Power law behavior associated with a Fibonacci Lucas model and generalized statistical models
Aram Z. Mekjian

TL;DR
This paper introduces a Fibonacci-Lucas based statistical model demonstrating scale-invariant power law behavior, connecting number theory, complex networks, and Bose-Einstein condensation phenomena.
Contribution
It develops a novel statistical framework linking Fibonacci-Lucas numbers with power laws and complex networks, extending understanding of scale invariance in physical and mathematical systems.
Findings
Power law behavior emerges at a critical point in the model.
The model's power law exponent relates to hypergeometric function parameters.
Connections between Fibonacci numbers, Bose-Einstein condensation, and complex networks are established.
Abstract
A Fibonacci-Lucas based statistical model and several other related models are studied. The canonical and grand canonical partition functions for these models are developed.Partition structure such as the distribution of sizes as in a cluster distribution is explored.Ensemble averaging over all partitions leads to a scale invariant power law behavior at a particular critical like point. The canonical ensemble of the Fibonacci-Lucas case involves the Gegenbauer polynomial.The model has a hyperbolic power law behavior, a feature linked to the golden mean ratio of two adjacent Fibonacci numbers and also the connection of Lucas numbers to the golden mean. The relation to other power law behavior, such as Zipf and Pareto laws, is mentioned. For the cases considered, the grand canonical ensemble involves the Gauss hypergeometric function F(a,b,c,z) with specific values for a,b,c. The general…
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Taxonomy
TopicsAdvanced Mathematical Theories and Applications · Statistical Mechanics and Entropy · Complex Systems and Time Series Analysis
