William W. L. Chen
Macquarie University
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Mathematika | 1980
William W. L. Chen
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Quarterly Journal of Mathematics | 1983
William W. L. Chen
We study the L w -norm (2 < W < oo) of the discrepancy of a sequence of points in the unit cube relative to similar copies of a given convex polygon. In particular, we prove the rather surprising result that the estimates obtained have the same order of magnitude as the analogous question when the sequence of points is replaced by a set of points.
Handbook of discrete and computational geometry | 1997
J. Ralph Alexander; József Beck; William W. L. Chen
A sequence s1, s2, . . . in U = [0, 1) is said to be uniformly distributed if, in the limit, the number of sj falling in any given subinterval is proportional to its length. Equivalently, s1, s2, . . . is uniformly distributed if the sequence of equiweighted atomic probability measures μN (sj) = 1/N , supported by the initial N -segments s1, s2, . . . , sN , converges weakly to Lebesgue measure on U. This notion immediately generalizes to any topological space with a corresponding probability measure on the Borel sets. Uniform distribution, as an area of study, originated from the remarkable paper of Weyl [Wey16], in which he established the fundamental result known nowadays as the Weyl criterion (see [Cas57, KN74]). This reduces a problem on uniform distribution to a study of related exponential sums, and provides a deeper understanding of certain aspects of Diophantine approximation, especially basic results such as Kronecker’s density theorem. Indeed, careful analysis of the exponential sums that arise often leads to Erdős-Turán type upper bounds, which in turn lead to quantitative statements concerning uniform distribution. Today, the concept of uniform distribution has important applications in a number of branches of mathematics such as number theory (especially Diophantine approximation), combinatorics, ergodic theory, discrete geometry, statistics, numerical analysis, etc. In this chapter, we focus on the geometric aspects of the theory.
Archive | 2008
William W. L. Chen; Maxim Skriganov
Suppose that \( \mathcal{A}_N \) is a distribution of N > 1 points, not necessarily distinct, in the n-dimensional unit cube U n = [0, l) n , where n ≥ 2. We consider the L2-discrepancy
Lecture Notes in Mathematics | 2014
William W. L. Chen; Anand Srivastav; Giancarlo Travaglini
Journal of The London Mathematical Society-second Series | 1997
József Beck; William W. L. Chen
\mathcal{L}_2 \left[ {\mathcal{A}_N } \right] = \left( {\int\limits_{U^n } {\left| {\mathcal{L}\left[ {\mathcal{A}_N ;Y} \right]} \right|} ^2 dY} \right)^{1/2} ,
Journal of Complexity | 2007
William W. L. Chen; Giancarlo Travaglini
Archive | 2004
William W. L. Chen
where for every Y = (y1,..., y n) ∈ U n , the local discrepancy \( \mathcal{L}\left[ {\mathcal{A}_N ;Y} \right] \) is given by
Quarterly Journal of Mathematics | 1985
William W. L. Chen
Journal of The Australian Mathematical Society | 1996
William W. L. Chen
\mathcal{L}\left[ {\mathcal{A}_N ;Y} \right] = \# \left( {\mathcal{A}_N \cap B_Y } \right) - N vol B_Y .