Litcius/Paper detail

Sampling hypergraphs with given degrees

Dyer, M. (Martin), Greenhill, C. (Catherine), Kleer, P.S. (Pieter), Ross, J. (James), Stougie, L. (Leen)

2021Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands20 citationsDOI

Abstract

There is a well-known connection between hypergraphs and bipartite graphs, obtained by treating the incidence matrix of the hypergraph as the biadjacency matrix of a bipartite graph. We use this connection to describe and analyse a rejection sampling algorithm for sampling simple uniform hypergraphs with a given degree sequence. Our algorithm uses, as a black box, an algorithm A for sampling bipartite graphs with given degrees, uniformly or nearly uniformly, in (expected) polynomial time. The expected runtime of the hypergraph sampling algorithm depends on the (expected) runtime of the bipartite graph sampling algorithm A, and the probability that a uniformly random bipartite graph with given degrees corresponds to a simple hypergraph. We give some conditions on the hypergraph degree sequence which guarantee that this probability is bounded below by a positive constant.

Topics & Concepts

HypergraphBipartite graphMathematicsCombinatoricsDiscrete mathematicsIncidence matrixBounded functionSampling (signal processing)GraphAlgorithmComputer scienceStructural engineeringEngineeringFilter (signal processing)Node (physics)Computer visionMathematical analysisMarkov Chains and Monte Carlo MethodsSparse and Compressive Sensing TechniquesPoint processes and geometric inequalities