任意基数项链生成的正态数的差界

IF 1.8 2区 数学 Q1 MATHEMATICS
Roswitha Hofer, Gerhard Larcher
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引用次数: 0

摘要

Mordecay B.Levin(1999)构造了一个在2基数上正常的数λ,使得序列({2nλ})n=0,1,2,…具有非常小的差异n·DN=O(log⁡N) 2)。Becher和Carton(2019)推广了这一构造技术,他们通过嵌套的完美项链生成了正态数,对它们的差异估计上限相同。在本文中,我们导出了所谓的半完全嵌套项链的一个上界,并证明了对于任意素数p上的Levin正规数,这个上界是最可能的。这一结果推广了作者(2022)在基2中的先前结果。我们对任何素数基中的Levin正规数的结果可能支持O((log⁡N) 2)是N中正规数可以达到的最佳阶,而另一方面,通过引入半完全项链来推广已知正规数类可能有助于搜索满足较小差异界的正规数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discrepancy bounds for normal numbers generated by necklaces in arbitrary base

Mordechay B. Levin (1999) has constructed a number λ which is normal in base 2, and such that the sequence ({2nλ})n=0,1,2, has very small discrepancy NDN=O((logN)2). This construction technique was generalized by Becher and Carton (2019), who generated normal numbers via nested perfect necklaces, for which the same upper discrepancy estimate holds. In this paper we derive an upper discrepancy bound for so-called semi-perfect nested necklaces and show that for Levin's normal number in arbitrary prime base p this upper bound for the discrepancy is best possible. This result generalizes a previous result by the authors (2022) in base 2.

Our result for Levin's normal number in any prime base might support the guess that O((logN)2) is the best order in N that can be achieved by a normal number, while generalizing the class of known normal numbers by introducing semi-perfect necklaces on the other hand might help for the search of normal numbers that satisfy smaller discrepancy bounds.

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来源期刊
Journal of Complexity
Journal of Complexity 工程技术-计算机:理论方法
CiteScore
3.10
自引率
17.60%
发文量
57
审稿时长
>12 weeks
期刊介绍: The multidisciplinary Journal of Complexity publishes original research papers that contain substantial mathematical results on complexity as broadly conceived. Outstanding review papers will also be published. In the area of computational complexity, the focus is on complexity over the reals, with the emphasis on lower bounds and optimal algorithms. The Journal of Complexity also publishes articles that provide major new algorithms or make important progress on upper bounds. Other models of computation, such as the Turing machine model, are also of interest. Computational complexity results in a wide variety of areas are solicited. Areas Include: • Approximation theory • Biomedical computing • Compressed computing and sensing • Computational finance • Computational number theory • Computational stochastics • Control theory • Cryptography • Design of experiments • Differential equations • Discrete problems • Distributed and parallel computation • High and infinite-dimensional problems • Information-based complexity • Inverse and ill-posed problems • Machine learning • Markov chain Monte Carlo • Monte Carlo and quasi-Monte Carlo • Multivariate integration and approximation • Noisy data • Nonlinear and algebraic equations • Numerical analysis • Operator equations • Optimization • Quantum computing • Scientific computation • Tractability of multivariate problems • Vision and image understanding.
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