Deterministic Search for CNF Satisfying Assignments in Almost Polynomial Time

R. Servedio, Li-Yang Tan
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引用次数: 10

Abstract

We consider the fundamental derandomization problem of deterministically finding a satisfying assignment to a CNF formula that has many satisfying assignments. We give a deterministic algorithm which, given an n-variable \poly(n)-clause CNF formula F that has at least ≥ 2^n satisfying assignments, runs in time \[ n^{\tilde{O}(\log\log n)^2} \] for ≥ \ge 1/\polylog(n) and outputs a satisfying assignment of F. Prior to our work the fastest known algorithm for this problem was simply to enumerate over all seeds of a pseudorandom generator for CNFs; using the best known PRGs for CNFs \cite{DETT10, this takes time n^{\tilde{Ω}(\log n)} even for constant ≥. Our approach is based on a new general framework relating deterministic search and deterministic approximate counting, which we believe may find further applications.
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几乎多项式时间内满足赋值的CNF的确定性搜索
我们考虑一个基本的非随机化问题,即确定性地找到一个有许多满意赋值的CNF公式的满意赋值。我们给出了一个确定性算法,给定一个n变量\poly(n)-clause - CNF公式F,它至少具有≥2^n个满足的赋值,运行时间\[n^{\tilde{O}(\log\log n)^2} \] for ≥\ge 1/\polylog(n)并输出一个令人满意的赋值f。在我们的工作之前,已知最快的算法是简单地枚举CNFs的伪随机生成器的所有种子;对于CNFs \cite{DETT10,使用最著名的PRGs,即使对于常数≥,也需要n^{\tilde{Ω}(\log n)}时间。我们的方法是基于一个与确定性搜索和确定性近似计数相关的新的通用框架,我们相信这可能会找到进一步的应用。
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