Spectral Independence in High-Dimensional Expanders and Applications to the Hardcore Model

Autor: Kuikui Liu, Nima Anari, Shayan Oveis Gharan
Rok vydání: 2020
Předmět:
Zdroj: FOCS
DOI: 10.1109/focs46700.2020.00125
Popis: 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 independent, then the corresponding high dimensional simplicial complex is a local spectral expander. Using a line of recent works on mixing time of high dimensional walks on simplicial complexes \cite{KM17,DK17,KO18,AL19}, this implies that the corresponding Glauber dynamics mixes rapidly and generates (approximate) samples from $\mu$. As an application, we show that natural Glauber dynamics mixes rapidly (in polynomial time) to generate a random independent set from the hardcore model up to the uniqueness threshold. This improves the quasi-polynomial running time of Weitz's deterministic correlation decay algorithm \cite{Wei06} for estimating the hardcore partition function, also answering a long-standing open problem of mixing time of Glauber dynamics \cite{LV97,LV99,DG00,Vig01,EHSVY16}.
Comment: Fixed a bug in the decoupling lemma of section 4, and in the proof of Theorem 3.1
Databáze: OpenAIRE