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Inner measures are like outer measures, except not.
An inner measure is a function defined on all subsets of a given set, taking values in the extended real number system. It can be thought of as a counterpart to an [[outer measure]]. Whereas outer measures define the "size" of a set via a minimal covering set (from the outside), inner measures define the size of a set by approximating it with a maximal subset (from the inside). Although it is possible to develop measure theory with outer measures alone -- and many modern textbooks do just this<ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §1.4 </ref><ref name="Bass">Richard F. Bass, ''Real Analysis for Graduate Students: Version 4.2'', §4.1 </ref> -- Henri Lebesgue, in his 1902 thesis "Intégrale, longueur, aire" ("Integral, Length, Area"), used both inner measures and outer measures to construct the foundations of measure theory. It was not until Constantin Carathéodory made further contributions to the development of measure theory that inner measures were found to be redundant and an alternative notion of a "measurable" set was found<ref name="Bruckner">Bruckner, Bruckner, and Thomson, ''Real Analysis, second edition'', §2.1 </ref>.
 
== Definition ==
 
Let <math>A \subseteq \mathbb{R}</math> be an open set, and define a function <math>\mu : 2^\mathbb{R} \rightarrow [0, \infty]</math> as follows. If <math>A = \emptyset</math>, then <math>\mu(A) = 0</math>, and if <math>A</math> is unbounded, then <math>\mu(A) = \infty</math>. Otherwise, if <math>A</math> is open, then it can be written as a disjoint union of open intervals. Define <math>\mu(I) = b - a</math> for any open interval <math>I = (a,b)</math>, and
 
:<math> \mu(A) = \sum_{k=1}^\infty \mu(I_k) </math>
 
whenever <math>A</math> is a disjoint union of open intervals, <math>A = \cup_{k=1}^\infty I_k</math>.
 
It remains to show how <math>\mu</math> is defined on closed, bounded subsets of <math>\mathbb{R}</math> (equivalently, compact subsets of <math>\mathbb{R}</math>, by the Heine-Borel theorem). Let <math>B \subseteq \mathbb{R}</math> be compact, and suppose <math>[a,b]</math> is the smallest closed interval containing <math>B</math>. Define
 
:<math>\mu(B) = b - a - \mu((a,b) \setminus B).</math>
 
In other words, <math>\mu(B)</math> is the measure of the smallest interval containing <math>B</math>, minus the measure of the complement of <math>B</math> (which is an open set, and hence defined).
 
It is worth noting that this implies a particularly nice result, namely
 
:<math>\mu((a,b)) = \mu(B) + \mu((a,b) \setminus B).</math>
 
=== Outer Measures ===
 
The Lebesgue outer measure <math>\mu^*</math> is usually defined<ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §1.4 </ref> in terms of open intervals as
 
:<math> \mu^*(A) = \inf \left\{ \sum_{i=1}^\infty |b_i - a_i| : A \subseteq \bigcup_{i=1}^\infty (a_i, b_i) \right\}. </math>
 
Using the function <math>\mu</math> defined above, this can be rewritten in terms of general open sets as
 
:<math> \mu^*(A) = \inf \{ \mu(G) : A \subseteq G, G \text{ open} \}. </math>
 
=== Inner Measures ===
 
The Lebesgue inner measure of an arbitrary subset <math>A \subseteq \mathbb{R}</math> is defined as
 
:<math> \mu_*(A) = \sup \{ \mu(F) : F \subseteq A, F \text{ compact} \}. </math>
 
Since <math>E</math> may not contain any intervals (e.g. in the case of the singleton <math>\{ x \}</math>), there is no corresponding way to write this definition using open intervals<ref name="Bruckner">Bruckner, Bruckner, and Thomson, ''Real Analysis, second edition'', §2.1 </ref>. However, it is possible to define the Lebesgue inner measure in terms of the Lebesgue outer measure, as follows.
 
:<math>\mu_*(A) = b - a - \mu^*([a,b] \setminus A).</math>
 
=== Measurable Sets ===
 
Both inner measures and outer measures have one glaring flaw, namely that <math>\mu^*(A_1 \cup A_2)</math> need not be equal to <math>\mu^*(A_1) + \mu^*(A_2)</math> (and equivalently for <math>\mu_*</math>). However, if one restricts to sets where <math>\mu^*(A) = \mu_*(A)</math>, then countable additivity does hold. Hence, <math>A \subseteq \mathbb{R}</math> is said to be a Lebesgue-measurable set if <math>\mu^*(A) = \mu_*(A)</math>. The collection of Lebesgue-measurable sets forms a [[Sigma-algebra | <math>\sigma</math>-algebra]], denoted
 
:<math>\mathcal{A} = \{ A \subseteq \mathbb{R} : \mu^*(A) = \mu_*(A) \}.</math>
 
The Lebesgue measure <math>\lambda: \mathcal{A} \rightarrow [0, \infty]</math> can then be defined by <math>\lambda(A) = \mu^*(A)</math> for all <math>A \in \mathcal{A}</math>.
 
These definitions differ from those in common use today<ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §1.4 </ref><ref name="Bass">Richard F. Bass, ''Real Analysis for Graduate Students: Version 4.2'', §4.1 </ref>, but they agree with Henri Lebesgue's usage in his 1902 thesis. Later, Carathéodory removed the need for inner measures and defined a <math>\mu^*</math>-measurable set to be any set <math>A \subseteq \mathbb{R}</math> that satisfies
 
:<math>\mu^*(E) = \mu^*(E \cap A) + \mu^*(E \setminus A)</math>
 
for all <math>E \subseteq \mathbb{R}</math>.
 
== References ==

Latest revision as of 23:04, 13 November 2020

An inner measure is a function defined on all subsets of a given set, taking values in the extended real number system. It can be thought of as a counterpart to an outer measure. Whereas outer measures define the "size" of a set via a minimal covering set (from the outside), inner measures define the size of a set by approximating it with a maximal subset (from the inside). Although it is possible to develop measure theory with outer measures alone -- and many modern textbooks do just this[1][2] -- Henri Lebesgue, in his 1902 thesis "Intégrale, longueur, aire" ("Integral, Length, Area"), used both inner measures and outer measures to construct the foundations of measure theory. It was not until Constantin Carathéodory made further contributions to the development of measure theory that inner measures were found to be redundant and an alternative notion of a "measurable" set was found[3].

Definition

Let be an open set, and define a function as follows. If , then , and if is unbounded, then . Otherwise, if is open, then it can be written as a disjoint union of open intervals. Define for any open interval , and

whenever is a disjoint union of open intervals, .

It remains to show how is defined on closed, bounded subsets of (equivalently, compact subsets of , by the Heine-Borel theorem). Let be compact, and suppose is the smallest closed interval containing . Define

In other words, is the measure of the smallest interval containing , minus the measure of the complement of (which is an open set, and hence defined).

It is worth noting that this implies a particularly nice result, namely

Outer Measures

The Lebesgue outer measure is usually defined[1] in terms of open intervals as

Using the function defined above, this can be rewritten in terms of general open sets as

Inner Measures

The Lebesgue inner measure of an arbitrary subset is defined as

Since may not contain any intervals (e.g. in the case of the singleton ), there is no corresponding way to write this definition using open intervals[3]. However, it is possible to define the Lebesgue inner measure in terms of the Lebesgue outer measure, as follows.

Measurable Sets

Both inner measures and outer measures have one glaring flaw, namely that need not be equal to (and equivalently for ). However, if one restricts to sets where , then countable additivity does hold. Hence, is said to be a Lebesgue-measurable set if . The collection of Lebesgue-measurable sets forms a -algebra, denoted

The Lebesgue measure can then be defined by for all .

These definitions differ from those in common use today[1][2], but they agree with Henri Lebesgue's usage in his 1902 thesis. Later, Carathéodory removed the need for inner measures and defined a -measurable set to be any set that satisfies

for all .

References

  1. 1.0 1.1 1.2 Gerald B. Folland, Real Analysis: Modern Techniques and Their Applications, second edition, §1.4
  2. 2.0 2.1 Richard F. Bass, Real Analysis for Graduate Students: Version 4.2, §4.1
  3. 3.0 3.1 Bruckner, Bruckner, and Thomson, Real Analysis, second edition, §2.1