Proving that a certian subset of L^1([0,1]) is closed

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In summary, the problem is to show that the set M, consisting of all f in L^1([0,1]) relative to the Lebesgue measure, such that the integral from 0 to 1 of f(t)dt is equal to 1, is a closed convex subset of L^1([0,1]) containing infinitely many elements of minimal norm. This can be proven by defining a linear functional and showing that M is convex and closed, using the topology on the space.
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benorin
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The problem: Let M be the set of all [tex]f\in L^1 \left( \left[ 0,1\right] \right) [/tex] relative to the Lebesgue measure, such that

[tex]\int_{t=0}^{1}f(t)dt = 1[/tex].

Show that M is a closed convex subset of [tex]L^1 \left( \left[ 0,1\right] \right) [/tex] which contains infinitely many elements of minimal norm.

What I've got: Define the linear functional [tex]\Lambda f = \int_{t=0}^{1}f(t)dt[/tex]

Convexity is easy, for any f,g in M and s in (0,1) put [tex]h_s(t)=sf(t)+(1-s)h(t)[/tex] so that

[tex]\Lambda h_s = \Lambda \left( sf+(1-s)h\right) = s\Lambda f + (1-s)\Lambda g = s + (1-s) = 1\Rightarrow \int_{t=0}^{1}h_s(t)dt = 1\Rightarrow h_s\in M[/tex]

by which it is understood that M is convex.

That M is closed is my first trouble. Let [tex]\left\{ f_k\right\} \rightarrow f[/tex] be a sequence of vectors such that [tex]f_k\in M,\forall k\in\mathbb{N}[/tex]. Then we know that

[tex]\forall \epsilon >0, \exists N\in\mathbb{N}\mbox{ such that }k\geq N\Rightarrow \| f_k - f\| = \Lambda \left( |f_k - f|\right) < \epsilon[/tex]

How do I prove that [tex]f\in M[/tex] ? Can I show that [tex]\Lambda[/tex] is a bounded linear map (actually functional) from [tex]L^1 \left( \left[ 0,1\right] \right)[/tex] into [tex]\mathbb{C}[/tex]?
 
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  • #2
Think I got the closed part:

[tex]|1 - \Lambda f |=|\Lambda f_k - \Lambda f |=|\Lambda \left( f_k - f\right) |\leq \Lambda \left( |f_k - f|\right) < \epsilon\Rightarrow 1-\epsilon < \Lambda f < 1+ \epsilon[/tex]

anbd since [tex]\epsilon[/tex] is arbitrary, [tex]\Lambda f =1\Rightarrow f\in M,[/tex] right?
 
  • #3
I think you're making it more complicated than it is. I mean, what is the topology on the space? Surely it is then trivial that the inverse image of a the point 1 under the (continuous, from the topology you put on the space!) functional f--> integral(f) is closed.
 

1. What is L^1([0,1])?

L^1([0,1]) is a function space that contains all integrable functions on the interval [0,1]. This means that the integral of the absolute value of the function over the interval is finite.

2. What does it mean for a subset of L^1([0,1]) to be closed?

A subset of L^1([0,1]) is considered closed if it contains all its limit points. In simpler terms, this means that any sequence of functions within the subset that converges will also converge to a function within the subset.

3. How do you prove that a certain subset of L^1([0,1]) is closed?

To prove that a subset of L^1([0,1]) is closed, you must show that it contains all its limit points. This can be done by assuming a sequence of functions within the subset converges to a point outside of the subset, and then showing that this leads to a contradiction. This proves that the subset contains all its limit points and is therefore closed.

4. What is the importance of proving that a subset of L^1([0,1]) is closed?

Proving that a subset of L^1([0,1]) is closed is important because it ensures that the subset is a complete and self-contained space. This means that all possible limits of sequences within the subset are also within the subset, making it a more robust and useful mathematical concept.

5. Are there any real-world applications for proving that a subset of L^1([0,1]) is closed?

Yes, there are many real-world applications for proving that a subset of L^1([0,1]) is closed. One example is in signal processing, where L^1([0,1]) is used to model signals. By proving that a subset of L^1([0,1]) is closed, we can ensure that our models are complete and accurate, leading to better understanding and analysis of signals in various fields such as telecommunications and biomedicine.

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