A theorem about Borel measures

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In summary, a Borel measure is a mathematical concept used in measure theory to assign a numerical value to certain sets of numbers. The significance of a theorem about Borel measures lies in its ability to provide a framework for analyzing and working with measures, which has practical applications in various fields. The Borel-Cantelli lemma is a fundamental result in probability theory that relates to the convergence of infinite sequences of events. The Borel measure is different from other measures because it is specifically defined for Borel sets, which have important properties and applications in mathematics. Some real-world applications of Borel measures include measuring physical systems, analyzing wealth distribution, and optimizing algorithms.
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Homework Statement


There is a theorem in Folland's book (Real Analysis) in which he gives three statements that are equivalent. In the proof he decides to take the first statement and prove the other two, but in the end he derives a statement that looks different than what is given in the theorem. This means that the statement he derived is the same as the statement in the proof, but I am not able to go from one to the other.

Theorem: Let [tex]E \in R[/tex](reals). Then the following are equivalent.

(a) [tex]E[/tex] is measurable.
(b) [tex]E = V[/tex] [tex]- N_{1} [/tex] where [tex] V [/tex] is a [tex]G_{\delta}[/tex] set and [tex]\mu(N_{1})=0[/tex].

There is a (c) but let us ignore that for now. The measure is the Lebesgue measure and the domain I think is the extended Borel sigma algebra, so both [tex]V[/tex] and [tex] N_{1} [/tex] are measurable.

In the book, the author assumes (a) and then shows that:

(d) there exists a [tex]G_{\delta}[/tex] set [tex]V \subset E[/tex] such that [tex]\mu(V-E)=0[/tex].

I am trying to either go from this statement to (b) or from (b) to (d), but I don't know how.

2. The attempt at a solutionI don't know how to go from (d) to (b) because I don't know how one can conclude that sets are equal based on their measures. So I tried to go from (b) to (d). I have to show that [tex] E \in V [/tex] and [tex]\mu(E-V)[/tex] is zero.

If [tex] E = V-N_{1}[/tex], then

[tex] \mu(E) = \mu(V) - \mu(V \cap N_{1})[/tex],

[tex] \mu(E) = \mu(V)[/tex].

I don't know what to do next.
 
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I thought about using the fact that E is measurable and V is a G_{\delta} set, but I don't know how to connect those to conclude that E is also a G_{\delta} set. I also tried using the fact that \mu(N_{1})=0, but I couldn't see how that could help either. Can someone please give me some hints or guidance on how to proceed?

First of all, it's important to note that in the proof of the theorem, the author is not trying to show that (b) is equivalent to (d). Instead, they are showing that (b) implies (d) and (d) implies (b), which is enough to establish the equivalence of (a), (b), and (d).

To go from (b) to (d), you can use the fact that V is a G_{\delta} set, which means it can be written as a countable intersection of open sets. Let's say V = \bigcap_{n=1}^{\infty} U_n. Then, by definition, V \subset U_n for all n. Since E = V - N_{1}, it follows that E \subset U_n - N_{1} for all n. But U_n - N_{1} is an open set, since N_{1} has measure zero and thus does not affect the openness of U_n. Therefore, E is contained in a countable union of open sets, and hence it is a G_{\delta} set.

To go from (d) to (b), you can use the fact that V \subset E. Since V is a G_{\delta} set, it can be written as a countable intersection of open sets, say V = \bigcap_{n=1}^{\infty} U_n. Then, by definition, V \subset U_n for all n, and hence E \subset U_n for all n. This implies that E is contained in a countable union of open sets, and therefore it is a G_{\delta} set. Additionally, since \mu(V-E)=0, it follows that \mu(V \cap E) = \mu(V) - \mu(V-E) = \mu(V) = \mu(E), which shows that E and V have the same measure, as required in (b).
 

1. What is a Borel measure?

A Borel measure is a mathematical concept used in measure theory to assign a numerical value to certain sets of numbers. It is used to measure the size or extent of a set and is based on the idea of counting the number of elements in a set.

2. What is the significance of a theorem about Borel measures?

Theorem about Borel measures is significant because it helps us understand how Borel measures behave and interact with other mathematical concepts. It provides a framework for analyzing and working with measures, which has many practical applications in fields such as physics, engineering, and economics.

3. What is the Borel-Cantelli lemma?

The Borel-Cantelli lemma is a fundamental result in probability theory that relates to the convergence of infinite sequences of events. It states that if the sum of the probabilities of a sequence of events is finite, then the probability of infinitely many of those events occurring is zero.

4. How is the Borel measure different from other measures?

The Borel measure is different from other measures because it is specifically defined for Borel sets, which are a special type of set in mathematics. Borel sets are important because they are the smallest class of sets that contains all open intervals and are closed under certain operations, making them useful in many mathematical applications.

5. What are some real-world applications of Borel measures?

Borel measures have many real-world applications, such as in physics to measure the size or extent of physical systems, in economics to measure the distribution of wealth or income, and in statistics to analyze the convergence of random variables. They are also used in fields like computer science and engineering to analyze and optimize algorithms and systems.

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