Why Does Monotone Convergence Theorem Confirm Integral Bounds?

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    Bounded Integrals
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Discussion Overview

The discussion revolves around the Monotone Convergence Theorem and its implications for establishing bounds on integrals of non-negative, integrable functions over measurable sets. Participants explore the relationship between integrals over truncated sets and the integral over the entire set.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant suggests that if the integral over the entire set E is strictly greater than a fixed number e, then the integral over the truncated sets E_k must also exceed e for sufficiently large k.
  • Another participant questions the reasoning behind this assertion and asks for clarification on the properties of integrable functions being utilized.
  • A different approach is proposed where for a fixed epsilon > 0, the integrals over E_k are bounded by epsilon/2^k, leading to a series that converges to epsilon.
  • One participant expresses uncertainty about whether it is valid to use an epsilon that depends on k, while another clarifies that epsilon is a fixed number.
  • A later reply introduces the characteristic function and applies the Monotone Convergence Theorem to relate the limit of the integrals over E_k to the integral over E.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the best approach to prove the integral bounds, with multiple competing views and methods presented throughout the discussion.

Contextual Notes

There are unresolved questions regarding the legality of using an epsilon that depends on k and the implications of the Monotone Convergence Theorem in this context.

tjkubo
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Say f is a non-negative, integrable function over a measurable set E. Suppose
[tex] \int_{E_k} f\; dm \leq \epsilon[/tex]
for each positive integer [itex]k[/itex], where
[tex] E_k = E \cap [-k,k][/tex]
Then, why is it true that
[tex] \int_E f\; dm \leq \epsilon \quad ?[/tex]

I know that
[tex] \bigcup_k E_k = E[/tex]
and intuitively it seems reasonable, but I don't know how to prove it.
 
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Proceed by indirect method : if the integral over E is strictly > e ,then the integral over E_k should also exceed e for sufficiently large k.
 
Why is that so? Are you using some property of integrable functions I'm not seeing?
 
I think you could also prove it this way. Given [itex]\epsilon > 0[/itex], for each [itex]k \in \mathbb{Z}^+[/itex] [itex]\int_{E_k} f \; dm \leq \epsilon/2^k[/itex]. Then
[tex] \int_E f \; dm = \int_{\bigcup_k E_k} f \; dm \leq \sum_{k=1}^\infty \int_{E_k} f \; dm \leq \sum_{k=1}^\infty \frac{\epsilon}{2^k} = \epsilon \frac{1}{2} \frac{1}{1 - \frac{1}{2}} = \epsilon \; .[/tex]

The only question I have is if it's legal to have an epsilon that depends on k, but I think it is since I think your given information held for all [itex]\epsilon > 0[/itex] and all positive integers k.
 
Actually, the epsilon is a fixed number. That is why it's stumbling me. Sorry I wasn't clear.
 
define [itex]f_k(x)=\textbf{1}_{E_k}(x)f(x)[/itex] where [itex]\textbf{1}[/itex] is the characteristic function.
From the monotone convergence theorem you have
[tex]\epsilon \ge \lim_{k\to\infty} \int_{E_k} f \; dm = \lim_{k\to\infty} \int_E f_k \; dm = \int_E f \; dm[/tex]
 

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