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We consider a bipartite version of the color degree matrix problem. A bipartite graph $G(U,V,E)$ is half-regular if all vertices in $U$ have the same degree. We give necessary and sufficient conditions for a bipartite degree matrix (also…

Combinatorics · Mathematics 2016-02-16 Mark Aksen , Istvan Miklos , Kathleen Zhou

Sampling uniform simple graphs with power-law degree distributions with degree exponent $\tau\in(2,3)$ is a non-trivial problem. We propose a method to sample uniform simple graphs that uses a constrained version of the configuration model…

Probability · Mathematics 2017-11-17 Tom Bannink , Remco van der Hofstad , Clara Stegehuis

In this paper, we study a bipartite analogue of the `random graphs evolving by degrees' process. We are given a bipartitioned set of vertices $V$ into two disjoint parts ${L}$ and ${R}$ and possibly unequal positive constants $\alpha$ and…

Probability · Mathematics 2025-09-30 Neeladri Maitra

We study Markov chains for randomly sampling $k$-colorings of a graph with maximum degree $\Delta$. Our main result is a polynomial upper bound on the mixing time of the single-site update chain known as the Glauber dynamics for planar…

Probability · Mathematics 2011-09-01 Thomas P. Hayes , Juan C. Vera , Eric Vigoda

The approach mapping from a matching of bipartite graphs to digraphs has been successfully used for forcing set problem, in this paper, it is extended to uniquely restricted matching problem. We show to determine a uniquely restricted…

Computational Complexity · Computer Science 2010-09-29 Guohun Zhu

This paper introduces a concept of approximate spectral gap to analyze the mixing time of Markov Chain Monte Carlo (MCMC) algorithms for which the usual spectral gap is degenerate or almost degenerate. We use the idea to analyze a class of…

Computation · Statistics 2019-08-26 Yves F. Atchadé

Mahlmann and Schindelhauer (2005) defined a Markov chain which they called $k$-Flipper, and showed that it is irreducible on the set of all connected regular graphs of a given degree (at least 3). We study the 1-Flipper chain, which we call…

Discrete Mathematics · Computer Science 2018-06-14 Colin Cooper , Martin Dyer , Catherine Greenhill , Andrew Handley

The motivation of this work is to extend the techniques of higher order random walks on simplicial complexes to analyze mixing times of Markov chains for combinatorial problems. Our main result is a sharp upper bound on the second…

Data Structures and Algorithms · Computer Science 2020-02-07 Vedat Levi Alev , Lap Chi Lau

We show that the number of $k$-matching in a given undirected graph $G$ is equal to the number of perfect matching of the corresponding graph $G_k$ on an even number of vertices divided by a suitable factor. If $G$ is bipartite then one can…

Computational Complexity · Computer Science 2016-08-31 Shmuel Friedland , Daniel Levy

A joint degree matrix (JDM) specifies the number of connections between nodes of given degrees in a graph, for all degree pairs and uniquely determines the degree sequence of the graph. We consider the space of all balanced realizations of…

Combinatorics · Mathematics 2015-07-14 Péter L. Erdős , István Miklós , Zoltán Toroczkai

In [Combinatorics, Probability and Computing 16 (2007), 557 - 593, Theorem 1] we proved a polynomial-time bound on the mixing rate of the switch chain for sampling d-regular graphs. This corrigendum corrects a technical error in the proof.…

Combinatorics · Mathematics 2012-03-29 Colin Cooper , Martin Dyer , Catherine Greenhill

Statistical analysis of bipartite networks frequently requires randomly sampling from the set of all bipartite networks with the same degree sequence as an observed network. Trade algorithms offer an efficient way to generate samples of…

Numerical Analysis · Mathematics 2024-09-04 Zachary P. Neal

Counting and sampling directed acyclic graphs from a Markov equivalence class are fundamental tasks in graphical causal analysis. In this paper we show that these tasks can be performed in polynomial time, solving a long-standing open…

Machine Learning · Computer Science 2023-08-22 Marcel Wienöbst , Max Bannach , Maciej Liśkiewicz

We study the problem of generating a sample from the stationary distribution of a Markov chain, given a method to simulate the chain. We give an approximation algorithm for the case of a random walk on a regular graph with n vertices that…

Probability · Mathematics 2007-05-23 Itai Benjamini , Ben Morris

We establish the first polynomial upper bound for the mixing time of random edge flips on rooted quadrangulations: we show that the spectral gap of the edge flip Markov chain on quadrangulations with $n$ faces admits, up to constants, an…

Probability · Mathematics 2022-01-13 Alessandra Caraceni , Alexandre Stauffer

We address the problem of sampling colorings of a graph $G$ by Markov chain simulation. For most of the article we restrict attention to proper $q$-colorings of a path on $n$ vertices (in statistical physics terms, the one-dimensional…

Probability · Mathematics 2007-05-23 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

This paper analyzes the performance of sequential importance sampling algorithms for estimating the number of perfect matchings in bipartite graphs. Precise bounds on the number of samples required to yield an accurate estimate are derived.…

Probability · Mathematics 2021-01-01 Andy Tsao

Quantum walks on graphs have been shown in certain cases to mix quadratically faster than their classical counterparts. Lifted Markov chains, consisting of a Markov chain on an extended state space which is projected back down to the…

Quantum Physics · Physics 2018-03-22 Danial Dervovic

We present a novel approach to quantizing Markov chains. The approach is based on the Markov chain coupling method, which is frequently used to prove fast mixing. Given a particular coupling, e.g., a grand coupling, we construct a…

Quantum Physics · Physics 2025-12-24 Kristan Temme , Pawel Wocjan

We propose a new approach for estimating the finite dimensional transition matrix of a Markov chain using a large number of independent sample paths observed at random times. The sample paths may be observed as few as two times, and the…

Methodology · Statistics 2025-05-20 Daphne Aurouet , Valentin Patilea