García-Pérez Guillermo, Serrano M Ángeles, Boguñá Marián
Departament de Física Fonamental, Universitat de Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Aug;90(2):022806. doi: 10.1103/PhysRevE.90.022806. Epub 2014 Aug 12.
Natural numbers can be divided in two nonoverlapping infinite sets, primes and composites, with composites factorizing into primes. Despite their apparent simplicity, the elucidation of the architecture of natural numbers with primes as building blocks remains elusive. Here, we propose a new approach to decoding the architecture of natural numbers based on complex networks and stochastic processes theory. We introduce a parameter-free non-Markovian dynamical model that naturally generates random primes and their relation with composite numbers with remarkable accuracy. Our model satisfies the prime number theorem as an emerging property and a refined version of Cramér's conjecture about the statistics of gaps between consecutive primes that seems closer to reality than the original Cramér's version. Regarding composites, the model helps us to derive the prime factors counting function, giving the probability of distinct prime factors for any integer. Probabilistic models like ours can help to get deeper insights about primes and the complex architecture of natural numbers.
自然数可分为两个不重叠的无限集,即质数和合数,合数可分解为质数。尽管它们看似简单,但以质数为基石来阐明自然数的结构仍然难以捉摸。在此,我们基于复杂网络和随机过程理论提出一种解码自然数结构的新方法。我们引入一个无参数的非马尔可夫动力学模型,该模型能以极高的精度自然生成随机质数及其与合数的关系。我们的模型作为一种涌现性质满足质数定理,以及克拉默关于连续质数之间间隔统计的一个改进版本,这个版本似乎比原始的克拉默版本更接近现实。关于合数,该模型帮助我们推导出质因数计数函数,给出任意整数具有不同质因数的概率。像我们这样的概率模型有助于更深入地洞察质数以及自然数的复杂结构。