English

Optimal Inapproximability of Generalized Linear Equations over a Finite Group

Computational Complexity 2026-05-12 v1

Abstract

Constraint satisfaction problems (CSPs) consist of a set of variables taking values from some finite domain and a set of local constraints on these variables. The objective is to find an assignment to the variables that maximizes the fraction of satisfied constraints. In this work, we study the CSP where the constraints are generalized linear equations over a finite group G. More specifically, for a given SGS \subseteq G, the constraints in this CSP are of the form addition of the values to the variables (similarly, product for non-abelian groups), belonging to the set SS. We give an approximation algorithm for this problem on satisfiable instances and show that it is optimal for certain SS assuming PNPP\neq NP. This natural predicate is one of the very few known predicates that are approximation resistant on almost satisfiable instances, assuming PNPP\neq NP, but admits a non-trivial approximation algorithm on satisfiable instances.

Keywords

Cite

@article{arxiv.2605.10010,
  title  = {Optimal Inapproximability of Generalized Linear Equations over a Finite Group},
  author = {Amey Bhangale and Yezhou Zhang},
  journal= {arXiv preprint arXiv:2605.10010},
  year   = {2026}
}