How to determine the smallest subspace?

Click For Summary
The smallest subspace containing two subspaces U and W in a vector space V is their sum, denoted as U+W, which includes all linear combinations of elements from both subspaces. To determine if one subspace is smaller than another, it is necessary to show that it is a subset of the other, meaning U is smaller than W if U is contained within W. In cases where neither subspace is a subset of the other, such as U = {(x,0,0) | x ∈ ℝ} and W = {(0,y,0) | y ∈ ℝ}, neither can be considered smaller. The dimension of a subspace is crucial in this determination, as it reflects the number of independent directions it spans. Ultimately, the closure under addition confirms that U+W is indeed the smallest subspace containing both U and W.
maNoFchangE
Messages
115
Reaction score
4
Two examples are:
  1. Given two subspaces ##U## and ##W## in a vector space ##V##, the smallest subspace in ##V## containing those two subspaces mentioned in the beginning is the sum between them, ##U+W##.
  2. The smallest subspace containing vectors in the list ##(u_1,u_2,...,u_n)## is ##\textrm{span}(u_1,u_2,...,u_n)##.
How can one know how small a subspace is? initially I thought it was determined from the number of elements in the subspace, but there infinite number of elements. Can also someone please give an example by giving two subspaces and show the ways to compare which one is smaller than which?
 
Physics news on Phys.org
maNoFchangE said:
Two examples are:
  1. Given two subspaces ##U## and ##W## in a vector space ##V##, the smallest subspace in ##V## containing those two subspaces mentioned in the beginning is the sum between them, ##U+W##.
  2. The smallest subspace containing vectors in the list ##(u_1,u_2,...,u_n)## is ##\textrm{span}(u_1,u_2,...,u_n)##.
How can one know how small a subspace is? initially I thought it was determined from the number of elements in the subspace, but there infinite number of elements. Can also someone please give an example by giving two subspaces and show the ways to compare which one is smaller than which?
For 1:
##U+W## is the smallest subspace containing ##U## and ##W## means that if ##Z## is as subspace of ##V## with ##U \subseteq Z, W \subseteq Z##, then ##U+W \subseteq Z##.
Similarly for 2. Any subspace containing ##(u_1,u_2,...,u_n)## will also contain ##\textrm{span}(u_1,u_2,...,u_n)##.

Given two subpaces ##U, W##, you show that ##U## is smaller than ##W## by showing ##U \subset W##.
It is of course possible that for two subspaces, neither is smaller than the other.
Example in ##\mathbb R³##:
##U=\{(x,0,0)|x \in \mathbb R\}##,##W=\{(0,y,0)|y \in \mathbb R\}##. Neither subspace is a subset of the other, so there is no smallest of the two.
##U+W=\{(x,y,0)|x,y \in \mathbb R\}## is the smallest subspace of ##\mathbb R³## containing both ##U## and ##W##.
 
Last edited:
  • Like
Likes maNoFchangE
maNoFchangE said:
Two examples are:
  1. Given two subspaces ##U## and ##W## in a vector space ##V##, the smallest subspace in ##V## containing those two subspaces mentioned in the beginning is the sum between them, ##U+W##.
  2. The smallest subspace containing vectors in the list ##(u_1,u_2,...,u_n)## is ##\textrm{span}(u_1,u_2,...,u_n)##.
How can one know how small a subspace is? initially I thought it was determined from the number of elements in the subspace, but there infinite number of elements. Can also someone please give an example by giving two subspaces and show the ways to compare which one is smaller than which?

It is the number of dimensions in the subspace. A line has one, a plane two, a solid three, etc.
 
Samy_A said:
Given two subpaces U,WU,WU, W, you show that UUU is smaller than WWW by showing U⊂WU⊂WU \subset W.
Thanks, that really makes sense.
Samy_A said:
For 1:
##U+W## is the smallest subspace containing ##U## and ##W## means that if ##Z## is as subspace of ##V## with ##U \subseteq Z, W \subseteq Z##, then ##U+W \subseteq Z##.
I get that ##U\subseteq U+W## and ##W\subseteq U+W##, therefore both ##U## and ##W## are smaller than ##U+W##. But I have a problem with convincing myself that the smallest subspace which contains ##U## and ##W## together is indeed ##U+W##, in other words, how can we be sure that there are no subspaces in ##U+W## which can contain both ##U## and ##W##. I am thinking that it may be because of the requirement of the closure under addition which must be true for a subset to be called subspace, but it's still hazy in my mind and I cannot sort what I am thinking into an ordered logical reasoning.
Hornbein said:
It is the number of dimensions in the subspace. A line has one, a plane two, a solid three, etc.
Do you mean, the smallest subspace which contain ##U## and ##W## must have the same dimension as a subspace formed by adding the two subspaces, i.e. ##U+W##?
 
maNoFchangE said:
I get that ##U\subseteq U+W## and ##W\subseteq U+W##, therefore both ##U## and ##W## are smaller than ##U+W##. But I have a problem with convincing myself that the smallest subspace which contains ##U## and ##W## together is indeed ##U+W##, in other words, how can we be sure that there are no subspaces in ##U+W## which can contain both ##U## and ##W##. I am thinking that it may be because of the requirement of the closure under addition which must be true for a subset to be called subspace, but it's still hazy in my mind and I cannot sort what I am thinking into an ordered logical reasoning.
(bolding mine)
What I bolded in your post is indeed the key.
A subspace that contains both ##U## and ##W## must contain all the sums of elements of ##U## and ##W## (as it must be closed under addition). In other words, it must contain ##U+W##. As ##U+W## is a subspace, we conclude it is the smallest subspace containing ##U## and ##W##.
 
Alright thanks, at least now I am convinced that I have been going in the right direction in this matter.
 
I am studying the mathematical formalism behind non-commutative geometry approach to quantum gravity. I was reading about Hopf algebras and their Drinfeld twist with a specific example of the Moyal-Weyl twist defined as F=exp(-iλ/2θ^(μν)∂_μ⊗∂_ν) where λ is a constant parametar and θ antisymmetric constant tensor. {∂_μ} is the basis of the tangent vector space over the underlying spacetime Now, from my understanding the enveloping algebra which appears in the definition of the Hopf algebra...

Similar threads

  • · Replies 15 ·
Replies
15
Views
4K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 3 ·
Replies
3
Views
5K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 19 ·
Replies
19
Views
5K