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CSPs with Global Modular Constraints: Algorithms and Hardness via Polynomial Representations

机译:具有全局模块化约束的CSP:通过多项式表示的算法和硬度

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We study the complexity of Boolean constraint satisfaction problems (CSPs) when the assignment must have Hamming weight in some congruence class modulo M , for various choices of the modulus M . Due to the known classification of tractable Boolean CSPs, this mainly reduces to the study of three cases: 2SAT, HornSAT, and LIN-MOD2 (linear equations mod 2 ). We classify the moduli M for which these respective problems are polynomial time solvable, and when they are not (assuming the ETH). Our study reveals that this modular constraint lends a surprising richness to these classic, well-studied problems, with interesting broader connections to complexity theory and coding theory. The HornSAT case is connected to the covering complexity of polynomials representing the NAND function mod M . The LIN-MOD2 case is tied to the sparsity of polynomials representing the OR function mod M , which in turn has connections to modular weight distribution properties of linear codes and locally decodable codes. In both cases, the analysis of our algorithm as well as the hardness reduction rely on these polynomial representations, highlighting an interesting algebraic common ground between hard cases for our algorithms and the gadgets which show hardness. These new complexity measures of polynomial representations merit further study.The inspiration for our study comes from a recent work by N?gele, Sudakov, and Zenklusen on submodular minimization with a global congruence constraint. Our algorithm for HornSAT has strong similarities to their algorithm, and in particular identical kind of set systems arise in both cases. Our connection to polynomial representations leads to a simpler analysis of such set systems, and also sheds light on (but does not resolve) the complexity of submodular minimization with a congruency requirement modulo a composite M .
机译:我们研究了布尔约束满足问题(CSP)的复杂性,其中赋值必须在某些同余类模M中具有汉明权重,并且可以选择各种模数M。由于已知易处理布尔CSP的分类,这主要简化为三种情况的研究:2SAT,HornSAT和LIN-MOD2(线性方程mod 2)。我们对模数M进行分类,对于这些模数M,这些相应的问题可以在多项式时间上求解,而在不能解决时(假设ETH)。我们的研究表明,这种模块化的约束为这些经典的,经过充分研究的问题提供了令人惊讶的丰富性,并且与复杂性理论和编码理论之间形成了有趣的广泛联系。 HornSAT的情况与代表NAND函数mod M的多项式的覆盖复杂度有关。 LIN-MOD2情况与表示OR函数mod M的多项式的稀疏性相关,而OR函数mod M则与线性代码和可本地编码的模块权重分布属性有关。在这两种情况下,我们算法的分析以及硬度降低都依赖于这些多项式表示法,突出了我们算法的硬案例与显示硬度的小工具之间有趣的代数共同点。这些新的多项式表示形式的复杂性度量值得进一步研究。我们的研究灵感来自于N?gele,Sudakov和Zenklusen最近关于具有全局一致性约束的子模最小化的研究。我们针对HornSAT的算法与它们的算法有很强的相似性,在两种情况下,特别是出现了相同类型的集合系统。我们与多项式表示的联系可以简化此类集合系统的分析,并且可以阐明(但不能解决)子模最小化的复杂性以及对复合M进行模数一致性的要求。

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