15 research outputs found
Improved Bounds on the Phase Transition for the Hard-Core Model in 2-Dimensions
For the hard-core lattice gas model defined on independent sets weighted by
an activity , we study the critical activity
for the uniqueness/non-uniqueness threshold on the 2-dimensional integer
lattice . The conjectured value of the critical activity is
approximately . Until recently, the best lower bound followed from
algorithmic results of Weitz (2006). Weitz presented an FPTAS for approximating
the partition function for graphs of constant maximum degree when
where is the
infinite, regular tree of degree . His result established a certain
decay of correlations property called strong spatial mixing (SSM) on
by proving that SSM holds on its self-avoiding walk tree
where and is an ordering on the neighbors of vertex . As
a consequence he obtained that . Restrepo et al. (2011) improved Weitz's approach for
the particular case of and obtained that
. In this paper, we establish an upper bound for
this approach, by showing that, for all , SSM does not hold on
when . We also present a
refinement of the approach of Restrepo et al. which improves the lower bound to
.Comment: 19 pages, 1 figure. Polished proofs and examples compared to earlier
versio
Approximate Capacities of Two-Dimensional Codes by Spatial Mixing
We apply several state-of-the-art techniques developed in recent advances of
counting algorithms and statistical physics to study the spatial mixing
property of the two-dimensional codes arising from local hard (independent set)
constraints, including: hard-square, hard-hexagon, read/write isolated memory
(RWIM), and non-attacking kings (NAK). For these constraints, the strong
spatial mixing would imply the existence of polynomial-time approximation
scheme (PTAS) for computing the capacity. It was previously known for the
hard-square constraint the existence of strong spatial mixing and PTAS. We show
the existence of strong spatial mixing for hard-hexagon and RWIM constraints by
establishing the strong spatial mixing along self-avoiding walks, and
consequently we give PTAS for computing the capacities of these codes. We also
show that for the NAK constraint, the strong spatial mixing does not hold along
self-avoiding walks
Spatial mixing and approximation algorithms for graphs with bounded connective constant
The hard core model in statistical physics is a probability distribution on
independent sets in a graph in which the weight of any independent set I is
proportional to lambda^(|I|), where lambda > 0 is the vertex activity. We show
that there is an intimate connection between the connective constant of a graph
and the phenomenon of strong spatial mixing (decay of correlations) for the
hard core model; specifically, we prove that the hard core model with vertex
activity lambda < lambda_c(Delta + 1) exhibits strong spatial mixing on any
graph of connective constant Delta, irrespective of its maximum degree, and
hence derive an FPTAS for the partition function of the hard core model on such
graphs. Here lambda_c(d) := d^d/(d-1)^(d+1) is the critical activity for the
uniqueness of the Gibbs measure of the hard core model on the infinite d-ary
tree. As an application, we show that the partition function can be efficiently
approximated with high probability on graphs drawn from the random graph model
G(n,d/n) for all lambda < e/d, even though the maximum degree of such graphs is
unbounded with high probability.
We also improve upon Weitz's bounds for strong spatial mixing on bounded
degree graphs (Weitz, 2006) by providing a computationally simple method which
uses known estimates of the connective constant of a lattice to obtain bounds
on the vertex activities lambda for which the hard core model on the lattice
exhibits strong spatial mixing. Using this framework, we improve upon these
bounds for several lattices including the Cartesian lattice in dimensions 3 and
higher.
Our techniques also allow us to relate the threshold for the uniqueness of
the Gibbs measure on a general tree to its branching factor (Lyons, 1989).Comment: 26 pages. In October 2014, this paper was superseded by
arxiv:1410.2595. Before that, an extended abstract of this paper appeared in
Proc. IEEE Symposium on the Foundations of Computer Science (FOCS), 2013, pp.
300-30
Analyticity for classical gasses via recursion
We give a new criterion for a classical gas with a repulsive pair potential
to exhibit uniqueness of the infinite volume Gibbs measure and analyticity of
the pressure. Our improvement on the bound for analyticity is by a factor
over the classical cluster expansion approach and a factor over the known
limit of cluster expansion convergence. The criterion is based on a contractive
property of a recursive computation of the density of a point process. The key
ingredients in our proofs include an integral identity for the density of a
Gibbs point process and an adaptation of the algorithmic correlation decay
method from theoretical computer science. We also deduce from our results an
improved bound for analyticity of the pressure as a function of the density
Representation and poly-time approximation for pressure of lattice models in the non-uniqueness region
We develop a new pressure representation theorem for nearest-neighbour Gibbs
interactions and apply this to obtain the existence of efficient algorithms for
approximating the pressure in the -dimensional ferromagnetic Potts,
multi-type Widom-Rowlinson and hard-core models. For Potts, our results apply
to every inverse temperature but the critical. For Widom-Rowlinson and
hard-core, they apply to certain subsets of both the subcritical and
supercritical regions. The main novelty of our work is in the latter.Comment: 37 pages, 2 figure
Spatial mixing and the connective constant: Optimal bounds
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 (which is defined as a weighted sum over all matchings where each matching is given a weight γ^(|V| –2|M|) in terms of a fixed parameter γ called the monomer activity) and the hard core model (which is defined as a weighted sum over all independent sets where an independent set I is given a weight γ^(|I|) in terms of a fixed parameter γ called the vertex activity). The connective constant is a natural measure of the average degree of a graph which has been studied extensively in combinatorics and mathematical physics, and can be bounded by a constant even for certain unbounded degree graphs such as those sampled from the sparse Erdös-Rényi model (n, d/n).
Our main technical contribution is to prove the best possible rates of decay of correlations in the natural probability distributions induced by both the hard core model and the monomer-dimer model in graphs with a given bound on the connective constant. These results on decay of correlations are obtained using a new framework based on the so-called message approach that has been extensively used recently to prove such results for bounded degree graphs. We then use these optimal decay of correlations results to obtain FPTASs for the two problems on graphs of bounded connective constant.
In particular, for the monomer-dimer model, we give a deterministic FPTAS for the partition function on all graphs of bounded connective constant for any given value of the monomer activity. The best previously known deterministic algorithm was due to Bayati, Gamarnik, Katz, Nair and Tetali [STOC 2007], and gave the same runtime guarantees as our results but only for the case of bounded degree graphs. For the hard core model, we give an FPTAS for graphs of connective constant Δ whenever the vertex activity λ λ_c(Δ) would imply that NP=RP [Sly, FOCS 2010]. The previous best known result in this direction was a recent paper by a subset of the current authors [FOCS 2013], where the result was established under the suboptimal condition λ < λc(Δ + 1).
Our techniques also allow us to improve upon known bounds for decay of correlations for the hard core model on various regular lattices, including those obtained by Restrepo, Shin, Vigoda and Tetali [FOCS 11] for the special case of ℤ^2 using sophisticated numerically intensive methods tailored to that special case
Spatial mixing and the connective constant: optimal bounds
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 (which is defined as a weighted sum over all matchings where each matching is given a weight γ|V|−2|M| in terms of a fixed parameter γ called the monomer activity) and the hard core model (which is defined as a weighted sum over all independent sets where an independent set I is given a weight λ^(|I|) in terms of a fixed parameter λ called the vertex activity). The connective constant is a natural measure of the average degree of a graph which has been studied extensively in combinatorics and mathematical physics, and can be bounded by a constant even for certain unbounded degree graphs such as those sampled from the sparse Erdős–Rényi model G(n,d/n). Our main technical contribution is to prove the best possible rates of decay of correlations in the natural probability distributions induced by both the hard core model and the monomer-dimer model in graphs with a given bound on the connective constant. These results on decay of correlations are obtained using a new framework based on the so-called message approach that has been extensively used recently to prove such results for bounded degree graphs. We then use these optimal decay of correlations results to obtain fully polynomial time approximation schemes (FPTASs) for the two problems on graphs of bounded connective constant. In particular, for the monomer-dimer model, we give a deterministic FPTAS for the partition function on all graphs of bounded connective constant for any given value of the monomer activity. The best previously known deterministic algorithm was due to Bayati et al. (Proc. 39th ACM Symp. Theory Comput., pp. 122–127, 2007), and gave the same runtime guarantees as our results but only for the case of bounded degree graphs. For the hard core model, we give an FPTAS for graphs of connective constant Δ whenever the vertex activity λ λ_c(Δ) would imply that NP=RP (Sly and Sun, Ann. Probab. 42(6):2383–2416, 2014). The previous best known result in this direction was in a recent manuscript by a subset of the current authors (Proc. 54th IEEE Symp. Found. Comput. Sci., pp 300–309, 2013), where the result was established under the sub-optimal condition λ < λ_c(Δ+1). Our techniques also allow us to improve upon known bounds for decay of correlations for the hard core model on various regular lattices, including those obtained by Restrepo et al. (Probab Theory Relat Fields 156(1–2):75–99, 2013) for the special case of Z^2 using sophisticated numerically intensive methods tailored to that special case