Vector Subspaces: Understanding Closure Properties

In summary, the conversation discusses a question about subspaces and determining if a given set meets the criteria for being a subspace. The set in question consists of a single point at (0, 0) and the conversation goes through the process of showing that this set meets the criteria for being a subspace, including checking for the zero vector, closure under scalar addition, and closure under scalar multiplication. The conversation also includes a discussion about the form of u + v and how it relates to the individual vectors u and v in the set. Ultimately, it is determined that the set does meet the criteria for being a subspace.
  • #1
nayfie
50
0
Hello :)

I've been doing a lot of work on subspaces but have come across this question and need a bit of help!

Homework Statement



[itex]W = {(x, y) \in R^{2} | x^{2} + y^{2} = 0}[/itex]

Homework Equations



1. 0 ∈ W
2. ∀ u,v ∈ W; u+v ∈ W
3. ∀ c ∈ R and u ∈ W; cu ∈ W

The Attempt at a Solution



Check for 0 vector

[itex]x^{2} + y^{2} = 0[/itex]

[itex]0^{2} + 0^{2} = 0[/itex]

[itex]0 = 0[/itex]

Check closure under scalar addition

Let [itex]u = x^{2} + y^{2} = 0[/itex]; let [itex]v = a^{2} + b^{2} = 0[/itex]

[itex]u + v = (x^{2} + a^{2}) + (y^{2} + b^{2}) = 0 + 0 = 0[/itex]

Check for closure under scalar multiplication

[itex]ku = (kx)^{2} + (ky)^{2} = 0[/itex]

[itex]= k^{2}(x^{2} + y^{2}) = 0[/itex]

[itex]x^{2} + y^{2} = \frac{0}{k^{2}}[/itex]

[itex]x^{2} + y^{2} = 0[/itex]

-----------------------------------

I have shown that the zero vector is in the set, and that it is closed under scalar multiplication, however; I'm not sure whether or not it is closed under scalar multiplication.

I have shown that u + v = 0, but, u + v does not have the same form as u and v individually, so I don't think u + v is part of the set?
 
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  • #2
Just took another look at this question and might have solved it.

[itex]u = (a, b), v = (c, d), u + v = (a + c, b + d)[/itex]

[itex](a + c)^{2} + (b + d)^{2} = 0[/itex]

[itex]a^{2} + 2ac + c^{2} + b^{2} + 2bd + d^{2} = 0[/itex]

But, we know from the constraints of the subspace that;

[itex]a^{2} + b^{2} = 0; c^{2} + b^{2} = 0[/itex]

So if we cancel those out, we get;

[itex]2ac + 2bd = 0[/itex]

So in general, scalar addition breaks the constraint.

Does this even make sense or do I need more sleep?
 
  • #3
Yes, you need more sleep.

Think about what your set looks like - W = {(x, y) [itex]\in[/itex] R2| x2 + y2 = 0}.

This set consists of a single point at (0, 0). If u [itex]\in[/itex] W and v [itex]\in[/itex] W, what must u and v be? It should be easy to show that u + v [itex]\in[/itex] W.
 

FAQ: Vector Subspaces: Understanding Closure Properties

1. What is a vector subspace?

A vector subspace is a subset of a vector space that satisfies the closure properties of addition and scalar multiplication. In other words, a vector subspace contains all possible linear combinations of its elements and is closed under addition and scalar multiplication.

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

To determine if a set is a vector subspace, you need to check if it satisfies the closure properties of addition and scalar multiplication. This means that the set must contain the zero vector, be closed under vector addition and scalar multiplication, and contain all possible linear combinations of its elements.

3. What is the significance of closure properties in vector subspaces?

The closure properties of addition and scalar multiplication ensure that the set remains a vector subspace even after performing operations on its elements. This allows us to perform mathematical operations and manipulate vectors within the subspace without leaving it.

4. Can a vector subspace have an infinite number of elements?

Yes, a vector subspace can have an infinite number of elements. As long as the set satisfies the closure properties of addition and scalar multiplication, it can be considered a vector subspace regardless of the number of elements it contains.

5. What are some examples of vector subspaces?

Some examples of vector subspaces include the set of all 2D and 3D vectors, the set of all polynomials of degree n or less, and the set of all solutions to a homogeneous system of linear equations. Any subset of a vector space that satisfies the closure properties can also be considered a vector subspace.

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