Determine if all vectors of form (a,0,0) are subspace of R3

In summary, the conversation discusses how to prove both closure axioms for a vector subspace. It is suggested to pick a vector arbitrarily and determine the orthogonal complement of the set containing that vector. It is also mentioned that this method can be used in proofs of completeness in the l_{2} space.
  • #1
7sqr
4
0
I have the feeling that it is, but I am not really sure how to start the proof. I know I have to prove both closure axioms; u,v ∈ W, u+v ∈ W and k∈ℝ and u∈W then ku ∈ W.
Do I just pick a vector arbitrarily say a vector v = (x,y,z) and go from there?
 
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  • #2
pick vectors that are of the form (a,0,0), and otherwise arbitrary.
 
  • #3
proving u+v
let u, v ∈ W
u=(a1,0,0) v= (a2,0,0)
u+v = (a1+a2, 0,0) ∈ W
∴u+v ∈ W

am i anywhere close to doing that right?
 
  • #4
Yes, that's the right way to do it.
 
  • #5
Thank you guys, I really appreciate the help.
 
  • #6
The usual way is to determine the subspace ⊥ (a, 0, 0) - which is the subspace spanned by all vectors (x, y, z) such that (a, 0, 0)⋅(x, y, z) = 0. Since the scalar product is ax, this means that x = 0 and thus the normal subspace is spanned by (0, 1, 0) and (0, 0, 1). Therefore the original subspace has dimension 1 and is spanned by (1, 0, 0).
 
  • #7
Svein said:
The usual way is to determine the subspace ⊥ (a, 0, 0) - which is the subspace spanned by all vectors (x, y, z) such that (a, 0, 0)⋅(x, y, z) = 0. Since the scalar product is ax, this means that x = 0 and thus the normal subspace is spanned by (0, 1, 0) and (0, 0, 1). Therefore the original subspace has dimension 1 and is spanned by (1, 0, 0).
This is true, but all you have to do to see it is to write ##(a,0,0)=a(1,0,0,)##.
 
  • #8
Fredrik said:
This is true, but all you have to do to see it is to write (a,0,0)=a(1,0,0,)(a,0,0)=a(1,0,0,).

Yes, in this case it is easy. But if the specification had been more complicated, having a standard recipe is not a bad idea.
 
  • #9
Svein thanks for that, it clears up the concept a little more.
 
  • #10
The orthogonal complement of a set ##S## is defined as the set ##S^\perp## of all vectors that are orthogonal to all the vectors in ##S##.

What Svein described is how to find the orthogonal complement of the orthogonal complement of the set W. This is always a subspace, even if W isn't. If you know this, you can find out if ##W## is a subspace by checking if ##W^{\perp\perp}=W##. This is rarely (never?) the easiest way to do it.
 
  • #11
Fredrik said:
The orthogonal complement of a set ##S## is defined as the set ##S^\perp## of all vectors that are orthogonal to all the vectors in ##S##.

What Svein described is how to find the orthogonal complement of the orthogonal complement of the set W. This is always a subspace, even if W isn't. If you know this, you can find out if ##W## is a subspace by checking if ##W^{\perp\perp}=W##. This is rarely (never?) the easiest way to do it.
Well, in the [itex]l_{2}[/itex] space (with the standard scalar product), this algorithm is used in proofs of completeness...
 

Related to Determine if all vectors of form (a,0,0) are subspace of R3

1. What is a vector?

A vector is a mathematical object that has both magnitude (size) and direction. It is often represented as an arrow pointing in a specific direction and has a specific length. In physics and engineering, vectors are used to represent forces, velocities, and other physical quantities.

2. What is a subspace?

A subspace is a subset of a vector space that is closed under the operations of addition and scalar multiplication. This means that any vector in the subspace, when added or multiplied by a scalar, will still remain in the subspace. In other words, the subspace contains all linear combinations of its vectors.

3. How can we determine if all vectors of form (a,0,0) are a subspace of R3?

In order for a set of vectors to be a subspace, it must satisfy three conditions: it must contain the zero vector, it must be closed under addition, and it must be closed under scalar multiplication. Therefore, to determine if all vectors of form (a,0,0) are a subspace of R3, we need to check if these three conditions are met.

4. What are the three conditions for a subspace?

The three conditions for a subspace are: 1) it must contain the zero vector, 2) it must be closed under addition, and 3) it must be closed under scalar multiplication. A set of vectors that satisfies these conditions is considered a subspace of the vector space it is a part of.

5. Can you give an example of a vector that is not a subspace of R3?

Yes, an example of a vector that is not a subspace of R3 is the set of all vectors with only two components, (a,b). This set does not contain the zero vector, and therefore does not satisfy the first condition for a subspace. It also does not contain all linear combinations of its vectors, so it does not satisfy the third condition. Therefore, it is not a subspace of R3.

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