Lebesgue Measure
📂Measure TheoryLebesgue Measure
Definition
Let us define the function m:M→[0,∞] with respect to E∈M as follows m(E):=m∗(E). m is called the (Lebesgue) measure.
Description
The outer measure was neatly defined by m∗:P(R)→[0,∞], but it left something to be desired as a generalization of length. Limiting its domain to the real numbers’ sigma-field completed the ideal ‘generalization of length.’ This can be seen as a step back conditionally to meet the Carathéodory condition.
Of course, this is a special case in X=R when compared to general measures.
Basic Properties
Assuming A,B,E∈M and for all n∈N, let’s say An,Bn,∈M. The measure has the following properties:
- [1]: A⊂B⟹m(A)≤m(B)
- [2]: If A⊂B then, m(A)<∞⟹m(B∖A)=m(B)−m(A)
- [3]: t∈R⟹m(E)=m(E+t)
- [4]: m(A△B)=0⟹B∈Mm(A)=m(B)
- [5]: For all ε>0,A⊂R, there exists an open O that satisfies the following.
A⊂Om(O)≤m∗(A)+ε
- [6]: For all A⊂R, there exists a sequence of open sets {On} that satisfies the following.
A⊂n⋂Onm(n⋂On)=m∗(A)
- [7]: An⊂An+1⟹m(n=1⋃∞An)=n→∞limm(An)
- [8]: If An+1⊂An then, m(A1)<∞⟹m(n=1⋂∞An)=n→∞limm(An)
- [9]: m(i=1⨆nAi)=i=1∑nm(Ai)
- [10]: m is continuous in ∅.
- [11]: Bn→∅⟹m(Bn)→0
- A△B=(A∖B)∪(B∖A) is true.
Proof
[1]
Since m=m∗∣M, it naturally follows from the properties of outer measure.
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[2]
First, it’s necessary to prove (B∖A)∈M. Given (B∖A)=B∩(R∖A)=B∩Ac since A∈M, thus Ac∈M. Therefore, (B∖A)∈M and (B∖A)∩A=∅ and (B∖A)∪A=B, thus m(B∖A)+m(A)=m(B) is true. Assuming m(A)<∞, rearranging gives m(B∖A)=m(B)−m(A).
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[3]
Since m=m∗∣M, it naturally follows from the properties of outer measure.
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[4]
Since B=(A∩B)∪(B∖A)=A∖(A∖B)∪(B∖A), B∈M is true. Meanwhile, since m(A△B)=0, m(A∖B)=0 and m(B∖A)=0. Therefore,
m(B)=m(B∖A)+m(B∩A)=m(A∖B)+m(A∩B)=m(A)
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[7]
If we assume Bn:=An∖An−1, for i=j, Bi∩Bj=∅ and n=1⋃∞An=n=1⨆∞Bn are true. Therefore,
m(n=1⋃∞An)=m(n=1⨆∞Bn)=n=1∑∞m(Bn)=n→∞limk=1∑nm(Bk)=n→∞limm(k=1⨆nBk)=n→∞limm(An)
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[8]
Since (A1∖An)⊂(A1∖An+1), by [7]
m(n=1⋃∞(A1∖An))=n→∞limm(A1∖An)
And since m(An)<∞, by [3]
m(A1∖An)=m(A1)−m(An)
Meanwhile, since n=1⋃∞(A1∖An)=A1∖n=1⋂∞An
m(n=1⋃∞(A1∖An))=m(A1)−m(n=1⋂∞An)
Summarizing,
m(n=1⋃∞(A1∖An))=m(A1)−n→∞limm(An)=m(A1)−m(n=1⋂∞An)
Therefore, n→∞limm(An)=m(n=1⋂∞An)
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Generalization