Toward a comprehensive simulation framework for hypergraphs: a Python-base approach

TL;DR

This paper introduces HyperRD, a Python package that facilitates hypergraph computation and simulation, addressing the lack of dedicated tools and enabling advanced research in complex network analysis.

Contribution

The paper presents HyperRD, a new Python-based framework for hypergraph simulation and interoperability, along with implementations of Schelling's and SIR models.

Findings

HyperRD enables efficient hypergraph simulations in Python.

The package supports integration with existing graph analysis tools.

Simulations demonstrate the framework's applicability to social and epidemiological models.

Abstract

Hypergraphs, or generalization of graphs such that edges can contain more than two nodes, have become increasingly prominent in understanding complex network analysis. Unlike graphs, hypergraphs have relatively few supporting platforms, and such dearth presents a barrier to more widespread adaptation of hypergraph computational toolboxes that could enable further research in several areas. Here, we introduce HyperRD, a Python package for hypergraph computation, simulation, and interoperability with other powerful Python packages in graph and hypergraph research. Then, we will introduce two models on hypergraph, the general Schelling's model and the SIR model, and simulate them with HyperRD.