Dual basis problem. (Linear Algebra)

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Homework Help Overview

The discussion revolves around a problem in linear algebra concerning the existence of a non-zero vector in an n-dimensional vector space that is orthogonal to a set of linear functionals. The original poster seeks to prove this property under the condition that the number of functionals is less than the dimension of the space.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants explore the representation of linear functionals in terms of basis vectors and consider the implications of setting up a system of equations based on these functionals. There are discussions about the possibility of finding coefficients for the basis vectors that satisfy the orthogonality condition.

Discussion Status

Participants are actively engaging with the problem, sharing their thoughts on how to approach the solution. Some have suggested using properties of linear functionals and the dual space, while others are questioning the implications of the number of equations versus unknowns in the context of linear systems. There is no explicit consensus yet, but various productive lines of reasoning are being explored.

Contextual Notes

Participants note the condition that m < n, which is central to the discussion. There is also mention of the relationship between the dual space and the original space, as well as the implications of having a system of linear equations with more unknowns than equations.

Gramsci
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Homework Statement


Prove that if m < n and if y_1,...,y_m are linear functionals on an n-dimensional vector space V, then there exists a non-zero vector x in V such that [x,y_j] = 0 for j = 1,..., m


Homework Equations





The Attempt at a Solution


My thinking is somehow that we should write every functional in terms of its value at the basis vectors, but well, I'm not really sure what to do. Any help would be nice.
 
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If e1, e2, ..., en are the basis vectors, we wish to find x = a1e1 + a2e2 + ... + anen such that

[tex]\left[<br /> \begin{array}{c}<br /> y_1(a_1e_1 + a_2e_2 + \ldots + a_ne_n) \\<br /> y_2(a_1e_1 + a_2e_2 + \ldots + a_ne_n) \\<br /> \vdots \\<br /> y_m(a_1e_1 + a_2e_2 + \ldots + a_ne_n)<br /> \end{array}\right] = \left[<br /> \begin{array}{c}<br /> 0 \\ 0 \\ \vdots \\ 0<br /> \end{array}\right][/tex]​

All I've done is rephrased the problem. From this, do you see how you would find a1, a2, ..., an?
 
I've reached that point before, but from there I'm kinda stuck. My first thought was letting the first m entries of the vector be 0, but that wouldn't do anything. I thought something about representing each linear functional as a linear combination of the dual base vectors, but well, not completely sure how that'd help.
 
Can you go from a basis of the dual space to find a corresponding basis in the original space?
 
In continuation of my earlier advice, you will need to use the fact that each yj is a linear functional.
 
Tedjn: I've used the properties to rewrite them into the form:
a_1y_1(e_1)+...+a_ny_1(e_n) = 0
etc. for all functionals. But still, nothing.
Office_Shredder:
I don't really understand what you're hinting at, sorry.
 
Each yj(ei) is a constant element of the field. If V is a real vector space, then each yj(ei) is a constant real number. Does that format remind you of anything?
 
Tedjn:
Linear systems! Then if each y_j(e_i) produces a constant real number, we have a system of linear equations in n unknowns with m equations, right?
 
I believe that should work.
 
  • #10
Then we have to know that it has a non-trivial solution, right? Is there any way to know that besides reasoning that builds on "matrices"?
 
  • #11
And oh, there's a small follow up-question:
"What does this result say in general about the solutions of linear equations?"
I'd say that if we have n unknowns and m equations, there's a non-trivial solution, but that's just me.
 
  • #12
It may be possible; maybe you can approach it from a different angle by working with the dual basis as Office_Shredder suggested earlier. Personally, I prefer to think of this solution as one that builds on our knowledge of systems of linear equations, where matrices are just a form of bookkeeping for our coefficients.

EDIT: To the follow up, indeed it tells us that if m < n. But since we used that fact in the first place, it does make me wonder whether they were looking for a different solution.
 

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