Proving some properties on a complete measure space

In summary, a complete measure space is a mathematical concept used in measure theory that includes a set, sigma-algebra, and measure with the completeness property. Completeness is important in measure theory as it ensures accurate and precise calculations and allows for the proof of various properties, such as the Carathéodory extension theorem and Lebesgue convergence theorem. Proving properties on a complete measure space involves using the definition of completeness and properties of the measure function, and it has applications in various areas of mathematics and other fields, including probability theory and economics.
  • #1
mahler1
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Homework Statement .

A space ##(X,\Sigma, \mu)## is a complete measure space if given ## Z \in \Sigma## such that ##\mu(Z)=0##, for every ##Y \subset Z##, we have ##Y \in \Sigma##. In this case, prove that

a) If ##Z_1 \in \Sigma##, ##Z_1ΔZ_2 \in \Sigma## and ##\mu(Z_1ΔZ_2)=0##, then ##Z_2 \in \Sigma##.

b) If ##E_1, E_2 \in \Sigma## and ##\mu(E_1ΔE_2)=0##, then ##\mu(E_1)=\mu(E_2)##.



The attempt at a solution.

For a), ##Z_2\setminus Z_1 \subset Z_1ΔZ_2##, by definition of complete measure space, we have that ##Z_2\setminus Z_1 \in \Sigma##. If I could prove that ##Z_1\cap Z_2 \in \Sigma##, then, I could conclude that ##Z_2=(Z_2\setminus Z_1) \cup (Z_1 \cap Z_2) \in \Sigma##. I got stuck trying to prove the last part.

For b), I think I got it but I would like to check if my solution is correct:

First notice that since we are in a measure space and ##E_1, E_2 \in \Sigma \implies {E_1}^c, {E_2}^c \in \Sigma \implies E_1 \cap E_2=({E_1}^c \cup {E_2}^c)^c \in \Sigma##. Moreover, since it is a complete measure space, ##E_1\setminus E_2, E_2 \setminus E_1 \in \Sigma##. Having said that, we can write ##E_1=(E_1 \setminus E_2) \cup (E_1 \cap E_2)##, the same goes for ##E_2##. As ##\mu## is a measure, we have that ##\mu(E_1)=\mu(E_1 \setminus E_2) + \mu(E_1 \cap E_2)##, and ##\mu(E_2)=\mu(E_2 \setminus E_1) + \mu(E_1 \cap E_2)##.

Again, since ##\mu## is a measure, ##0\leq \mu(E_1 \setminus E_2),\mu(E_2 \setminus E_1)\leq \mu(E_1ΔE_2)=0 \implies \mu(E_1 \setminus E_2)=0=\mu(E_2 \setminus E_1)##.

But then, ##\mu(E_1)=0+\mu(E_1 \cap E_2)=\mu(E_2)##, which was what we wanted to prove.


I would appreciate some help for part a)
 
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  • #2
mahler1 said:
Homework Statement .

A space ##(X,\Sigma, \mu)## is a complete measure space if given ## Z \in \Sigma## such that ##\mu(Z)=0##, for every ##Y \subset Z##, we have ##Y \in \Sigma##. In this case, prove that

a) If ##Z_1 \in \Sigma##, ##Z_1ΔZ_2 \in \Sigma## and ##\mu(Z_1ΔZ_2)=0##, then ##Z_2 \in \Sigma##.

b) If ##E_1, E_2 \in \Sigma## and ##\mu(E_1ΔE_2)=0##, then ##\mu(E_1)=\mu(E_2)##.
The attempt at a solution.

For a), ##Z_2\setminus Z_1 \subset Z_1ΔZ_2##, by definition of complete measure space, we have that ##Z_2\setminus Z_1 \in \Sigma##. If I could prove that ##Z_1\cap Z_2 \in \Sigma##, then, I could conclude that ##Z_2=(Z_2\setminus Z_1) \cup (Z_1 \cap Z_2) \in \Sigma##. I got stuck trying to prove the last part.

For b), I think I got it but I would like to check if my solution is correct:

First notice that since we are in a measure space and ##E_1, E_2 \in \Sigma \implies {E_1}^c, {E_2}^c \in \Sigma \implies E_1 \cap E_2=({E_1}^c \cup {E_2}^c)^c \in \Sigma##. Moreover, since it is a complete measure space, ##E_1\setminus E_2, E_2 \setminus E_1 \in \Sigma##. Having said that, we can write ##E_1=(E_1 \setminus E_2) \cup (E_1 \cap E_2)##, the same goes for ##E_2##. As ##\mu## is a measure, we have that ##\mu(E_1)=\mu(E_1 \setminus E_2) + \mu(E_1 \cap E_2)##, and ##\mu(E_2)=\mu(E_2 \setminus E_1) + \mu(E_1 \cap E_2)##.

Again, since ##\mu## is a measure, ##0\leq \mu(E_1 \setminus E_2),\mu(E_2 \setminus E_1)\leq \mu(E_1ΔE_2)=0 \implies \mu(E_1 \setminus E_2)=0=\mu(E_2 \setminus E_1)##.

But then, ##\mu(E_1)=0+\mu(E_1 \cap E_2)=\mu(E_2)##, which was what we wanted to prove.I would appreciate some help for part a)

##Z_1## and ##Z_1 \setminus Z_2## are in ##\Sigma##. ##(Z_1 \cap Z_2) = Z_1 \setminus (Z_1\setminus Z_2)##. The measureable sets form a sigma algebra, right?
 
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  • #3
Dick said:
##Z_1## and ##Z_1 \setminus Z_2## are in ##\Sigma##. ##(Z_1 \cap Z_2) = Z_1 \setminus (Z_1\setminus Z_2)##. The measureable sets form a sigma algebra, right?

Oh, I see, as you've said ##(Z_1 \cap Z_2) = Z_1 \setminus (Z_1\setminus Z_2)##, and, ##Z_1 \setminus (Z_1\setminus Z_2)=Z_1 \cap (Z_1 \setminus Z_2)^c##, since a ##σ-## algebra is closed under countable intersection, one can deduce from here that ##Z_1 \cap Z_2 \in \Sigma## (for example, I can set ##\bigcap_{i \in \mathbb N} E_i## with ##E_1=Z_1, E_2=(Z_1 \setminus Z_2)^c## and ##E_i=A## for ##i\geq 2##). In a similar way, using the fact that a ##σ-##algebra is closed under countable union, it is proved that ##Z_2=(Z_2 \setminus Z_1) \cup (Z_1 \cap Z_2) \in \Sigma##

Thanks!
 
  • #4
mahler1 said:
Oh, I see, as you've said ##(Z_1 \cap Z_2) = Z_1 \setminus (Z_1\setminus Z_2)##, and, ##Z_1 \setminus (Z_1\setminus Z_2)=Z_1 \cap (Z_1 \setminus Z_2)^c##, since a ##σ-## algebra is closed under countable intersection, one can deduce from here that ##Z_1 \cap Z_2 \in \Sigma## (for example, I can set ##\bigcap_{i \in \mathbb N} E_i## with ##E_1=Z_1, E_2=(Z_1 \setminus Z_2)^c## and ##E_i=A## for ##i\geq 2##). In a similar way, using the fact that a ##σ-##algebra is closed under countable union, it is proved that ##Z_2=(Z_2 \setminus Z_1) \cup (Z_1 \cap Z_2) \in \Sigma##

Thanks!

You're welcome! And you can just say that if C and D are in the sigma algebra then ##C \cap D## is in the sigma algebra. You don't have to spell out the whole countable intersection. Two is countable.
 

1. What is a complete measure space?

A complete measure space is a mathematical concept used in measure theory. It consists of a set, a sigma-algebra (a collection of subsets of the set), and a measure (a function that assigns a non-negative real number to each set in the sigma-algebra). The completeness property means that all subsets of sets with measure zero are also included in the sigma-algebra.

2. Why is completeness important in measure theory?

Completeness is important because it ensures that the measure space is well-defined and all necessary sets are included in the sigma-algebra. This allows for more accurate and precise calculations and proofs in measure theory.

3. What are some common properties that can be proven on a complete measure space?

Some common properties that can be proven on a complete measure space include the Carathéodory extension theorem, the Lebesgue convergence theorem, and the Vitali-Hahn-Saks theorem.

4. How is a property proven on a complete measure space?

To prove a property on a complete measure space, one must use the definition of completeness and the properties of the measure function. This may involve constructing specific sets or using techniques such as monotone convergence or Fatou's lemma.

5. What are some applications of proving properties on a complete measure space?

Proving properties on a complete measure space is essential in many areas of mathematics, such as probability theory, functional analysis, and harmonic analysis. It allows for the rigorous and accurate study of measure and integration, which has numerous applications in physics, economics, and other fields.

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