Proving Vector Spaces to Solving Homework Problems

In summary, the conversation discusses a question about proving whether a given set is a vector space or not. The approach of using ten axioms to determine if a set belongs to a vector space is mentioned. The main focus is on checking whether the set is closed under vector addition and scalar multiplication, and it is suggested to pick a specific element of the set and see if it satisfies the conditions. The importance of the x1^2=x2^3 relation in determining which vectors are in the set is also emphasized.
  • #1
phys2
22
0

Homework Statement



Hi, I am really having trouble with questions regarding proving whether a given set is a vector space or not.

So one of the questions is [ x ε R2|x12=x23 ]

So I have to prove whether the following set is a vector space

Homework Equations





The Attempt at a Solution



Having a peek at the textbook, it tells me that there are ten axioms that satisfy whether a set belongs to a vector space.

What I did was go x12 - x23 = 0

u+ v = v + u -For this one, I did the following: I let x1 and x2 have a value each and named it a vector u, then I let x1 and x2 have some other values and named it a vector v.

So x1 = 1 and x2 = 2 and u = 12 - 23
And x1 = 4 and x2 = 5 and v = 42 - 53

u + v = v + u should work out and I used the same method for the rest of the axioms...I need to know two things

(a) Is the method I am doing correct? If not, could you point me in the right direction?
(b) How do I go about checking the first axiom for the above set u + v lies in the set. If I do the same old substitution, all i get is a number, whatever it is!

Thanks

 
Physics news on Phys.org
  • #2
Many of the axioms will be satisfied automatically because this set (let's give it a name: [itex]S[/itex]) is a subset of a vector space.

For example, if [itex]u[/itex] and [itex]v[/itex] are in [itex]S[/itex], then they are also in [itex]\mathbb{R}^2[/itex], and since [itex]\mathbb{R}^2[/itex] is a vector space, addition is commutative. Therefore [itex]u + v = v + u[/itex].

The main things to check are whether [itex]S[/itex] is closed under vector addition and scalar multiplication. The fact that [itex]S[/itex] is defined in terms of squares and cubes of the vector coordinates is a pretty good indication that [itex]S[/itex] is not a vector space. This is because squaring and cubing are both nonlinear operations, and vector spaces are all about linearity.

Try picking a specific element of [itex]S[/itex], for example [itex]v = (1,1)[/itex]. Is there a scalar multiple of [itex]v[/itex] that is not in [itex]S[/itex]? Is [itex]v + v[/itex] in [itex]S[/itex]?
 
  • #3
Yea, that is really the part (b) of the problem that I faced. I don't think I can take v = (1,1) though since both numbers have to be different x12 - x23 Anyway, even if I take two different numbers, what I get is another number. How do I know whether that number is part of set S or not?

For instance, if I take v = (1,2), I will get 1-8 = -7. How do I know -7 is in S?

I did check all the rules using the method that you have mentioned, taking numbers and figuring out whether the axioms are satisfied...but I wasn't sure whether that was a reasonable method...but since you argue in the same way, I guess it is.

Thanks for your input.
 
  • #4
phys2 said:
Yea, that is really the part (b) of the problem that I faced. I don't think I can take v = (1,1) though since both numbers have to be different x12 - x23 Anyway, even if I take two different numbers, what I get is another number. How do I know whether that number is part of set S or not?

For instance, if I take v = (1,2), I will get 1-8 = -7. How do I know -7 is in S?
I think you're misunderstanding the condition [itex]x_1^2 = x_2^3[/itex]. The vector [itex]v[/itex] is in [itex]S[/itex] if and only if its components satisfy [itex]x_1^2 = x_2^3[/itex]. In your example, [itex]x_1 = 1[/itex] and [itex]x_2 = 2[/itex], so [itex]x_1^2 = 1[/itex] and [itex]x_2^3 = 8[/itex]. Since [itex]1 \neq 8[/itex], this means that [itex]v[/itex] is not in [itex]S[/itex].

Now consider my example again: [itex]v = (1,1)[/itex]. In this case, [itex]x_1 = 1[/itex] and [itex]x_2 = 1[/itex], so [itex]x_1^2 = 1[/itex] and [itex]x_2^3 = 1[/itex]. Therefore [itex]x_1^2 = x_2^3[/itex], so [itex]v \in S[/itex].

So now that we have established that [itex]v = (1,1)[/itex] is in [itex]S[/itex], you can easily use this to show that [itex]S[/itex] is not closed under addition and scalar multiplication, so [itex]S[/itex] is not a vector space. It doesn't matter that it satisfies the other axioms. If it isn't closed under addition and scalar multiplication, it cannot be a vector space.

To show that [itex]S[/itex] is not closed under addition and scalar multiplication, consider the vector [itex]v + v = (2,2)[/itex]. If [itex]S[/itex] is a vector space, then [itex](2,2)[/itex] must be in [itex]S[/itex]. Is it?
 
Last edited:
  • #5
To show that S is not closed under addition and scalar multiplication, consider the vector v+v=(2,2). If S is a vector space, then (2,2) must be in S. Is it?

(2,2) is not in S because 22 = 4 and 23 = 8 and 4≠8.

I am still confused about showing that S is not closed under addition and scalar multiplication.

With addition, I know that the axiom is u + v = v + u

So if I take v = (2,2), u = (1,2), do I just do it the normal vector addition way; adding the x1s together and the x2s together?

So v+ u = [ (22 + 12) , ( 23 + 23) ] = (5, 16)

u + v= [ (12 + 22) , (23 + 23) ] = (5,16)

Seems like it is closed under vector addition or I am probably doing something wrong?
 
  • #6
phys2 said:
So if I take v = (2,2), u = (1,2), do I just do it the normal vector addition way; adding the x1s together and the x2s together?

So v+ u = [ (22 + 12) , ( 23 + 23) ] = (5, 16)
Addition is defined in the usual way: [itex](2,2) + (1,2) = (2+1, 2+2) = (3,4)[/itex]. The [itex]x_1^2 = x_2^3[/itex] relation is just a constraint which tells you which vectors are in [itex]S[/itex]. It has nothing to do with how you add vectors or multiply by scalars.
 
  • #7
The x21=x32 relation is just a constraint which tells you which vectors are in S. It has nothing to do with how you add vectors or multiply by scalars.

Oh, I think I get it. What we have done so far is find vectors that belong or do not belong to S. Example: v = (1,2) does not belong to S and v= (1,1) belongs to S.

But v = (1,1), even if it belongs to S, that does not necessarily make it a vector space, I need to do do the addition and scalar multiplication to figure it out. Is my understanding correct so far?

If S is a vector space, then (2,2) must be in S.

v = (2,2) is not in S so S is not a vector space? What I know about vector spaces is that, take R2 for an example. R2 is a vector space because you can take any linear combinations of vectors (x1, x2) and they all lie in R2.
 
  • #8
phys2 said:
Oh, I think I get it. What we have done so far is find vectors that belong or do not belong to S. Example: v = (1,2) does not belong to S and v= (1,1) belongs to S.

But v = (1,1), even if it belongs to S, that does not necessarily make it a vector space, I need to do do the addition and scalar multiplication to figure it out. Is my understanding correct so far?
Yes, that's right.

v = (2,2) is not in S so S is not a vector space? What I know about vector spaces is that, take R2 for an example. R2 is a vector space because you can take any linear combinations of vectors (x1, x2) and they all lie in R2.
Right. Now, we already established that v = (1,1) is in S. Now let's take a linear combination of elements of S: (1,1) + (1,1) = (2,2) is a linear combination, namely 1v + 1v. If S is a vector space, then S must contain all linear combinations of its elements. Therefore if (2,2) is not in S, then S cannot be a vector space.
 
  • #9
Yes, I finally get it now. Using the same method, I should be able to get through all the problems.

Thanks a lot for your help!
 

Related to Proving Vector Spaces to Solving Homework Problems

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of objects, called vectors, and a set of operations that can be performed on those vectors. The operations include addition and scalar multiplication, and they must satisfy certain properties to be considered a vector space.

2. What are the properties that a vector space must satisfy?

A vector space must satisfy 10 properties, which include closure under addition and scalar multiplication, associativity and commutativity of addition, existence of an additive identity element, existence of additive inverses, distributivity of scalar multiplication over addition, and compatibility of scalar multiplication with the field of scalars.

3. What is the difference between a vector space and a subspace?

A subspace is a subset of a vector space that also satisfies the properties of a vector space. In other words, a subspace is a smaller vector space that is contained within a larger vector space. A subspace must contain the zero vector and be closed under addition and scalar multiplication.

4. How are linear transformations related to vector spaces?

Linear transformations are functions that map vectors from one vector space to another. They preserve the structure of the vector space, meaning that the properties of the vector space are still satisfied after the transformation. Linear transformations are important in linear algebra because they can be represented by matrices, which allow for efficient calculations.

5. What are some real-world applications of vector spaces?

Vector spaces have many applications in physics, engineering, and computer science. They are used to model physical systems, such as forces acting on objects, and to solve problems in optimization and data analysis. In computer graphics, vector spaces are used to represent and manipulate 2D and 3D objects, and in machine learning, they are used to represent and process data.

Similar threads

  • Calculus and Beyond Homework Help
Replies
8
Views
753
  • Calculus and Beyond Homework Help
Replies
1
Views
1K
  • Calculus and Beyond Homework Help
Replies
7
Views
462
  • Calculus and Beyond Homework Help
Replies
0
Views
481
  • Calculus and Beyond Homework Help
Replies
4
Views
1K
  • Calculus and Beyond Homework Help
Replies
9
Views
1K
  • Calculus and Beyond Homework Help
Replies
15
Views
2K
  • Calculus and Beyond Homework Help
Replies
16
Views
2K
  • Calculus and Beyond Homework Help
Replies
15
Views
838
  • Calculus and Beyond Homework Help
Replies
18
Views
1K
Back
Top