Generalized Discrete Fractal Dimensions of Graph Families

Quantifying the self-similarity of complex networks via discrete fractal dimensions is a fundamental problem in network science. In this paper, we investigate some general fractal dimensions of graph families based on q-energy and Rényi entropy. We first establish several bounds for the energy, and then discuss the monotonicity, measure invariance of the dimensions, as well as some concrete graph families.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-29
DOI
https://doi.org/10.48550/arxiv.2610.39187
Primary Topic
Graph theory and applications
Type
preprint
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preprint

Generalized Discrete Fractal Dimensions of Graph Families

Qingcheng Zeng, Jiantao Liu, Yumei Xue, Cheng Zeng
arXiv (Cornell University)
Graph theory and applications
preprint

Generalized Discrete Fractal Dimensions of Graph Families

Qingcheng Zeng, Jiantao Liu, Yumei Xue, Cheng Zeng
preprint en

Abstract

Quantifying the self-similarity of complex networks via discrete fractal dimensions is a fundamental problem in network science. In this paper, we investigate some general fractal dimensions of graph families based on q-energy and Rényi entropy. We first establish several bounds for the energy, and then discuss the monotonicity, measure invariance of the dimensions, as well as some concrete graph families.

arXiv (Cornell University)
Graph theory and applications
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Generalized Discrete Fractal Dimensions of Graph Families — Qingcheng Zeng, Jiantao Liu, et al. · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS