A sequence (
s1,
s2,
s3, ...) of
real numbers is said to be
equidistributed on a non-degenerate
interval [
a,
b] if for every subinterval [
c,
d] of [
a,
b] we have :\lim_{n\to\infty}{ \left|\{\,s_1,\dots,s_n \,\} \cap [c,d] \right| \over n}={d-c \over b-a} . (Here, the notation |{
s1,...,
sn} ∩ [
c,
d]| denotes the number of elements, out of the first
n elements of the sequence, that are between
c and
d.) For example, if a sequence is equidistributed in [0, 2], since the interval [0.5, 0.9] occupies 1/5 of the length of the interval [0, 2], as
n becomes large, the proportion of the first
n members of the sequence which fall between 0.5 and 0.9 must approach 1/5. Loosely speaking, one could say that each member of the sequence is equally likely to fall anywhere in its range. However, this is not to say that (
sn) is a sequence of
random variables; rather, it is a determinate sequence of real numbers.
Discrepancy We define the
discrepancy DN for a sequence (
s1,
s2,
s3, ...) with respect to the interval [
a,
b] as :D_N = \sup_{a \le c \le d \le b} \left\vert \frac{\left|\{\,s_1,\dots,s_N \,\} \cap [c,d] \right|}{N} - \frac{d-c}{b-a} \right\vert . A sequence is thus equidistributed if the discrepancy
DN tends to zero as
N tends to infinity. Equidistribution is a rather weak criterion to express the fact that a sequence fills the segment leaving no gaps. For example, the drawings of a random variable uniform over a segment will be equidistributed in the segment, but there will be large gaps compared to a sequence which first enumerates multiples of ε in the segment, for some small ε, in an appropriately chosen way, and then continues to do this for smaller and smaller values of ε. For stronger criteria and for constructions of sequences that are more evenly distributed, see
low-discrepancy sequence.
Riemann integral criterion for equidistribution Recall that if
f is a
function having a
Riemann integral in the interval [
a,
b], then its integral is the limit of
Riemann sums taken by sampling the function
f in a
set of points chosen from a fine partition of the interval. Therefore, if some sequence is equidistributed in [
a,
b], it is expected that this sequence can be used to calculate the integral of a Riemann-integrable function. This leads to the following criterion for an equidistributed sequence: Suppose (
s1,
s2,
s3, ...) is a sequence contained in the interval [
a,
b]. Then the following conditions are equivalent: • The sequence is equidistributed on [
a,
b]. • For every Riemann-integrable (
complex-valued) function {{nowrap|
f : [
a,
b] → \mathbb{C}}}, the following limit holds: :: \lim_{N \to \infty}\frac{1}{N}\sum_{n=1}^{N} f\left(s_n\right) = \frac{1}{b-a}\int_a^b f(x)\,dx : This criterion leads to the idea of
Monte-Carlo integration, where integrals are computed by sampling the function over a sequence of random variables equidistributed in the interval. It is not possible to generalize the integral criterion to a class of functions bigger than just the Riemann-integrable ones. For example, if the
Lebesgue integral is considered and
f is taken to be in
L1, then this criterion fails. As a
counterexample, take
f to be the
indicator function of some equidistributed sequence. Then in the criterion, the left hand side is always 1, whereas the right hand side is zero, because the sequence is
countable, so
f is zero
almost everywhere. In fact, the
de Bruijn–Post Theorem states the converse of the above criterion: If
f is a function such that the criterion above holds for any equidistributed sequence in [
a,
b], then
f is Riemann-integrable in [
a,
b]. ==Equidistribution modulo 1==