CNF Encodings of Symmetric Functions

IF 0.6 4区 计算机科学 Q4 COMPUTER SCIENCE, THEORY & METHODS Theory of Computing Systems Pub Date : 2024-03-26 DOI:10.1007/s00224-024-10168-w
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引用次数: 0

Abstract

Many Boolean functions that need to be encoded as CNF in practice, have only exponential size CNF representations. To avoid this effect, one usually introduces nondeterministic variables. For example, whereas the minimum number of clauses in a CNF computing the parity function \(x_1\oplus x_2 \oplus \cdots \oplus x_n\) is  \(2^{n-1}\) , one can use \(n-1\) nondeterministic variables to get a CNF encoding with 4n clauses. In this paper, we prove tradeoffs between various parameters (the number of clauses, the width of clauses, and the number of nondeterministic variables) of CNF encodings of various symmetric functions. In particular, we show that a folklore way of encoding parity as CNF is provably optimal. We do this by using a tight connection between CNF encodings and depth-3 circuits. This connection shows that CNF encodings is an interesting computational model for Boolean functions: on the one hand, it is routinely used in practice when translating a computational problem to a format acceptable by a SAT solver, on the other hand, lower bounds on the size of CNF encodings imply depth-3 circuit lower bounds.

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对称函数的 CNF 编码
摘要 在实践中,许多需要用 CNF 编码的布尔函数,其 CNF 表示的大小仅为指数级。为了避免这种影响,我们通常会引入非确定变量。例如,计算奇偶校验函数 \(x_1\oplus x_2 \oplus \cdots \oplus x_n\) 的 CNF 中的最小子句数是 \(2^{n-1}\),而我们可以使用 \(n-1\) 个非确定变量来得到一个有 4n 个子句的 CNF 编码。在本文中,我们证明了各种对称函数的 CNF 编码的各种参数(子句数、子句宽度和非确定变量数)之间的权衡。特别是,我们证明了将奇偶性编码为 CNF 的民间方法是可证明的最优方法。我们通过使用 CNF 编码和深度-3 电路之间的紧密联系来实现这一点。这种联系表明,CNF 编码是布尔函数的一个有趣的计算模型:一方面,当把一个计算问题转换成 SAT 解算器可接受的格式时,CNF 编码经常被用于实践;另一方面,CNF 编码大小的下限意味着深度-3 电路的下限。
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来源期刊
Theory of Computing Systems
Theory of Computing Systems 工程技术-计算机:理论方法
CiteScore
1.90
自引率
0.00%
发文量
36
审稿时长
6-12 weeks
期刊介绍: TOCS is devoted to publishing original research from all areas of theoretical computer science, ranging from foundational areas such as computational complexity, to fundamental areas such as algorithms and data structures, to focused areas such as parallel and distributed algorithms and architectures.
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