Exploring Vector Subspaces and the Zero Vector

In summary, the conversation discusses the existence of the zero vector in a vector subspace. It is agreed that the zero vector must be defined in the original vector space, but there is some confusion about whether it also needs to be explicitly defined in the subspace. It is clarified that the zero vector must be an element of the subspace for it to be considered a subspace. The definition of a subspace is also discussed.
  • #1
matheinste
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Hello Everyone.

In a thread in this forum relating to a problem on Subspaces I read that as long as a Vector SubSpace is closed under addition and multiplication we always have the zero vector. I can see that we can always get the zero vector but do we not have to define a zero vector first as given in the Vector Space axioms or can we make it by manipulation IE multiplying a vector by minus one and adding this to the original vector. This seems somehow contrived to me so is it OK to get the zero vector in this manner or does it first need to exist by definition.If we can always get it by manipulation in this way it seems unnecessary to require it by definition.

( I know that we are allowed the Zero Vector alone to be a vector space and so cannot get it any other way in this case )

Thanks for any clarification on this query as I am still learning and want to understand fully.

Matheinste
 
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  • #2
Remember that you are talking about a subspace of an already given vector space. Since the subspace must first be a subset of that space, and use the same operation, you already know that the zero vector exists as part of the original vector space.

Suppose V is a vector space with operations of scalar multiplication and vector addition already defined, 0 as its zero vector. If U is a subset of V closed under both scalar multiplication and vector addition (as defined in V) then for any vector v, (-1)v is in U (closure under scalar multiplication) and so v+ (-1)v= 0. That is, the 0 vector defined in V must also be in U. Since for any vector v in V, v+ 0= v, for any vector u in U (which is also in V) u+ 0= u and so 0 is also the zero vector in U.
 
  • #3
Thanks HallsofIvy.

I was forgetting that the zero vector was already defined in the original vector space.

Matheinste.
 
  • #4
Why all this adding v to -v? It is a trivial exercise in the early weeks of the course to show that 0v=0 for any v, so any set closed under scalar multiplication contains 0 - you do not even need closed under addition. (Actually, you probably do in the proof that 0v=0, I suppose, but given that one is a *subset* of the other with the same operations, I'm OK.)
 
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  • #5
The reason that we require the 0 vector to be an element of the subset for it to be a subspace is simply to rule out the empty set. Surely the empty set is a subset of any vector space, and the empty set is closed under linear combinations. Thus we need another criteria somewhere in order to rule out the empty set.
 
  • #6
A subspace is defined to be a non-empty set satisfying certain rules. 0 is not a priori specified as an element of that non-empty set.
 
  • #7
Thanks for all help and comments.

I think I have realized where I was going wrong. When testing that a vector space is a subspace of another vector space I was wrongly assuming that because we can make the zero vector by manipulating vectors within the possible subspace that the zero vector was in that possible subspace. Of course it may not be. To prove that a vector space is a subspace I need to show that it contains the zero vector and not just that we can make the zero vector with elements from the possible subspace.

Does this seem OK.

Thanks. Matheinste.
 
  • #8
matheinste said:
To prove that a vector space is a subspace I need to show that it contains the zero vector and not just that we can make the zero vector with elements from the possible subspace.

Does this seem OK.

Not quite. If you can make the zero vector with elements from the subset, then the zero vector is in your subset, and you've already shown it. The key is that there actually has to be an element in your subset in order to do that.

I assume your definition of subspace is something like this:

Let [itex]V[/itex] be a vector space. Then a subset [itex]U[/itex] of [itex]V[/itex] is a subspace if and only if both of the following hold:

1. The zero vector is in [itex]U[/itex].
2. [itex]U[/itex] is closed under linear combinations.

Maybe you'd be more at ease with the following (equivalent) definition:

Let [itex]V[/itex] be a vector space. Then a subset [itex]U[/itex] of [itex]V[/itex] is a subspace if and only if both of the following hold:

1. [itex]U[/itex] is nonempty.
2. [itex]U[/itex] is closed under linear combinations.

Can you see why they are equivalent?
 
  • #9
Thanks Moo Of Doom.

I have thoughtr about it. If U is nonempty it must contain at least one ( for our purposes one vector ) element. If this element is the zero vector there is no more to be said. If it contains a non zero vector then by the vector space axioms we can make the zero vector ( among others ). ?

Matheinste.
 

1. What is a vector subspace?

A vector subspace is a subset of a vector space that satisfies the three properties of closure, addition, and scalar multiplication. This means that any linear combination of vectors in the subspace will also be in the subspace, and the subspace is closed under addition and scalar multiplication.

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

To determine if a set of vectors is a subspace, you need to check if it satisfies the three properties of closure, addition, and scalar multiplication. If all three properties are satisfied, then the set of vectors is a subspace. If not, then it is not a subspace.

3. What is the zero vector in a vector subspace?

The zero vector in a vector subspace is the vector that has all components equal to zero. It is also known as the additive identity, as it does not change the result when added to any other vector in the subspace. The zero vector is always included in a vector subspace.

4. Can the zero vector be a subspace on its own?

No, the zero vector cannot be a subspace on its own. This is because it does not satisfy the property of closure. Any scalar multiple of the zero vector will also be the zero vector, and the zero vector does not contain any other vectors that can be added together to form a new vector.

5. Why is it important to understand vector subspaces and the zero vector?

Understanding vector subspaces and the zero vector is important because they are fundamental concepts in linear algebra and have various applications in fields such as physics, engineering, and computer science. They also play a crucial role in solving systems of linear equations and understanding the properties of vector spaces.

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