English

Hierarchical deposition and scale-free networks: a visibility algorithm approach

Statistical Mechanics 2022-12-13 v3 Mathematical Physics math.MP

Abstract

The growth of an interface formed by the hierarchical deposition of particles of unequal size is studied in the framework of a dynamical network generated by a horizontal visibility algorithm. For a deterministic model of the deposition process, the resulting network is scale-free with dominant degree exponent γe=ln3/ln2\gamma_e = \ln{3}/\ln{2} and transient exponent γo=1\gamma_o = 1. An exact calculation of the network diameter and clustering coefficient reveals that the network is scale invariant and inherits the modular hierarchical nature of the deposition process. For the random process, the network remains scale free, where the degree exponent asymptotically converges to γ=3\gamma =3, independent of the system parameters. This result shows that the model is in the class of fractional Gaussian noise (fGn) through the relation between the degree exponent and the series' Hurst exponent HH. Finally, we show through the degree-dependent clustering coefficient C(k)C(k) that the modularity remains present in the system.

Keywords

Cite

@article{arxiv.2202.05125,
  title  = {Hierarchical deposition and scale-free networks: a visibility algorithm approach},
  author = {Jonas Berx},
  journal= {arXiv preprint arXiv:2202.05125},
  year   = {2022}
}

Comments

v2: expanded to include random model; removed Supplemental Material

R2 v1 2026-06-24T09:30:25.937Z