Why is it confusing to determine whether sets form subspaces in ℝ2?

In summary: So far I understand that when applying the zero vector, both sets remain closed under addition. But how can you show this for all vectors?To show that a set is closed under addition, you must show that for any two vectors in the set, their sum is also in the set. For example, let's take the set from part A, {(x1, x2)T | x1 + x2 = 0}. We can choose any two vectors from this set, for example, (1, -1)T and (2, -2)T. Their sum is (1, -1)T + (2, -2)T = (3, -3)T. However, (
  • #1
kr0z3n
8
0

Homework Statement



Determine whether the following sets form subspaces of ℝ2:
(a) {(x1, x2)T | x1 + x2 = 0}

(b) {(x1, x2)T | x1 * x2 = 0}

Homework Equations



The Attempt at a Solution


I know that a is a subspace and b is not, but I would like to know why.
For part A, I let x=[c, -c]T
∂[c,-c]= [∂c, -∂c]
[c, -c] + [ ∂, -∂] = [c+∂, -c-∂]
Thus S is closed under scalar multiplication and addition.
But what if I let x=[1, -1]? Wouldn't that break the conditions since
∂[1,-1]=[∂,-∂] and [1,-1] + [1, -1]= [2,-2]?

And for part B the book states "No, this is not a subspace. Every element of S has at
least one component equal to 0. The set is closed under scalar multiplication, but
not under addition. For example, both (1, 0)T and (0,1)T are elements of S, but their sum is not."

But can't I let [x1 and x2] be the zero vectors and S would be a subspace?

I am confused about how sometimes I can multiply or add using variables and other times I have to use constants. Can someone please explain to me. Thanks
 
Last edited:
Physics news on Phys.org
  • #2
kr0z3n said:

Homework Statement



Determine whether the following sets form subspaces of ℝ2:
(a) {(x1, x2)T | x1 + x2 = 0}

(b) {(x1, x2)T | x1 * x2 = 0}

Homework Equations



The Attempt at a Solution


I know that a is a subspace and b is not, but I would like to know why.
For part A, I let x=[c, -c]T
∂[c,-c]= [∂c, -∂c]
[c, -c] + [ ∂, -∂] = [c+∂, -c-∂]
Thus S is closed under scalar multiplication and addition.
But what if I let x=[1, -1]? Wouldn't that break the conditions since
∂[1,-1]=[∂,-∂] and [1,-1] + [1, -1]= [2,-2]?

well, x1=2, x2=-2, so x1+x2=0, so it's still a member of the subspace.
 
  • #3
In order for a set to form a subspace, it must meet the three criteria. It must contain the identity, and be closed under addition and scalar multiplication.

Closure under an operation means that when the operation is performed on any two elements from a set, it will produce another element from the set.

For example, for any two real numbers a and b, a + b is still a real number. Thus a + b is still in the set of real numbers. Hence, the real numbers are closed under addition.

The key fact is that the operation must produce an element from the set for any two elements. Every possible combination of elements must produce another element in the set when the operation is applied on them. So if you can find two real numbers that, when added together, produce a complex number, then you would have proven that the real numbers are not closed under addition.

For part B you want to take any two vectors from R2, such that both vectors are in the set, but their sum is not. In order for a vector to be an element of set B, it needs to have components x1, x2 such that x1*x2=0.

Your answer sheet gives you two elements that fit the definition of set B, but when you add them together, the resulting vector has components that do not fit the definition. Hence the result of addition on the set B is not contained in B. So the set B is not closed under addition.

So your thought to let x1 and x2 be zero is insufficient to show closure, since closure demands the operation holds for every element of the set.
 
  • #4
kr0z3n said:
And for part B the book states "No, this is not a subspace. Every element of S has at
least one component equal to 0. The set is closed under scalar multiplication, but
not under addition. For example, both (1, 0)T and (0,1)T are elements of S, but their sum is not."

But can't I let [x1 and x2] be the zero vectors and S would be a subspace?
It is not sufficient that there exist vectors of the set whose sum is in the set, it must be true that the sum of any two vectors in the set is in the set.

I am confused about how sometimes I can multiply or add using variables and other times I have to use constants. Can someone please explain to me. Thanks
I have no idea what you mean by this. What "variables" or "constants"? Could you give an example?
 
  • #5
After reading all the comments, I understand it now! Thanks to all who replied!
 
  • #6


I have read through these posts and still don't seem to understand how to determine whether the following sets form subspaces of ℝ[itex]^{2}[/itex] :
(a) {(x[itex]_{1}[/itex] , x[itex]_{2}[/itex] )[itex]^{T}[/itex] | x[itex]_{1}[/itex] + x[itex]_{2}[/itex] = 0}
(b) {(x[itex]_{1}[/itex] , x[itex]_{2}[/itex] )[itex]^{T}[/itex] | x[itex]_{1}[/itex]x[itex]_{2}[/itex] = 0}

I do understand that the set must remain closed under addition an scalar multiplication. However I don't understand how to show this.
 

FAQ: Why is it confusing to determine whether sets form subspaces in ℝ2?

What is a subspace?

A subspace is a subset of a vector space that meets certain criteria. It must contain the zero vector, be closed under vector addition, and be closed under scalar multiplication.

How is a subspace different from a vector space?

A subspace is a subset of a vector space that also meets the criteria of being closed under vector addition and scalar multiplication. It is a smaller space within a larger space.

What is the importance of understanding subspaces?

Understanding subspaces is important in linear algebra and many other fields of mathematics. Subspaces allow us to simplify complex vector spaces and make calculations easier. They also have many applications in areas such as computer graphics and physics.

How do you determine if a set is a subspace?

To determine if a set is a subspace, you must check if it contains the zero vector, is closed under vector addition, and is closed under scalar multiplication. If it meets all three criteria, then it is a subspace.

Can a subspace have more than one basis?

Yes, a subspace can have more than one basis. A basis is a set of vectors that span the subspace, and there can be many different sets of vectors that can span the same subspace.

Back
Top