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

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Discussion Overview

The discussion revolves around determining whether all vectors of the form (a, 0, 0) constitute a subspace of R³. Participants explore the necessary conditions for a set to be a subspace, including closure under addition and scalar multiplication, and discuss various approaches to proving this concept.

Discussion Character

  • Homework-related
  • Mathematical reasoning
  • Technical explanation

Main Points Raised

  • One participant expresses uncertainty about how to start the proof and suggests picking an arbitrary vector.
  • Another participant advises to specifically pick vectors of the form (a, 0, 0) for the proof.
  • A participant demonstrates closure under addition by showing that the sum of two vectors of the form (a1, 0, 0) and (a2, 0, 0) remains in the same form.
  • Several participants agree that the approach to proving the subspace is correct.
  • One participant introduces the concept of the orthogonal complement and discusses its relevance to determining subspaces, noting that the orthogonal complement of a subspace is always a subspace.
  • Another participant mentions that checking if the double orthogonal complement equals the original set can determine if it is a subspace, although this method is not always the simplest.

Areas of Agreement / Disagreement

Participants generally agree on the approach to proving that the set of vectors of the form (a, 0, 0) is a subspace, but there are multiple methods discussed, including the use of orthogonal complements, which introduces some complexity and differing perspectives on the best approach.

Contextual Notes

Some participants note that the specification of the problem could affect the complexity of the proof, suggesting that a standard method may be beneficial in more complicated cases.

Who May Find This Useful

Students and individuals interested in linear algebra, particularly those studying subspaces and vector spaces, may find this discussion beneficial.

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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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pick vectors that are of the form (a,0,0), and otherwise arbitrary.
 
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?
 
Yes, that's the right way to do it.
 
Thank you guys, I really appreciate the help.
 
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).
 
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,)##.
 
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.
 
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 l_{2} space (with the standard scalar product), this algorithm is used in proofs of completeness...
 

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