English

Non-Redundancy of Low-Arity Symmetric Boolean CSPs

Data Structures and Algorithms 2026-05-15 v1 Computational Complexity

Abstract

Non-redundancy, introduced by Bessiere, Carbonnel, and Katsirelos (AAAI 2020), is a structural parameter for Constraint Satisfaction Problems (CSPs\mathsf{CSPs}) that governs kernelization, exact and approximate sparsification, and exact streaming complexity. It is the largest size of a CSP\mathsf{CSP} instance admitting no smaller subinstance with the same satisfying assignments. We study non-redundancy NRDn(R)\mathsf{NRD}_n(R) for Boolean symmetric CSPs\mathsf{CSPs} defined by an rr-ary relation RR whose value depends only on Hamming weight. An instance of CSP(R)\mathsf{CSP}(R) has nn variables and constraints given by rr-tuples; a constraint is satisfied exactly when the induced tuple lies in RR. This class includes natural predicates such as cuts and kk-SAT clauses. Our main result is a near-complete classification of the asymptotic growth of NRDn(R)\mathsf{NRD}_n(R) for symmetric Boolean predicates of arity at most 55. Using computational experiments and algebraic upper- and lower-bound criteria, we resolve every predicate of arity at most 44 and all but two predicates of arity 55. For upper bounds, we introduce tt-balancedness, a lifted, higher-degree version of the balancedness notion of Chen, Jansen, and Pieterse (Algorithmica 2020). We prove that tt-balancedness is equivalent to the existence of degree-tt multilinear polynomials capturing RR, and hence implies NRDn(R)=O(nt)\mathsf{NRD}_n(R)=O(n^t). For lower bounds, we use Carbonnel's (CP 2022) framework: predicates admitting a special reduction from kk-ary OR inherit OR's lower bound Ω(nk)\Omega(n^k). The only unresolved arity-55 predicates in our framework have bounds Ω(n2)\Omega(n^2) and O(n3)O(n^3); we reduce their exact classification to natural extremal set-system questions.

Keywords

Cite

@article{arxiv.2605.14007,
  title  = {Non-Redundancy of Low-Arity Symmetric Boolean CSPs},
  author = {Amatya Sharma and Santhoshini Velusamy},
  journal= {arXiv preprint arXiv:2605.14007},
  year   = {2026}
}