Basis for the image of a surjective linear map.

Click For Summary

Homework Help Overview

The problem involves vector spaces V and W, and a surjective linear map T: V -> W. The original poster is tasked with showing that the image of a specific basis of V under T forms a basis for W, given that the kernel of T is spanned by another set of vectors.

Discussion Character

  • Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • The original poster has demonstrated that the image of a certain set spans W but is uncertain about proving linear independence. They explore the implications of linear combinations equating to zero and question the role of the kernel in this context.

Discussion Status

Participants are actively engaging with the original poster's reasoning, providing hints and clarifications. Some participants suggest that the relationship between the linear combinations of the basis vectors and the kernel is crucial for establishing linear independence. There is acknowledgment of the complexity in the proof, particularly regarding the kernel's influence on the linear combinations.

Contextual Notes

There is an ongoing discussion about the dimensions of the vector spaces involved, specifically how the dimensions relate to the surjectivity of the map and the implications for the kernel. The original poster and others are navigating potential misunderstandings about the properties of the linear map.

snipez90
Messages
1,095
Reaction score
5

Homework Statement


Let V and W be vector spaces over F, and let T: V -> W be a surjective (onto) linear map. Suppose that {v1, ..., v_m, u1, ... , u_n} is a basis for V such that ker(T) = span({u1, ... , u_n}). Show that {T(v1), ... , T(v_m)} is a basis for W.


Homework Equations


Basic properties of linear maps. Linear independence.


The Attempt at a Solution


I have already proven that {T(v1), ... , T(v_m)} spans W, which I thought would be harder than showing linear independence. But here is where I am confused. We have to show that {T(v1), ... , T(v_m)} is linearly independent.

Suppose (a_1)T(v1) + ... + (a_m)T(v_m) = 0 for (a_1), ... (a_m) in F. Then
T( (a_1)(v1) + ... + (a_m)(v_m) ) = 0 since T is linear. Now if we also suppose that (a_1)(v1) + ... + (a_m)(v_m) = 0, then clearly (a_1) = (a_2) = ... = (a_m) = 0 since the set {v_1, ... , v_m} is linearly independent.

But I think I'm confused when (a_1)(v1) + ... + (a_m)(v_m) =/= 0 (which is certainly possible right?). However, I have an idea and I think that in this case, we still get (a_1) = ... = (a_m) = 0?
 
Physics news on Phys.org
well, if T(w)=0 then w is in the KerT, so we can write this as a linear combination of the u's.

you shouldn't need any more of a hint than this.
 
Thanks xao, I think that was exactly what I had in mind (and I should have sorted out this case before I made the post). Basically then, setting a linear combination of the v's equal to a linear combination of the u's implies (by isolating 0 on one side) that all coefficients of vectors are 0.
 
Sorry, I misread the problem.
 
Last edited by a moderator:
But ker(T) = {0} if and only if T is injective, and surjectivity does not rule out the possibility that a nonzero vector is mapped to the 0 vector.

And just to clarify, the u's xao is talking about are also in the linearly independent set (consisting of v1 to v_m and u1 to u_n, sorry for not using latex). So currently my proof of linear independence looks like this:

Suppose

[itex] a_1T(v_1)+ a_2T(v_2)+ \cdot\cdot\cdot+ a_mT(v_m)= T(a_1v_1+ a_2v_2+ \cdot\cdot\cdot+ a_mv_m)= 0[/itex]

But kert(T) = span({u1, ... , u_n}), so we can write
[itex]a_1v_1+ a_2v_2+ \cdot\cdot\cdot+ a_mv_m = b_1u_1+ b_2v_2+ \cdot\cdot\cdot+ b_nu_n.[/itex]

Then
[itex]a_1v_1+ a_2v_2+ \cdot\cdot\cdot+ a_mv_m = b_1u_1 - b_2v_2 - \cdot\cdot\cdot - b_nu_n = 0[/itex]

and it follows that [itex]a_1 = a_2 = \cdot\cdot\cdot= a_m = 0[/itex].
 
Last edited:
i'm hoping that '=' was a typo in the last step.

it looks like the dimension of V is m+n (the v's plus u's) while the dimension of W is m, so a surjective map only needs m (the v's) of the m+n basis vectors. that leaves n basis vectors (the u's) spanning KerT to map onto the zero of W.
 
Yeah sorry I really screwed up the latex on that last line. It should read

Then

[itex] a_1v_1+ a_2v_2+ \cdot\cdot\cdot+ a_mv_m - b_1u_1 - b_2u_2 - \cdot\cdot\cdot - b_nu_n = 0[/itex]

so the conclusion follows.
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
1K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 5 ·
Replies
5
Views
4K
  • · Replies 9 ·
Replies
9
Views
2K
Replies
34
Views
4K
Replies
1
Views
2K
Replies
15
Views
3K
Replies
9
Views
2K
Replies
8
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K