Optimal Inapproximability of Satisfiable k-LIN over Non-Abelian Groups
Abstract
A seminal result of Hastad [J. ACM, 48(4):798--859, 2001] shows that it is NP-hard to find an assignment that satisfies 1|G|+ fraction of the constraints of a given k-LIN instance over an abelian group, even if there is an assignment that satisfies (1-) fraction of the constraints, for any constant >0. Engebretsen et al. [Theoretical Computer Science, 312(1):17--45, 2004] later showed that the same hardness result holds for k-LIN instances over any finite non-abelian group. Unlike the abelian case, where we can efficiently find a solution if the instance is satisfiable, in the non-abelian case, it is NP-complete to decide if a given system of linear equations is satisfiable or not, as shown by Goldmann and Russell [Information and Computation, 178(1):253--262. 2002]. Surprisingly, for certain non-abelian groups G, given a satisfiable k-LIN instance over G, one can in fact do better than just outputting a random assignment using a simple but clever algorithm. The approximation factor achieved by this algorithm varies with the underlying group. In this paper, we show that this algorithm is optimal by proving a tight hardness of approximation of satisfiable k-LIN instance over any non-abelian G, assuming P ≠ NP. As a corollary, we also get 3-query probabilistically checkable proofs with perfect completeness over large alphabets with improved soundness.
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