We present a Weitz-type FPTAS for the ferromagnetic Ising model across the entire Lee--Yang zero-free region, without relying on the strong spatial mixing (SSM) property. Our algorithm is Weitz-type for two reasons. First, it expresses the partition function as a telescoping product of ratios, with the key being to approximate each ratio. Second, it uses Weitz's self-avoiding walk tree, and truncates it at logarithmic depth to give a good and efficient approximation. The key difference from the standard Weitz algorithm is that we approximate a carefully designed edge-deletion ratio instead of the marginal probability of a vertex being assigned a particular spin, ensuring our algorithm does not require SSM. Furthermore, by establishing local dependence of coefficients (LDC), we prove a novel form of SSM for these edge-deletion ratios, which, in turn, implies the standard SSM for the random cluster model. This is the first SSM result for the random cluster model on general graphs, beyond lattices. Our proof of LDC is based on a new divisibility relation, and we show such relations hold quite universally. This leads to a broadly applicable framework for proving LDC across a variety of models, including the Potts model, the hypergraph independence polynomial, and Holant problems. Combined with existing zero-freeness results for these models, we derive new SSM results for them.
翻译:我们提出了一种Weitz型FPTAS(完全多项式时间近似方案),用于铁磁伊辛模型在整个李-杨零自由区域的计算,且不依赖于强空间混合(SSM)性质。我们的算法被称为Weitz型基于两个原因:首先,它将配分函数表示为比率之伸缩积,关键在于近似每个比率;其次,它采用Weitz的自回避行走树,并在对数深度处截断以提供高效的良好近似。与标准Weitz算法的关键区别在于,我们近似精心设计的边删除比率,而非顶点被分配特定自旋的边际概率,这确保算法无需SSM。此外,通过建立系数的局部依赖性(LDC),我们为这些边删除比率证明了一种新颖的SSM形式,这进而暗示了随机簇模型的标准SSM。这是针对一般图(超越晶格结构)上随机簇模型的首次SSM结果。我们对LDC的证明基于一种新的可除关系,并表明此类关系具有普遍适用性。这形成了一个广泛适用的框架,可用于证明多种模型(包括Potts模型、超图独立多项式及Holant问题)的LDC。结合这些模型现有的零自由性结果,我们为它们推导出了新的SSM结论。