Improved Bounds for Sampling Solutions of Random CNF Formulas.

SODA(2023)

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摘要
Let $\Phi$ be a random $k$-CNF formula on $n$ variables and $m$ clauses, where each clause is a disjunction of $k$ literals chosen independently and uniformly. Our goal is, for most $\Phi$, to (approximately) uniformly sample from its solution space. Let $\alpha=m/n$ be the density. The previous best algorithm runs in time $n^{\mathsf{poly}(k,\alpha)}$ for any $\alpha\lesssim2^{k/300}$ [Galanis, Goldberg, Guo, and Yang, SIAM J. Comput.'21]. In contrast, our algorithm runs in near-linear time for any $\alpha\lesssim2^{k/3}$.
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关键词
sampling solutions,improved bounds
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