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A 1-2 model configuration is a subset of edges of a hexagonal lattice satisfying the constraint that each vertex is incident to 1 or 2 edges. We introduce Markov chains to sample the 1-2 model configurations on 2D hexagonal lattice and…

Probability · Mathematics 2019-01-01 Zhongyang Li

We investigate the asymptotic number of induced subgraphs in power-law uniform random graphs. We show that these induced subgraphs appear typically on vertices with specific degrees, which are found by solving an optimization problem.…

Combinatorics · Mathematics 2022-02-23 Clara Stegehuis

We present an exclusion process based approach for sampling densest $k$-sub-graphs from regular graphs $L$ with connected complement. By interpreting an exclusion process as a Markov chain on a corresponding Token Graph $\mathfrak{L}_k$, we…

Probability · Mathematics 2023-01-12 Jens Walter Fischer

Since 1997 a considerable effort has been spent on the study of the swap (switch) Markov chains on graphic degree sequences. Several results were proved on rapidly mixing Markov chains on regular simple, on regular directed, on half-regular…

Combinatorics · Mathematics 2019-11-07 Péter L. Erdős , Tamás Róbert Mezei , István Miklós

In this paper we consider the problem of sampling from the low-temperature exponential random graph model (ERGM). The usual approach is via Markov chain Monte Carlo, but Bhamidi et al. showed that any local Markov chain suffers from an…

Probability · Mathematics 2022-10-05 Guy Bresler , Dheeraj Nagaraj , Eshaan Nichani

In this paper we study first-passage percolation in the configuration model with empirical degree distribution that follows a power-law with exponent $\tau \in (2,3)$. We assign independent and identically distributed (i.i.d.)\ weights to…

Probability · Mathematics 2018-02-14 Erwin Adriaans , Julia Komjathy

We study Markov chains for $\alpha$-orientations of plane graphs, these are orientations where the outdegree of each vertex is prescribed by the value of a given function $\alpha$. The set of $\alpha$-orientations of a plane graph has a…

Combinatorics · Mathematics 2023-06-22 Stefan Felsner , Daniel Heldt

We study convergence to equilibrium for a large class of Markov chains in random environment. The chains are sparse in the sense that in every row of the transition matrix $P$ the mass is essentially concentrated on few entries. Moreover,…

Probability · Mathematics 2018-01-23 Charles Bordenave , Pietro Caputo , Justin Salez

We present an improved coupling technique for analyzing the mixing time of Markov chains. Using our technique, we simplify and extend previous results for sampling colorings and independent sets. Our approach uses properties of the…

Probability · Mathematics 2007-05-23 Thomas P. Hayes , Eric Vigoda

In a random graph, counts for the number of vertices with given degrees will typically be dependent. We show via a multivariate normal and a Poisson process approximation that, for graphs which have independent edges, with a possibly…

Probability · Mathematics 2009-12-25 K. Lin , G. Reinert

Uniform sampling of simple graphs having a given degree sequence is a known problem with exponential complexity in the square of the mean degree. For undirected graphs, randomised approximation algorithms have nonetheless been shown to…

Probability · Mathematics 2022-06-28 Femke van Ieperen , Ivan Kryven

We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain. The constants in this inequality are explicit and depend on computable bounds on the mixing rate of the…

Statistics Theory · Mathematics 2013-03-05 Gersende Fort , Eric Moulines , Pierre Priouret , Pierre Vandekerkhove

Exponential random graphs are used extensively in the sociology literature. This model seeks to incorporate in random graphs the notion of reciprocity, that is, the larger than expected number of triangles and other small subgraphs.…

Probability · Mathematics 2008-12-15 Shankar Bhamidi , Guy Bresler , Allan Sly

A simple way to sample a uniform triangulation of the sphere with a fixed number $n$ of vertices is a Monte-Carlo method: we start from an arbitrary triangulation and flip repeatedly a uniformly chosen edge. We give a lower bound in…

Probability · Mathematics 2018-06-28 Thomas Budzinski

We show how to exploit symmetries of a graph to efficiently compute the fastest mixing Markov chain on the graph (i.e., find the transition probabilities on the edges to minimize the second-largest eigenvalue modulus of the transition…

Probability · Mathematics 2009-06-17 Stephen Boyd , Persi Diaconis , Pablo A. Parrilo , Lin Xiao

Markov chains are one of the well-known tools for modeling and analyzing stochastic systems. At the same time, they are used for constructing random walks that can achieve a given stationary distribution. This paper is concerned with…

Information Theory · Computer Science 2025-01-07 Saber Jafarizadeh

The Onion Decomposition has recently been shown to provide principled models of complex graphs that better reproduce the sparse networks found in nature, but at the cost of complicated connection rules. We propose a k-edge swapping MCMC…

Statistical Mechanics · Physics 2024-10-01 François Thibault , Laurent Hébert-Dufresne , Antoine Allard

Given a set of snapshots from a temporal network we develop, analyze, and experimentally validate a so-called network interpolation scheme. Our method allows us to build a plausible, albeit random, sequence of graphs that transition between…

Social and Information Networks · Computer Science 2021-02-22 Thomas Reeves , Anil Damle , Austin R. Benson

We survey recent results concerning the total-variation mixing time of the simple exclusion process on the segment (symmetric and asymmetric) and a continuum analog, the simple random walk on the simplex with an emphasis on cutoff results.…

Probability · Mathematics 2021-11-15 Hubert Lacoin

Random graphs with prescribed degree sequences have been widely used as a model of complex networks. Comparing an observed network to an ensemble of such graphs allows one to detect deviations from randomness in network properties. Here we…

Statistical Mechanics · Physics 2007-05-23 R. Milo , N. Kashtan , S. Itzkovitz , M. E. J. Newman , U. Alon