\Rightarrow ~~ \vec 0 ~\epsilon ~ \mathbb{V} ~\text{(property of vector space. Which we proved earlier.)}\\
\Rightarrow ~~ \vec 0 ~ \epsilon ~ \mathbb{W}~ \text{(as they share the same operations)}$$

what??

How can same operations imply that if ##\vec 0## is in ##\mathbb{V}## it also must be in ##\mathbb{W}## ??
What is said here is, that ##0_\mathbb{V} = 0 \cdot w =: 0_\mathbb{W}## is the same vector.
 
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  • #5
Kaguro said:
That's the problem, I don't know that 0##\vec w = \vec 0## in W because it is not a Vector Space yet.

PeroK said:
An important subtlety is that you know that ##0 \vec{w} = \vec{0}## because ##W \subset V## and this property holds for all vectors in ##V##, hence all vectors in ##W##.
 
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  • #6
Oh! Of course..
Now when you put it this way, it seems clear!

Thank you both!:smile:
 
  • #7
Kaguro said:
Let ##\vec u~ \epsilon ~\mathbb{W}##
$$ \Rightarrow~~ 0\vec u ~ \epsilon ~\mathbb{W} ~\text{(closed under scalar multiplication.)}\\
\Rightarrow ~~ 0\vec u ~ \epsilon ~ \mathbb{V} ~\text{(property of subset)}\\
\Rightarrow ~~ \vec 0 ~\epsilon ~ \mathbb{V} ~\text{(property of vector space. Which we proved earlier. ***)}\\
\Rightarrow ~~ 0\vec u = \vec{0} ~\text{(property of vector space. Which we proved earlier.+++)}\\\Rightarrow ~~ \vec 0 ~ \epsilon ~ \mathbb{W}~ \text{(as they share the same operations)}$$

Actually, I would say this is not quite right. I would replace the statement marked *** with the one marked +++.
 
  • #8
PeroK said:
Actually, I would say this is not quite right. I would replace the statement marked *** with the one marked +++.
Yes, the for all elements is the important thing.
 

1. What is a subset?

A subset is a set that contains elements from another set. In other words, all the elements of a subset are also elements of the larger set.

2. What is a subspace?

A subspace is a subset of a vector space that satisfies all the properties of a vector space. This means that it is closed under vector addition and scalar multiplication.

3. When is a subset a subspace?

A subset is a subspace when it satisfies all the properties of a vector space, such as closure under vector addition and scalar multiplication.

4. What are the main properties of a subspace?

The main properties of a subspace are closure under vector addition and scalar multiplication, and containing the zero vector.

5. How can I determine if a subset is a subspace?

To determine if a subset is a subspace, you can check if it satisfies all the properties of a vector space, such as closure under vector addition and scalar multiplication. You can also check if it contains the zero vector.

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