Gap Amplification for Reconfiguration Problems
arXiv:2310.14160 · doi:10.1137/1.9781611977912.54
Abstract
In this paper, we demonstrate gap amplification for reconfiguration problems. In particular, we prove an explicit factor of PSPACE-hardness of approximation for three popular reconfiguration problems only assuming the Reconfiguration Inapproximability Hypothesis (RIH) due to Ohsaka (STACS 2023). Our main result is that under RIH, Maxmin 2-CSP Reconfiguration is PSPACE-hard to approximate within a factor of . Moreover, the same result holds even if the constraint graph is restricted to -expander for arbitrarily small . The crux of its proof is an alteration of the gap amplification technique due to Dinur (J. ACM, 2007), which amplifies the vs. gap for arbitrarily small up to the vs. gap. As an application of the main result, we demonstrate that Minmax Set Cover Reconfiguration and Minmax Dominating Set Reconfiguratio} are PSPACE-hard to approximate within a factor of under RIH. Our proof is based on a gap-preserving reduction from Label Cover to Set Cover due to Lund and Yannakakis (J. ACM, 1994). Unlike Lund--Yannakakis' reduction, the expander mixing lemma is essential to use. We highlight that all results hold unconditionally as long as "PSPACE-hard" is replaced by "NP-hard," and are the first explicit inapproximability results for reconfiguration problems without resorting to the parallel repetition theorem. We finally complement the main result by showing that it is NP-hard to approximate Maxmin 2-CSP Reconfiguration within a factor better than .
arXiv comment45 pages. A preliminary version of this paper appeared in Proc. 35th Annu. ACM-SIAM Symp. Discrete Algorithms (SODA 2024)
References in corpus (7)
- Clustering of solutions in the random satisfiability problem
- The Overlap Gap Property: a Geometric Barrier to Optimizing over Random Structures
- Reconfiguration Problems on Submodular Functions
- Gap Preserving Reductions Between Reconfiguration Problems
- On Inapproximability of Reconfiguration Problems: PSPACE-Hardness and some Tight NP-Hardness Results
- Alphabet Reduction for Reconfiguration Problems
- Optimal PSPACE-hardness of Approximating Set Cover Reconfiguration