Optimal FPT-Approximability for Modular Linear Equations
Abstract
We show optimal FPT-approximability results for solving almost satisfiable systems of modular linear equations, completing the picture of the parameterized complexity and FPT-approximability landscape for the Min-r-Lin(Zm) problem for every r and m. In Min-r-Lin(Zm), we are given a system S of linear equations modulo m, each on at most r variables, and the goal is to find a subset Z ⊂eq S of minimum cardinality such that S - Z is satisfiable. The problem is UGC-hard to approximate within any constant factor for every r ≥ 2 and m ≥ 2, which motivates studying it through the lens of parameterized complexity with solution size as the parameter. From previous work (Dabrowski et al. SODA'23/TALG and ESA'25) we know that Min-r-Lin(Zm) is W[1]-hard to FPT-approximate within any constant factor when r ≥ 3, and that Min-2-Lin(Zm) is in FPT when m is prime and W[1]-hard when m has at least two distinct prime factors. The case when m = pd for some prime p and d ≥ 2 has remained an open problem. We resolve this problem in this paper and prove the following: (1) We prove that Min-2-Lin(Zpd) is in FPT for every prime p and d ≥ 1. This implies that Min-2-Lin(Zm) can be FPT-approximated within a factor of ω(m), where ω is the number of distinct prime factors of m. (2) We show that, under the ETH, Min-2-Lin(Zm) cannot be FPT-approximated within ω(m) - ε for any ε > 0. Our main algorithmic contribution is a new technique coined balanced subgraph covering, which generalizes important balanced subgraphs of Dabrowski et al. (SODA'23/TALG) and shadow removal of Marx and Razgon (STOC'11/SICOMP). For the lower bounds, we develop a framework for proving optimality of FPT-approximation factors under the ETH.
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