Combining the K-CNF and XOR Phase-Transitions

Abstract

The runtime performance of modern SAT solvers on random k-CNF formulas is deeply connected with the 'phase-transition' phenomenon seen empirically in the satisfiability of random k-CNF formulas. Recent universal hashing-based approaches to sampling and counting crucially depend on the runtime performance of SAT solvers on formulas expressed as the conjunction of both k-CNF and XOR constraints (known as k-CNF-XOR formulas), but the behavior of random k-CNF-XOR formulas is unexplored in prior work. In this paper, we present the first study of the satisfiability of random k-CNF-XOR formulas. We show empirical evidence of a surprising phase-transition that follows a linear trade-off between k-CNF and XOR constraints. Furthermore, we prove that a phase-transition for k-CNF-XOR formulas exists for k = 2 and (when the number of k-CNF constraints is small) for k > 2. PDF

Cite

Text

Dudek et al. "Combining the K-CNF and XOR Phase-Transitions." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Dudek et al. "Combining the K-CNF and XOR Phase-Transitions." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/dudek2016ijcai-combining/)

BibTeX

@inproceedings{dudek2016ijcai-combining,
  title     = {{Combining the K-CNF and XOR Phase-Transitions}},
  author    = {Dudek, Jeffrey M. and Meel, Kuldeep S. and Vardi, Moshe Y.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {727-734},
  url       = {https://mlanthology.org/ijcai/2016/dudek2016ijcai-combining/}
}