Proving Measurable Functions Convergence in Finite Measure Sets

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In the discussion on proving convergence of measurable functions in finite measure sets, participants explore the conditions under which a sequence of measurable functions converges almost everywhere and uniformly. The key points include the existence of measurable sets where convergence holds, ensuring that the measure of the complement is zero. A proposed approach involves partitioning the set E into subsets where the functions exhibit uniform convergence. The importance of maintaining finiteness and measurability in the functions is emphasized, along with the necessity of addressing potential convergence issues in subsets of null measure. The conversation highlights the complexity of the problem and the need for careful construction of measurable sets to demonstrate the desired convergence properties.
SqueeSpleen
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Let E be of finite measure and let \{ f_{n} \} _{n \geq 1} : E \rightarrow \overline{\mathbb{R}} measurable functions, finites almost everywhere in E such that f_{n} \rightarrow_{n \to \infty} f almost everywhere in E. Prove that exists a sequence (E_{i})_{i \geq 1} of measurable sets of E such that:
1) | E- \displaystyle \bigcup_{i=1}^{\infty} E_{i} | = 0
2) For every i \geq 1, f \rightrightarrows_{n \to \infty} in E_{i}

Notation:
f_{n} \rightarrow_{n \to \infty} f means "f_{n} converges to f as n \to \infty"
f \rightrightarrows_{n \to \infty} means "f_{n} converges uniformly to f as n \to \infty"
I don't know if there are multiple common definitions, but here is the mine:
A function f : \mathbb{R}^{n} \rightarrow \mathbb{R} is measurable if for all a \in \mathbb{R}:
\{ f > a \} = \{ x \in \mathbb{R}^{n} / f(x) > a \} is measurable in the sense of Lebesgue.
E \in R^{n} is measurable in the Lebesgue sense if for every \varepsilon > 0 \exists U \in \mathcal{U} / E \in U \wedge |U-E|_{e} < \varepsilon
Where | |_{e} is the outer measure.Attemp/idea:
I tried to divide E in E_{k,n} = \{ x \in E / | f(x)-f_{n} | < \frac{1}{k} \} but it will not help at all because something may "converge" similar in the first m terms but converge otherwise later.
 
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SqueeSpleen said:
medible functions

Sorry, did you mistype this? I don't know what it means.
 
This was a mistake, I meant measurable.
 
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In a previous exercise (I didn't realize it could be useful here, so I didn't post it) I had the following result:
Let E be a set of finite measure and \{ f_{k} \}_{k \in \mathbb{N}} : E \rightarrow \mathbb{R} a sequence of measurable functions such that for every x \in E, exists M_{x} \in \mathbb{R}_{>0}:
| f_{k} (x) | \leq M_{x}, \forall k \in \mathbb{N}
Then for every \varepsilon > 0 exists F \subset E closed and M \in \mathbb{R}_{>0} such that:
| E - F | < \varepsilon and | f_{k} (x) | \leq M, \forall k \in \mathbb{N}, \forall x \in F

If there's a set where \forall M \in \mathbb{R}_{>0} \exists k \in \mathbb{N} / | f - f_{k} | > M, then this set has to have null measure, because either the functions doesn't converge here or they're not finite.

Let's be E = H \cup Z where \{ f_{k} \}_{k \in \mathbb{N}} are finite and converges to f in H and | Z | = 0 (E-Z=H) (They may be not finite in differents sets, but all are of zero measure and the countable union of sets of null measure has null measure).

As H is measurable, for every \varepsilon > 0 exists C closed such that C \in H and | H - C | < \varepsilon.

I'll try with E_{k} = \{ x \in H / f_{n} (x) < k \forall n \in \mathbb{N}

Edit: I had a non-trivial mistake so I was trying to fix it but I failed and I have a lecture in 6 hours, so I'd better to sleep now.
 
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Getting late here -- will look at this tomorrow if someone doesn't help you sooner.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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