Abstract 1 Introduction 2 Preliminaries 3 Hardness of Induced 2-Disjoint Paths in string graphs 4 Hardness of detecting a subcubic graph as an induced subdivision References

Induced Disjoint Paths Without an Induced Minor

Pierre Aboulker ORCID DIENS, École normale supérieure, CNRS, PSL University, Paris, France Édouard Bonnet ORCID CNRS, ENS de Lyon, Université Claude Bernard Lyon 1, LIP UMR 5668, Lyon, France Timothé Picavet ORCID LaBRI, Université de Bordeaux, France Nicolas Trotignon ORCID CNRS, ENS de Lyon, Université Claude Bernard Lyon 1, LIP UMR 5668, Lyon, France
Abstract

We exhibit a new obstacle to the nascent algorithmic theory for classes excluding an induced minor. We indeed show that on the class of string graphs – which avoids the 1-subdivision of, say, K5 as an induced minor – Induced 2-Disjoint Paths is NP-complete. So, while k-Disjoint Paths, for a fixed k, is polynomial-time solvable in general graphs, the absence of a graph as an induced minor does not make its induced variant tractable, even for k=2. This answers a question of Korhonen and Lokshtanov [SODA ’24], and complements a polynomial-time algorithm for Induced k-Disjoint Paths in classes of bounded genus by Kobayashi and Kawarabayashi [SODA ’09]. In addition to being string graphs, our produced hard instances are subgraphs of a constant power of bounded-degree planar graphs, hence have bounded twin-width and bounded maximum degree.

We also leverage our new result to show that there is a fixed subcubic graph H such that deciding if an input graph contains H as an induced subdivision is NP-complete. Until now, all the graphs H for which such a statement was known had a vertex of degree at least 4. This answers a question by Chudnovsky, Seymour, and Trotignon [JCTB ’13], and by Le [JGT ’19]. Finally we resolve another question of Korhonen and Lokshtanov by exhibiting a subcubic graph H without two adjacent degree-3 vertices and such that deciding if an input n-vertex graph contains H as an induced minor is NP-complete, and unless the Exponential-Time Hypothesis fails, requires time 2Ω(n). This complements an algorithm running in subexponential time 2O~(n2/3) by these authors [SODA ’24] under the same technical condition.

Keywords and phrases:
Induced Disjoint Paths, string graphs, induced subdivisions, induced minors
Category:
Track A: Algorithms, Complexity and Games
Copyright and License:
[Uncaptioned image] © Pierre Aboulker, Édouard Bonnet, Timothé Picavet, and Nicolas Trotignon; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Theory of computation Problems, reductions and completeness
; Mathematics of computing Graph theory
Related Version:
Full Version: https://arxiv.org/abs/2502.05289
Acknowledgements:
We thank Théo Pierron and Jean-Florent Raymond with whom this project started. We also thank Tuukka Korhonen, Daniel Lokshtanov, and Martin Milanič for some discussions, and in particular for asking about the flow problem (as opposed to the linkage one).
Funding:
ÉB and NT were supported by the ANR projects TWIN-WIDTH (ANR-21-CE48-0014-01) and DIGRAPHS (ANR-19-CE48-0013-01).
Editors:
Keren Censor-Hillel, Fabrizio Grandoni, Joël Ouaknine, and Gabriele Puppis

1 Introduction

In k-Disjoint Paths, one is given a graph G, together with k pairs of vertices, often called terminals, (s1,t1),,(sk,tk), and has to decide if G admits k vertex-disjoint paths P1,,Pk such that for every i{1,,k}, the endpoints of Pi are si and ti. This problem is also called k-Linkage as the pairs to connect are prescribed. In the “flow variant” of this problem, Disjoint ST Paths, the input consists of a graph G and two disjoint vertex subsets S,TV(G) with |S|=|T|, and the question is whether there are |S| vertex-disjoint paths, each with one endpoint in S and the other endpoint in T. These problems are polynomial-time solvable in general graphs, respectively by the work of Robertson and Seymour [27] (for k-Disjoint Paths), and simply by Menger’s theorem [24] (for Disjoint ST Paths).

In this paper, we are interested in their induced variants Induced k-Disjoint Paths and Induced Disjoint ST Paths, where the paths are further requested to be mutually induced (i.e., no edge of the graph is incident to two of these paths). These problems are NP-complete for k=2 and for |S|=|T|=2, respectively, in general graphs [8, 1]. Note that Induced Disjoint ST Paths with |S|=|T|=k can be solved with k! calls to Induced k-Disjoint Paths. So when k is constant, the former problem admits a polynomial-time Turing reduction to the latter, and thus cannot be harder.

Kawarabayashi and Kobayashi give a linear-time algorithm for Induced k-Disjoint Paths (for any fixed k) in planar graphs [18], and a polynomial-time algorithm in classes of bounded genus [19]. The latter result is lifted to the model checking of the FO+SDP logic (i.e., first-order with scattered disjoint paths predicates, which can natively express the existence of a constant number of induced disjoint paths between some specified pairs of terminals) in fixed-parameter tractable (FPT) time in classes of bounded genus [13]. It is believed that the tractability of Induced k-Disjoint Paths (and perhaps even of FO+SDP model checking) holds more generally in classes excluding a fixed minor, and could be shown by combining the irrelevant-vertex techniques (developed for the planar and bounded-genus cases) with the graph structure theorem of Robertson and Seymour [28]. However, to our knowledge, this has not been proven yet (provided it indeed holds).

Induced k-Disjoint Paths is polynomial-time solvable on classes of bounded mim-width on which mim-width can be efficiently approximated [17], which includes for instance interval graphs and permutation graphs. In claw-free graphs (i.e., graphs excluding K1,3 as an induced subgraph), Induced k-Disjoint Paths is solvable in polynomial time for any fixed k [10], and even in FPT time in parameter k [11]. In graphs without asteroidal triple, this problem is polynomial-time solvable even if k is part of the input [12]. Finally, in (theta, wheel)-free graphs, there is a polynomial-time algorithm for Induced k-Disjoint Paths [26], while its complexity in theta-free graphs is open.

To understand better the tractability frontier of Induced k-Disjoint Paths, Korhonen and Lokshtanov [20] ask if this problem is NP-hard in H-induced-minor-free graphs for some fixed k and H. We resolve this question already in the case when k=2 and H is the 1-subdivision of K5 (or of K3,3). Indeed string graphs (i.e., intersection graphs of curves in the plane) exclude the 1-subdivision of any non-planar graph as an induced minor.

Theorem 1.

Induced 2-Disjoint Paths is NP-complete in string graphs that are subgraphs of a constant power of bounded-degree planar graphs.

We actually show the stronger result that Induced Disjoint ST Paths with |S|=|T|=2 is NP-complete in this subclass of string graphs. Note that subgraphs of constant powers of bounded-degree planar graphs both have bounded twin-width [3, 2] and bounded maximum degree. Thus Theorem 1 considerably limits the scope within which the existing polynomial algorithms could be extended.

The Exponential-Time Hypothesis (ETH for short), a stronger assumption than P NP but still widely believed, asserts that there is a real λ>1 such that n-variable 3-SAT cannot be solved in time O(λn) [15]. More quantitatively, the proof of Theorem 1, by providing a linear reduction from a variant of Planar 3-SAT (see [23]), implies the following.

Theorem 2.

Induced Disjoint ST Paths with |S|=|T|=2 is NP-complete in string graphs of bounded maximum degree and twin-width, and requires time 2Ω(n) on n-vertex such graphs, unless the Exponential-Time Hypothesis fails.

Our result has some consequences for the detection of induced subdivisions, which we now turn our attention to.

Detecting induced subdivisions and induced minors

Let H-Induced Subdivision Containment (H-ISC for short) input a graph G and ask whether H is an induced subdivision of G. This problem has attracted some attention. Chudnovsky and Seymour introduced the Three-In-A-Tree problem – whether there is an induced subtree containing three given vertices – and showed how to solve it in polynomial time via the so-called extended strip decompositions, in order to obtain a polynomial algorithm for K2,3-ISC [4]. The first graphs H for which H-ISC is NP-complete came from [22] where several examples are given: notably the complete graph K5 and some trees, among other graphs. In the same paper, some other examples of tractable H-ISC were given, all relying on the polynomial-time algorithm for Three-In-A-Tree. There are also some ad hoc algorithms for H-ISC when H is the net (i.e., the graph obtained by adding a pendant neighbor to each vertex of a triangle) [5], when H is K4 [21], or when H is the disjoint union of a fixed number of triangles [25].

Despite this line of work, no subcubic graph H was known to make H-ISC NP-hard. Actually, Chudnovsky, Seymour, and Trotignon [5] and Le [21] asked whether there is a polynomial-time algorithm for H-ISC for any subcubic graph H. As a consequence of Theorem 1, we answer this question by the negative by exhibiting a subcubic graph H (the graph of Figure 1) for which H-ISC is NP-hard.

Figure 1: The subcubic graph H. Both H[A1] and H[A2] are the 1-subdivision of K3,3. Both H[A3] and H[A4] are obtained from K3,3 by subdividing every edge once but one edge that is subdivided twice. The vertices of H which are not in i[4]Ai are labeled s,t,s,t. In total H has 66 vertices.
Theorem 3.

H-Induced Subdivision Containment is NP-complete for the subcubic graph H of Figure 1, and requires time 2Ω(n) on n-vertex graphs, unless the ETH fails.

Theorem 3 holds within subgraphs of a constant power of bounded-degree planar graphs that are string graphs plus a constant number of (bounded-degree) apices, which are graphs of bounded twin-width [3, 2] excluding a fixed induced minor. In other words, Theorem 3 holds in the graphs for which Theorem 1 holds augmented by a constant number of vertices of bounded degree.

Theorem 1 also has consequences for the detection of induced minors, topic that we now briefly survey. Let H-Induced Minor Containment (H-IMC for short) input a graph G and ask whether H is an induced minor of G. It was first shown by Fellows et al. [9] that H-IMC can be NP-hard for a fixed graph H (unlike the minor containment). The latter graph H was not planar, which prompted the authors to ask if there is a planar graph H for which H-IMC is NP-hard, and whether H-IMC is always polynomial-time solvable when H is a tree. Recently, Korhonen and Lokshtanov [20] answered both questions by showing that H-IMC is NP-hard for some fixed tree H (whose number of vertices is not explicit, and estimated to be larger than 2300 in [7]). Dallard et al. [6] show that K2,3-IMC can be solved in polynomial time. Finding the disjoint union of a constant number of triangles as an induced minor or as an induced subdivision is all the same, so for any natural t, tK3-IMC is also in P [25]. For a more complete survey on the complexity of H-IMC, we refer the reader to the introduction of [7]; the paper provides some polynomial-time algorithms for three infinite families of graphs H, and notes that H-IMC is in P for every graph H on at most 5 vertices, except for three remaining open cases.

As a similar consequence to Theorem 2, we show a 2Ω(n) lower bound for H-IMC on n-vertex graphs, under the ETH. This can be put in perspective with a 2O~(n2/3)-time algorithm for H-IMC when every edge of H is incident to a vertex of degree at most 2 [20]. The authors ask if the mere NP-hardness of H-IMC can be shown for some graph H with this property. Actually by subdividing eight edges in the graph of Figure 1, we obtain a graph H satisfying the property, and for which we can show the same lower bound.

Theorem 4.

There is a subcubic graph H such that every edge of H is incident to a vertex of degree 2, and H-Induced Minor Containment is NP-complete, and requires time 2Ω(n) on n-vertex graphs, unless the ETH fails.

We observe that it is not too difficult to show Theorems 3 and 4 with connected graphs H and H (having the extra properties of their respective statement). As this complicates a bit their proofs without being a significantly stronger result, we opted against doing it explicitly.

Open questions

We suggest the following open questions, which come more or less directly from our work and the literature. In light of the surveyed polynomial algorithms applying more generally to Induced k-Disjoint Paths and the hardness proofs applying more generally to Induced Disjoint ST Paths with |S|=|T|=k, we wonder if there is a hereditary graph class in which Induced k-Disjoint Paths is NP-complete but Induced Disjoint ST Paths with |S|=|T|=k is polynomial-time solvable; the case k=2 is of particular interest.

The string graphs that our proof of Theorem 1 produces do not seem to be 1-string graphs (i.e., realizable with strings every pair of which intersects at most once). We leave open the complexity of Induced k-Disjoint Paths in 1-string graphs, and also in segment intersection graphs (a further restriction to 1-string graphs).

A natural conjecture stems from our paper and existing algorithms, under P NP.

Conjecture 5.

For any subcubic graph H, H-ISC is in P if and only if H is planar.

2 Preliminaries

If i is a positive integer, we denote by [i] the set of integers {1,2,,i}.

2.1 Subgraphs, induced subgraphs, neighborhoods, and some graphs

We denote by V(G) and E(G) the set of vertices and edges of a graph G, respectively. A graph H is a subgraph of a graph G if H can be obtained from G by vertex and edge deletions. Graph H is an induced subgraph of G if H is obtained from G by vertex deletions only. A graph G is H-free if G does not contain H as an induced subgraph. For SV(G), the subgraph of G induced by S, denoted G[S], is obtained by removing from G all the vertices that are not in S (together with their incident edges). Then GS is a short-hand for G[V(G)S]. A collection of paths P1,,Ph in a graph G is said mutually induced if G[i[h]V(Pi)] is exactly the disjoint union of paths P1,,Ph.

A set XV(G) is connected (in G) if G[X] has a single connected component. A vertex whose removal increases the number of connected components is called a cutvertex. Similarly, a bridge is an edge whose removal increases the number of connected components. We denote by Gr the r-th power of G, that is, the graph with vertex set V(G) and an edge between any two vertices at (shortest-path) distance at most r in G. A constant power of G is Gr for some constant r.

subdivision of a graph G is any graph obtained from G by replacing each edge of G by a path of at least one edge. In a subdivision of G the vertices of G are called branching vertices, and the created vertices are called subdivision vertices. The s-subdivision of G is the graph obtained from G by replacing each edge of G by a path of s+1 edges.

We denote by NG(v) and NG[v], the open, respectively closed, neighborhood of v in G. For SV(G), we set NG(S):=(vSNG(v))S and NG[S]:=NG(S)S. The degree dG(v) of a vertex vV(G) is the cardinality of NG(v), and the maximum degree of G is defined as maxvV(G)dG(v). A subcubic graph is a graph of maximum degree at most 3.

The t-clique, denoted by Kt, is obtained by making adjacent every pair of two distinct vertices among t vertices, and the biclique Kt,t with bipartition (A,B) such that |A|=|B|=t is obtained by making every vertex of A adjacent to every vertex of B. A theta is any subdivision of K2,3. A wheel is any graph obtained by adding to a cycle of length at least 4, a vertex with at least three neighbors on the cycle.

string graph is the intersection graph of some collection of (non-self-intersecting) curves in the plane (usually called strings), or equivalently the intersection graph of a collection of connected sets of some planar graph. The collection of strings is called string representation. We may see the string representation as a planar diagram with one vertex at each string endpoint and at each intersection of two strings. For instance, any string representation defines an infinite face (the infinite face of this planar diagram).

It is known (and easy to see) that the 1-subdivision of any non-planar graph is not a string graph [29].

2.2 Induced subdivisions and induced minors

A graph H is an induced subdivision of a graph G if a subdivision of H is isomorphic to an induced subgraph of G. An induced subdivision model of H in G is given by an injective map ϕ:V(H)V(G) and a collection of paths (Pe)eE(H) in G such that for every uvE(H), Puv is a ϕ(u)ϕ(v) path, and G[eE(H)V(Pe)] has no more edges than the paths (Pe)eE(H) themselves.

An induced minor model of H in G is a collection :={X1,,X|V(H)|} of pairwise-disjoint connected subsets of V(G), called branch sets, together with a bijective map ϕ:V(H) such that uvE(H) if and only if there is at least one edge in G between ϕ(u) and ϕ(v). In which case, we may say that the branch sets ϕ(u) and ϕ(v) are adjacent. We then say that H is an induced minor of G (or otherwise that G is H-induced-minor-free). Or equivalently, H can be obtained from G after a series of vertex deletions and edge contractions.

An induced minor model ({X1,,Xh},ϕ) of an h-vertex graph H is minimal if for every X1X1,,XhXh, the fact that ({X1,,Xh},ϕ) is an induced minor model of H with ϕ(u)=Xiϕ(u)=Xi for every uV(H), implies that for every i[h], Xi=Xi.

With the second given definition of string graphs (see end of Section 2.1), it is easy to see that the class of string graphs is closed under taking induced minors. Thus no string graph admits the 1-subdivision of a non-planar graph as an induced minor.

2.3 Useful facts on twin-width

As we only mention twin-width in side remarks, we refrain from giving a definition. We list the theorems useful in Section 3. This can be read in a black-box fashion.

It was first proven in [3] that the class of planar graphs has bounded twin-width. The current best upper bound is 8 [14].

Theorem 6 (Theorem 6.3 in [3], [14]).

Planar graphs have bounded twin-width, more precisely upper bounded by 8.

The constant powers of bounded twin-width graphs have bounded twin-width, as a special case of so-called first-order transductions.

Theorem 7 (Theorem 8.1 in [3]).

There is a function f such that for any graph G of twin-width d and for any positive integer r, Gr has twin-width at most f(d,r).

Among weakly sparse classes (excluding a Kt,t as a subgraph), the subgraph closure of any class of bounded twin-width has bounded twin-width.

Theorem 8 ([2]).

There is a function g such that for any graph G of twin-width d excluding Kt,t as a subgraph (or in particular, of maximum degree at most t1), then any subgraph of G has twin-width at most g(d,t).

3 Hardness of Induced 2-Disjoint Paths in string graphs

In this section, we show that Induced 2-Disjoint Paths is NP-complete in (a proper subclass of) string graphs.

See 1

Proof.

We reduce from the NP-complete problem Clause-Linked Planar E3-Occ 3-SAT, with variables x1,,xn and clauses c1,,cm where every clause cj is on two or three variables, each variable appears in exactly three clauses, and the variable-clause incidence graph is planar even when the cycle c1c2cmc1 is added. This problem has been proven NP-complete by Fellows et al. [9], even in a restricted form with some additional constraint on the clauses, but we will not need this restriction. To get a unique representation of the variable gadget, we assume that every variable has exactly three occurrences: two positive and one negative, or two negative and one positive. Indeed variables appearing only positively (or only negatively) can be set to true (or to false). We refer the reader to [30] for the complexity of variants of Planar 3-SAT.

We present the variable gadgets, clause gadgets, and variable-clause incidences, which assembled together form the graph G input to Induced 2-Disjoint Paths. The reader can also refer to Figure 2 where these three elements are depicted.

Variable gadget.

For each variable xi, we now describe the variable gadget 𝒢(xi). For each clause cj containing xi, we add to 𝒢(xi) two vertices wjN(xi),wjS(xi) if xi appears positively in cj, and we add two vertices wjN(¬xi),wjS(¬xi) if, instead, xi appears negatively in cj. We finally turn 𝒢(xi) into an induced biclique by adding every edge between pairs of vertices wjd(xi),wjd(¬xi) for d,d{N,S} and j,j may be equal or distinct. Observe that every variable gadget is isomorphic to the bipartite complete graph K2,4.

Clause gadget.

We describe the clause gadget 𝒢(cj) for each clause cj. Let 1,2,3 be the three literals of cj (or 1,2 if cj is a 2-clause). The gadget 𝒢(cj) has 16 vertices (or 12 if cj is a 2-clause): four entry points ujN,ujS,uj+1N,uj+1S, and four vertices vjNW(a),vjNE(a),vjSW(a),vjSE(a) for each a{1,2,3} (for each a{1,2}). We add an edge between a pair of vertices vjd(a), vjd(a), with d,d{NW,NE,SW,SE}, whenever aa. Thus those 12 vertices (8 vertices) form a tripartite complete graph K4,4,4 (bipartite complete graph K4,4). For every d{N,S} and a{1,2,3} (a{1,2}), we also add the six (four) edges ujdvjdW(a), and the six (four) edges vjdE(a)uj+1d. This finishes the description of 𝒢(cj). Note that 𝒢(cj) and 𝒢(cj+1) share two vertices: uj+1N and uj+1S.

Variable-clause incidence.

Finally for every clause cj and literal in cj, and each d{N,S}, we add the edges vjdW()wjd() and wjdE()vjd().

The graph G, input of Induced 2-Disjoint Paths, is obtained by having a gadget for each variable and each clause, and adding the edges as described in the previous sentence. We set the first terminal pair to u1N,um+1N and the second terminal pair to u1S,um+1S. This finishes the construction; see Figure 2.

Figure 2: The clause gadget 𝒢(cj) with cj=xj1¬xj2xj3, variables xj1,xj2 in one face defined by cycle c1c2cmc1 (above), and xj3 in the other face (below). We also drew the variable gadget 𝒢(xj1) when xj1 appears positively in cj and cj, and negatively in cj′′. Edges linking two rounded boxes represent bicliques.

The next two lemmas show the correctness of the reduction.

Claim 9.

If c1cm is satisfiable, then G admits two u1Num+1N and u1Sum+1S mutually induced paths.

Proof.

We fix a truth assignment 1,,n of the variables satisfying c1cm, with i{xi,¬xi} for every i[n]. For each clause cj, we choose any literal (cj) of cj such that (cj)=i for some i[n]. For each d{N,S}, we build the path Pd:

u1d,v1dW((c1)),w1d((c1)),v1dE((c1)),u2d,v2dW((c2)),w2d((c2)),v2dE((c2)),,
umd,vmdW((cm)),wmd((cm)),vmdE((cm)),um+1d.

Note that PN is a u1Num+1N path in G, PS is a u1Sum+1S path, and PN,PS are vertex-disjoint. We claim there is no chord between PN and PS. This is essentially because

  • within every 𝒢(cj), V(PN) and V(PS) induce a 4K2 comprising four edges of PNPS,

  • apart from edges incident to entry points, there is no edge between two clause gadgets,

  • PN and PS enter each variable gadget on the same side of the induced biclique,

which concludes the proof of the claim.

Claim 10.

If G admits two u1Num+1N and u1Sum+1S mutually induced paths, then c1cm is satisfiable.

Proof.

Let PN,PS be two mutually induced paths in G such that Pd is a u1dum+1d path for each d{N,S}. We think of Pd as going from u1d, its start, to um+1d, its end. We first show the following invariant. For every j[m], there exists a literal of cj such that for each d{N,S}, the path Pd goes from ujd to uj+1d via the 4-edge subpath ujd,vjdW(),wjd(),vjdE(),uj+1d.

Fix some j[m], and assume that the invariant holds for every j[j1] (with [0]=). The vertex following ujN along PN cannot be in 𝒢(cj1) as either j=1 (and this gadget does not exist) or it would create a chord between PN and PS, by the induction hypothesis. Thus it has to be vjNW() for some literal of cj. To avoid a chord between PN and PS, the vertex following ujS along PS has to be vjSW(). Then the next vertex along PN (resp. PS) has to be wjN() (resp. wjS()). As the variable gadget of literal  is an induced biclique, the next vertices have to be back to the clause gadget 𝒢(cj): vjNE() along PN, and vjSE() along PS. Finally the next vertices have to be uj+1N along PN, and uj+1S along PS. This completes the proof that the invariant holds for every j[m].

Let 𝒜 be the truth assignment setting xi to true if PN (resp. PS) does not contain any vertex wjN(¬xi) (resp. wjS(¬xi)), and to false otherwise. As PN,PS are mutually induced, in the latter case PN (resp. PS) does not contain any vertex wjN(xi) (resp. wjS(xi)). Thus, for every clause cj, the vertex vjNW()PN is such that literal is satisfied by 𝒜. Hence 𝒜 is a satisfying assignment.

Observe that the invariant in the first paragraph of the proof of Claim 10 still holds under the weaker assumption that the endpoints of PN,PS are in {um+1N,um+1S} (but are unspecified). Therefore finding two mutually induced paths between {u1N,u1S} and {um+1N,um+1S} in G (the induced flow problem) is equivalent to the induced linkage problem.

We now show that G is as advertised by the theorem statement. We start by giving a string representation for G.

Claim 11.

G is a string graph.

Proof.

First, we draw a planar embedding 𝒫 of the variable-clause incidence graph augmented with the cycle c1c2cmc1. We refer to one face delimited by this cycle as the upper face (drawn in the figures “above” the path c1c2cm), and the other face as the lower face. Second, for every clause cj, draw 𝒢(cj), and the six (or four, if cj is a 2-clause) vertices in variable gadgets that are adjacent to 𝒢(cj), as the intersection graph of strings such that

  • the strings of ujN,ujS,uj+1N,uj+1S protrude in the infinite face,111In all these items, the faces are those of the planar diagram of the string representation of 𝒢(cj), except the upper and lower faces, which are defined above.

  • as well as wjN() (resp. wjS()) if is a literal of cj whose variable is drawn in the upper face (resp. lower face) in 𝒫,

  • these strings appear along the infinite face in the order prescribed by 𝒫, and

  • for each literal of cj, there is a face that contains a substring of wjN() and a substring of wjS(), one of which bounding the infinite face (as requested by the second item).

Such a string representation is given in Figure 3.

Figure 3: String representation of the clause gadget of Figure 2 satisfying all four items. The string intersections for the 342=48 adjacencies of the K4,4,4 occur in the dashed box with rounded corners. It is also easy to check that no two strings of the same color intersect, so the K4,4,4 remains induced. We kept “half” of the strings of ujN,ujS,uj+1N,uj+1S uncrossed for the representation of clause gadgets 𝒢(cj1) and 𝒢(cj+1).

The figure illustrates the case when no three variables of the clause lie on the same face. However it is easy to mirror the green strings to draw the other case. For 2-clauses, one can simply remove four strings of the same color (red, blue, or green) from Figure 3.

At this point, the string representation of G has all the desired edges (intersections) except for those of the K2,4 in variable gadgets. It has no extra edge, due to the planarity of 𝒫. Figure 4 finally shows how to edit the strings wN() and wS() to add these edges, without incurring any other edges.

Figure 4: How to realize the K2,4 of the variable gadget 𝒢(xi) without creating any other string intersections. The black strings represent vertices of 𝒢(xi), and the red strings, vertices in clause gadgets. In this example, xi is in the upper face, and has two positive occurrences and one negative occurrence.

After editing every string of the variable gadgets, we obtain a string representation for G.

We finally show the following property of G.

Claim 12.

There is a subcubic planar graph H such that G is a subgraph of H16.

Proof.

In the planar drawing 𝒫 (see proof of Claim 11), replace every clause vertex by a path of length 16, and every variable vertex by a cycle of length 12, in such a way that the obtained graph H is subcubic, still planar, and the variable-clause incidences are preserved. It is then easy to see that G is a subgraph of H16.

This finishes the proof of the main theorem.

We then derive the following.

See 2

Proof.

By Theorem 6, planar graphs have bounded twin-width. By Theorem 7, constant powers of planar graphs have bounded twin-width. Constant powers of bounded-degree graphs have themselves bounded maximum degree, and in particular, no Kt,t subgraph for some constant t. Thus by Theorem 8, the graphs produced by the previous reduction have bounded twin-width. Besides, they are bounded-degree string graphs.

The previous reduction also works for Induced Disjoint ST Paths as the invariant shown in Claim 10 can be established in the same way under the weaker assumption that G admits two mutually induced paths between u1N and {um+1N,um+1S}, and between u1S and {um+1N,um+1S}, respectively. In particular, the invariant shows that (if there is at least one clause) there cannot be u1Num+1S and u1Sum+1N paths that are mutually induced in G.

The reduction from Clause-Linked Planar E3-OCC 3-SAT of the proof of Theorem 1 is linear. Indeed it creates a constant number of vertices for each variable and for each clause. By the Sparsification Lemma of Impagliazzo, Paturi, and Zane [16] and classic linear reductions (see [9, 30]), n-variable Clause-Linked Planar E3-OCC 3-SAT requires time 2Ω(n), under the ETH. We conclude that Induced Disjoint ST Paths with |S|=|T|=2 requires time 2Ω(n) on n-variable string graphs of bounded twin-width and maximum degree.

4 Hardness of detecting a subcubic graph as an induced subdivision

As a consequence of the previous section, we can prove Theorem 3, which we recall.

See 3

Proof.

We reduce from Induced 2-Disjoint Paths in string graphs. Given any input (G,s1,t1,s2,t2), we construct a graph G as follows. Take the disjoint union of G and H, remove the edges st and st (of H), and identify s1 with s, t1 with t, s2 with s, and t2 with t. For the sake of clarity, for any i[4], vertex set Ai (in H) is renamed Bi in G. Hence V(G)=V(G)i[4]Bi. One can observe that if (G,s1,t1,s2,t2) is a positive instance of Induced 2-Disjoint Paths, then H is an induced subdivision of G. We show that the converse also holds, hence this linear reduction is correct.

Let (ϕ:V(H)V(G),(Pe)eE(H)) be an induced subdivision model of H in G. We say that a vertex of H is mapped to its image by ϕ.

Claim 13.

For any i[4], no vertex of Ai can be mapped to a vertex of V(G).

Proof.

No subdivision of K3,3 has a bridge. However, any induced subdivision in G whose branching vertices intersect both V(G) and i[4]Bi contains a bridge. This is because any of s,t,s,t is a cutvertex in G. Thus for every i[4], ϕ(Ai)i[4]Bi or ϕ(Ai)V(G). We now simply have to rule out the latter. Observe that there is no path in G between two vertices in V(G) that exits V(G). Thus, if ϕ(Ai)V(G), G would contain an induced subdivision of the 1-subdivision of K3,3, which does not hold as G is a string graph.

Claim 13 implies that ϕ(i[4]Ai)=i[4]Bi. Again, the absence of cutvertices in each H[Ai] and G[Bi] implies that for every i[4] there is some j[4] such that ϕ(Ai)=Bj. As |A1|=|A2||A3|=|A4| and ϕ is injective, {ϕ(A1),ϕ(A2)}={B1,B2} and {ϕ(A3),ϕ(A4)}={B3,B4}. Now for the induced subdivision model of H to be completed, there has to be in G two mutually induced paths between s1 and t1, and between s2 and t2. Thus (G,s1,t1,s2,t2) is indeed a positive instance.

The previous reduction also works for H-Induced Minor Containment. However, the proof is slightly more involved. We tune H a little bit such that it is still subcubic but has no two adjacent vertices of degree 3 (so that the forthcoming result answers a question of Korhonen and Lokshtanov). We call the resulting graph H; see Figure 5.

Figure 5: The graph H obtained from H of Figure 1 by subdividing in each Ai the two edges incident to the vertex with a neighbor in {s,t,s,t}. In total H has 74 vertices.

See 4

Proof.

Again, we reduce from Induced 2-Disjoint Paths in string graphs and build from any input (G,s1,t1,s2,t2), a graph G in the following way: Take the disjoint union of G and H, remove the edges st and st (of H), and identify s1 with s, t1 with t, s2 with s, and t2 with t. For any i[4], vertex set Ai (in H) is renamed Bi in G. Thus V(G)=V(G)i[4]Bi. If (G,s1,t1,s2,t2) is a positive instance of Induced 2-Disjoint Paths, then H is an induced subdivision, and hence an induced minor of G. Again, we show that the converse also holds.

Let h:=|V(H)|=74, and (:={X1,,Xh},ϕ:V(H)) be a minimal induced minor model of H in G. First, assume that there is an i[4] and xAi such that ϕ(x)V(G). As G is a string graph (but H[Ai] is not), there is also some yAi and j[4] such that ϕ(y)Bj. Let u be the vertex of {s1,t1,s2,t2} with a neighbor in Bj. As u is a cutvertex in G that disconnects Bj from the rest of G, there is a zAi such that uϕ(z).

As every branch set is connected, for every zAi{z}, either ϕ(z)Bj or ϕ(z)V(GBj). Furthermore, as H[Ai] has no cutvertex (in particular z is not a cutvertex of H[Ai]), either for every zAi{z}, ϕ(z)Bj, or for every zAi{z}, ϕ(z)V(GBj). The latter would contradict the minimality of (,ϕ) as the (non-empty subset of) vertices of Bj could then be removed from every branch set; and in particular ϕ(y) would strictly decrease.

Therefore, for every zAi{z}, ϕ(z)Bj. Moreover, it should hold that z has a neighbor in {s,t,s,t}, say s. Now, one can change the induced minor model by moving ϕ(z)V(GBj) to the adjacent branch set ϕ(s). This indeed still works as an induced minor model of H in G, and can greedily be made minimal (if need be).

After at most three more similar steps, we obtain a (minimal) induced minor model (,ϕ) such that for every xi[4]Ai, ϕ(x)i[4]Bi. We may then conclude as in the proof of Theorem 3. The ETH lower bound is a direct consequence of Theorem 2 and of the fact that the present reduction is linear.

References

  • [1] Daniel Bienstock. On the complexity of testing for odd holes and induced odd paths. Discret. Math., 90(1):85–92, 1991. See also Corrigendum by B. Reed, Discrete Mathematics, 102:109–109, 1992. doi:10.1016/0012-365X(91)90098-M.
  • [2] Édouard Bonnet, Colin Geniet, Eun Jung Kim, Stéphan Thomassé, and Rémi Watrigant. Twin-width II: small classes. Combinatorial Theory, 2(2), 2022. doi:10.5070/C62257876.
  • [3] Édouard Bonnet, Eun Jung Kim, Stéphan Thomassé, and Rémi Watrigant. Twin-width I: tractable FO model checking. J. ACM, 69(1):3:1–3:46, 2022. doi:10.1145/3486655.
  • [4] Maria Chudnovsky and Paul Seymour. The three-in-a-tree problem. Combinatorica, 30(4):387–417, 2010. doi:10.1007/S00493-010-2334-4.
  • [5] Maria Chudnovsky, Paul Seymour, and Nicolas Trotignon. Detecting an induced net subdivision. Journal of Combinatorial Theory, series B, 103(5):630–641, 2013. doi:10.1016/J.JCTB.2013.07.005.
  • [6] Clément Dallard, Maël Dumas, Claire Hilaire, Martin Milanic, Anthony Perez, and Nicolas Trotignon. Detecting K2,3 as an Induced Minor. In Adele Anna Rescigno and Ugo Vaccaro, editors, Combinatorial Algorithms - 35th International Workshop, IWOCA 2024, Ischia, Italy, July 1-3, 2024, Proceedings, volume 14764 of Lecture Notes in Computer Science, pages 151–164. Springer, 2024. doi:10.1007/978-3-031-63021-7_12.
  • [7] Clément Dallard, Maël Dumas, Claire Hilaire, and Anthony Perez. Sufficient conditions for polynomial-time detection of induced minors, 2025. doi:10.48550/arXiv.2501.00161.
  • [8] Michael R. Fellows. The Robertson-Seymour theorems: A survey of applications. Contemporary Mathematics, 89:1–18, 1989.
  • [9] Michael R. Fellows, Jan Kratochvíl, Matthias Middendorf, and Frank Pfeiffer. The complexity of induced minors and related problems. Algorithmica, 13(3):266–282, 1995. doi:10.1007/BF01190507.
  • [10] Jirí Fiala, Marcin Kaminski, Bernard Lidický, and Daniël Paulusma. The k-in-a-Path Problem for Claw-free Graphs. Algorithmica, 62(1-2):499–519, 2012. doi:10.1007/S00453-010-9468-Z.
  • [11] Petr A. Golovach, Daniël Paulusma, and Erik Jan van Leeuwen. Induced Disjoint Paths in Claw-Free Graphs. SIAM J. Discret. Math., 29(1):348–375, 2015. doi:10.1137/140963200.
  • [12] Petr A. Golovach, Daniël Paulusma, and Erik Jan van Leeuwen. Induced Disjoint Paths in AT-free graphs. J. Comput. Syst. Sci., 124:170–191, 2022. doi:10.1016/J.JCSS.2021.10.003.
  • [13] Petr A. Golovach, Giannos Stamoulis, and Dimitrios M. Thilikos. Model-checking for first-order logic with disjoint paths predicates in proper minor-closed graph classes. In Nikhil Bansal and Viswanath Nagarajan, editors, Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, SODA 2023, Florence, Italy, January 22-25, 2023, pages 3684–3699. SIAM, 2023. doi:10.1137/1.9781611977554.CH141.
  • [14] Petr Hlinený and Jan Jedelský. Twin-width of planar graphs is at most 8, and at most 6 when bipartite planar. In Kousha Etessami, Uriel Feige, and Gabriele Puppis, editors, 50th International Colloquium on Automata, Languages, and Programming, ICALP 2023, July 10-14, 2023, Paderborn, Germany, volume 261 of LIPIcs, pages 75:1–75:18. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2023. doi:10.4230/LIPICS.ICALP.2023.75.
  • [15] Russell Impagliazzo and Ramamohan Paturi. On the Complexity of k-SAT. J. Comput. Syst. Sci., 62(2):367–375, 2001. doi:10.1006/jcss.2000.1727.
  • [16] Russell Impagliazzo, Ramamohan Paturi, and Francis Zane. Which problems have strongly exponential complexity? J. Comput. Syst. Sci., 63(4):512–530, 2001. doi:10.1006/jcss.2001.1774.
  • [17] Lars Jaffke, O-joung Kwon, and Jan Arne Telle. Mim-Width I. Induced path problems. Discret. Appl. Math., 278:153–168, 2020. doi:10.1016/J.DAM.2019.06.026.
  • [18] Ken-ichi Kawarabayashi and Yusuke Kobayashi. A linear time algorithm for the induced disjoint paths problem in planar graphs. J. Comput. Syst. Sci., 78(2):670–680, 2012. doi:10.1016/J.JCSS.2011.10.004.
  • [19] Yusuke Kobayashi and Ken-ichi Kawarabayashi. Algorithms for finding an induced cycle in planar graphs and bounded genus graphs. In Claire Mathieu, editor, Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2009, New York, NY, USA, January 4-6, 2009, pages 1146–1155. SIAM, 2009. doi:10.1137/1.9781611973068.124.
  • [20] Tuukka Korhonen and Daniel Lokshtanov. Induced-minor-free graphs: Separator theorem, subexponential algorithms, and improved hardness of recognition. In David P. Woodruff, editor, Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, SODA 2024, Alexandria, VA, USA, January 7-10, 2024, pages 5249–5275. SIAM, 2024. doi:10.1137/1.9781611977912.188.
  • [21] Ngoc-Khang Le. Detecting an induced subdivision of K4. Journal of Graph Theory, 90(2):160–171, 2019. doi:10.1002/JGT.22374.
  • [22] Benjamin Lévêque, David Y. Lin, Frédéric Maffray, and Nicolas Trotignon. Detecting induced subgraphs. Discret. Appl. Math., 157(17):3540–3551, 2009. doi:10.1016/J.DAM.2009.02.015.
  • [23] David Lichtenstein. Planar formulae and their uses. SIAM J. Comput., 11(2):329–343, 1982. doi:10.1137/0211025.
  • [24] Karl Menger. Zur allgemeinen kurventheorie. Fundamenta Mathematicae, 10(1):96–115, 1927.
  • [25] Tung Nguyen, Alex D. Scott, and Paul Seymour. Induced paths in graphs without anticomplete cycles. J. Comb. Theory B, 164:321–339, 2024. doi:10.1016/J.JCTB.2023.10.003.
  • [26] Marko Radovanovic, Nicolas Trotignon, and Kristina Vuskovic. The (theta, wheel)-free graphs part IV: induced paths and cycles. J. Comb. Theory B, 146:495–531, 2021. doi:10.1016/J.JCTB.2020.06.002.
  • [27] Neil Robertson and Paul Seymour. Graph Minors. XIII. The Disjoint Paths Problem. Journal of Combinatorial Theory, Series B, 63(1):65–110, 1995. doi:10.1006/jctb.1995.1006.
  • [28] Neil Robertson and Paul Seymour. Graph minors. XVI. excluding a non-planar graph. J. Comb. Theory B, 89(1):43–76, 2003. doi:10.1016/S0095-8956(03)00042-X.
  • [29] Frank W. Sinden. Topology of thin film RC circuits. Bell System Technical Journal, 45(9):1639–1662, 1966.
  • [30] Simon Tippenhauer and Wolfgang Muzler. On planar 3-SAT and its variants. Fachbereich Mathematik und Informatik der Freien Universitat Berlin, 2016.