GraphSAT -- a decision problem connecting satisfiability and graph theory
CoRR(2021)
Abstract
Satisfiability of boolean formulae (SAT) has been a topic of research in logic and computer science for a long time. In this paper we are interested in understanding the structure of satisfiable and unsatisfiable sentences. In previous work we initiated a new approach to SAT by formulating a mapping from propositional logic sentences to graphs, allowing us to find structural obstructions to 2SAT (clauses with exactly 2 literals) in terms of graphs. Here we generalize these ideas to multi-hypergraphs in which the edges can have more than 2 vertices and can have multiplicity. This is needed for understanding the structure of SAT for sentences made of clauses with 3 or more literals (3SAT), which is a building block of NP-completeness theory. We introduce a decision problem that we call GraphSAT, as a first step towards a structural view of SAT. Each propositional logic sentence can be mapped to a multi-hypergraph by associating each variable with a vertex (ignoring the negations) and each clause with a hyperedge. Such a graph then becomes a representative of a collection of possible sentences and we can then formulate the notion of satisfiability of such a graph. With this coarse representation of classes of sentences one can then investigate structural obstructions to SAT. To make the problem tractable, we prove a local graph rewriting theorem which allows us to simplify the neighborhood of a vertex without knowing the rest of the graph. We use this to deduce several reduction rules, allowing us to modify a graph without changing its satisfiability status which can then be used in a program to simplify graphs. We study a subclass of 3SAT by examining sentences living on triangulations of surfaces and show that for any compact surface there exists a triangulation that can support unsatisfiable sentences, giving specific examples of such triangulations for various surfaces.
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Key words
satisfiability,graphsat theory,decision problem
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