On the hardness of recognizing graphs of small mim-width and its variants

TL;DR

This paper proves that recognizing graphs with small mim-width and its variants remains NP-hard, even at very low width values, highlighting the computational difficulty of these structural graph parameters.

Contribution

It introduces a new parameter Omim-width and demonstrates NP-hardness of recognizing graphs with mim-width and variants at small widths, including linear versions.

Findings

Deciding sim-width = 1 is NP-hard.

Deciding omim-width = 1 is NP-hard.

Deciding mim-width ≤ 2 is NP-hard.

Abstract

The mim-width of a graph is a powerful structural parameter that, when bounded by a constant, allows several hard problems to be polynomial-time solvable - with a recent meta-theorem encompassing a large class of problems [SODA2023]. Since its introduction, several variants such as sim-width and omim-width were developed, along with a linear version of these parameters. It was recently shown that mim-width and all these variants all paraNP-hard, a consequence of the NP-hardness of distinguishing between graphs of linear mim-width at most 1211 and graphs of sim-width at least 1216 [ICALP2025]. The complexity of recognizing graphs of small width, particularly those close to $1$, remained open, despite their especially attractive algorithmic applications. In this work, we show that the width recognition problems remain NP-hard even on small widths. Specifically, after introducing the novel parameter Omim-width sandwiched between omim-width and mim-width, we show that: (1) deciding whether a graph has sim-width = 1, omim-width = 1, or Omin-width = 1 is NP-hard, and the same is true for their linear variants; (2) the problems of deciding whether mim-width $\leq$ 2 or linear mim-width $\leq$ 2 are both NP-hard. Interestingly, our reductions are relatively simple and are from the Unrooted Quartet Consistency problem, which is of great interest in computational biology but is not commonly used (if ever) in the theory of algorithms.