This work describes a simple variant of this method that determines on its own when to stop and that outputs samples in exact accordance with the desired distribution, and uses couplings which have also played a role in other sampling schemes.Expand

This paper gives a new algorithm for generating random spanning trees of an undirected graph that is easy to code up, has small running time constants, and has a nice proof that it generates trees with the right probabilities.Expand

We show how to combine Fourier analysis with coupling arguments to bound the mixing times of a variety of Markov chains. The mixing time is the number of steps a Markov chain takes to approach its… Expand

We consider a class of zero-sum two-player stochastic games called tug-of-war and use them to prove that every bounded real-valued Lipschitz function F on a subset Y of a length space X admits a… Expand

Algorithms for generating a random sample from the state space of a Markov chain in accordance with the steady-state probability law of the chain are given, improving on earlier results and exploiting the duality between the two problems.Expand

A random walk on $\mathbb{Z}^d$ is excited if the first time it visits a vertex there is a bias in one direction, but on subsequent visits to that vertex the walker picks a neighbor uniformly at… Expand

We give a rigorous and self-contained survey of the abelian sandpile model and rotor-router model on finite directed graphs, highlighting the connections between them. We present several intriguing… Expand

The purpose of this note is to describe a framework which unifies radial, chordal and dipolar SLE. When the definition of SLE(κ; ρ) is extended to the setting where the force points can be in the… Expand

Using this order parameter, it is proved that the 2‐SAT phase transition is continuous with an order parameter critical exponent of 1 and the values of two other critical exponents are determined, showing that the exponents of 2-SAT are identical to those of the random graph.Expand

A new method for generating perfectly random samples from the stationary distribution of a Markov chain that can be run using a read-once stream of randomness is given, related to coupling from the past (CFTP), but only runs the MarkovChain forwards in time, and never restarts it at previous times in the past.Expand