We study continuous time Glauber dynamics for random configurations with local constraints (e.g. proper coloring, Ising and Potts models) on finite graphs with n vertices and of bounded degree. We show that the relaxation time (defined as the reciprocal of the spectral gap |λ1−λ2|) for the dynamics on trees and on planar hyperbolic graphs, is polynomial in n. For these hyperbolic graphs, this yields a general polynomial sampling algorithm for random configurations. We then show that for general graphs, if the relaxation time τ2 satisfies τ2=O(1), then the correlation coefficient, and the mutual information, between any local function (which depends only on the configuration in a fixed window) and the boundary conditions, decays exponentiall...
The mixing time of the Glauber dynamics for spin systems on trees is closely related to the reconstr...
Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional d...
Spectral independence is a recently-developed framework for obtaining sharp bounds on the convergenc...
We study a continuous time Glauber dynamics reversible with respect to the Ising model on hyperbolic...
We study a continuous time Glauber dynamics reversible with respect to the Ising model on hyperbolic...
Let T be a tree on n vertices and with maximum degree ∆. We show that for k ≥ ∆ + 1 the Glauber dyna...
We study the effect of boundary conditions on the relaxation time (i.e., inverse spectral gap) of th...
We consider the performance of Glauber dynamics for the random cluster model with real parameter q >...
We study the effect of boundary conditions on the relaxation time of the Glauber dynamics for the ha...
We study the stochastic Ising model on finite graphs with n vertices and bounded degree and analyze ...
Motivated by the `subgraphs world' view of the ferromagnetic Ising model, we analyse the mixing time...
Spectral independence is a recently-developed framework for obtaining sharp bounds on the convergenc...
We study the Glauber dynamics for Ising model on (sequences of) dense graphs. We view the dense grap...
In this thesis we study the mixing times of Markov chains, e.g., therate of convergence of Markov ch...
We study the mixing properties of the single-site Markov chain known as the Glauber dynamics for sam...
The mixing time of the Glauber dynamics for spin systems on trees is closely related to the reconstr...
Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional d...
Spectral independence is a recently-developed framework for obtaining sharp bounds on the convergenc...
We study a continuous time Glauber dynamics reversible with respect to the Ising model on hyperbolic...
We study a continuous time Glauber dynamics reversible with respect to the Ising model on hyperbolic...
Let T be a tree on n vertices and with maximum degree ∆. We show that for k ≥ ∆ + 1 the Glauber dyna...
We study the effect of boundary conditions on the relaxation time (i.e., inverse spectral gap) of th...
We consider the performance of Glauber dynamics for the random cluster model with real parameter q >...
We study the effect of boundary conditions on the relaxation time of the Glauber dynamics for the ha...
We study the stochastic Ising model on finite graphs with n vertices and bounded degree and analyze ...
Motivated by the `subgraphs world' view of the ferromagnetic Ising model, we analyse the mixing time...
Spectral independence is a recently-developed framework for obtaining sharp bounds on the convergenc...
We study the Glauber dynamics for Ising model on (sequences of) dense graphs. We view the dense grap...
In this thesis we study the mixing times of Markov chains, e.g., therate of convergence of Markov ch...
We study the mixing properties of the single-site Markov chain known as the Glauber dynamics for sam...
The mixing time of the Glauber dynamics for spin systems on trees is closely related to the reconstr...
Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional d...
Spectral independence is a recently-developed framework for obtaining sharp bounds on the convergenc...