Vector Spaces, Subsets, and Subspaces

In summary: The set of all (x,y) where x and y are both integers does not satisfy that requirement, since scalar multiplication by a real number may result in an element that is not in the original set. Therefore, it is an example of a subset that is not a subspace of R^2. In summary, the conversation discusses finding an example of a subset of R^2 that is closed under vector addition and taking additive inverses, but not a subspace. The example given is the set of all (x,y) where x and y are both integers, which does not satisfy the requirement of being closed under scalar multiplication.
  • #1
mrroboto
35
0

Homework Statement




What is an example of a subset of R^2 which is closed under vector addition and taking additive inverses which is not a subspace of R^2?

R, in this question, is the real numbers.


Homework Equations



I know that, for example, V={(0,0)} is a subset for R^2 that is also a subspace, but I can't figure out how something can be a subset and not a subspace.



The Attempt at a Solution



Does this have anything to do with scalar multiplication being closed on the vector space?
 
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  • #2
Think about the set of all (x,y) where x and y are both integers.
 
  • #3
So for example, if we let the subset = (a,b) s.t. a,b are elements of Z. Then it is closed under addition but not under scalar multiplication. i.e. Let (a,b) = (1,3) and multiply by 1/2 for example (which is the example we used to figure it out). Then you get (1/2, 3/2), neither of which are in Z.
 
  • #4
Sure, but it does have additive inverses.
 
  • #5
Dick said:
Think about the set of all (x,y) where x and y are both integers.

or both rational numbers
 
  • #6
mrroboto said:

Homework Statement




What is an example of a subset of R^2 which is closed under vector addition and taking additive inverses which is not a subspace of R^2?

R, in this question, is the real numbers.


Homework Equations



I know that, for example, V={(0,0)} is a subset for R^2 that is also a subspace, but I can't figure out how something can be a subset and not a subspace.
It's very easy to be a subset without being a subspace! Just look at any subset that does not satisfy the requirements for a subpace- what about { (1, 0)}?



The Attempt at a Solution



Does this have anything to do with scalar multiplication being closed on the vector space?
In order for a subset to be a subspace, it must be closed under addition, have additive inverses, and be closed under scalar multiplication. Since you are asked about a subset that IS closed under addition and has additive inverses, looks like there is only one thing left!
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors and two operations: vector addition and scalar multiplication. It follows a set of axioms, such as closure, commutativity, and associativity, and is typically denoted by V.

2. What are the requirements for a subset to be a subspace?

For a subset to be considered a subspace, it must satisfy three conditions: it must contain the zero vector, it must be closed under vector addition, and it must be closed under scalar multiplication. In other words, it must be a vector space in its own right.

3. How do you determine if a subset is a subspace?

To determine if a subset is a subspace, you can use the three conditions mentioned above. If the subset satisfies all three conditions, then it is a subspace. Another method is to check if the subset is spanned by a set of vectors from the original vector space.

4. Can a subspace have a dimension greater than its parent vector space?

No, a subspace cannot have a dimension greater than its parent vector space. The dimension of a subspace is always less than or equal to the dimension of its parent vector space. This is because a subspace is a subset of the parent vector space and cannot contain more linearly independent vectors than the parent space.

5. How are subspaces related to linear independence?

Subspaces and linear independence are closely related. A set of vectors is linearly independent if none of the vectors can be written as a linear combination of the other vectors. Subspaces, being a set of vectors, can also have linearly independent vectors. In fact, a subspace is said to have a basis, which is a set of linearly independent vectors that span the subspace.

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