Proof of Hahn decomposition theorem

In summary, the conversation is about a theorem regarding signed measures and measurable subsets. The strategy of the proof is to find a negative set B and define A as the difference between X and B. If A is not positive, then it can be shown that it doesn't have any negative subsets. However, a subset E_0 can still have a negative size. The goal is to show that E_0-\bigcup_{k=1}^\infty E_k is negative. The proof involves using the smallest integer m_k and choosing a measurable set F to reach a contradiction. Finally, the speaker expresses gratitude and compliments the expert on their clear explanation.
  • #1
Fredrik
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I'm trying to read this proof, and I'm stuck on the inequality on page 27 following the statement "It follows that every measurable subset..." Why does it hold?

The theorem is about signed measures, i.e. functions that are like measures, but can assign both positive and negative "sizes" to sets. A measurable set is said to be positive if all its measurable subsets have a non-negative size. The term negative is defined similarly. The theorem asserts that the set X is a disjoint union of a positive set A and a negative set B. The strategy of the proof is roughly this: First find a set B and show that it's negative. Define A=X-B. Suppose that A is not positive. (This will lead to a contradiction). It's not too hard to see that A doesn't have any negative subsets, but we can still pick a subset [itex]E_0\subset A[/itex] that has a negative size. Then we cut away disjoint pieces of [itex]E_0[/itex], denoted by [itex]E_1,E_2,\dots[/itex] that have positive sizes. The goal is to show that [itex]E_0-\bigcup_{k=1}^\infty E_k[/itex] is negative.
 
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  • #2
Hmm, it tool me a while, but I've got it. Remember that [itex]m_k[/itex] is the smallest integer such that there is a set [itex]E_k[/itex].

[tex]\mu (E_k)\geq \frac{1}{m_k}[/tex]

Now take F measurable, if

[tex]\mu(F)\geq \frac{1}{m_k-1}[/tex]

then [itex]m_k-1[/itex] is a smaller integer and [itex]F[/itex] is another set for which

[tex]\mu(F)\geq \frac{1}{m_k-1}[/tex]

This is in contradiction with the choice of [itex]m_k[/itex]. Thus it must hold that

[tex]\mu(F)<\frac{1}{m_k-1}[/tex]
 
  • #3
You sir, are awesome. That was crystal clear. Thank you.
 

1. What is the Hahn decomposition theorem?

The Hahn decomposition theorem is a mathematical theorem that states any measurable space can be divided into two disjoint measurable sets, such that any measurable set in the original space can be written as the union of a set contained in the first set and a set contained in the second set.

2. What is the significance of the Hahn decomposition theorem?

The Hahn decomposition theorem is an important tool in measure theory as it provides a way to break down a complex measurable space into simpler, disjoint parts. This allows for the simplification of some measure-theoretic problems and has applications in various fields of mathematics such as probability theory and functional analysis.

3. How is the Hahn decomposition theorem proved?

The proof of the Hahn decomposition theorem involves constructing two sets using the properties of measurable spaces and applying the completeness axiom of the real numbers. The theorem can also be proved using the Riesz representation theorem and Carathéodory's extension theorem.

4. What are the assumptions for the Hahn decomposition theorem to hold?

The Hahn decomposition theorem holds for any measurable space, which is a space equipped with a sigma-algebra of measurable sets and a measure function that satisfies certain properties such as countable additivity and monotonicity.

5. What are some applications of the Hahn decomposition theorem?

The Hahn decomposition theorem has various applications in mathematics, including in probability theory for proving the existence of conditional expectations, in functional analysis for studying topological vector spaces, and in ergodic theory for studying dynamical systems. It also has applications in economics and game theory for analyzing decision-making processes.

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