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Concept of area in any dimension
In measure theory, a branch of mathematics, the Lebesgue measure, named after French mathematician Henri Lebesgue, is the standard way of assigning a measure to subsets of higher dimensional Euclidean n-spaces. For lower dimensions n = 1 , 2 , or 3 {\displaystyle n=1,2,{\text{or }}3} , it coincides with the standard measure of length, area, or volume. In general, it is also called n-dimensional volume, n-volume, hypervolume, or simply volume.[1] It is used throughout real analysis, in particular to define Lebesgue integration. Sets that can be assigned a Lebesgue measure are called Lebesgue-measurable; the measure of the Lebesgue-measurable set A {\displaystyle A} is here denoted by λ ( A ) {\displaystyle \lambda (A)} .
Henri Lebesgue described this measure in the year 1901 which, a year after, was followed up by his description of the Lebesgue integral. Both were published as part of his dissertation in 1902.[2]
For any interval I = [ a , b ] {\displaystyle I=[a,b]} , or I = ( a , b ) {\displaystyle I=(a,b)} , in the set R {\displaystyle \mathbb {R} } of real numbers, let ℓ ( I ) = b − a {\displaystyle \ell (I)=b-a} denote its length. For any subset E ⊆ R {\displaystyle E\subseteq \mathbb {R} } , the Lebesgue outer measure[3] λ ∗ ( E ) {\displaystyle \lambda ^{\!*\!}(E)} is defined as an infimum
λ ∗ ( E ) = inf { ∑ k = 1 ∞ ℓ ( I k ) : ( I k ) k ∈ N is a sequence of open intervals with E ⊂ ⋃ k = 1 ∞ I k } . {\displaystyle \lambda ^{\!*\!}(E)=\inf \left\{\sum _{k=1}^{\infty }\ell (I_{k}):{(I_{k})_{k\in \mathbb {N} }}{\text{ is a sequence of open intervals with }}E\subset \bigcup _{k=1}^{\infty }I_{k}\right\}.}
The above definition can be generalised to higher dimensions as follows.[4] For any rectangular cuboid C {\displaystyle C} which is a Cartesian product C = I 1 × ⋯ × I n {\displaystyle C=I_{1}\times \cdots \times I_{n}} of open intervals, let vol ( C ) = ℓ ( I 1 ) × ⋯ × ℓ ( I n ) {\displaystyle \operatorname {vol} (C)=\ell (I_{1})\times \cdots \times \ell (I_{n})} (a real number product) denote its volume. For any subset E ⊆ R n {\displaystyle E\subseteq \mathbb {R^{n}} } ,
λ ∗ ( E ) = inf { ∑ k = 1 ∞ vol ( C k ) : ( C k ) k ∈ N is a sequence of products of open intervals with E ⊂ ⋃ k = 1 ∞ C k } . {\displaystyle \lambda ^{\!*\!}(E)=\inf \left\{\sum _{k=1}^{\infty }\operatorname {vol} (C_{k}):{(C_{k})_{k\in \mathbb {N} }}{\text{ is a sequence of products of open intervals with }}E\subset \bigcup _{k=1}^{\infty }C_{k}\right\}.}
A set E {\displaystyle E} satisfies the Carathéodory criterion whenever, for every A ⊆ R n {\displaystyle A\subseteq \mathbb {R^{n}} } , we have:
λ ∗ ( A ) = λ ∗ ( A ∩ E ) + λ ∗ ( A ∩ E ∁ ) . {\displaystyle \lambda ^{\!*\!}(A)=\lambda ^{\!*\!}(A\cap E)+\lambda ^{\!*\!}(A\cap E^{\complement }).}
Here, E ∁ {\displaystyle E^{\complement }} is the complement of E {\displaystyle E} . Sets E {\displaystyle E} satisfying the Carathéodory criterion are said to be Lebesgue-measurable. The set of all such E {\displaystyle E} forms a σ-algebra.
The Lebesgue measure of such a set is defined as its Lebesgue outer measure:
λ ( E ) = λ ∗ ( E ) {\displaystyle \lambda (E)=\lambda ^{\!*\!}(E)} .
ZFC proves that non-measurable sets do exist; examples are the Vitali sets.
The first part of the definition states that the subset E {\displaystyle E} of the real numbers is reduced to its outer measure by coverage by sets of open intervals. Each of these sets of intervals I {\displaystyle I} covers E {\displaystyle E} in a sense, since the union of these intervals contains E {\displaystyle E} . The total length of any covering interval set may overestimate the measure of E , {\displaystyle E,} because E {\displaystyle E} is a subset of the union of the intervals, and so the intervals may include points which are not in E {\displaystyle E} . The Lebesgue outer measure emerges as the greatest lower bound (infimum) of the lengths from among all possible such sets. Intuitively, it is the total length of those interval sets which fit E {\displaystyle E} most tightly and do not overlap.
That characterizes the Lebesgue outer measure. Whether this outer measure translates to the Lebesgue measure proper depends on an additional condition. This condition is tested by taking subsets A {\displaystyle A} of the real numbers using E {\displaystyle E} as an instrument to split A {\displaystyle A} into two partitions: the part of A {\displaystyle A} which intersects with E {\displaystyle E} and the remaining part of A {\displaystyle A} which is not in E {\displaystyle E} : the set difference of A {\displaystyle A} and E {\displaystyle E} . These partitions of A {\displaystyle A} are subject to the outer measure. If for all possible such subsets A {\displaystyle A} of the real numbers, the partitions of A {\displaystyle A} cut apart by E {\displaystyle E} have outer measures whose sum is the outer measure of A {\displaystyle A} , then the outer Lebesgue measure of E {\displaystyle E} gives its Lebesgue measure. Intuitively, this condition means that the set E {\displaystyle E} must not have some curious properties which causes a discrepancy in the measure of another set when E {\displaystyle E} is used as a "mask" to "clip" that set, hinting at the existence of sets for which the Lebesgue outer measure does not give the Lebesgue measure. (Such sets are, in fact, not Lebesgue-measurable.)
The Lebesgue measure on R n {\displaystyle \mathbb {R} ^{n}} has the following properties:
All the above may be succinctly summarized as follows (although the last two assertions are non-trivially linked to the following):
The Lebesgue-measurable sets form a
σ-algebracontaining all products of intervals, and
λ {\displaystyle \lambda }is the unique
complete translation-invariant measureon that
σ-algebra with
λ ( [ 0 , 1 ] × [ 0 , 1 ] × ⋯ × [ 0 , 1 ] ) = 1. {\displaystyle \lambda ([0,1]\times [0,1]\times \cdots \times [0,1])=1.}The Lebesgue measure also has the property of being σ-finite.
A subset of R n {\displaystyle \mathbb {R} ^{n}} is a null set if, for every ε > 0 {\displaystyle \varepsilon >0} , it can be covered with countably many products of n intervals whose total volume is at most ε {\displaystyle \varepsilon } . All countable sets are null sets.
If a subset of R n {\displaystyle \mathbb {R} ^{n}} has Hausdorff dimension less than n then it is a null set with respect to n-dimensional Lebesgue measure. Here Hausdorff dimension is relative to the Euclidean metric on R n {\displaystyle \mathbb {R} ^{n}} (or any metric Lipschitz equivalent to it). On the other hand, a set may have topological dimension less than n and have positive n-dimensional Lebesgue measure. An example of this is the Smith–Volterra–Cantor set which has topological dimension 0 yet has positive 1-dimensional Lebesgue measure.
In order to show that a given set A {\textstyle A} is Lebesgue-measurable, one usually tries to find a "nicer" set B {\textstyle B} which differs from A {\textstyle A} only by a null set (in the sense that the symmetric difference ( A ∖ B ) ∪ ( B ∖ A ) {\textstyle (A\setminus B)\cup (B\setminus A)} is a null set) and then show that B {\textstyle B} can be generated using countable unions and intersections from open or closed sets.
Construction of the Lebesgue measure[edit]The modern construction of the Lebesgue measure is an application of Carathéodory's extension theorem. It proceeds as follows.
Fix n ∈ N {\displaystyle n\in \mathbb {N} } . A box in R n {\displaystyle \mathbb {R} ^{n}} is a set of the form B = ∏ i = 1 n [ a i , b i ] , {\displaystyle B=\prod _{i=1}^{n}[a_{i},b_{i}]\,,} where b i ≥ a i {\displaystyle b_{i}\geq a_{i}} , and the product symbol here represents a Cartesian product. The volume of this box is defined to be vol ( B ) = ∏ i = 1 n ( b i − a i ) . {\displaystyle \operatorname {vol} (B)=\prod _{i=1}^{n}(b_{i}-a_{i})\,.} For any subset A {\displaystyle A} of R n {\displaystyle \mathbb {R} ^{n}} , we can define its outer measure λ ∗ ( A ) {\displaystyle \lambda ^{\!*\!}(A)} by: λ ∗ ( A ) = inf { ∑ B ∈ C vol ( B ) : C is a countable collection of boxes whose union covers A } . {\displaystyle \lambda ^{*}(A)=\inf \left\{\sum _{B\in {\mathcal {C}}}\operatorname {vol} (B):{\mathcal {C}}{\text{ is a countable collection of boxes whose union covers }}A\right\}.} We then define the set A {\displaystyle A} to be Lebesgue-measurable if for every subset S {\displaystyle S} of R n {\displaystyle \mathbb {R} ^{n}} , λ ∗ ( S ) = λ ∗ ( S ∩ A ) + λ ∗ ( S ∖ A ) . {\displaystyle \lambda ^{*}(S)=\lambda ^{*}(S\cap A)+\lambda ^{*}(S\setminus A)\,.} These Lebesgue-measurable sets form a σ-algebra, and the Lebesgue measure is defined by λ ( A ) = λ ∗ ( A ) {\displaystyle \lambda (A)=\lambda ^{\!*\!}(A)} for any Lebesgue-measurable set A {\displaystyle A} .
The existence of sets that are not Lebesgue-measurable is a consequence of the set-theoretical axiom of choice, which is independent from many of the conventional systems of axioms for set theory. The Vitali theorem, which follows from the axiom, states that there exist subsets of R {\displaystyle \mathbb {R} } that are not Lebesgue-measurable. Assuming the axiom of choice, non-measurable sets with many surprising properties have been demonstrated, such as those of the Banach–Tarski paradox.
In 1970, Robert M. Solovay showed that the existence of sets that are not Lebesgue-measurable is not provable within the framework of Zermelo–Fraenkel set theory in the absence of the axiom of choice (see Solovay's model).[9]
Relation to other measures[edit]The Borel measure agrees with the Lebesgue measure on those sets for which it is defined; however, there are many more Lebesgue-measurable sets than there are Borel measurable sets. While the Lebesgue measure on R n {\displaystyle \mathbb {R} ^{n}} is automatically a locally finite Borel measure, not every locally finite Borel measure on R n {\displaystyle \mathbb {R} ^{n}} is necessarily a Lebesgue measure. The Borel measure is translation-invariant, but not complete.
The Haar measure can be defined on any locally compact group and is a generalization of the Lebesgue measure ( R n {\displaystyle \mathbb {R} ^{n}} with addition is a locally compact group).
The Hausdorff measure is a generalization of the Lebesgue measure that is useful for measuring the subsets of R n {\displaystyle \mathbb {R} ^{n}} of lower dimensions than n, like submanifolds, for example, surfaces or curves in R 3 {\displaystyle \mathbb {R} ^{3}} and fractal sets. The Hausdorff measure is not to be confused with the notion of Hausdorff dimension.
It can be shown that there is no infinite-dimensional analogue of Lebesgue measure.
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