A\subset\Rn
\Rn
Let μ be the Lebesgue measure on the Euclidean space Rn and A be a Lebesgue measurable subset of Rn. Define the approximate density of A in a ε-neighborhood of a point x in Rn as
d | ||||
|
where Bε denotes the closed ball of radius ε centered at x.
Lebesgue's density theorem asserts that for almost every point x of A the density
d(x)=\lim\varepsilon\tod\varepsilon(x)
exists and is equal to 0 or 1.
In other words, for every measurable set A, the density of A is 0 or 1 almost everywhere in Rn.[1] However, if μ(A) > 0 and, then there are always points of Rn where the density is neither 0 nor 1.
For example, given a square in the plane, the density at every point inside the square is 1, on the edges is 1/2, and at the corners is 1/4. The set of points in the plane at which the density is neither 0 nor 1 is non-empty (the square boundary), but it is negligible.
The Lebesgue density theorem is a particular case of the Lebesgue differentiation theorem.
Thus, this theorem is also true for every finite Borel measure on Rn instead of Lebesgue measure, see Discussion.