Sampling bipartite graphs with given vertex degrees and fixed edges and non-edges
arXiv:1608.03177
Abstract
We consider the problem of sampling a bipartite graph with given vertex degrees where a set of edges and non-edges which need to be contained is predefined. Our general result shows that the repeated swap of edges and non-edges in alternating cycles of at most size ('-swaps' with ) in a current graph lead to an ergodic Metropolis Markov chain whenever does not contain a cycle of length with This leads to useful Markov chains whenever is not too large. If is a forest, - and -swaps are sufficient. Furthermore, we prove that -swaps are sufficient when does not contain a matching of size We extend the Curveball algorithm of Strona et al. \cite{Strona2014b} to our cases.
19 pages, 5 figures