Discrepancy of a sequence
In mathematics, a sequence {s1, s2, s3, ...} of real numbers is said to be equidistributed, or uniformly distributed, if the proportion of terms falling in a subinterval is proportional to the length of that interval. Such sequences are studied in Diophantine approximation theory and have applications to Monte Carlo integration.
A sequence {s1, s2, s3, ...} of real numbers is said to be equidistributed on a non-degenerate interval [a, b] if for any subinterval [c, d] of [a, b] we have
(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.
We define the discrepancy DN for a sequence {s1, s2, s3, ...} with respect to the interval [a, b] as
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. See low-discrepancy sequence for stronger criteria and constructions of low-discrepancy sequences for constructions of sequences which are more evenly distributed.
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