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We present novel results for fast mixing of Glauber dynamics using the newly introduced and powerful Spectral Independence method from [Anari, Liu, Oveis-Gharan: FOCS 2020]. We mainly focus on the Hard-core model and the Ising model. We…

Discrete Mathematics · Computer Science 2025-04-29 Charilaos Efthymiou

We present novel results for fast mixing of Glauber dynamics using the newly introduced and powerful Spectral Independence method from [Anari, Liu, Oveis-Gharan: FOCS 2020]. In our results, the parameters of the Gibbs distribution are…

Probability · Mathematics 2022-11-08 Charilaos Efthymiou

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 optimal $O(n \log n)$ sampling algorithms on bounded-degree graphs…

Data Structures and Algorithms · Computer Science 2023-10-16 Ivona Bezáková , Andreas Galanis , Leslie Ann Goldberg , Daniel Štefankovič

We prove an optimal $\Omega(n^{-1})$ lower bound on the spectral gap of Glauber dynamics for anti-ferromagnetic two-spin systems with $n$ vertices in the tree uniqueness regime. This spectral gap holds for all, including unbounded, maximum…

Data Structures and Algorithms · Computer Science 2021-11-22 Xiaoyu Chen , Weiming Feng , Yitong Yin , Xinyuan Zhang

We present a new lower bound on the spectral gap of the Glauber dynamics for the Gibbs distribution of a spectrally independent $q$-spin system on a graph $G = (V,E)$ with maximum degree $\Delta$. Notably, for several interesting examples,…

Data Structures and Algorithms · Computer Science 2021-05-05 Vishesh Jain , Huy Tuan Pham , Thuy Duong Vuong

For general spin systems, we prove that a contractive coupling for any local Markov chain implies optimal bounds on the mixing time and the modified log-Sobolev constant for a large class of Markov chains including the Glauber dynamics,…

We prove an optimal mixing time bound on the single-site update Markov chain known as the Glauber dynamics or Gibbs sampling in a variety of settings. Our work presents an improved version of the spectral independence approach of Anari et…

Discrete Mathematics · Computer Science 2023-03-24 Zongchen Chen , Kuikui Liu , Eric Vigoda

We consider spin systems on general $n$-vertex graphs of unbounded degree and explore the effects of spectral independence on the rate of convergence to equilibrium of global Markov chains. Spectral independence is a novel way of…

Probability · Mathematics 2023-08-30 Antonio Blanca , Xusheng Zhang

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

We study the problem of deterministic approximate counting of matchings and independent sets in graphs of bounded connective constant. More generally, we consider the problem of evaluating the partition functions of the monomer-dimer model…

Data Structures and Algorithms · Computer Science 2014-10-10 Alistair Sinclair , Piyush Srivastava , Daniel Štefankovič , Yitong Yin

We develop a new framework to prove the mixing or relaxation time for the Glauber dynamics on spin systems with unbounded degree. It works for general spin systems including both $2$-spin and multi-spin systems. As applications for this…

Data Structures and Algorithms · Computer Science 2024-07-08 Xiaoyu Chen , Weiming Feng

The hard-core model has as its configurations the independent sets of some graph instance $G$. The probability distribution on independent sets is controlled by a `fugacity' $\lambda>0$, with higher $\lambda$ leading to denser…

Probability · Mathematics 2026-01-14 Mark Jerrum

The spectral independence approach of Anari et al. (2020) utilized recent results on high-dimensional expanders of Alev and Lau (2020) and established rapid mixing of the Glauber dynamics for the hard-core model defined on weighted…

Data Structures and Algorithms · Computer Science 2020-07-17 Zongchen Chen , Andreas Galanis , Daniel Štefankovič , Eric Vigoda

We study how to establish $\textit{spectral independence}$, a key concept in sampling, without relying on total influence bounds, by applying an $\textit{approximate inverse}$ of the influence matrix. Our method gives constant upper bounds…

Data Structures and Algorithms · Computer Science 2024-04-09 Xiaoyu Chen , Xiongxin Yang , Yitong Yin , Xinyuan Zhang

We extend the notion of spectral independence (introduced by Anari, Liu, and Oveis Gharan [ALO20]) from the Boolean domain to general discrete domains. This property characterises distributions with limited correlations, and implies that…

Data Structures and Algorithms · Computer Science 2020-07-17 Weiming Feng , Heng Guo , Yitong Yin , Chihao Zhang

We study the stochastic Ising model on finite graphs with n vertices and bounded degree and analyze the effect of boundary conditions on the mixing time. We show that for all low enough temperatures, the spectral gap of the dynamics with…

Probability · Mathematics 2008-11-10 Alessandra Bianchi

The hardcore model is one of the most classic and widely studied examples of undirected graphical models. Given a graph $G$, the hardcore model describes a Gibbs distribution of $\lambda$-weighted independent sets of $G$. In the last two…

Data Structures and Algorithms · Computer Science 2026-01-08 Zongchen Chen , Tianhui Jiang

We study the single-site Glauber dynamics for the fugacity $\lambda$, Hard-core model on the random graph $G(n, d/n)$. We show that for the typical instances of the random graph $G(n,d/n)$ and for fugacity $\lambda <…

Discrete Mathematics · Computer Science 2023-02-14 Charilaos Efthymiou , Weiming Feng

We study the mixing time of the single-site update Markov chain, known as the Glauber dynamics, for generating a random independent set of a tree. Our focus is obtaining optimal convergence results for arbitrary trees. We consider the more…

Discrete Mathematics · Computer Science 2025-03-05 Charilaos Efthymiou , Thomas P. Hayes , Daniel Stefankovic , Eric Vigoda

We say a probability distribution $\mu$ is spectrally independent if an associated correlation matrix has a bounded largest eigenvalue for the distribution and all of its conditional distributions. We prove that if $\mu$ is spectrally…

Data Structures and Algorithms · Computer Science 2020-09-21 Nima Anari , Kuikui Liu , Shayan Oveis Gharan
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