Model of Simplicial Complexes with dimension-wise preferential attachment

Fuente: arXiv
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Main Authors: Febbe, Diego, Fanelli, Duccio, Carletti, Timoteo
Format: Preprint
Published: 2026
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author Febbe, Diego
Fanelli, Duccio
Carletti, Timoteo
author_facet Febbe, Diego
Fanelli, Duccio
Carletti, Timoteo
contents Network science is a powerful framework allowing to model complex systems, it is capable to describe and take into account the intricate web of connections existing among the constituting basic element of the system. Recently scholars have brought to the fore the relevance of higher-order networks, namely structures allowing to encode for many-body interaction, differently from the pairwise case handled by networks. This novel research field opens new avenues of research with applications ranging from neurosciences to social sciences; there is thus a need for generative models of higher-order network capable to reproduce features present in empirical data. In this work we present a model for growing simplicial complex rooted on a preferential attachment process acting dimension-wise, i.e., returning a power law distribution for the generalized degree of simplexes of different dimension.
format Preprint
id arxiv_https___arxiv_org_abs_2605_17004
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Model of Simplicial Complexes with dimension-wise preferential attachment
Febbe, Diego
Fanelli, Duccio
Carletti, Timoteo
Statistical Mechanics
Network science is a powerful framework allowing to model complex systems, it is capable to describe and take into account the intricate web of connections existing among the constituting basic element of the system. Recently scholars have brought to the fore the relevance of higher-order networks, namely structures allowing to encode for many-body interaction, differently from the pairwise case handled by networks. This novel research field opens new avenues of research with applications ranging from neurosciences to social sciences; there is thus a need for generative models of higher-order network capable to reproduce features present in empirical data. In this work we present a model for growing simplicial complex rooted on a preferential attachment process acting dimension-wise, i.e., returning a power law distribution for the generalized degree of simplexes of different dimension.
title Model of Simplicial Complexes with dimension-wise preferential attachment
topic Statistical Mechanics
url https://arxiv.org/abs/2605.17004