Proof regarding linear functionals

Box##Assume that both functions ##\Phi_1,\Phi_2## are not equal to zero identically. Then there exist a vector ##v## such that ##\Phi_1(v)\Phi_2(v)\ne 0##.So that ##\sigma(\lambda v)=\lambda^2\Phi_1(v)\Phi_2(v)\Longrightarrow \sigma( v)=\lambda\Phi_1(v)\Phi_2(v),\quad \forall\lambda\ne 0##This is possible if only ##\Phi_1(v)\Phi_2(v)=0## Contradiction. ##\Box##
  • #1
Adgorn
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Homework Statement


Let V be a vector space over R. let Φ1, Φ2 ∈ V* (the duel space) and suppose σ:V→R, defined by σ(v)=Φ1(v)Φ2(v), also belongs to V*. Show that either Φ1 = 0 or Φ2 = 0.

Homework Equations


N/A

The Attempt at a Solution


Since σ is also an element of the duel space, it is linear, so σ(v+u)=σ(v)+σ(u). Translating both sides into terms of Φ1 and Φ[SUB}2[/SUB], I came up with the equation
(1) Φ1(v)Φ2(u)+Φ1(u)Φ2(v)=0.

Doing the same with σ(av+bu) and plugging in equation (1) produced the equation
(2) a2Φ1(v)Φ2(v)+b2Φ1(u)Φ2(u)=aΦ1(v)Φ2(v)+bΦ1(u)Φ2

This is where I got stuck, perhaps there is a trick I am not seeing to this equation or perhaps I approached this the wrong way. Any help would be appreciated.
 
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  • #2
Adgorn said:

Homework Statement


Let V be a vector space over R. let Φ1, Φ2 ∈ V* (the duel space) and suppose σ:V→R, defined by σ(v)=Φ1(v)Φ2(v), also belongs to V*. Show that either Φ1 = 0 or Φ2 = 0.

Homework Equations


N/A

The Attempt at a Solution


Since σ is also an element of the duel space, it is linear, so σ(v+u)=σ(v)+σ(u). Translating both sides into terms of Φ1 and Φ[SUB}2[/SUB], I came up with the equation
(1) Φ1(v)Φ2(u)+Φ1(u)Φ2(v)=0.

Doing the same with σ(av+bu) and plugging in equation (1) produced the equation
(2) a2Φ1(v)Φ2(v)+b2Φ1(u)Φ2(u)=aΦ1(v)Φ2(v)+bΦ1(u)Φ2

This is where I got stuck, perhaps there is a trick I am not seeing to this equation or perhaps I approached this the wrong way. Any help would be appreciated.

You're on the right track. Go back to equation (1) and try ##u = v##.
 
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  • #3
PeroK said:
You're on the right track. Go back to equation (1) and try ##u = v##.
I see, thank you for the help, I solved it.
 
  • #4
Adgorn said:
I see, thank you for the help, I solved it.

Are you sure?
 
  • #5
PeroK said:
Are you sure?
I think so. Plugging in u=v into Φ1(v)Φ2(u)+Φ1(u)Φ2(v)=0 resulted in Φ1(v)Φ2(v)+Φ1(v)Φ2(v)=0, meaning Φ1(v)Φ2(v)=0. Since these are elements of a field, it means either Φ1(v)=0 or Φ2(v)=0, and since v is arbitrary, this means either Φ1=0 or Φ2=0.
 
  • #6
Adgorn said:
I think so. Plugging in u=v into Φ1(v)Φ2(u)+Φ1(u)Φ2(v)=0 resulted in Φ1(v)Φ2(v)+Φ1(v)Φ2(v)=0, meaning Φ1(v)Φ2(v)=0. Since these are elements of a field, it means either Φ1(v)=0 or Φ2(v)=0, and since v is arbitrary, this means either Φ1=0 or Φ2=0.

I guessed that is what you had done! What you have shown there is:

##\forall \ v: \ \Phi_1(v) = 0## or ##\Phi_2(v) = 0## (Equation 3)

That means that for some ##v## it could be ##\Phi_1(v) = 0## and for some other ##v## it could be ##\Phi_2(v) = 0##. But, you haven't shown that either ##\Phi_1 = 0## or ##\Phi_2 = 0##.

So, there is still work to do. Let me help with the next step. Suppose ##\Phi_1 \ne 0##. We have to show that then ##\Phi_2 = 0##.

Can you use equations (1) and (3) to do this?
 
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  • #7
I see. So let us assume Φ1≠0, Then it means there exists w∈V such that Φ1(w)≠0, let us denote the set of all such vectors with S. since for every vector v∈V Φ1(v) is either 0 or not 0, V=S∪Ker(Φ1).We plug one of these (arbitrary) w into equation 3 and get Φ1(w)Φ2(w)=0, since Φ1(w)≠0, it means Φ2(w)=0. And since this applies to every w∈S, it means Φ2(S)=0.

Now we must show that Φ2(u)=0 ∀u∈Ker(Φ1). Let us take an arbitrary vector u from Ker(Φ1) and plug it in equation 1 along with another vector w∈S: Φ1(u)Φ2(w)+Φ1(w)Φ2(u)=0. Since u∈Ker(Φ1), Φ1(u)Φ2(w)=0. Thus, Φ1(w)Φ2(u)=0, and since Φ1(w)≠0 by definition, this means Φ2(u)=0 ∀u∈Ker(Φ1).

Combining these two results give us Φ2(v)=0 ∀v∈V, and so Φ2=0. Doing the same process by assuming Φ2≠0 produces the result Φ1=0.
 
  • #8
Adgorn said:
I see. So let us assume Φ1≠0, Then it means there exists w∈V such that Φ1(w)≠0, let us denote the set of all such vectors with S. since for every vector v∈V Φ1(v) is either 0 or not 0, V=S∪Ker(Φ1).We plug one of these (arbitrary) w into equation 3 and get Φ1(w)Φ2(w)=0, since Φ1(w)≠0, it means Φ2(w)=0. And since this applies to every w∈S, it means Φ2(S)=0.

Now we must show that Φ2(u)=0 ∀u∈Ker(Φ1). Let us take an arbitrary vector u from Ker(Φ1) and plug it in equation 1 along with another vector w∈S: Φ1(u)Φ2(w)+Φ1(w)Φ2(u)=0. Since u∈Ker(Φ1), Φ1(u)Φ2(w)=0. Thus, Φ1(w)Φ2(u)=0, and since Φ1(w)≠0 by definition, this means Φ2(u)=0 ∀u∈Ker(Φ1).

Combining these two results give us Φ2(v)=0 ∀v∈V, and so Φ2=0. Doing the same process by assuming Φ2≠0 produces the result Φ1=0.

I can't see any mistakes there, although your solution is more complicated than I was expecting. If I pick up your proof from here:

Adgorn said:
I see. So let us assume Φ1≠0, Then it means there exists w∈V such that Φ1(w)≠0

Then, I would use equation 3 to note that ##\Phi_2(w) = 0## and hence (from equation 1) we have:

##\forall v \in V: \ \Phi_1(w)\Phi_2(v) = 0##

Hence ##\forall v \in V: \ \Phi_2(v) = 0##

And the result follows.

Note also that there is no need to repeat the process for ##\Phi_2##. If ##\Phi_1 = 0##, then we are done. And, if ##\Phi_1 \ne 0## we have shown that ##\Phi_2 = 0##. In either case, one of the functionals must be ##0##. And, there is no need to do any more.
 
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  • #9
Adgorn said:
Let V be a vector space over R. let Φ1, Φ2 ∈ V* (the duel space) and suppose σ:V→R, defined by σ(v)=Φ1(v)Φ2(v), also belongs to V*. Show that either Φ1 = 0 or Φ2 = 0.
Assume that both functions ##\Phi_1,\Phi_2## are not equal to zero identically. Then there exist a vector ##v## such that ##\Phi_1(v)\Phi_2(v)\ne 0##.
So that ##\sigma(\lambda v)=\lambda^2\Phi_1(v)\Phi_2(v)\Longrightarrow \sigma( v)=\lambda\Phi_1(v)\Phi_2(v),\quad \forall\lambda\ne 0##
This is possible if only ##\Phi_1(v)\Phi_2(v)=0## Contradiction.
 

Related to Proof regarding linear functionals

What is a linear functional?

A linear functional is a mathematical function that takes in a vector as input and returns a scalar value as output. It is a mapping from a vector space to its underlying field of scalars.

How is a linear functional different from a linear transformation?

A linear transformation is a mapping between two vector spaces, while a linear functional is a mapping from a vector space to its underlying field of scalars. In other words, a linear functional operates on individual vectors, while a linear transformation operates on entire vector spaces.

What is the null space of a linear functional?

The null space of a linear functional is the set of all vectors in the domain that are mapped to the zero scalar in the range. In other words, it is the set of all vectors that the linear functional maps to zero.

How do you prove that a function is a linear functional?

To prove that a function is a linear functional, you must show that it satisfies two properties: additivity and homogeneity. Additivity means that f(x + y) = f(x) + f(y), and homogeneity means that f(cx) = cf(x), where x and y are vectors and c is a scalar. If a function satisfies these two properties, it can be considered a linear functional.

What are some real-world applications of linear functionals?

Linear functionals have many applications in fields such as physics, engineering, and economics. For example, in physics, linear functionals can be used to represent physical quantities such as energy, momentum, and angular momentum. In economics, they can be used to represent utility and cost functions. In engineering, they can be used to represent forces and moments in a system.

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