通过所有度数的光谱独立性实现格劳伯动力学的快速混合

IF 1.2 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS SIAM Journal on Computing Pub Date : 2024-06-13 DOI:10.1137/22m1474734
Xiaoyu Chen, Weiming Feng, Yitong Yin, Xinyuan Zhang
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引用次数: 0

摘要

SIAM 计算期刊》,提前印刷。 摘要。我们证明了在树状唯一性机制中具有[math]顶点的反铁磁双自旋系统的格劳伯动力学谱缺口的最优[math]下限。对于任何最大度[math],包括无界最大度[math],这个谱间隙都是成立的。因此,对于满足松弛[math]唯一性条件的模型,我们有如下混合时间边界:[其中最大度[math]可能取决于顶点数[math],而[math]只取决于[math]。我们的证明建立在最近发展起来的自旋系统格劳伯动力学与高维扩展漫步之间的联系之上。特别是,我们证明了一种更强的谱独立性概念,称为完全谱独立性,并使用一种新颖的马尔可夫链,称为场动力学,将这种更强的谱独立性与所有度数的格劳伯动力学的快速混合联系起来。
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Rapid Mixing of Glauber Dynamics via Spectral Independence for All Degrees
SIAM Journal on Computing, Ahead of Print.
Abstract. We prove an optimal [math] lower bound on a spectral gap of the Glauber dynamics for antiferromagnetic two-spin systems with [math] vertices in the tree uniqueness regime. This spectral gap holds for any, including unbounded, maximum degree [math]. Consequently, we have the following mixing time bounds for the models satisfying the uniqueness condition with a slack [math]: [math] mixing time for the hardcore model with fugacity [math] and [math] mixing time for the Ising model with edge activity [math], where the maximum degree [math] may depend on the number of vertices [math] and [math] depends only on [math]. Our proof is built on the recently developed connections between the Glauber dynamics for spin systems and high-dimensional expander walks. In particular, we prove a stronger notion of spectral independence, called complete spectral independence, and use a novel Markov chain, called field dynamics, to connect this stronger spectral independence to the rapid mixing of Glauber dynamics for all degrees.
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来源期刊
SIAM Journal on Computing
SIAM Journal on Computing 工程技术-计算机:理论方法
CiteScore
4.60
自引率
0.00%
发文量
68
审稿时长
6-12 weeks
期刊介绍: The SIAM Journal on Computing aims to provide coverage of the most significant work going on in the mathematical and formal aspects of computer science and nonnumerical computing. Submissions must be clearly written and make a significant technical contribution. Topics include but are not limited to analysis and design of algorithms, algorithmic game theory, data structures, computational complexity, computational algebra, computational aspects of combinatorics and graph theory, computational biology, computational geometry, computational robotics, the mathematical aspects of programming languages, artificial intelligence, computational learning, databases, information retrieval, cryptography, networks, distributed computing, parallel algorithms, and computer architecture.
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