A Scale Invariant Distribution of the Prime Numbers

Computation

Wayne S. Kendal²  Bent Jørgensen¹ 

[1] Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, Odense M DK-5230, Denmark; E-Mail:;Division of Radiation Oncology, University of Ottawa, 501 Smyth Road, Ottawa, ON K1H 8L6, Canada

关键词: exponential dispersion models;    1/f noise;    fractal scaling;    self-organized criticality;   

DOI  :  10.3390/computation3040528

来源: mdpi

【 摘 要 】

The irregular distribution of prime numbers amongst the integers has found multiple uses, from engineering applications of cryptography to quantum theory. The degree to which this distribution can be predicted thus has become a subject of current interest. Here, we present a computational analysis of the deviations between the actual positions of the prime numbers and their predicted positions from Riemann’s counting formula, focused on the variance function of these deviations from sequential enumerative bins. We show empirically that these deviations can be described by a class of probabilistic models known as the Tweedie exponential dispersion models that are characterized by a power law relationship between the variance and the mean, known by biologists as Taylor’s power law and by engineers as fluctuation scaling. This power law behavior of the prime number deviations is remarkable in that the same behavior has been found within the distribution of genes and single nucleotide polymorphisms (SNPs) within the human genome, the distribution of animals and plants within their habitats, as well as within many other biological and physical processes. We explain the common features of this behavior through a statistical convergence effect related to the central limit theorem that also generates 1/f noise.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.