Title: Hard Instance Generation for Sat
نویسنده
چکیده
We consider the problem of generating hard instances for the Satisfying Assignment Search Problem (in short, SAT). It is not known whether SAT is difficult on average, while it has been believed that the Factorization Problem (in short, FACT) is hard on average. Thus, one can expect to generate hard-on-average instances by using a reduction from FACT to SAT. Although the asymptotically best reduction is obtained by using the Fast Fourier Transform [SS71] (in short, FFT), its constant factor is too big in practice. Here we propose to use the Chinese Remainder Theorem for constructing efficient yet simple reductions from FACT to SAT. First by using the Chinese Remainder Theorem recursively, we define a reduction that produces, from n bit FACT instances, SAT instances in the conjunctive normal form with O(n) variables, where ǫ > 0 is any fixed constant. (Cf. The reduction using FFT yields instances with O(n logn log logn) variables.) Next we demonstrate the efficiency of our approach with some concrete examples; we define a reduction that produces relatively small SAT instances. For example, it is possible to construct SAT instances with about 5,600 variables that is as hard as factorizing 100 bit integers. (Cf. The straightforward reduction yields SAT instances with 7,600 variables.)
منابع مشابه
Hard Instance Generation for Sat Title: Hard Instance Generation for Sat
We consider the problem of generating hard instances for the Satisfying Assignment Search Problem (in short, SAT). It is not known whether SAT is di cult on average, while it has been believed that the Factorization Problem (in short, FACT) is hard on average. Thus, one can expect to generate hard-on-average instances by using a reduction from FACT to SAT. Although the asymptotically best reduc...
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