# Improved bounds on the phase transition for the hard-core model in 2 dimensions

Juan C. Vera, E. Vigoda, L. Yang

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

## Abstract

For the hard-core lattice gas model defined on independent sets weighted by an activity $\lambda$, we study the critical activity $\lambda_c(\mathbb{Z}^2)$ for the uniqueness/nonuniqueness threshold on the 2-dimensional integer lattice $\mathbb{Z}^2$. The conjectured value of the critical activity is approximately 3.796. Until recently, the best lower bound followed from algorithmic results of Weitz [Proceedings of the $38$th Annual ACM Symposium on Theory of Computing, ACM, New York, 2006, pp. 140--149]. Weitz presented a fully polynomial-time approximation scheme for approximating the partition function for graphs of constant maximum degree $\Delta$ when $\lambda<\lambda_c(\mathbb{T}_\Delta)$, where $\mathbb{T}_\Delta$ is the infinite, regular tree of degree $\Delta$. His result established a certain decay of correlations property called strong spatial mixing (SSM) on $\mathbb{Z}^2$ by proving that SSM holds on its self-avoiding walk tree $T_{\mathrm{saw}}^\sigma(\mathbb{Z}^2)$, where $\sigma=(\sigma_v)_{v\in \mathbb{Z}^2}$ and $\sigma_v$ is an ordering on the neighbors of vertex $v$. As a consequence he obtained that $\lambda_c(\mathbb{Z}^2)\geq\lambda_c( \mathbb{T}_4) = 1.675$. Restrepo et al. [Probab. Theory Related Fields, 156 (2013), pp. 75--99] improved Weitz's approach for the particular case of $\mathbb{Z}^2$ and obtained that $\lambda_c(\mathbb{Z}^2)>2.388$. In this paper, we establish an upper bound for this approach, by showing that, for all $\sigma$, SSM does not hold on $T_{\mathrm{saw}}^\sigma(\mathbb{Z}^2)$ when $\lambda>3.4$. We also present a refinement of the approach of Restrepo et al. which improves the lower bound to $\lambda_c(\mathbb{Z}^2)>2.48$.
Original language English 1895–1915 21 SIAM Journal on Discrete Mathematics 29 4 https://doi.org/10.1137/140976923 Published - 1 Oct 2015

## Keywords

• approximate counting
• MCMC
• strong spatial mixing
• branching matrices
• linear programming

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