Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Qi, Lin, Zhang, Jiaxin
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2511.05869
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866911634180538368
author Qi, Lin
Zhang, Jiaxin
author_facet Qi, Lin
Zhang, Jiaxin
contents Fractals represent one of the fundamental manifestations of complexity, and fractal networks serve as tools for characterizing and investigating the fractal structures and properties of large-scale systems. Higher-order networks have emerged as a research hotspot due to their ability to express interactions among multiple nodes. This study proposes an iterative generation model for higher-order fractal networks. The iteration is controlled by three parameters: the dimension K of the simplicial complex, the multiplier m, and the iteration count t. The constructed network is a pure simplicial complex. Theoretical analysis using the similarity dimension and experimental verification using the box-counting dimension demonstrate that the generated networks exhibit fractal characteristics. When the multiplier m is large, the generalized degree distribution of the generated networks is characterized by its scale-free nature.
format Preprint
id arxiv_https___arxiv_org_abs_2511_05869
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Iterative Generation and Generalized Degree Distribution of Higher-Order Fractal Scale-Free Networks
Qi, Lin
Zhang, Jiaxin
Combinatorics
Fractals represent one of the fundamental manifestations of complexity, and fractal networks serve as tools for characterizing and investigating the fractal structures and properties of large-scale systems. Higher-order networks have emerged as a research hotspot due to their ability to express interactions among multiple nodes. This study proposes an iterative generation model for higher-order fractal networks. The iteration is controlled by three parameters: the dimension K of the simplicial complex, the multiplier m, and the iteration count t. The constructed network is a pure simplicial complex. Theoretical analysis using the similarity dimension and experimental verification using the box-counting dimension demonstrate that the generated networks exhibit fractal characteristics. When the multiplier m is large, the generalized degree distribution of the generated networks is characterized by its scale-free nature.
title Iterative Generation and Generalized Degree Distribution of Higher-Order Fractal Scale-Free Networks
topic Combinatorics
url https://arxiv.org/abs/2511.05869