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The Hard Problems Are Almost Everywhere For Random CNF-XOR Formulas

机译:随机CNF-XOR公式的难题几乎无处不在

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Recent universal-hashing based approaches to sampling and counting crucially depend on the run-time performance of SAT solvers on formulas expressed as the conjunction of both CNF constraints and variable-width XOR constraints (known as CNF-XOR formulas). In this paper, we present the first study of the runtime behavior of SAT solvers equipped with XOR-reasoning techniques on random CNF-XOR formulas. We empirically demonstrate that a state-of-the-art SAT solver scales exponentially on random CNF-XOR formulas across a wide range of XOR-clause densities, peaking around the empirical phase-transition location. On the theoretical front, we prove that the solution space of a random CNF-XOR formula 'shatters' at all nonzero XOR-clause densities into well-separated components, similar to the behavior seen in random CNF formulas known to be difficult for many SAT-solving algorithms.
机译:基于对采样和计数的基于普遍散列的方法是至关重要的,这取决于SAT溶剂的运行时性能,表示为CNF约束和可变宽度XOR约束的结合(称为CNF-XOR公式)。在本文中,我们介绍了在随机CNF-XOR公式上配备了XOR推理技术的SAT溶剂的运行行为的第一次研究。我们经验证明,在跨越XOR-CliS密度的随机CNF-XOR公式上呈指数上的最先进的SAT求解尺度,围绕经验相转移位置达到峰值。在理论前面,我们证明了所有非零XOR-Z-Charlyities的随机CNF-XOR公式“散击的解决方案到分离成分的良好分离的组分中,类似于在许多饱和的随机CNF公式中所看到的行为-Solving算法。

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