Grid Recognition: Classical and Parameterized Computational Perspectives
Siddharth Gupta, Guy Sa'ar, Meirav Zehavi

TL;DR
This paper explores the computational complexity of recognizing grid graphs, providing new fixed-parameter tractability results and hardness proofs, and introduces a novel parameter relating graph and geometric distances.
Contribution
It offers new FPT algorithms for grid graph recognition based on parameters like component size and treedepth, and establishes hardness results for certain graph classes.
Findings
Recognition is FPT when parameterized by component size and treedepth.
Recognition is NP-hard on graphs of pathwidth 2 for certain grid sizes.
A new parameter relating graph and geometric distances is introduced and analyzed.
Abstract
Grid graphs, and, more generally, grid graphs, form one of the most basic classes of geometric graphs. Over the past few decades, a large body of works studied the (in)tractability of various computational problems on grid graphs, which often yield substantially faster algorithms than general graphs. Unfortunately, the recognition of a grid graph is particularly hard -- it was shown to be NP-hard even on trees of pathwidth 3 already in 1987. Yet, in this paper, we provide several positive results in this regard in the framework of parameterized complexity (additionally, we present new and complementary hardness results). Specifically, our contribution is threefold. First, we show that the problem is fixed-parameter tractable (FPT) parameterized by where is the maximum size of a connected component of . This also implies that the problem is…
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