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Computing the Independence Polynomial: from the Tree Threshold down to the Roots

机译:计算独立多项式:从树阈值下降到根部

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We study an algorithm for approximating the multivariate independence polynomial Z(z), with negative and complex arguments. While the focus so far has been mostly on computing combinatorial polynomials restricted to the univariate positive setting (with seminal results for the independence polynomial by Weitz (2006) and Sly (2010)), the independence polynomial with negative or complex arguments has strong connections to combinatorics and to statistical physics. The independence polynomial with negative arguments, Z(-p), determines the Shearer region, the maximal region of probabilities to which the Lovasz Local Lemma (LLL) can be extended (Shearer 1985). In statistical physics, complex zeros of the independence polynomial relate to existence of phase transitions. Our main result is a deterministic algorithm to compute approximately the independence polynomial in any root-free complex polydisc centered at the origin. More precisely, we can (1 + ε)-approximate the independence polynomial Z(z) for an n-vertex graph of degree at most d, for any complex vector z such that Z(z') ≠ 0 for |z'_i| ≤ (1 + α)|z_i|, in running time (n/εα)~(O(log(d)/{the square root of}α)). Our result also extends to graphs of unbounded degree that have a bounded connective constant. Our algorithm is essentially the same as Weitz's algorithm for positive parameters up to the tree uniqueness threshold. The core of the analysis is a novel multivariate form of the correlation decay technique, which can handle non-uniform complex parameters. In summary, we provide a unifying algorithm for all known regions where Z(z) is approximately computable. In particular, in the univariate real setting our work implies that Weitz's algorithm works in an interval between two critical points (-λ'_c(d), λ_c(d)), and outside of this interval an approximation of Z(λ) is known to be NP-hard. As an application, we provide an algorithm to test membership in Shearer's region within a multiplicative error of 1 + α, in running time (n/α)~(O({the square root of}(n/α) log d)). We also give a deterministic algorithm for Shearer's lemma (extending the LLL) with n events on m independent variables under slack α, with running time (nm/α)~(O({the square root of}(m/α)log d)). On the hardness side, we prove that evaluating Z(z) at an arbitrary point in Shearer's region, and testing membership in Shearer's region, are #P-hard problems. For Weitz's correlation decay technique in the negative regime, we show that the 1/{the square root of}α dependence in the exponent is optimal.
机译:我们研究了一种近似多变量独立多项式z(z)的算法,具有负和复杂的参数。虽然到目前为止的重点主要是在计算组合多项式上限制为单变量阳性设置的组合多项式(Weitz(2006)和Sly(2010)的独立多项式的初始结果),具有负面或复杂的参数的独立多项式具有很强的连接组合学与统计物理学。具有负参数,z(-P)的独立多项式确定用于延长Lovasz局部引理(LLL)的概率区域的用于延长的最大概率(采血1985)。在统计物理学中,独立多项式的复合零与相变的存在涉及相位过渡的存在。我们的主要结果是确定在原点以来的任何无根复合多地区的独立多项式中计算的确定性算法。更确切地说,我们可以(1 +ε) - 批量独立多项式z(z)对于最多D的n个顶点图,对于任何复数矢量z,使得z(z')≠0 for | z'_i | ≤(1 +α)| z_i |,在运行时间(n /εα)〜(o(o(d)/ {}α的平方根))。我们的结果也延伸到具有有界连接常数的无限度的图表。我们的算法与Weitz的算法基本相同,以实现树唯一度阈值的正参数。分析的核心是一种新型多变量形式的相关衰减技术,可以处理非均匀的复杂参数。总之,我们为所有已知区域提供了一个统一算法,其中z(z)近似可计算。特别是,在单变量真实设置中,我们的工作意味着Weitz的算法在两个关键点(-λ'_c(d),λ_c(d))之间的间隔工作,并且在该间隔之外的z(λ)的近似值已知是np-hard。作为应用程序,我们提供了一种算法,以在运行时间(n /α)〜(o(n /α)log d)的乘法(n /α)〜(o({(n /α)log d)中的乘法误差内测试成员资格。我们还提供了一种确定性算法,用于在Slackα下的M独立变量上使用n个事件进行剪切者的引导算法(扩展lll),运行时间(nm /α)〜(o({{m /α)log d的log d )))。在硬度方面,我们证明了评估了Z(Z)在采煤机区域的任意点,以及在牧羊人地区测试成员资格,是#P难题。对于Weitz在负面制度中的相关性衰减技术,我们表明1 / {}α依赖性在指数中的依赖性是最佳的。

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