English

The set of solutions of random XORSAT formulae

Discrete Mathematics 2015-09-10 v2 Disordered Systems and Neural Networks Probability

Abstract

The XOR-satisfiability (XORSAT) problem requires finding an assignment of nn Boolean variables that satisfy mm exclusive OR (XOR) clauses, whereby each clause constrains a subset of the variables. We consider random XORSAT instances, drawn uniformly at random from the ensemble of formulae containing nn variables and mm clauses of size kk. This model presents several structural similarities to other ensembles of constraint satisfaction problems, such as kk-satisfiability (kk-SAT), hypergraph bicoloring and graph coloring. For many of these ensembles, as the number of constraints per variable grows, the set of solutions shatters into an exponential number of well-separated components. This phenomenon appears to be related to the difficulty of solving random instances of such problems. We prove a complete characterization of this clustering phase transition for random kk-XORSAT. In particular, we prove that the clustering threshold is sharp and determine its exact location. We prove that the set of solutions has large conductance below this threshold and that each of the clusters has large conductance above the same threshold. Our proof constructs a very sparse basis for the set of solutions (or the subset within a cluster). This construction is intimately tied to the construction of specific subgraphs of the hypergraph associated with an instance of kk-XORSAT. In order to study such subgraphs, we establish novel local weak convergence results for them.

Keywords

Cite

@article{arxiv.1107.5377,
  title  = {The set of solutions of random XORSAT formulae},
  author = {Morteza Ibrahimi and Yash Kanoria and Matt Kraning and Andrea Montanari},
  journal= {arXiv preprint arXiv:1107.5377},
  year   = {2015}
}

Comments

Published at http://dx.doi.org/10.1214/14-AAP1060 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)