We say a probability distribution μ is spectrally independent if an associated pairwise
influence matrix has a bounded largest eigenvalue for the distribution and all of its …

We study the problem of approximating the partition function of the ferromagnetic Ising
model with both pairwise as well as higher order interactions (equivalently, in graphs as well …

We present a simple algorithm that perfectly samples configurations from the unique Gibbs
measure of a spin system on a potentially infinite graph G. The sampling algorithm assumes …

We study the hard-core (gas) model defined on independent sets of an input graph where
the independent sets are weighted by a parameter (aka fugacity) λ>0. For constant Δ, the …

We study the connection between the correlation decay property (more precisely, strong
spatial mixing) and the zero-freeness of the partition function of 2-spin systems on graphs of …

Spectral independence is a recently developed framework for obtaining sharp bounds on
the convergence time of the classical Glauber dynamics. This new framework has yielded …

Approximate counting via correlation decay is the core algorithmic technique used in the
sharp delineation of the computational phase transition that arises in the approximation of …

We consider the problem of sampling from the Potts model on random regular graphs. It is
conjectured that sampling is possible when the temperature of the model is in the so-called …

The hard-sphere model is one of the most extensively studied models in statistical physics. It
describes the continuous distribution of spherical particles, governed by hard-core …

We provide a perfect sampling algorithm for the hard-sphere model on subsets of $\mathbb
{R}^ d $ with expected running time linear in the volume under the assumption of strong …