Abstract 1 Introduction 2 Preliminaries 3 Sim-width, omim-width and Omim-width 4 Mim-width and linear mim-width 5 Open problems References

On the Hardness of Recognizing Graphs of Small Mim-Width and Its Variants

Max Dupré la Tour ORCID Department of Computer Science, McGill University, Montreal, Canada    Manuel Lafond ORCID Department of Computer Science, Université de Sherbrooke, Canada    Ndiamé Ndiaye ORCID Department of Mathematics, McGill University, Montreal, Canada
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 are 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 Omim-width = 1 is NP-hard, and the same is true for their linear variants; (2) the problems of deciding whether mim-width ≤ 2 or linear mim-width ≤ 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 in the theory of algorithms.

Keywords and phrases:
Mim-width, NP-hardness, Computational Biology
Category:
Track A: Algorithms, Complexity and Games
Copyright and License:
[Uncaptioned image] © Max Dupré la Tour, Manuel Lafond, and Ndiamé Ndiaye; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Mathematics of computing → Graph algorithms
Related Version:
Full Version: https://arxiv.org/pdf/2512.06186
Editors:
Sayan Bhattacharya, Danupon Nanongkai, Michael Benedikt, and Gabriele Puppis

1 Introduction

Many hard problems on graphs become easier when the underlying graph has a simple structure, and over the years several “width” parameters have been developed to capture such structure. One of these is the mim-width (maximum induced matching width), introduced by Vatshelle [23]. A branch decomposition of a graph G is a ternary tree whose leaves represent the vertices of G, and each of its edges naturally defines a cut of the graph. For any such decomposition, each cut induces a bipartite graph, in which we consider the size of a maximum induced matching. The mim-width of G is then the minimum, over all branch decompositions of G, of the maximum size of such an induced matching across all cuts of the decomposition [23, 3].

It is a powerful parameter that can be constant even on graphs of high clique-width, and several algorithmic problems are polynomial-time solvable on graphs of constant mim-width [12, 13, 11], under the assumption that a branch decomposition is given. This is notably witnessed by a recent logic-based meta-theorem that solves many problems in polynomial-time under these assumptions [5].

Since its inception, several variants of mim-width were developed: the sim-width parameter is the same, except that edges of G within both sides of the cut are kept [14, 16]; the one-sided mim-width (omim−width) keeps only the edges within either side of the cut and takes the minimum [7]; the large one-sided mim-width (Omim−width), which we introduce in this work, instead takes the maximum; and the linear variant of all these parameters require the branch decomposition to be a caterpillar (see precise definitions below).

Recognizing graphs of mim-width at most k was quickly established to be W[1]-hard in parameter k [20], but the question of XP membership was posed several times since the creation of the parameter (in addition to the previous references, this was also raised in [8, 7, 18, 5]). The same remained open for all the aforementioned variants of mim-width, except the linear sim-width = 1 case shown NP-hard in [24]. All these questions were finally answered by Bergougnoux, Bonnet, and Duron [4], where the authors showed that it is NP-hard to distinguish between graphs of linear mim-width at most 1211 and graphs of sim-width at least 1216, implying the paraNP-hardness of mim−width but also of all the above variants.

It is still open whether there is a constant c<1211 such that recognizing graphs of mim-width (and variants) at most c is in P. Determining whether such a c exists is quite relevant, because graphs of small width are those that matter for algorithmic applications. In this work, we reduce this knowledge gap significantly by proving the following results:

Theorem 1.

The problem of deciding whether a graph has sim-width, omim-width, or Omim-width equal to 1 is NP-complete. Moreover, assuming the ETH, it cannot be solved in time 2o⁢(n), where n is the number of vertices of the graph. The same holds for the linear variant of these three parameters.

Theorem 2.

The problem of deciding whether a graph has mim-width or linear mim-width at most 2 is NP-complete. Moreover, assuming the ETH, it cannot be solved in time 2o⁢(n), where n is the number of vertices of the graph.

Note that the ETH refers to the Exponential Time Hypothesis [10]. We also point out that the new parameter Omim−width is a lower bound on mim−width, and an upper bound on omim−width, which in turn is an upper bound on sim−width.

Our reductions are relatively simple and arguably less involved than in [4], which require a series of reductions with complex gadgets. Another unique aspect of our reductions is that they are all from the Unrooted Quartet Consistency (UQC) problem, shown NP-hard in [22]. The input to UQC is a set of trees on four leaves, and one must decide whether there is a single tree that contains all of them.

This is not a common problem to reduce from, as UQC is often more seen as an “end-user” problem, in the sense that it is mostly popular for its bioinformatics applications. Its hardness has mainly been used to justify heuristics and approximations. The only notable exception we are aware of is the use of UQC to prove the NP-hardness of the so-called Triangle Ordinal Clustering problem [21], which was then used to show that recognizing the graph class of leaf powers and some of its generalizations is NP-hard [15]. Inspired by the latter, our approach shows that UQC may be well-suited for problems that require finding a branch decomposition, since UQC is a tree reconstruction problem. It is possible that UQC or similar variants may be useful for other open XP membership problems that involve graph-to-tree representations (for instance module-width [19, 3], not to be confused with modular-width, which is within a factor two of clique-width, or other similar problems stated in [9]).

Although our results do not imply hardness for mim-width and variants between 3 and 1210, they indicate that there is little hope of recognizing graphs of small width efficiently. The notable cases of mim-width 1 and linear mim-width 1 remain open. These two graph classes have exploitable structural properties, for instance graphs of mim-width 1 are weakly chordal [23] and graphs of linear mim-width 1 have no so-called asteroidal edge triples [9], and their membership in P is still possible. The aforementioned class of leaf powers is one of the most natural subclasses of graphs of mim-width 1, so its hardness may be seen as evidence for the mim-width 1 hardness. On the other hand, recognizing linear leaf powers, a subclass of graphs of linear mim-width 1, is in P [6].

2 Preliminaries

2.1 Notations and Definitions

All graphs considered are simple and undirected. The vertex set and edge set of a graph G are denoted by V⁢(G) and E⁢(G), respectively. An edge between two vertices u and v is denoted by u⁢v (or equivalently v⁢u). For a subset X⊆V⁢(G), let G⁢[X] denote the subgraph of G induced by X, and let EG⁢[X] denote the edge set of G⁢[X]. For a set of edges F⊆E⁢(G), we write G−F for the graph obtained from G by deleting all edges in F.

A matching of G is a set of edges no two of which share a common endpoint. An induced matching of G is a matching M such that every edge of G is incident with at most one edge of M. A cut of G is a bipartition (A,B) of V⁢(G). We denote by G⁢[A,B] the bipartite subgraph of G with edge set {u⁢v∈E⁢(G)∣u∈A,v∈B}.

Unless stated otherwise, all trees in this work are unrooted. A tree is ternary if each vertex has either 1 or 3 neighbors111 Note, ternary trees are sometimes called binary, but here we prefer “ternary” to emphasize that internal vertices have 3 neighbors, not 2.. A caterpillar is a tree in which the set of internal vertices induces a path, called its spine. Given a total order ≤ on a set P of n≥4 points, we define the ternary caterpillar realizing ≤, with leaf set P as follows. If p1<p2<⋯<pn−1<pn, then the interval [2,n−1] forms the spine of the caterpillar. Attach each leaf pi to the integer i, and additionally attach p1 to 2 and pn to n−1. Note that a given ternary caterpillar with leaf set P realizes several total orders, since we may choose which end of the spine is the minimum/maximum and, at each end, which of the two incident leaves plays the “endpoint” role.

Width parameters

Given a cut (A,B): The mim-value of (A,B), denoted mimG⁡(A,B), is the maximum size of an induced matching in G⁢[A,B].

The sim-value of (A,B), denoted simG⁡(A,B), is the maximum size of a matching in G⁢[A,B] that is also an induced matching of G (hence, edges within A and within B are also considered but cannot be in the matching).

For a subset X⊆V⁢(G), the upper-induced matching number of X is the maximum size of a matching in G⁢[X,V⁢(G)∖X] that is an induced matching of the graph G−EG⁢[V⁢(G)∖X].

The omim-value of a cut (A,B), denoted omimG⁡(A,B), is the minimum of the upper-induced matching numbers of A and B.

The Omim-value of a cut (A,B), denoted OmimG⁡(A,B), is the maximum of the upper-induced matching numbers of A and B.

Note that it directly follows from the definitions of the parameters that mimG⁡(A,B)≥OmimG⁡(A,B)≥omimG⁡(A,B)≥simG⁡(A,B).

mimG⁡(A,B)=4
OmimG⁡(A,B)=3
omimG⁡(A,B)=2
simG⁡(A,B)=1
Figure 1: A graph illustrating the differences of the width parameters on a specific cut (A,B).

A branch decomposition of a graph G is a ternary tree T whose leaves correspond exactly to the vertices of G. Given such a tree T, each edge e of T defines a cut (Ae,Be), where Ae and Be are the vertex sets corresponding to the two connected components of T−{e}. The mim-width (resp. sim-width, omim-width, Omim-width) of T is the maximum, over all edges e of T, of mimG⁡(Ae,Be) (resp. simG⁡(Ae,Be), omimG⁡(Ae,Be), OmimG⁡(Ae,Be)). Finally, the mim-width (resp. sim-width, omim-width, Omim-width) of G is the minimum, over all branch decompositions T of G, of the mim-width (resp. sim-width, omim-width, Omim-width) of T.

Each of these width parameters has a linear variant, which require T to be a caterpillar. We denote such a variant by prefixing the parameter name with “linear”, e.g., linear-mim-width(G) is the minimum mim-width of all branch decompositions of G that are caterpillars.

The following easily follows from the definitions.

Lemma 3.

For any graph G, we have

mim−width⁡(G)≥Omim−width⁡(G)≥omim−width⁡(G)≥sim−width⁡(G).

This chain of inequalities also holds by replacing each parameter by their linear variant. Moreover, linear−mim−width⁡(G)≥mim−width⁡(G), and similarly for each variant of the width parameter.

2.2 Unrooted Quartet Consistency

Given a set of points P, a quartet (over P) consists of two unordered pairs of distinct elements of P that do not intersect. For clarity, such a quartet q={{pi,pj},{pk,pℓ}} is instead denoted q=[pi⁢pj|pk⁢pℓ]. Slightly abusing notation, we may write p∈q when p is one of the four elements involved in q.

In a ternary tree T with leaves labeled {p1,…,pn}, consider any four leaves pi,pj,pk,pℓ. If there exists an edge e of T such that pi and pj lie on one side of T−{e}, and pk and pℓ lie on the other, we denote this relation by

pi⁢pj∣T⁢pk⁢pℓ.

In this case, we say that T satisfies the quartet q=[pi⁢pj∣pk⁢pℓ]. If Q is a set of quartets, then T satisfies Q if it satisfies each q∈Q.

Because T is ternary, given four leaves pi,pj,pk,pℓ, exactly one of the three configurations holds:

pi⁢pj∣T⁢pk⁢pℓ,pi⁢pk∣T⁢pj⁢pℓ,orpi⁢pℓ∣T⁢pj⁢pk.

The NP-hard problem used in our reductions is the Unrooted Quartet Consistency (UQC) problem, introduced by Steel [22].

Input: A set of points P={p1,p2,…,pn} and a set Q of quartets over P.
Question: Does there exist a ternary tree T with leaves labeled by the points in P that satisfies every quartet in Q?

The hardness of UQC is proved by a reduction from Betweenness, a classical problem that was shown to be NP-complete by Opatrný [17]. In that problem, the input is a set B of ordered triples whose elements are from a set of points U. One must decide whether there is a total order < on U such that, for each (a,b,c)∈B, one of a<b<c or c<b<a holds. Steel’s reduction proves a slightly stronger result than NP-hardness, which we will use.

Theorem 4 ([22]).

There is a polynomial-time reduction from Betweenness to UQC. Moreover, if an instance of Betweenness is a YES-instance, then there exists a caterpillar that satisfies the corresponding UQC instance.

By analyzing the chain of reductions used to prove Theorem 4, we can also obtain a slightly stronger result under ETH.

Theorem 5.

Assuming the ETH, the UQC problem cannot be solved in time 2o⁢(n+m), where n is the number of points of an instance and m is the number of quartets.

Proof.

The result can be deduced by simply revisiting the chain of reductions resulting in the NP-hardness of UQC. The first reduction is from 3-Set Splitting to Betweenness. In 3-Set Splitting, we receive sets S of size 3 over a universe U and must color U with two colors so that no set of S is monochromatic. This cannot be solved in time 2o⁢(|U|+|S|) under the ETH (a proof appears in [1], or more specifically in the full version on arXiv [2, Proposition 5.1], under the formulation of the Monotone NAE 3-SAT problem, which is equivalent to 3-Set Splitting).

Opatrný’s reduction from 3-Set Splitting to Betweenness [17, Lemma 2] produces from (S,U) an instance (B,UB) with |B|=2⁢|S| and |UB|=|S|+|U|+1 (each set in S becomes two betweenness triples, each element of U∪S has a corresponding elements in UB, plus an extra point is added). It follows that Betweenness cannot be solved in time 2o⁢(|B|+|UB|).

Finally, Steel’s reduction [22] from Betweenness to UQC transforms (B,UB) to an instance (Q,P) with |Q|=6⁢|B| (each betweenness triple becomes 6 quartets) and |P|=|UB|+2+4⁢|B| (the point set consists of the elements of UB and two extra points, and each betweenness constraint adds four points). Since |P|+|Q| is linear in |B|+|UB|, UQC cannot be solved in time 2o⁢(|P|+|Q|)=2o⁢(n+m). ◀

3 Sim-width, omim-width and Omim-width

We start with a single reduction showing that it is NP-hard to decide whether a given graph has sim-width, omim-width, or Omim-width equal to 1. The same holds for their linear variants. Given a UQC instance (Q,P), we define the following graph G:

  • ■

    Vertices: For each element p∈P, we introduce a vertex p in G. For each quartet q=[pi⁢pj∣pk⁢pℓ]∈Q, we introduce four additional vertices in G:

    {uiq,ujq,ukq,uℓq}.

    Let U denote the set of all such u-vertices, so that |U|=4⁢|Q|.

  • ■

    Edges: For each quartet q=[pi⁢pj∣pk⁢pℓ]∈Q, add the edges

    pi⁢uiq,uiq⁢ujq,ujq⁢pj, and ⁢pk⁢ukq,ukq⁢uℓq,uℓq⁢pℓ.

    In addition, connect every pair of vertices u,u′∈U whenever they correspond to different quartets. That is, for uiq,ujr∈U, we add the edge uiq⁢ujr whenever q≠r.

    Observe that P forms an independent set, and that each uiq∈U has only two non-neighbors in U.

Figure 2: Subgraph of G corresponding to a quartet q=[pi⁢pj∣pk⁢pℓ].

Note that |V⁢(G)|=|P|+4⁢|Q|. The fact that |V⁢(G)| is linear in |P| and |Q| will be used to obtain the ETH-based hardness part of our result. Note that we are not able to obtain the stronger lower bound under ETH of 2o⁢(|E⁢(G)|), because the number of edges in this reduction is quadratic.

The combination of Lemma 3, Theorem 5, and the following proposition will imply our first hardness result, Theorem 1.

Proposition 6.

If there is a caterpillar satisfying the UQC instance (Q,P), then linear−Omim−width⁡(G)=1. Otherwise, if (Q,P)∉UQC, then any branch decomposition T of G satisfies sim−widthG⁡(T)=2, and in particular sim−width⁡(G)=2.

We split the proof in two lemmas.

Lemma 7.

If (Q,P)∉UQC, then any branch decomposition T of G satisfies sim−widthG⁡(T)=2, and in particular sim−width⁡(G)=2.

Proof.

We start by proving that sim−width⁡(G)≤2.

This follows directly from the fact that the maximum induced matching in the full graph G has size at most 2. Suppose, for contradiction, that there exists an induced matching of size at least 3. Since the set P is an independent set in G, at least one endpoint of every edge in the matching must belong to U. By construction, each vertex in U is adjacent to all other vertices of U except two, which themselves are adjacent. Hence, among any three such vertices of U, there must exist at least one edge between them, contradicting the assumption that they form an induced matching.

We now prove that if (Q,P)∉UQC, then sim−width⁡(G)≥2.

Let (Q,P)∉UQC, and let T be a branch decomposition of G. There must exist a quartet q=[pi⁢pj∣pk⁢pℓ]∈Q not satisfied by T, otherwise (Q,P) would be in UQC. Assume without loss of generality that pi⁢pk∣T⁢pj⁢pℓ, and let e be an edge of T inducing the cut (Ae,Be) such that pi,pk∈Ae and pj,pℓ∈Be. At least one of the edges along the path pi−uiq−ujq−pj must cross this cut, and similarly, one of the edges along the path pk−ukq−uℓq−pℓ must also cross the cut. Because there is no edge with one endpoint in the first path and the other in the second path, these two edges form an induced matching in G, and therefore sim−widthG⁡(T)≥2 for every branch decomposition T. Consequently, sim−width⁡(G)≥2. ◀

Lemma 8.

If there is a caterpillar satisfying the UQC instance (Q,P), then linear−Omim−width⁡(G)=1.

Proof.

Let T be such a caterpillar, and let ≤ be a total order on P that T realizes. For each pi∈P, define

Ci={pi}∪{uiq∣q∈Q,pi∈q},

that is, Ci consists of all vertices in P∪U whose index is i. We extend ≤ to a total order ≤′ on P∪U as follows.

For all pi,pj∈P with pi<pj, and for all x∈Ci, y∈Cj, we set x<′y. Within each Ci, the relative position of pi and any uiq depends on the quartet q:

If q=[pi⁢pj∣pk⁢pℓ], then, since T satisfies q, we have either pi,pj≤pk,pℓ or pk,pℓ≤pi,pj (because the four vertices are distinct). In the former case (pi,pj≤pk,pℓ) we set pi<′uiq, in the latter case (pk,pℓ≤pi,pj) we set uiq<′pi. Note that this implies that we have either

pi<′uiq<′ukq,uℓq, or ⁢ukq,uℓq<′uiq<′pi.

We choose an arbitrary order within Ci among the u-vertices to the left of pi and among those to the right of pi. We then consider the ternary caterpillar T′ realizing ≤′. We now prove that Omim−widthG⁡(T′)=1, that is, OmimG⁡(Ae,Be)=1 for every edge e of T′.

Because T′ is a caterpillar, it suffices to consider the cuts induced by the edges of its spine. Let e be an edge of the spine, and let (Ae,Be) be the cut induced by e. Since T′ realizes the order ≤′, one side of the cut corresponds to an initial segment of ≤′. Thus, we have either for all a∈Ae and b∈Be, a<′b, or for all a∈Ae and b∈Be, b<′a.

To prove that OmimG⁡(Ae,Be)=1, we need to prove that the upper induced matching numbers of Ae and Be are both equal to one. This means that there is no matching of size 2 in G⁢[Ae,Be] that is an induced matching in the graph G−EG⁢[Ae] or in the graph G−EG⁢[Be]. Let a1⁢b1,a2⁢b2∈E⁢(G) be two edges with disjoint endpoints such that a1,a2∈Ae and b1,b2∈Be. To prove that it is not an induced matching in G−EG⁢[Ae] or G−EG⁢[Be], it suffices to show that one of the two following conditions holds:

  1. 1.

    One of the diagonals a1⁢b2 or a2⁢b1 is an edge, or

  2. 2.

    Both a1⁢a2 and b1⁢b2 are edges.

Suppose for the sake of contradiction that neither condition holds. Each vertex pi∈P is connected only to vertices of the form uiq. Consider two edges pi⁢uiq and pj⁢ujq′ with i≠j. By the construction of the order ≤′, we have either pi,uiq<′pj,ujq′ or pj,ujq′<′pi,uiq. Given that the cut can only separate pi from at most one of its neighbours in G, it is therefore impossible for the cut (Ae,Be) to contain both edges pi⁢uiq and pj⁢ujq′. Consequently, at most one vertex among {a1,a2,b1,b2} can belong to P.

Suppose that exactly one vertex among {a1,a2,b1,b2} belongs to P. Without loss of generality, assume that a1=pi. Then b1 must be of the form uiq. We are supposing that condition 1 is false and that a2⁢b1 is not an edge. Since b1∈U, the only vertices in U that are not adjacent to uiq are those corresponding to the other side of the same quartet. That is, if q=[pi⁢pj∣pk⁢pℓ], then these vertices are ukq and uℓq. By the definition of the order ≤′, we have either pi<′uiq<′ukq,uℓq, or ukq,uℓq<′uiq<′pi. Since the edge e lies on the path between a1=pi and b1=uiq in T′, the vertices ukq and uℓq cannot belong to Ae. This yields a contradiction.

Now suppose that all vertices {a1,a2,b1,b2} belong to U. Let q be the quartet associated with a1 and q′ the quartet associated with b1. As before, We are supposing that condition 1 is false, and that neither a1⁢b2 nor a2⁢b1 is an edge. The only vertices in U not adjacent to a1 correspond to the other side of the same quartet, so q must also be the quartet of b2. Similarly, q′ must be the quartet of a2.

If q=q′, then we have {a1,a2,b1,b2}={uiq,ujq,ukq,uℓq} for some q=[pi⁢pj∣pk⁢pℓ]∈Q. The only edges among these vertices are uiq⁢ujq and ukq⁢uℓq, which are both separated by e. Consequently, the quartet [uiq⁢ujq∣ukq⁢uℓq] is not satisfied by T′, which, by the definition of ≤′, implies that q is not satisfied by T, and we have a contradiction.
On the other hand, if q≠q′, then both a1⁢a2 and b1⁢b2 are edges, which contradicts the supposition that condition 2 holds. ◀

Proposition 6 follows from Lemma 7 and Lemma 8. We are now ready to prove Theorem 1.

Theorem 1. [Restated, see original statement.]

The problem of deciding whether a graph has sim-width, omim-width, or Omim-width equal to 1 is NP-complete. Moreover, assuming the ETH, it cannot be solved in time 2o⁢(n), where n is the number of vertices of the graph. The same holds for the linear variant of these three parameters.

Proof.

Let σ be one of the parameters sim−width,omim−width,Omim−width, linear−sim−width,linear−omim−width, or linear−Omim−width. We want to show that deciding whether σ⁢(G)=1 is NP-complete. Membership in NP is easy since a branch decomposition is an easily verifiable certificate.

For NP-hardness, for technical accuracy we need to use Theorem 4 and reduce Betweenness to deciding σ⁢(G)=1. Take an instance I of Betweenness and let (Q,P) be the UQC instance obtained from Theorem 4, and then obtain G as constructed above from that UQC instance. If I is a YES-instance of Betweenness, then (Q,P)∈ UQC and by Theorem 4 there is a ternary caterpillar that satisfies Q. Then, Proposition 6 implies that linear−Omim−width⁡(G)=1. This implies that σ⁢(G)=1, since linear−Omim−width⁡(G) is an upper bound on all the possible σ parameters listed above (by Lemma 3).

Conversely, if I is a NO-instance of Betweenness, then no tree satisfies the UQC instance (Q,P). By Proposition 6, sim−width⁡(G)=2, which implies σ⁢(G)≥2 since sim−width⁡(G) is a lower bound on all the possible σ parameters listed above (by Lemma 3). Therefore, I is a YES-instance of Betweenness if and only if σ⁢(G)=1.

Moreover |V⁢(G)|=|P|+4⁢|Q|, therefore an algorithm recognising graphs with σ parameter equal to one in time 2o⁢(|V⁢(G)|) could be used to solve UQC in time 2o⁢(|P|+|Q|), contradicting Theorem 5 assuming ETH. ◀

Remarks on the graph class of hard instances

Let us observe that, denoting by Ck the chordless cycle on k vertices, our construction produces a graph G that contains no induced Ck nor its complement, for any k≥5. Indeed, G has no such induced Ck because the pi vertices are simplicial and thus are not in a Ck, and the U vertices induce the complement of a set of disjoint C4s. Likewise, U induce no Ck in G¯. So a Ck would contain some pi∈P, which in the cycle would be in an induced path of the form pi−ujq−uiq of G¯, at which point there is no way to prolong the induced path and form a Ck. It follows that the hard instances are weakly chordal, a subclass of perfect graphs. Although all graphs of mim−width 1 are weakly chordal [23], this is not the case for graphs of (linear) sim-width 1. We note that for chordal graphs, i.e., graphs that are Ck-free for every k≥4, whether linear−sim−width⁡(G)=1 can be decided in polynomial time [24]. The set of forbidden induced cycles from our construction is therefore, in some sense, tight for the case linear−sim−width equal to 1.

Using a similar reduction for mim-width 1 (or linear mim-width 1)?

It is interesting to ponder the possibility of using a similar reduction for mim−width=1. It appears difficult to do so and here we provide the intuitive reasons for this. The high-level idea in our reduction is to construct a graph G that includes vertices representing the elements of the UQC instance and, for each quartet q, a gadget Hq. A reduction for mim−width=1 would have the following intended properties.

  1. 1.

    In any branch decomposition of G, if the four vertices of a quartet q do not satisfy q, then some edge of the decomposition induces a cut within Hq containing an induced matching of size 2. Thus, Hq is meant to “force” a particular shape for the subtree containing these four vertices in any branch decomposition of mim-width 1.

  2. 2.

    If the UQC instance is satisfiable, then there exists a branch decomposition of G whose mim-width is exactly 1.

The difficulty arises when we try to satisfy these conditions simultaneously. Consider two different quartets q and q′ with corresponding gadgets Hq and Hq′. In the branch decomposition guaranteed by property 2, the subtrees corresponding to these two gadgets may overlap (it seems hard to avoid this). As a consequence, an edge of Hq used in the induced matching when q is unsatisfied (property 1) may lie in the same cut as an edge of Hq′ used when q′ is unsatisfied.

To ensure mim-width 1, we must prevent these two edges from forming an induced matching. This forces us to add blocking edges between certain endpoints of edges coming from Hq and Hq′ in order to destroy the unwanted induced matchings. In our reduction, the blocking edges correspond to the edges between the u-vertices corresponding to different quartets.

However, these blocking edges create a new problem: they may themselves form an induced matching of size 2 across some cut, contradicting property 2 and preventing the existence of a mim-width 1 decomposition even when the UQC instance is satisfiable. In our reduction, this corresponds to the last case in the proof of Lemma 8: the matching of the type uxq⁢uyq′, uwq′⁢uzq for different q,q′, which is only destroyed with edges not in the cut.

In short, enforcing quartet constraints independently via the gadgets Hq inevitably causes interactions (either among the gadgets or among the blocking edges) that create new induced matchings. We found no way around this, which is why our approach does not seem extendable to mim-width 1 (or linear mim-width 1).

4 Mim-width and linear mim-width

In this section, we describe two closely related reductions. The first is used to prove the hardness of recognizing graphs with mim−width 2, and the second establishes the hardness of recognizing graphs with linear−mim−width 2.

We modify the previous reduction by adding four new vertices per quartet. Additionally, one extra vertex is introduced in the non-linear version.

Given a UQC instance (Q,P), we define the following graph G:

  • ■

    Vertices: For each element p∈P, we introduce a vertex p. For each quartet q=[pi⁢pj∣pk⁢pℓ]∈Q, we introduce eight additional vertices:

    {uiq,ujq,ukq,uℓq,γiq,γjq,γkq,γℓq}

    Let U (resp. Γ) denote the set of all such u-vertices (resp. γ-vertices).

  • ■

    Edges: For each quartet q=[pi⁢pj∣pk⁢pℓ]∈Q, add the edges

    {pi,uiq},{uiq,ujq},{ujq,pj},{pk,ukq},{ukq,uℓq},{uℓq,pℓ},

    together with

    {pi,γiq},{pj,γjq},{pk,γkq},{pℓ,γℓq}.

    Moreover, add all possible edges so that Γ forms a clique, add an edge between every pair of vertices u,u′∈U whenever they correspond to different quartets (i.e., whenever their superscript differs), and between every pair of vertices u∈U and γ∈Γ, whenever they correspond to different quartets.

The graph H is obtained from G by adding an extra vertex ω, sharing an edge with every vertex in U.

Figure 3: The gadget corresponding to a single quartet q=[pi⁢pj∣pk⁢pℓ], with the extra vertex ω of H represented.

Note, the constructed graphs G and H have mim−width at least 2, since Vatshelle argued that graphs of mim−width 1 [23, Corollary 3.7.4] have no induced cycle of length 5 or more, whereas these graphs have such cycles of the form pi−uiq−ujq−pj−γjq−γiq−pi.

Proposition 9.

If there is a caterpillar satisfying the UQC instance (Q,P), then linear−mim−width⁡(G)=2, and mim−width⁡(H)=2. Otherwise, if (Q,P)∉UQC then linear−mim−width⁡(G)≥3, and mim−width⁡(H)≥3.

The proof has the same structure as in the previous section, but require a more involved case analysis. We split it into several lemmas.

Lemma 10.

If (Q,P)∉UQC then linear−mim−width⁡(G)≥3.

Lemma 11.

If (Q,P)∉UQC then mim−width⁡(H)≥3.

The first step in the proofs of these two lemmas is similar. We begin by showing a result on any branch decomposition of G. Any branch decomposition of H can be transformed into one of G by deleting the ω-leaf. The result will therefore also apply to branch decompositions of H.

Let (Q,P)∉UQC, and let T be any branch decomposition of G. Assume by contradiction that mimG⁡(T)≤2. There must exist a quartet q=[pi⁢pj∣pk⁢pℓ]∈Q that is not satisfied by T; otherwise, (Q,P) would belong to UQC.

Without loss of generality, assume that pi⁢pk∣T⁢pj⁢pℓ is true. Let π be the set of all edges e of T inducing a cut (Ae,Be) such that pi,pk∈Ae and pj,pℓ∈Be. Note that π forms a path. Let A (resp. B) denote ⋂e∈πAe (resp. ⋂e∈πBe); that is, A (resp. B) consists of all vertices on the side of pi,pk (resp. pj,pℓ) of π.

Claim 12.

Either γiq,γjq,γkq,γℓq are all contained in A, or they are all contained in B.

Proof.

Suppose, for the sake of contradiction, that there exists an edge e of π such that one of the γ-vertices lies in Ae and another lies in Be. We will show that we can always find an induced matching of size 3 in G⁢[Ae,Be]. We proceed by a case analysis.

First, consider the case where both γiq and γkq lie in Ae. Choose x∈{j,ℓ} such that γxq is a γ-vertex in Be. Along the path pi−uiq−ujq−pj of G, at least one edge crosses the cut (Ae,Be); likewise, at least one edge of the path pk−ukq−uℓq−pℓ also crosses the cut. These two crossing edges, together with the edge γiq⁢γxq, form an induced matching in G⁢[Ae,Be]. Indeed, the only other edges that could appear among these six vertices in G are pi⁢γiq, which lies entirely within Ae, and px⁢γxq, which lies entirely within Be.

Therefore, we may assume that at least one of γiq or γkq is in Be. Without loss of generality, we may assume that γiq∈Be. By applying the symmetric argument on the pair γjq,γℓq, we may assume that one of the vertices γjq or γℓq lies in Ae.

Suppose now that ujq∈Ae. Then one of the edges on the path pk−ukq−uℓq−pℓ, together with the edges pi⁢γiq and ujq⁢pj, forms an induced matching in G⁢[Ae,Be]. Hence we may assume ujq∈Be.

Next, suppose that uiq∈Ae. Then one of the edges on the path pk−ukq−uℓq−pℓ, together with the edges pi⁢γiq and uiq⁢ujq, forms an induced matching in G⁢[Ae,Be]. Hence we may assume uiq∈Be.

If we had γjq∈Ae, then one of the edges on the path pk−ukq−uℓq−pℓ, together with the edges pi⁢uiq and γjq⁢pj, forms an induced matching in G⁢[Ae,Be]. Therefore γjq∈Be.

It follows that γℓq∈Ae, and by symmetry again, we have γkq,ukq,uℓq∈Ae as well. In this situation, the three edges uℓq⁢pℓ, pi⁢uiq, and γkq⁢γjq form an induced matching in G⁢[Ae,Be].

This establishes that either γiq,γjq,γkq,γℓq are all contained in A, or they are all contained in B. ⊲

We will assume without loss of generality that all the gammas are in B. We are now ready to finish the proof of Lemma 10.

Proof of Lemma 10.

We now assume for contradiction that T is a caterpillar satisfying linear−mim−width⁡(T)≤2, implying in particular that mim−width⁡(T)≤2. Note that Claim 12 is applicable to T since it holds for any branch decomposition. Now, one of pj or pℓ is adjacent to an endpoint of π in T (recall that π is the set of edges separating A and B). Without loss of generality, suppose it is pj, and let z be the neighbor of pj on the spine of the caterpillar. Let e be the edge incident to z that is not in π, other than z⁢pj (so, e is the next edge on the spine beyond π, going towards pℓ). This induces a cut (Ae,Be) with pℓ and all the γ-vertices in Be, and pi,pj,pk∈Ae. Consequently, the edges pi⁢γiq, pj⁢γjq, and pk⁢γkq form an induced matching in G⁢[Ae,Be]. This implies that linear−mim−width⁡(T)≥3, which contradicts our initial assumption that linear−mim−width⁡(T)≤2. ◀

The proof of Lemma 11 is slightly more complicated, because T might not be a caterpillar. Therefore, we need a case analysis depending on which vertices of B lie in the branch containing pj and which lie in the branch containing pℓ. The additional vertex ω is required to force an induced matching of size 3 in all configurations.

Proof of Lemma 11.

We assume for contradiction that T is a branch decomposition of H satisfying mim−width⁡(T)≤2. Let v be the endpoint of π that lies on the path between pj and pℓ in T (thus, one incident “side” of v contains pj, one contains pℓ, and the remaining side contains both pi and pk, see figure). Let em⁢i⁢d be the edge from v toward pi and pk, et⁢o⁢p the edge toward pj, and eb⁢o⁢t the edge toward pℓ. We denote by (Am⁢i⁢d,Bm⁢i⁢d), (Ab⁢o⁢t,Bb⁢o⁢t), and (At⁢o⁢p,Bt⁢o⁢p) the cuts induced by em⁢i⁢d, eb⁢o⁢t, et⁢o⁢p, respectively. We have Bm⁢i⁢d=B, and we partition B as B=Bb⁢o⁢t∪Bt⁢o⁢p, where Bb⁢o⁢t (resp. Bt⁢o⁢p) consists of the vertices of B in the branch toward pℓ (resp. toward pj).

The remainder of the proof accumulates a series of facts under our contradiction assumptions, ultimately showing that every possible placement of the u-vertices, the γ-vertices, and ω leads to a 3-induced matching across one of the edges em⁢i⁢d, eb⁢o⁢t, or et⁢o⁢p. Recall that we defined A=⋂e∈πAe and B=⋂e∈πBe.

Fact 1.

The γ-vertices γiq,γjq,γkq,γℓq of the quartet q all lie in A or all lie in B.

Proof.

Claim 12 still holds, because T can be turned into a branch decomposition of G by deleting the ω-leaf, which does not increase the mim-width of the decomposition. ◀

We will now assume without loss of generality that all γ-vertices of the quartet q lie in B

Fact 2.

All u-vertices uiq,ujq,ukq,uℓq of the quartet q lie in B.

Proof.

Suppose not, and assume without loss of generality that uiq∉B or ujq∉B (the cases ukq∉B or uℓq∉B are symmetric). Then one of the edges uiq⁢ujq or ujq⁢pj crosses the cut (Am⁢i⁢d,Bm⁢i⁢d) (with uiq∈Am⁢i⁢d in the first case). One of the edges of the path pk−ukq−uℓq−pℓ must also cross the cut. The vertex γiq is in B=Bm⁢i⁢d by Fact 1. These two edges, together with the edge pi⁢γiq, form an induced matching of size 3. ◀

Fact 3.

The vertex ω is in B.

Proof.

Assume for contradiction that ω∉B. Using Fact 1 and Fact 2, all the u and γ vertices are in B=Bm⁢i⁢d. In the cut (Am⁢i⁢d,Bm⁢i⁢d), the edges ω⁢ujq, pi⁢γiq, and pk⁢γkq form an induced matching of size 3. ◀

Fact 4.

Each side Bt⁢o⁢p and Bb⁢o⁢t contains at least one u-vertex.

Proof.

Note that by Fact 2, each u-vertex belongs to either Bt⁢o⁢p or Bb⁢o⁢t. If all the four u-vertices lie on the same side, say Bt⁢o⁢p, then across the cut (At⁢o⁢p,Bt⁢o⁢p) the edges pi⁢uiq, pk⁢ukq, and pℓ⁢uℓq form an induced matching of size 3. Likewise, not all four u-vertices can lie in Bb⁢o⁢t. ◀

Fact 5.

At least one of γkq,γℓq lies in Bb⁢o⁢t. Symmetrically, at least one of γiq,γjq lies in Bt⁢o⁢p.

Proof.

Using Fact 1, each γ-vertex is either in Bb⁢o⁢t or Bt⁢o⁢p. Assume γkq and γℓq are both in Bt⁢o⁢p. Then one of the edges of the path pi−uiq−ujq−pj must cross the cut (At⁢o⁢p,Bt⁢o⁢p). Together with the edges pk⁢γkq and pℓ⁢γℓq, this yields an induced matching of size 3, a contradiction. ◀

Using Fact 3, the vertex ω is either in Bb⁢o⁢t or in Bt⁢o⁢p. In the rest of the proof, we will assume without loss of generality that ω∈Bb⁢o⁢t (to see why this is without loss of generality, notice that if this is not the case, then we may swap the subscripts of pi and pk, and the subscripts of pj and pℓ without affecting the previous arguments since they all apply symmetrically to Bb⁢o⁢t and Bt⁢o⁢p).

Fact 6.

The vertices uiq and ujq are both in Bt⁢o⁢p.

Proof.

Consider uxq with x∈{i,j}. Using Fact 2, uxq is either in Bb⁢o⁢t or in Bt⁢o⁢p. Assume by contradiction that it is in Bb⁢o⁢t. We consider two subcases depending of the position of γℓq. Using Fact 1, γℓq is either in Bb⁢o⁢t or in Bt⁢o⁢p.

If γℓq is in Bt⁢o⁢p, across the cut (Ab⁢o⁢t,Bb⁢o⁢t), the following 3 edges form an induced matching:

  • ■

    px⁢uxq.

  • ■

    γℓq⁢pℓ.

  • ■

    One of the edge of the path pk−ukq−ω.

Otherwise γℓq is in Bb⁢o⁢t. Then across the cut (Ab⁢o⁢t,Bb⁢o⁢t), the following 3 edges form an induced matching:

  • ■

    px⁢uxq.

  • ■

    We take an edge joining a γ-vertex in Bt⁢o⁢p to γℓq in Bb⁢o⁢t (see Fact 5).

  • ■

    One of the edge of the path pk−ukq−ω.

◀

Fact 7.

At least one of γjq,γkq lies in Bt⁢o⁢p.

Proof.

Using Fact 1, each γ-vertex is either in Bb⁢o⁢t or Bt⁢o⁢p. Assume for contradiction that γjq and γkq are both in Bb⁢o⁢t. Across the cut (Ab⁢o⁢t,Bb⁢o⁢t), the following 3 edges form an induced matching: pj⁢γjq, pk⁢γkq, and uiq⁢ω (we know that uiq∈Bt⁢o⁢p using Fact 6). ◀

Fact 8.

The vertex ukq is in Bb⁢o⁢t.

Proof.

Using Fact 2, ukq is either in Bb⁢o⁢t or in Bt⁢o⁢p. Assume by contradiction that it is in Bt⁢o⁢p. Across the cut (At⁢o⁢p,Bt⁢o⁢p), the following 3 edges form an induced matching:

  • ■

    pi⁢uiq. We have uiq∈Bt⁢o⁢p by Fact 6.

  • ■

    uℓq⁢ukq. We are assuming that ukq∈Bt⁢o⁢p. Moreover, we know that uiq,ujq∈Bt⁢o⁢p (Fact 6), and that the u-vertices are not all in Bt⁢o⁢p (Fact 4); therefore uℓq is in Bb⁢o⁢t.

  • ■

    An edge joining a γ-vertex in Bb⁢o⁢t to either γjq or γkq in Bt⁢o⁢p. Such an edge exists using Fact 7.

◀

Fact 9.

The vertex γkq is the only gamma vertex in Bb⁢o⁢t.

Proof.

Assume by contradiction that there is a γ-vertex other than γkq in Bb⁢o⁢t. Across the cut (Ab⁢o⁢t,Bb⁢o⁢t), the following 3 edges form an induce matching:

  • ■

    pk⁢ukq. We know that ukq is in Bb⁢o⁢t by Fact 8.

  • ■

    uiq⁢ω. We know that uiq is in Bt⁢o⁢p by Fact 6.

  • ■

    An edge joining either γiq or γjq in Bt⁢o⁢p (Fact 5) to a γ-vertex in Bb⁢o⁢t that is not γkq.

◀

We can finally conclude the proof. By combining Fact 1 and Fact 9, we know that γiq and γℓq are both in Bt⁢o⁢p. Across the cut (At⁢o⁢p,Bt⁢o⁢p), the following 3 edges form an induced matching: pi⁢γiq, pℓ⁢γℓq, and ω⁢ujq (since ujq is in Bt⁢o⁢p by Fact 6). This completes the proof: in all cases we obtain an induced matching of size 3. ◀

Lemma 13.

If there is a caterpillar satisfying the UQC instance (Q,P), then linear−mim−width⁡(G)=2.

Proof.

As we already observed, mim−width⁡(G)≥2 because it contains induced cycles of length 6, implying linear−mim−width⁡(G)≥2. We focus on the upper bound.

Let T be a caterpillar satisfying (Q,P), and let ≤ be a total order on P that T realizes. For each pi∈P, define

Ci={pi}∪{uiq∣q∈Q,pi∈q}∪{γiq∣q∈Q,pi∈q},

that is, Ci consists of all vertices in P∪U∪Γ whose index is i. We extend ≤ to a total order ≤′ on P∪U∪Γ as follows: for all pi,pj∈P with pi<pj, and for all x∈Ci, y∈Cj, we set x<′y; within each Ci, the order is arbitrary. Let T′ be the ternary caterpillar realizing ≤′. We prove that mim−widthG⁡(T′)≤2, i.e., mimG⁡(Ae,Be)≤2 for every edge e of T′.

Because T′ is a caterpillar, it suffices to consider the cuts induced by the edges of its spine. Let e be an edge of the spine, and let (Ae,Be) be the cut induced by e. Since T′ realizes ≤′, one side of the cut is an initial segment of ≤′. Thus, either for all a∈Ae and b∈Be we have a<′b, or for all a∈Ae and b∈Be we have b<′a.

Let a1⁢b1,a2⁢b2,a3⁢b3∈E⁢(G) be three edges with pairwise disjoint endpoints such that a1,a2,a3∈Ae and b1,b2,b3∈Be. Suppose, for contradiction, that these three edges form an induced matching in G⁢[Ae,Be].

First, note that at most one of the six vertices lies in P. Indeed, a vertex pi∈P is adjacent only to vertices of Ci. If pi were among the six vertices, then e would separate pi from another element of Ci; by the construction of ≤′, this can happen for at most one index i.

We say that a vertex v of G is of type q for a quartet q if v is one of the eight vertices in U∪Γ corresponding to q (i.e., the type is the superscript q). Suppose a1⁢b1 is an edge with a1 of type q and b1 of type q′≠q. In our construction, the only vertices not adjacent to a1 are in P or of type q; hence b2 and b3 must each lie in P or be of type q. Symmetrically, the only vertices not adjacent to b1 are those in P or of type q′, so a2 and a3 must each lie in P or be of type q′. If, without loss of generality, a3 is the only possible vertex possibly in P, then a2 is of type q′ and b3 is of type q, which forces a2⁢b3∈E⁢(G), contradicting that the three edges form an induced matching.

Therefore, at most one of the six vertices in the induced matching is in P and the remaining vertices in U∪Γ all have the same type q=[pi⁢pj∣pk⁢pℓ]. The three matching edges must then be of the following kinds: γ–γ, u–u, p–u, or p–γ.

We cannot have two γ–γ edges, since Γ is a clique and there would be an extra edge between the γ-endpoints, violating the induced property.

Assume there are two u–u edges. The only possibilities are uiq⁢ujq and ukq⁢uℓq. Without loss of generality, let uiq,ukq∈Ae and ujq,uℓq∈Be. By the definition of ≤′, this implies uiq,ukq<′ujq,uℓq, hence pi,pk<pj,pℓ in ≤, which contradicts that T satisfies the quartet q.

Since at most one of the six vertices lies in P, it follows that exactly one matching edge is of type u–u (say a1⁢b1), exactly one is of type γ–γ (say a2⁢b2), and the remaining one (say a3⁢b3) is either p–u or p–γ.

Without loss of generality, let a3=pi∈P. If b3=γiq, then b3 is adjacent to a2 (both are γ-vertices), so the matching is not induced. Otherwise, if b3=uiq, then a1⁢b1 must be ukq⁢uℓq. Since e separates pi from uiq, the cut lies inside Ci; together with ukq⁢uℓq crossing the cut, this forces pi to lie between pk and pℓ in the order ≤, contradicting that T satisfies the quartet q. This contradiction shows that no induced matching of size 3 can appear in G⁢[Ae,Be], and hence mimG⁡(Ae,Be)≤2 for every spine edge e of T′. Therefore, mim−widthG⁡(T′)≤2 and linear−mim−width⁡(G)≤2. ◀

Lemma 14.

If there is a caterpillar satisfying the UQC instance (Q,P), then mim−width⁡(H)=2.

Figure 4: Expansion of pi in T into the subtree corresponding to Ci in T′.
Proof.

Again, mim−width⁡(H)≥2 follows from the existence of induced cycles of length 6 and we show that mim−width⁡(H)≤2.

Let T be a caterpillar satisfying (Q,P). For each pi∈P, define

Ci={pi}∪{uiq∣q∈Q,pi∈q}∪{γiq∣q∈Q,pi∈q},

that is, Ci consists of all vertices in P∪U∪Γ whose index is i.

We define a new tree T′ from T by adding the leaf ω anywhere on the caterpillar. For each i, replace the leaf pi by a rooted subtree whose leaves are exactly the vertices of Ci. The leaf pi is attached directly to the root of this subtree, and all the other leaves lie on the other branch (see Figure 4).

We prove that mim−widthH⁡(T′)≤2, i.e., mimH⁡(Ae,Be)≤2 for every edge e of T′. Fix any edge e of T′.

Let a1⁢b1,a2⁢b2,a3⁢b3∈E⁢(H) be three edges with pairwise disjoint endpoints such that a1,a2,a3∈Ae and b1,b2,b3∈Be. Suppose, for contradiction, that these three edges form an induced matching in H⁢[Ae,Be].

First note that none of the six endpoints lies in P. Indeed, each pi∈P is adjacent exactly to the vertices of Ci, and by the placement of pi in T′, any cut (Ae,Be) with pi∈Ae that separates pi from some vertex of Ci must be of one of two forms. Either Ae={pi}, then there is no matching of size 3; or Be⊆Ci because e is in the subtree containing Ci∖{pi}, then, since pi is adjacent to every vertex of Ci, the matching would not be induced.

As in the previous proof, we say that a vertex v of H is of type q for a quartet q if v is one of the eight vertices in U∪Γ corresponding to q. Suppose a1⁢b1 is an edge with a1 of type q and b1 of type q′≠q. In our construction of H, the only vertices nonadjacent to a1 are those in P, those of type q, and possibly ω. Since no endpoint is in P, it follows that b2 and b3 must be of type q or be ω; symmetrically, a2 and a3 must be of type q′ or be ω. If, without loss of generality, a3 is the only vertex that might be ω, then a2 is of type q′ and b3 is of type q, which forces a2⁢b3∈E⁢(H), contradicting that the three edges form an induced matching.

Hence all of the endpoints of the matching that are in U∪Γ belong to a common type (say q). Moreover, at most one of these endpoints is ω. Thus the three matching edges must be among the following kinds: γ–γ, u–u, or ω–u.

We cannot have two γ–γ edges, since Γ is a clique, which would create an extra edge between γ-endpoints and violate the induced property.

Assume there are two u–u edges. The only possibilities are uiq⁢ujq and ukq⁢uℓq. Without loss of generality, let uiq,ukq∈Ae and ujq,uℓq∈Be. This implies that in T′, the uiq−ujq path intersects the ukq−uℓq path (in particular, they intersect at the ends of e). By our construction of T′ from T, this in turn implies that in T′, the pi−pj path intersects the pk−pℓ path, and thus T′ does not satisfy q. Since our transformation from T′ to T does not alter its quartets but only adds new ones, this contradicts that T satisfies q.

Moreover, we cannot have simultaneously a u–u edge and an ω–u edge, because ω is adjacent to all u-vertices, creating a forbidden cross-edge and destroying the induced property. Since there is at most one ω–u edge, any third edge would have to be either u–u or γ–γ, both of which have been ruled out. Therefore no induced matching of size 3 can exist, a contradiction.

This proves that mimH⁡(Ae,Be)≤2 for every edge e of T′, and hence mim−widthH⁡(T′) ≤2. ◀

Theorem 2. [Restated, see original statement.]

The problem of deciding whether a graph has mim-width or linear mim-width at most 2 is NP-complete. Moreover, assuming the ETH, it cannot be solved in time 2o⁢(n), where n is the number of vertices of the graph.

Proof.

We proceed as in Theorem 1. Take an instance I of Betweenness and let (Q,P) be the UQC instance obtained from Theorem 4. Then let G and H be obtained from (Q,P) as described above. If I is a YES-instance, then (Q,P)∈UQC and by Theorem 4 some ternary caterpillar satisfies Q. Then by Proposition 9 we have linear−mim−width⁡(G)=2 and mim−width⁡(H)=2. If I is a NO-instance, then (Q,P)∉UQC and by Proposition 9 we have linear−mim−width⁡(G)≥3 and mim−width⁡(H)≥3. Thus I is a YES-instance of Betweenness if and only if linear−mim−width⁡(G)≤2, and if and only if mim−width⁡(H)≤2, which proves the NP-hardness of our two problems (and membership in NP is easy).

As for the ETH lower bound, we observe that |V⁢(G)|=|P|+8⁢|Q| and |V⁢(H)|=|P|+8⁢|Q|+1. Since |V⁢(G)| and |V⁢(H)| are linear in |P|+|Q|, Theorem 5 implies that no time 2o⁢(n) algorithm can recognize mim−width 2 and linear−mim−width 2 graphs under the ETH. ◀

5 Open problems

Many questions remain open. The most important one is whether graphs of mim-width 1 and graphs of linear mim-width 1 can be recognized in polynomial time.

Our result also does not imply that deciding whether (linear) mim−width⁡(G)≤c is NP-hard for every fixed constant c>2. One possible direction is to address the following question: Is there a graph operation that transforms any graph G into a graph G′ satisfying mim−width⁡(G′)=mim−width⁡(G)+1? Alternatively, is there a graph operation that multiplies the mim-width of any graph by a constant factor? The same question remains open for other width parameters as well.

Another question is whether UQC can be used to prove hardness of other graph-to-tree representations?

Finally, can one obtain inapproximability results, for instance via a reduction that yields an arbitrarily large approximation gap?

References

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