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, 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 is here denoted by λ(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]

Definition

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For any interval  , or  , in the set   of real numbers, let   denote its length. For any subset  , the Lebesgue outer measure[3]   is defined as an infimum

 

The above definition can be generalised to higher dimensions as follows.[4] For any rectangular cuboid   which is a Cartesian product   of open intervals, let   (a real number product) denote its volume. For any subset  ,

 

Some sets   satisfy the Carathéodory criterion, which requires that for every  ,

 

The sets   that satisfy the Carathéodory criterion are said to be Lebesgue-measurable, with its Lebesgue measure being defined as its Lebesgue outer measure:  . The set of all such   forms a σ-algebra.

A set   that does not satisfy the Carathéodory criterion is not Lebesgue-measurable. ZFC proves that non-measurable sets do exist; an example is the Vitali sets.

Intuition

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The first part of the definition states that the subset   of the real numbers is reduced to its outer measure by coverage by sets of open intervals. Each of these sets of intervals   covers   in a sense, since the union of these intervals contains  . The total length of any covering interval set may overestimate the measure of   because   is a subset of the union of the intervals, and so the intervals may include points which are not in  . 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   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   of the real numbers using   as an instrument to split   into two partitions: the part of   which intersects with   and the remaining part of   which is not in  : the set difference of   and  . These partitions of   are subject to the outer measure. If for all possible such subsets   of the real numbers, the partitions of   cut apart by   have outer measures whose sum is the outer measure of  , then the outer Lebesgue measure of   gives its Lebesgue measure. Intuitively, this condition means that the set   must not have some curious properties which causes a discrepancy in the measure of another set when   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.)

Examples

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Properties

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Translation invariance: The Lebesgue measure of   and   are the same.

The Lebesgue measure on Rn has the following properties:

  1. If A is a cartesian product of intervals I1 × I2 × ⋯ × In, then A is Lebesgue-measurable and  
  2. If A is a union of countably many pairwise disjoint Lebesgue-measurable sets, then A is itself Lebesgue-measurable and λ(A) is equal to the sum (or infinite series) of the measures of the involved measurable sets.
  3. If A is Lebesgue-measurable, then so is its complement.
  4. λ(A) ≥ 0 for every Lebesgue-measurable set A.
  5. If A and B are Lebesgue-measurable and A is a subset of B, then λ(A) ≤ λ(B). (A consequence of 2.)
  6. Countable unions and intersections of Lebesgue-measurable sets are Lebesgue-measurable. (Not a consequence of 2 and 3, because a family of sets that is closed under complements and disjoint countable unions does not need to be closed under countable unions:  .)
  7. If A is an open or closed subset of Rn (or even Borel set, see metric space), then A is Lebesgue-measurable.
  8. If A is a Lebesgue-measurable set, then it is "approximately open" and "approximately closed" in the sense of Lebesgue measure.
  9. A Lebesgue-measurable set can be "squeezed" between a containing open set and a contained closed set. This property has been used as an alternative definition of Lebesgue measurability. More precisely,   is Lebesgue-measurable if and only if for every   there exist an open set   and a closed set   such that   and  .[8]
  10. A Lebesgue-measurable set can be "squeezed" between a containing Gδ set and a contained Fσ. I.e, if A is Lebesgue-measurable then there exist a Gδ set G and an Fσ F such that G ⊇ A ⊇ F and λ(G \ A) = λ(A \ F) = 0.
  11. Lebesgue measure is both locally finite and inner regular, and so it is a Radon measure.
  12. Lebesgue measure is strictly positive on non-empty open sets, and so its support is the whole of Rn.
  13. If A is a Lebesgue-measurable set with λ(A) = 0 (a null set), then every subset of A is also a null set. A fortiori, every subset of A is measurable.
  14. If A is Lebesgue-measurable and x is an element of Rn, then the translation of A by x, defined by A + x = {a + x : aA}, is also Lebesgue-measurable and has the same measure as A.
  15. If A is Lebesgue-measurable and  , then the dilation of   by   defined by   is also Lebesgue-measurable and has measure  
  16. More generally, if T is a linear transformation and A is a measurable subset of Rn, then T(A) is also Lebesgue-measurable and has the measure  .

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-algebra containing all products of intervals, and λ is the unique complete translation-invariant measure on that σ-algebra with  

The Lebesgue measure also has the property of being σ-finite.

Null sets

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A subset of Rn is a null set if, for every ε > 0, it can be covered with countably many products of n intervals whose total volume is at most ε. All countable sets are null sets.

If a subset of Rn 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 Rn (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 is Lebesgue-measurable, one usually tries to find a "nicer" set B which differs from A only by a null set (in the sense that the symmetric difference (AB) ∪ (BA) is a null set) and then show that B can be generated using countable unions and intersections from open or closed sets.

Construction of the Lebesgue measure

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The modern construction of the Lebesgue measure is an application of Carathéodory's extension theorem. It proceeds as follows.

Fix nN. A box in Rn is a set of the form

 

where biai, and the product symbol here represents a Cartesian product. The volume of this box is defined to be

 

For any subset A of Rn, we can define its outer measure λ*(A) by:

 

We then define the set A to be Lebesgue-measurable if for every subset S of Rn,

 

These Lebesgue-measurable sets form a σ-algebra, and the Lebesgue measure is defined by λ(A) = λ*(A) for any Lebesgue-measurable set 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 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

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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. 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 (Rn 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 Rn of lower dimensions than n, like submanifolds, for example, surfaces or curves in R3 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.

See also

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References

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  1. ^ The term volume is also used, more strictly, as a synonym of 3-dimensional volume
  2. ^ Lebesgue, H. (1902). "Intégrale, Longueur, Aire". Annali di Matematica Pura ed Applicata. 7: 231–359. doi:10.1007/BF02420592. S2CID 121256884.
  3. ^ Royden, H. L. (1988). Real Analysis (3rd ed.). New York: Macmillan. p. 56. ISBN 0-02-404151-3.
  4. ^ "Lebesgue-Maß". 29 August 2022. Retrieved 9 March 2023 – via Wikipedia.
  5. ^ Asaf Karagila. "What sets are Lebesgue-measurable?". math stack exchange. Retrieved 26 September 2015.
  6. ^ Asaf Karagila. "Is there a sigma-algebra on R strictly between the Borel and Lebesgue algebras?". math stack exchange. Retrieved 26 September 2015.
  7. ^ Osgood, William F. (January 1903). "A Jordan Curve of Positive Area". Transactions of the American Mathematical Society. 4 (1). American Mathematical Society: 107–112. doi:10.2307/1986455. ISSN 0002-9947. JSTOR 1986455.
  8. ^ Carothers, N. L. (2000). Real Analysis. Cambridge: Cambridge University Press. pp. 293. ISBN 9780521497565.
  9. ^ Solovay, Robert M. (1970). "A model of set-theory in which every set of reals is Lebesgue-measurable". Annals of Mathematics. Second Series. 92 (1): 1–56. doi:10.2307/1970696. JSTOR 1970696.