哈罗斯图:实数的奇异表示

IF 2.2 4区 数学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Jorge Calero-Sanz, B. Luque, L. Lacasa
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引用次数: 2

摘要

本文介绍了Haros图,它提供了实数在经Farey二叉树路径到达的单位区间内的图论表示。我们展示了Haros图的拓扑结构如何产生实数的自然分类到族的层次结构中。为了揭示这种分类,我们在这些图上引入了一个熵泛函,并表明由于它的分形性质,它可以用广义de Rham曲线来表示。我们表明,该熵在黄金数的倒数处达到全局最大值,否则显示与特定的无理数(贵族数)和有理数相关的局部最大值和最小值的丰富层次,总体上根据熵原理提供了实数的奇异分类和表示。我们以一些猜想和哈罗斯图的研究计划来结束论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Haros graphs: an exotic representation of real numbers
This paper introduces Haros graphs, a construction which provides a graph-theoretical representation of real numbers in the unit interval reached via paths in the Farey binary tree. We show how the topological structure of Haros graphs yields a natural classification of the reals numbers into a hierarchy of families. To unveil such classification, we introduce an entropic functional on these graphs and show that it can be expressed, thanks to its fractal nature, in terms of a generalised de Rham curve. We show that this entropy reaches a global maximum at the reciprocal of the Golden number and otherwise displays a rich hierarchy of local maxima and minima that relate to specific families of irrationals (noble numbers) and rationals, overall providing an exotic classification and representation of the reals numbers according to entropic principles. We close the paper with a number of conjectures and outline a research programme on Haros graphs.
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来源期刊
Journal of complex networks
Journal of complex networks MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.20
自引率
9.50%
发文量
40
期刊介绍: Journal of Complex Networks publishes original articles and reviews with a significant contribution to the analysis and understanding of complex networks and its applications in diverse fields. Complex networks are loosely defined as networks with nontrivial topology and dynamics, which appear as the skeletons of complex systems in the real-world. The journal covers everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications leading to predictive models in molecular, biological, ecological, informational, engineering, social, technological and other systems. It includes, but is not limited to, the following topics: - Mathematical and numerical analysis of networks - Network theory and computer sciences - Structural analysis of networks - Dynamics on networks - Physical models on networks - Networks and epidemiology - Social, socio-economic and political networks - Ecological networks - Technological and infrastructural networks - Brain and tissue networks - Biological and molecular networks - Spatial networks - Techno-social networks i.e. online social networks, social networking sites, social media - Other applications of networks - Evolving networks - Multilayer networks - Game theory on networks - Biomedicine related networks - Animal social networks - Climate networks - Cognitive, language and informational network
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