Prime Numbers
Prime Numbers Prime Numbers
8.3 Quasi-Monte Carlo (qMC) methods 407 all that discrepancy is of profound practical importance. Moreover, there are some surprising new results that go some distance, as we shall see, to explain why actual qMC experiments are sometimes fare much better—provide far more accuracy—than the discrepancy bounds imply. A qMC sequence S should generally be one of low D ∗ , and it is in the construction of such S that number theory becomes involved. The first thing we need to observe is that there is a subtle distinction between a point-set discrepancy and the discrepancy of a sequence. Take D = 1 dimension for example, in which case the point set P = has D∗ N sequence S that enjoys the property D∗ N 1 3 1 , ,...,1 − 2N 2N 2N (P )=1/(2N). On the other hand, there exists no countably infinite (S) =O(1/N ). In fact, it was shown by [Schmidt 1972] that if S is countably infinite, then for infinitely many N, D ∗ ln N N(S) ≥ c N , where c is an absolute constant (i.e., independent of N and S). Actually, the constant can be taken to be c =3/50 [Niederreiter 1992], but the main point is that the requirement of an infinite qMC sequence, from which a researcher may draw arbitrarily large numbers of contiguous samples, gives rise to special considerations of error. The point set P above with its discrepancy 1/(2N) is allowed because, of course, the members of the sequence themselves depend on N. 8.3.2 Specific qMC sequences We are now prepared to construct some low-star-discrepancy sequences. A primary goal will be to define a practical low-discrepancy sequence for any given prime p, by counting in a certain clever fashion through base-p representations of integers. We shall start with a somewhat more general description for arbitrary base-B representations. For more than one dimension, a set of pairwise coprime bases will be used. Definition 8.3.3. For an integer base B ≥ 2, the van der Corput sequence for base B is the sequence SB =(ρB(n)) , n =0, 1, 2,..., where ρB is the radical-inverse function, defined on nonnegative integers n, with presumed base-B representation n = i niB i ,by: ρB(n) = niB −i−1 i
408 Chapter 8 THE UBIQUITY OF PRIME NUMBERS These sequences are easy to envision and likewise easy to generate in practice; in fact, their generation is easier than one might suspect. Say we desire the van der Corput sequence for base B = 2. Then we simply count from n =0, in binary n =0, 1, 10, 11, 100,..., and form the reversals of the bits to obtain (also in binary) S =(0.0, 0.10, 0.01, 0.11, 0.001,...). To put it symbolically, if we are counting and happen to be at integer index n = nknk−1 ...n1n0, then the term ρB(n) ∈ S is given by reversing the digits thus: ρB(n) =0.n0n1 ...nk. It is known that every van der Corput sequence has D ∗ N(SB) =O ln N N where the implied big-O constant depends only on B. It turns out that B =3 has the smallest such constant, but the main point affecting implementations is that the constant generally increases for larger bases B [Faure 1981]. For D>1 dimensions, it is possible to generate qMC sequences based on the van der Corput forms, in the following manner: Definition 8.3.4. Let ¯ B = {B1,B2,...,BD} be a set of pairwise-coprime bases, each Bi > 1. We define the Halton sequence for bases ¯ B by where , S ¯ B =(xn) , n =0, 1, 2,..., xn =(ρB1(n),...,ρBD (n)). In other words, a Halton sequence involves a specific base for each vector coordinate, and the respective bases are to be pairwise coprime. Thus for example, a qMC sequence of points in the (D = 3)-dimensional unit cube can be generated by choosing prime bases {B1,B2,B3} = {2, 3, 5} and counting n =0, 1, 2,... in those bases simultaneously, to obtain x0 =(0, 0, 0), x1 =(1/2, 1/3, 1/5), x2 =(1/4, 2/3, 2/5), x3 =(3/4, 1/9, 3/5), and so on. The manner in which these points deposit themselves in the unit 3-cube is interesting. We can see once again the basic, qualitative aspect
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8.3 Quasi-Monte Carlo (qMC) methods 407<br />
all that discrepancy is of profound practical importance. Moreover, there are<br />
some surprising new results that go some distance, as we shall see, to explain<br />
why actual qMC experiments are sometimes fare much better—provide far<br />
more accuracy—than the discrepancy bounds imply.<br />
A qMC sequence S should generally be one of low D ∗ , and it is in the<br />
construction of such S that number theory becomes involved. The first thing<br />
we need to observe is that there is a subtle distinction between a point-set<br />
discrepancy and the discrepancy of a sequence. Take D = 1 dimension for<br />
example, in which case the point set<br />
P =<br />
has D∗ N<br />
sequence S that enjoys the property D∗ N<br />
<br />
1 3<br />
1<br />
, ,...,1 −<br />
2N 2N 2N<br />
(P )=1/(2N). On the other hand, there exists no countably infinite<br />
(S) =O(1/N ). In fact, it was shown<br />
by [Schmidt 1972] that if S is countably infinite, then for infinitely many N,<br />
D ∗ ln N<br />
N(S) ≥ c<br />
N ,<br />
where c is an absolute constant (i.e., independent of N and S). Actually, the<br />
constant can be taken to be c =3/50 [Niederreiter 1992], but the main point<br />
is that the requirement of an infinite qMC sequence, from which a researcher<br />
may draw arbitrarily large numbers of contiguous samples, gives rise to special<br />
considerations of error. The point set P above with its discrepancy 1/(2N) is<br />
allowed because, of course, the members of the sequence themselves depend<br />
on N.<br />
8.3.2 Specific qMC sequences<br />
We are now prepared to construct some low-star-discrepancy sequences.<br />
A primary goal will be to define a practical low-discrepancy sequence<br />
for any given prime p, by counting in a certain clever fashion through<br />
base-p representations of integers. We shall start with a somewhat more<br />
general description for arbitrary base-B representations. For more than one<br />
dimension, a set of pairwise coprime bases will be used.<br />
Definition 8.3.3. For an integer base B ≥ 2, the van der Corput sequence<br />
for base B is the sequence<br />
SB =(ρB(n)) , n =0, 1, 2,...,<br />
where ρB is the radical-inverse function, defined on nonnegative integers n,<br />
with presumed base-B representation n = <br />
i niB i ,by:<br />
ρB(n) = <br />
niB −i−1<br />
i