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Uniformly sampling random directed hypergraphs with fixed degrees

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Abstract

Many complex systems show non-pairwise interactions, which can be captured by hypergraphs. In this work, we propose an edge-swapping method to sample random directed hypergraphs with fixed vertex and hyperarc degrees, which can be applied to different classes of directed hypergraphs (containing self-loops, degenerate hyperarcs and/or multi-hyperarcs). We prove that this method indeed samples uniformly from the classes with self-loops and multi-hyperarcs, and that the method may not sample uniformly from classes without self-loops, or with self-loops and degenerate hyperarcs but without multi-hyperarcs. We present a partial result on the class with self-loops, but without degenerate hyperarcs or multi-hyperarcs.

Original languageEnglish
Article number114961
JournalDiscrete mathematics
Volume349
Issue number6
Early online date5 Jan 2026
DOIs
Publication statusE-pub ahead of print/First online - 5 Jan 2026

Keywords

  • UT-Hybrid-D
  • Markov chain Monte Carlo sampling
  • Random graphs
  • Uniform sampling
  • Directed hypergraphs

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