Proof that two linear forms kernels are equal

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Discussion Overview

The discussion revolves around the proof that the kernels of two linearly dependent linear forms are equal. Participants explore the implications of the Rank–nullity theorem, the relationships between the images and kernels of the linear forms, and provide alternative exercises related to linear forms in vector spaces.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant applies the Rank–nullity theorem to conclude that the dimensions of the kernels of two linear forms, ##F## and ##G##, are both ##n-1##.
  • Another participant suggests that since ##F## and ##G## are linearly dependent, it follows that the image of ##F## is contained in the image of ##G##, leading to the conclusion that the kernels are equal.
  • A later reply confirms the correctness of the initial proof while suggesting that the second part is overly lengthy and could be simplified.
  • Additional exercises are proposed, asking participants to show conditions under which the intersection of the kernels of multiple linear forms implies a linear combination of those forms.
  • One participant provides a detailed attempt at the proposed exercise, discussing the implications of extending a set of independent linear forms to a basis of the dual space.

Areas of Agreement / Disagreement

Participants express varying degrees of confidence in the correctness of the initial proof, with some affirming its validity while others suggest it could be more elegant. The additional exercises and attempts at proofs indicate that multiple approaches and interpretations exist, and no consensus is reached on the elegance or simplicity of the solutions.

Contextual Notes

Some participants note the complexity of the proofs and the potential for simplification, but no specific assumptions or definitions are resolved. The discussion remains focused on the exploration of ideas rather than establishing definitive conclusions.

Who May Find This Useful

Readers interested in linear algebra, particularly those studying linear forms, kernel properties, and the Rank–nullity theorem, may find this discussion relevant.

Portuga
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TL;DR
Let ##F## and ##G## be non-zero linear forms in vector space ##V##, linearly dependent. Prove that ##\ker\left(F\right)=\ker\left(G\right)## and that its dimension is ##n-1## if ##\dim V=n##.
Attempt of a solution.
By the Rank–nullity theorem,
$$
\dim V=\dim Im_{F}+\dim\ker\left(F\right)
\Rightarrow n=1+\dim\ker\left(F\right)
\Rightarrow \dim\ker\left(F\right)=n-1.
$$
Similarly, it follows that $$\dim\ker\left(G\right)=n-1.$$

This first part, for obvious reasons, is very clear.
The next one offered me a terrible challenge.
I saw a solution, but it didn't convince me for sure.

Here it is.

As ##F## and ##G## are linearly dependent,
$$
\alpha F\left(u\right)+\beta G\left(u\right)=0
\Rightarrow G\left(u\right)=\frac{-\alpha}{\beta}F\left(u\right),
$$
since in this expression, ##\alpha## and ##\beta## have to be different from 0, because the two linear forms are non-zero. It follows that every vector in the image of ##F## is also a vector in the image of ##G##, which implies that ##Im_{F}=Im_{G}##. As for any subspace ##V##, ##V=\ker\left(F\right) \oplus Im_{F}##, where ##Im_{F}=Im_{G}##, then
$$
\ker\left(F\right)\oplus Im_{F}=\ker\left(G\right)\oplus Im_{G}
\Rightarrow \ker\left(F\right)\oplus Im_{F}=\ker\left(G\right)\oplus Im_{F}
\Rightarrow \ker\left(F\right)=\ker\left(G\right),
$$
as there is no intersection between the two sets.
I would like to know if this solution is correct and if is the best one, because it seems not elegant for me.
 
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You should type formulas as explained here:
https://www.physicsforums.com/help/latexhelp/

Your proof looks correct, from what I could read in this mess. The second part is definitely too long.
Since ##F## and ##G## are linear dependent, and non-zero, we immediately have ##F=\alpha \cdot G## for some scalar ##\alpha \neq 0.##

Now it is easy to see that ##\ker F \subseteq \ker G \subseteq \ker F## and that the images are equal, too: ##F(u)=\alpha \cdot G(u)=G(\alpha \cdot u).##
 
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Thank you very much! Sorry for the mess in latex.
 
It will also be a good exercise for OP. Let ##f_1,\ldots, f_n,f:\mathbb{R}^m\to\mathbb{R}## be linear forms. Show that
$$\bigcap_{i=1}^n\ker f_i\subset \ker f\Leftrightarrow f=\lambda_1 f_1+\ldots+\lambda_n f_n$$
 
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wrobel said:
It will also be a good exercise for OP. Let ##f_1,\ldots, f_n,f:\mathbb{R}^m\to\mathbb{R}## be linear forms. Show that
$$\bigcap_{i=1}^n\ker f_i\subset \ker f\Leftrightarrow f=\lambda_1 f_1+\ldots+\lambda_n f_n$$
Here is my attempt:

WLOG let us assume that ##f_i## s are independent.

##dim ~R^{m*}=m##

If ## m\leq n## then it becomes quite easier. Therefore, let's assume ## m \gt n## and ##n+r=m##. We can extend ##f_i s## to a basis of the dual space, let the basis be ##\{f_1, f_2, \cdots , f_n , f_{n+1}, \cdots , f_{n+r} \}##.

We're given that
$$
A = \bigcap_{i=1}^n ker (f_i) \subset ker (f)$$

As ##f## belongs to the dual space, we have
$$
f(v) = \lambda_1 f_1(v) +\cdots + \lambda_n f_n(v) + \lambda_{n+1} f_{n+1} (v) \cdots +\lambda_{n+r} f_{n+r} (v)$$

For any vector x belonging to A, we have
$$0= \lambda_{n+1} f_{n+1} (x) \cdots +\lambda_{n+r} f_{n+r} (x)$$

That's a contradiction, because that's the case for all the values of ## x\in \bigcap_{i=1}^n ker (f_i) ##.

Hence, ##f## must be a Linear combination of ##f_1, f_2, \cdots , f_n## only.

The converse is very easy to prove:

If ## f = \lambda_1 f_1 +\cdots + \lambda_n f_n##
Then, for all ## x \in A=\bigcap_{i=1}^n ker (f_i)## we would have
$$
f(x)=0$$
Hence, ## A \subset ker(f)##.
 

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