Which NP-Hard SAT and CSP Problems Admit Exponentially Improved Algorithms?

TL;DR

This paper classifies the complexity of certain NP-hard SAT and CSP problems based on algebraic properties, identifying conditions for exponential algorithm improvements and establishing tight bounds under SETH.

Contribution

It introduces a hierarchy of sign-symmetric languages via pSDI-operations, linking algebraic structure to algorithmic complexity and bounds for SAT($ extGamma$) problems.

Findings

Classified pSDI-operations into levels with a strongest and weakest operation.

Identified conditions under which SAT($ extGamma$) can be solved faster than $2^n$.

Established matching upper and lower bounds for classes of SAT($ extGamma$) problems under SETH.

Abstract

We study the complexity of SAT($\Gamma$) problems for potentially infinite languages $\Gamma$ closed under variable negation (sign-symmetric languages). Via an algebraic connection, this reduces to the study of restricted partial polymorphisms of $\Gamma$ we refer to as \emph{pSDI-operations} (for partial, self-dual and idempotent). First, we study the language classes themselves. We classify the structure of the least restrictive pSDI-operations, corresponding to the most powerful languages $\Gamma$, and find that these operations can be divided into \emph{levels}, corresponding to a rough notion of difficulty; and that within each level there is a strongest operation (the partial $k$-NU operation, preserving $(k-1)$-SAT) and a weakest operation (the $k$-universal operation $u_k$, preserving problems definable via bounded-degree polynomials). We show that every sign-symmetric $\Gamma$ not preserved by $u_k$ implements all $k$-clauses; thus if $\Gamma$ is not preserved by $u_k$ for any $k$, then SAT($\Gamma$) is trivially SETH-hard and cannot be solved faster than $O^*(2^n)$ unless SETH fails. Second, we study upper and lower bounds for SAT($\Gamma$) for such languages. We show that several classes in the hierarchy correspond to problems which can be solved faster than $2^n$ using previously known algorithmic strategies such as Subset Sum-style meet-in-the-middle and fast matrix multiplication. Furthermore, if the sunflower conjecture holds for sunflowers with k sets, then the partial k-NU language has an improved algorithm via local search. Complementing this, we show that for every class there is a concrete lower bound $c$ such that SAT($\Gamma$) cannot be solved faster than $O^*(c^n)$ for all problems in the class unless SETH fails. This gives the first known case of a SAT-problem which simultaneously has non-trivial upper and lower bounds under SETH.