The CNF Encoding Complexity of Boolean Functions
Andrew Krapivin, Benjamin Przybocki, Bernardo Subercaseaux
We study the minimum number of clauses required to encode a boolean function into a CNF formula with auxiliary variables. Our main result is that if a boolean function can be evaluated in nondeterministic time $t$ (in the RAM model) with $m$ bits of advice such that at most $b$ bits of advice are accessed for each input, then it admits a CNF encoding with $\widetilde{O}(t + \sqrt{mb})$ clauses. This constitutes a nonuniform generalization of Robson's (TCS'91) variant of the Cook--Levin theorem, for which a naïve generalization would yield $\widetilde{O}(t+m)$ clauses; our applications leverage $b = o(m)$ to obtain significantly better bounds. Since preprocessed data structures can be modeled as computation with advice, our result allows us to translate space- and time-efficient data structures to compact CNF encodings. As an application, we derandomize a data structure of Larsen and Williams (SODA'17) to show that every $k$-CNF function on $n$ inputs can be encoded with $n^k/2^{Ω_k(\sqrt{\lg n})}$ clauses. Notably, despite encoding a $k$-CNF function, the encoding itself necessarily contains clauses of unbounded width, since an information-theoretic argument shows that the minimum number of bounded-width clauses to encode such functions is $Ω_k(n^{k}/\lg n)$ in the worst case. In general terms, our results imply that for a wide variety of NP-complete problems, one can reduce to CNF-SAT in a way that results in asymptotically fewer clauses than previously known methods.
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