the impact of heterogeneity and geometry on the proof complexity of random satisfiability

ddc:004 Computational Geometry (cs.CG) FOS: Computer and information sciences Discrete Mathematics (cs.DM) DATA processing & computer science Probability (math.PR) G.3 G.2.1 02 engineering and technology Computational Complexity (cs.CC) 004 Computer Science - Computational Complexity Computer Science - Data Structures and Algorithms 0202 electrical engineering, electronic engineering, information engineering FOS: Mathematics Computer Science - Computational Geometry F.2.2; G.2.1; G.3 Data Structures and Algorithms (cs.DS) F.2.2 info:eu-repo/classification/ddc/004 Mathematics - Probability Computer Science - Discrete Mathematics
DOI: 10.13039/501100001659 Publication Date: 2021-01-01
ABSTRACT
AbstractSatisfiability is considered the canonical NP‐complete problem and is used as a starting point for hardness reductions in theory, while in practice heuristic SAT solving algorithms can solve large‐scale industrial SAT instances very efficiently. This disparity between theory and practice is believed to be a result of inherent properties of industrial SAT instances that make them tractable. Two characteristic properties seem to be prevalent in the majority of real‐world SAT instances, heterogeneous degree distribution and locality. To understand the impact of these two properties on SAT, we study the proof complexity of random ‐SAT models that allow to control heterogeneity and locality. Our findings show that heterogeneity alone does not make SAT easy as heterogeneous random ‐SAT instances have superpolynomial resolution size. This implies intractability of these instances for modern SAT‐solvers. In contrast, modeling locality with underlying geometry leads to small unsatisfiable subformulas, which can be found within polynomial time.
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