Random CNFs are Hard for Cutting Planes
Computational Complexity
2017-03-08 v1
Abstract
The random k-SAT model is the most important and well-studied distribution over k-SAT instances. It is closely connected to statistical physics; it is used as a testbench for satisfiability algorithms, and average-case hardness over this distribution has also been linked to hardness of approximation via Feige's hypothesis. We prove that any Cutting Planes refutation for random k-SAT requires exponential size, for k that is logarithmic in the number of variables, in the (interesting) regime where the number of clauses guarantees that the formula is unsatisfiable with high probability.
Cite
@article{arxiv.1703.02469,
title = {Random CNFs are Hard for Cutting Planes},
author = {Noah Fleming and Denis Pankratov and Toniann Pitassi and Robert Robere},
journal= {arXiv preprint arXiv:1703.02469},
year = {2017}
}