# Lebesgue Outer Measure

by | Nov 21, 2021 | Math Learning

## Introduction:

The Riemann integral of a bounded function over a closed, bounded interval is defined using approximations of the function that are associated with partitions of its domain into finite collections of subintervals. The generalization of the Riemann integral to the Lebesgue integral will be achieved by using approximations of the function that are associated with decompositions of its domain into finite collections of sets which we call Lebesgue measurable. Each interval is Lebesgue measurable. The richness of the collection of Lebesgue measurable sets provides better upper and lower approximations of a function, and therefore of its integral than are possible by just employing intervals. This leads to a larger class of functions that are Lebesgue integrable over very general domains and an integral that has better properties. For instance, under quite general circumstances we will prove that if a sequence of functions converges point-wise to a limiting function, then the integral of the limit function is the limit of the integrals of the approximating functions.

## Motivation:

One of the primary motivations for developing a theory has to do with the failure of the theory of Riemann integration to behave nicely undertaking point-wise limits of functions. In particular, it is well-known that point-wise convergence of a sequence of functions does not translate to the interchange of limits and integrals; for example, if then as , converges pointwise to the zero function.

If we take its integral, Which leads to . This inability to interchange a limit and an integral can be extremely inconvenient. One can interchange a limit and Riemann integration under certain circumstances like uniform convergence, but this is usually far too restrictive of a condition. What measure-theoretic integration gives you is a way to do this interchange provided we, have point-wise convergence and much weaker conditions than uniform convergence; in exchange, it forces us to throw out sets of measure zero. In addition, once the theory is developed we suddenly have extremely powerful tools to take limits of integrals you did not have before (Lebesgue dominated convergence theorem). So we have two main motivations to make a rich theory

1. To integrate more functions (Like Dirichlet Function )
2. To make space this is completely integrable.

There are more motivations like

1. Interchanging limits and integrals (e.g. the limit of a sequence of continuous functions may not be Riemann integrable)
2. Length of Curves (finding the length of curves that are only rectifiable, not continuously differentiable), etc.

## Definition:

To define Lebesgue Measure on a set we need some precious definitions and some important functions and classes or collections of subsets of .

### Length Function:

Let denote the collection of all intervals of . If an interval has endpoints and we write it as . By convention, the open interval . Let . Define the function by [lambda((a,b))=begin{cases} vert b-avert, ;;; & text{if } a,bin mathbb{R} \ +infty, ;;; & text{if either } a=-infty text{ or } b=+infty text{ or both} end{cases}] This is called length function defined on .

### Properties of Set Function:

1. is monotonic i.e.

Let be such that where for Then [lambda(I)=sum_{i=1}^{n}lambda(J_{i}) ]

Let be such that  Then [lambda(I)leq sum_{i=1}^{n}lambda(J_{i}) ]

Let  be such that where for Then [lambda(I)= sum_{i=1}^{infty}lambda(J_{i}) ]

Let be such that where Then [lambda(I)leq sum_{i=1}^{infty}lambda(J_{i}) ]

1. Translation Invariance

[lambda(I)=lambda(I+x),] For every and .

## Algebra on a set:

Let be any non-empty set and let a collection of subsets of . Then the collection is called an algebra of subsets of if  satisfies following properties:

1. whenever
2. whenever

Then is called Algebra on .

### Algebra on a set:

Let be any non-empty set and let a collection of subsets of . Then the collection is called an Algebra of subsets of if  satisfies following properties:-

1. whenever
2. for

Then is called Algebra on .

## Definition of Lebesgue Measure:

Def:- For every subsets of , the Lebesgue Outer Measure of , denoted by is defined by [displaystylemathit{m}^{*}(A)=infleftlbracesum_{i=1}^{infty}lambda(I_{i}):Asubsetbigcup_{i=1}^{n}I_{i}rightrbrace] Where varies over all possible sequence of open intervals of whose union contains .

### Properties of Lebesgue Outer Measure:

The Lebesgue Outer Measure is generated by length function which is defined on earlier so it’s preserves some of their properties.

1. is monotonic i.e.

Let be such that Then [mathit{m}^{*}(I)leq sum_{i=1}^{n}mathit{m}^{*}(J_{i}) ]

Let be such that where Then [mathit{m}^{*}(I)leq sum_{i=1}^{infty}mathit{m}^{*}(J_{i}) ]

1. Translation Invariance

[mathit{m}^{*}(I)=mathit{m}^{*}(I+x),] For every and . Now we already noticed that hasn’t had the properties of finitely additive and not countable additive (why?) A Vitali* Set in , has a positive measure Specifically, let  denote translation. (textit{That is, for and let }.) Note that outer measure  is invariant under translation, so [mathit{m}^{*}(Aoplus x)=mathit{m}^{*}(A)] Now let be a Vitali set, and let be an enumeration of the rationals in . By construction of , the sets are pair wise disjoints and their union is . By countable sub-additively we have

In particular we must have  So we can find an integer  sufficiently large that [N.mathit{m}^{*}(V)>1, text{ For } n=1,ldots,N], Let . Then the sets  are pair wise disjoint, and since  We have [E=bigcup_{n=1}^{N}E_{n}]. Hence by monotonicity, . On the other hand, [sum_{n=1}^{N}mathit{m}^{*}(E_{n})=sum_{n=1}^{N}mathit{m}^{*}(Voplus q_{n})=sum_{n=1}^{N}mathit{m}^{*}(V)=N.mathit{m}^{*}(V)>1.] So we have [mathit{m}^{*}(E)<sum_{n=1}^{N}mathit{m}^{*}(E_{n})] So we saw that is not finitely additive and it is also not countable sub-additive. Vitali: An elementary example of a set of real numbers which is not Lebesgue measurable. Definition: Measurable Set(Carathéodory Condition): A set is said to be Lebesgue-Measurable if [mathit{m}^{*}(A)=mathit{m}^{*}(Acap E)+mathit{m}^{*}(Acap E^{c}) text{ for all } Asubset mathbb{R}] This Condition is known as Carathéodory Condition.

## Properties of Measurable set in R

1. If is Lebesgue Measurable then also Lebesgue Measurable set in
2. and are Lebesgue Measurable
3. Every Interval in is Lebesgue Measurable.
4. Every countable set is Lebesgue Measurable with measure zero i.e.

If is a countable set in then [mathit{m}^{*}(B)=0.]

1. Every uncountable set has a non-zero measure (except Cantor Set)
2. Every Borel* set is Lebesgue Measurable.

(Borel Set: Collection of all and sets) Definition: Class :- Collection of all Lebesgue Measurable sets in . [mathcal{M}=lbrace E; : ; text{E is Lebesgue meusurable in }mathbb{R}; Esubseteqmathbb{R} rbrace] This Collection is a Algebra and it is the largest measurable Algebra over and ()  is called Measure Space which we want to achive.

## Conclusion:

Now we got a new developed theory on subsets of and we can now use the theory to integrate those kinds of functions which we can’t integrate by using Riemann Integration. Also, we can use the theory to find the length of those kinds of curves which is not continuously differentiable on and we can use to find the integration over rationalize functions too. This rich theory gave us more freedom to apply on the space or subsets in .

## Bibliography:

1. Yeh ; Real Analysis
2. Robert G. Bartle; The Elements of Integration and Lebesgue Measure.
3. Sheldon Axler; Measure, Integration, and Real Analysis.

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