Prove that the set T:={x∈Rn:Ax∈S} is a subspace of Rn.

  • Thread starter Thread starter squenshl
  • Start date Start date
  • Tags Tags
    Set Subspace
Click For Summary

Homework Help Overview

The problem involves proving that the set T, defined as T:={x∈Rn:Ax∈S}, is a subspace of Rn, where S is a subspace of Rm and A is an m×n matrix. The discussion centers around the conditions that must be satisfied for T to be considered a subspace.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the three conditions necessary for T to be a subspace, including the presence of the zero vector, closure under addition, and closure under scalar multiplication. Some participants question the correct application of these conditions and the definitions of the sets involved.

Discussion Status

The discussion is ongoing, with participants providing feedback on each other's reasoning and clarifying the definitions and relationships between the sets T and S. There is no explicit consensus yet, as participants are still refining their arguments and addressing misunderstandings.

Contextual Notes

Participants note the importance of correctly identifying the elements of T and S, as well as the implications of S being a subspace. There is an acknowledgment of the need to demonstrate the properties of T using elements specifically from T rather than mixing elements from T and S incorrectly.

squenshl
Messages
468
Reaction score
4
Homework Statement
1. Let ##S## be a subspace of ##\mathbb{R}^m## and let ##A## be a ##m\times n## matrix.
Prove that the set ##T:= \left\{\mathbf{x}\in \mathbb{R}^n:A\mathbf{x}\in S\right\}## is a subspace of ##\mathbb{R}^n##.
Relevant Equations
None
1. Let's show the three conditions for a subspace are satisfied:
Since ##\mathbf{0}\in \mathbb{R}^n##, ##A\times \mathbf{0} = \mathbf{0}\in S##.
Suppose ##x_1, x_2\in \mathbb{R}^n##, then ##A(x_1+x_2) = A(x_1)+A(x_2)\in S##.
Suppose ##x\in S## and ##\lambda\in \mathbb{R}##, then ##A(\lambda x) = \lambda A(x)\in S##.

Is this correct?
 
Last edited:
Physics news on Phys.org
squenshl said:
Problem Statement: 1. Let ##S## be a subspace of ##\mathbb{R}^m## and let ##A## be a ##m\times n## matrix.
Prove that the set ##T:= \left\{\mathbf{x}\in \mathbb{R}^n:A\mathbf{x}\in S\right\}## is a subspace of ##\mathbb{R}^n##.
Relevant Equations: None

1. Let's show the three conditions for a subspace are satisfied:
Since ##\mathbf{0}\in \mathbb{R}^n##, ##A\times \mathbf{0} = \mathbf{0}\in S##.
Suppose ##x_1, x_2\in \mathbb{R}^n##, then ##A(x_1+x_2) = A(x_1)+A(x_2)\in S##.
Suppose ##x\in S## and ##\lambda\in \mathbb{R}##, then ##A(\lambda x) = \lambda A(x)\in S##.

Is this correct?

Not really. At least the way you write it down does not fully convince me that you have the right idea.

You have to take ##x_1,x_2## in ##T## and then show that ##x_1+x_2\in T##.

Similarly you have to take ##x\in T, \lambda \in \mathbb{R}## and show that ##\lambda x\in T##.

Please also indicate where you use that ##S## is a subspace.

Addendum: Consider the linear transformation $$L:\mathbb{R}^n \to \mathbb{R}^m: x \mapsto Ax $$

This exercice wants you to show that the preimage ##T:=L^{-1}(S)## is a subspace of ##\mathbb{R}^n##.

This occurs in a lot of places in abstract algebra (and other disciplines): the inverse image of a subspace of the codomain is a subspace of the domain.

In abstract algebra, one can prove this result for groups, modules (of which vector spaces are general cases), rings etc. all at once by considering the notion of ##X##-groups.

If you are not familiar with abstract algebra, you can safely ignore the addendum.
 
Last edited by a moderator:
Thanks!

1.Since ##\mathbf{0}\in T##, ##A(\mathbf{0})\in S## which is non-empty.
2. Suppose ##x_1,x_2\in T##. Then there exists vectors ##x_1,x_2\in S## such that we have ##A(x_1)## and ##A(x_2)##. We then have that ##x_1+x_2\in S## and ##A(x_1+x_2) = A(x_1)+A(x_2)##, i.e. ##x_1+x_2\in T##.
3. Suppose ##\mathbf{x}\in T##, with ##\lambda\in \mathbb{R}##, then ##\lambda \mathbf{x}\in S## and ##A(\lambda \mathbf{x}) = \lambda A(\mathbf{x})## which shows that ##\lambda \mathbf{x}\in T##.
 
squenshl said:
Thanks!

1.Since ##\mathbf{0}\in T##, ##A(\mathbf{0})\in S## which is non-empty.
2. Suppose ##x_1,x_2\in T##. Then there exists vectors ##x_1,x_2\in S## such that we have ##A(x_1)## and ##A(x_2)##. We then have that ##x_1+x_2\in S## and ##A(x_1+x_2) = A(x_1)+A(x_2)##, i.e. ##x_1+x_2\in T##.
3. Suppose ##\mathbf{x}\in T##, with ##\lambda\in \mathbb{R}##, then ##\lambda \mathbf{x}\in S## and ##A(\lambda \mathbf{x}) = \lambda A(\mathbf{x})## which shows that ##\lambda \mathbf{x}\in T##.

Your proof for 2 and 3 are again wrong. You claim for example that ##x_1,x_2## live both in ##S## and ##T##, which doesn't make sense. These sets live in (possibly) different vector spaces.
 
Yeah that certainly doesn't make sense!

1. Suppose ##\mathbf{0}\in T##, ##A(\mathbf{0})\in S## which is non-empty.
2. Suppose ##x_1,x_2\in T##. We then have that ##A(x_1+x_2) = A(x_1)+A(x_2)\in S##, i.e. ##x_1+x_2\in T##.
3. Suppose ##\mathbf{x}\in T##, with ##\lambda\in \mathbb{R}##, ##A(\lambda \mathbf{x}) = \lambda A(\mathbf{x})\in S## which shows that ##\lambda \mathbf{x}\in T##.
 

Similar threads

  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 9 ·
Replies
9
Views
2K
Replies
1
Views
1K