Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-m9kch Total loading time: 0 Render date: 2024-05-01T18:05:03.472Z Has data issue: false hasContentIssue false

10 - Controlling the shape of generating matrices in global function field constructions of digital sequences

Published online by Cambridge University Press:  18 December 2014

Roswitha Hofer
Affiliation:
Johannes Kepler University Linz
Isabel Pirsic
Affiliation:
Johannes Kepler University Linz
Gerhard Larcher
Affiliation:
Johannes Kepler Universität Linz
Friedrich Pillichshammer
Affiliation:
Johannes Kepler Universität Linz
Arne Winterhof
Affiliation:
Austrian Academy of Sciences, Linz
Chaoping Xing
Affiliation:
Nanyang Technological University, Singapore
Get access

Summary

This paper is dedicated to H. Niederreiter on the occasion of his 70th birthday.

Abstract

Motivated by computational as well as theoretical considerations, we show how the shape and density of the generating matrices of two optimal constructions of (t, s)-sequences and (u, e, s)-sequences (the Xing–Niederreiter and Hofer–Niederreiter sequences) can be controlled by a careful choice of various parameters. We also present some experimental data to support our assertions and point out open problems.

Introduction

The usefulness of and need for well-distributed pseudorandom and quasi-random point sets in very high dimensions has been evidenced by the unbroken stream of publications and conferences with the topic of Monte Carlo and quasi-Monte Carlo (MCQMC) methods in scientific computing, most notably the biannual conference series and proceedings of the same name. Beginning with the well-known Koksma–Hlawka inequality up to the more recent higher order nets, it became clear that, in particular, applications pertaining to multivariate numerical integration are an important area covered by MCQMC methods. Numerous applications in diverse areas of applied mathematics profit from this fact; often cited are applications in finance, computer aided visualization and simulations. (The reader is referred to [5], [4], and [18].)

As regards the suitability of even arbitrary point sets for MCQMC methods, the notion of discrepancy is well established as a measure for the degree of equidistribution, which significantly determines, for example, the error of numerical integration. In brief, discrepancy can be defined as measuring the worst case integration error when applied to indicator functions of subintervals of the unit cube. When the coordinates of the intervals are restricted to b-adic rationals, we arrive at the notion of (t, s)-sequences (in base b)[16]; if, furthermore, a different granularity is permitted in different coordinates, we arrive at the recent refinement of (u, e, s)-sequences [10, 26].

We review the definitions of these concepts in more detail. In the following, let b ∈ ℕ {1}; N, m, s ∈ ℕ t, u ∈ ℕ0 and q ∈ ℕ a prime power.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] I. A., Antonov and V. M., Saleev, An effective method for the computation of λPτ-sequences (Russian). Zh. Vychisl. Mat. Mat. Fiz. 19(1), 243–245, 271, 1979.Google Scholar
[2] W., Bosma, J., Cannon and C., Playoust, The Magma algebra system. I. The user language. J. Symbol. Comput. 24, 235–265, 1997.Google Scholar
[3] P., Bratley, B. L., Fox and H., Niederreiter, Implementation and tests of low-discrepancy sequences. ACM Trans. Model. Comput. Simul. 2(3), 195–213, 1992.Google Scholar
[4] J., Dick and F., Pillichshammer, Digital Nets and Sequences: Discrepancy Theory and Quasi-Monte Carlo Integration. Cambridge University Press, Cambridge, 2010.
[5] J., Dick, F. Y., Kuo, G. W., Peters and I. H., Sloan (eds.), Monte Carlo and Quasi-Monte Carlo Methods 2012. Springer, Heidelberg, 2013.
[6] H., Faure, Discrépance de suites associées à un système de numération (en dimension s). Acta Arith. 41, 337–351, 1982.Google Scholar
[7] R., Hofer, A construction of digital (0, s)-sequences involving finite-row generator matrices. Finite Fields Appl. 18, 587–596, 2010.Google Scholar
[8] R., Hofer, A construction of low-discrepancy sequences involving finite-row digital (t, s)-sequences. Monatsh. Math. 171, 77–89, 2013.Google Scholar
[9] R., Hofer and G., Larcher, On existence and discrepancy of certain digital Niederreiter–Halton sequences. Acta Arith. 141, 369–394, 2010.Google Scholar
[10] R., Hofer and H., Niederreiter, A construction of (t, s)-sequences with finite-row generating matrices using global function fields. Finite Fields Appl. 21, 97–110, 2013.Google Scholar
[11] R., Hofer and G., Pirsic, An explicit construction of finite-row digital (0, s)-sequences. Unif. Distrib. Theory 6, 13–30, 2011.Google Scholar
[12] R., Hofer and G., Pirsic, A finite-row scrambling of Niederreiter sequences. In: J., Dick, F. Y., Kuo, G. W., Peter and I. H., Sloan (eds.), Monte Carlo and Quasi-Monte Carlo Methods 2012. Springer, Heidelberg, 2013.
[13] R., Hofer, P., Kritzer, G., Larcher and F., Pillichshammer, Distribution properties of generalized van der Corput–Halton sequences and their subsequences. Int. J. Number Theory 5, 719–746, 2009.Google Scholar
[14] H., Koch, Number Theory: Algebraic Numbers and Functions. Graduate Studies in Mathematics, volume 24. AMS, Providence, RI, 2000.
[15] D. J. S., Mayor and H., Niederreiter, A new construction of (t, s)-sequences and some improved bounds on their quality parameter. Acta Arith. 128, 177–191, 2007.Google Scholar
[16] H., Niederreiter, Point sets and sequences with small discrepancy. Monatsh. Math. 104, 273–337, 1987.Google Scholar
[17] H., Niederreiter, Low-discrepancy and low-dispersion sequences. J. Number Theory 30, 51–70, 1988.Google Scholar
[18] H., Niederreiter, Random Number Generation and Quasi-Monte Carlo Methods. CBMS-NSF Regional Conference Series in Applied Mathematics, volume 63. SIAM, Philadelphia, PA, 1992.
[19] H., Niederreiter and F., Özbudak, Low-discrepancy sequences using duality and global function fields. Acta Arith. 130, 79–97, 2007.Google Scholar
[20] H., Niederreiter and C.P., Xing, Rational Points on Curves over Finite Fields: Theory and Applications. Cambridge University Press, Cambridge, 2001.
[21] H., Niederreiter and A. S., Yeo, Halton-type sequences from global function fields. Sci. China Math. 56, 1467–1476, 2013.Google Scholar
[22] I. M., Sobol', Distribution of points in a cube and approximate evaluation of integrals (Russian). Z. Vyčisl. Mat. Mat. Fiz. 7, 784–802, 1967.Google Scholar
[23] H., Stichtenoth, Algebraic Function Fields and Codes, second edition. Springer, Berlin, 2009.
[24] S., Tezuka, Polynomial arithmetics of the Halton sequences. ACM Trans. Model. Comput. Simul. 3, 99–107, 1993.Google Scholar
[25] S., Tezuka, Uniform Random Numbers: Theory and Practice. Kluwer Academic Publishers, Boston, MA, 1995.
[26] S., Tezuka, On the discrepancy of generalized Niederreiter sequences. J. Complexity 29, 240–247, 2013.Google Scholar
[27] Wolfram Research, Inc., Mathematica Edition, Version 8.0. Wolfram Research, Champaign, IL, 2010.
[28] C. P., Xing and H., Niederreiter, A construction of low-discrepancy sequences using global function fields. Acta Arith. 73, 87–102, 1995.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×