Colouring Probe -Free Graphs
Abstract
The -complete problems Colouring and -Colouring ) are well studied on -free graphs, i.e., graphs that do not contain some fixed graph as an induced subgraph. We research to what extent the known polynomial-time algorithms for -free graphs can be generalized if we only know some of the edges of the input graph. We do this by considering the classical probe graph model introduced in the early nineties. For a graph , a partitioned probe -free graph consists of a graph , together with a set of probes and an independent set of non-probes, such that is -free for some edge set . We show the following:
-
We fully classify Colouring on partitioned probe -free graphs and show that the obtained complexity dichotomy differs from the known dichotomy of Colouring for -free graphs.
-
We fully classify -Colouring on partitioned probe -free graphs: we prove polynomial-time solvability for and -completeness for . In contrast, -Colouring on -free graphs is known to be polynomial-time solvable for and quasi-polynomial-time solvable for .
Our main result is our polynomial-time algorithm for -Colouring on partitioned -free graphs. For this result, and also for all our other polynomial-time results, we do not need to know the edge set ; we only need to know its existence. Moreover, the class of probe -free graphs includes not only paths of arbitrary length but even all bipartite graphs and is much richer than the class of -free graphs. The latter is also evidenced by the fact that there exist graph problems, such as Matching Cut, that are known to be polynomial-time solvable for -free graphs but -complete for partitioned probe -free graphs. In particular, unlike the class of -colourable -free graphs, the class of -colourable probe -free graphs has unbounded mim-width. Hence, our polynomial-time result for -Colouring for probe -free graphs suggests that there may be another, deeper overarching reason why -Colouring is polynomial-time solvable for -free graphs.
Keywords and phrases:
colouring, probe graph, forbidden induced subgraph, complexity dichotomyFunding:
Johannes Rauch: Supported by the German Academic Scholarship Foundation (Studienstiftung des Deutschen Volkes).Copyright and License:
2012 ACM Subject Classification:
Mathematics of computing Graph theory ; Theory of computation Graph algorithms analysis ; Theory of computation Problems, reductions and completenessAcknowledgements:
We thank Clément Dallard and Andrea Munaro for helpful discussions and ideas that ultimately led to the proof of Theorem 3.Editors:
Meena Mahajan, Florin Manea, Annabelle McIver, and Nguyá» n Kim TháșŻngSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl â Leibniz-Zentrum fĂŒr Informatik
1 Introduction
Colouring is a classical graph problem. Given a graph and a positive integer , it asks whether it is possible to colour the vertices of with colours such that any two adjacent vertices receive different colours. The variant where is fixed beforehand, and not part of the input anymore, is known as -Colouring. It is well known that 3-Colouring, and thus Colouring, are -complete problems [39]. This led to a rich body of literature that tries to understand what graph structure causes the computational hardness in Colouring. In our paper we extend this body of work by researching the computational complexity of Colouring and -Colouring on classes of graphs that generalize the well-known -free graphs (a graph is -free if does not contain as an induced subgraph) but for which we do not know all the edges. Before discussing our model of incomplete information, we first briefly survey some relevant known results for Colouring and -Colouring.
-Free Graphs.
KrĂĄl et al. [54] showed that if is a (not necessarily proper) induced subgraph of or , where denotes the path on vertices, then Colouring on -free graphs is solvable in polynomial time; otherwise, it is -complete. For -Colouring, the complexity status on -free graphs has not been resolved yet. For every , -Colouring for -free graphs is -complete if has a cycle [37] or an induced claw [50, 56]. However, the remaining case where is a linear forest (disjoint union of paths) has not been settled yet. For -free graphs, the cases , (trivial), , [49], , [9] and , [28, 29] are polynomial-time solvable and the cases , [51] and , [51] are -complete. The cases and are still open, despite some evidence that these cases are polynomial-time solvable due to a quasi-polynomial-time algorithm [60]. We refer to the survey [41] and some later articles [25, 26, 48, 53] for results on -Colouring for -free graphs if is a disconnected linear forest, and to [52] for the most recent results on Colouring for -free graphs, for which also still many cases remain open.
Probe -Free Graphs.
In this article, we aim to further our understanding of the complexity of Colouring and -Colouring by studying probe graphs. Probe graphs are used to model graphs for which the global structure is known (e.g. -freeness). However, we only know the complete set of neighbours for some vertices of a probe graph . These vertices are the probes of . The other vertices are the non-probes of and form an independent set in , as we do not know which of them are adjacent to each other. We only know that there exists a âcertifyingâ set of edges on the non-probes such that exhibits the global structure (e.g. being -free). In particular, the subgraph of induced by the set of probes already has this global structure (e.g. is -free). The notion of probe graphs was introduced by Zhang et al. [64] in genome research to make a genome mapping process more efficient.
Formally, for a graph class , the class consists of all graphs that can be modified into a graph from by adding some edges between an independent set of .
If for a graph in , the sets and are given, then we speak of a partitioned probe graph.
Hence, a partitioned probe -free graph consists of a graph , together with a set of probes and an independent set of non-probes, such that is -free for some edge set . We note that an -free graph itself is also a (partitioned) probe -free graph, namely with and . Hence, for every graph , the class of (partitioned) probe -free graphs contains the class of -free graphs. Consequently, any -completeness results for -free graphs immediately carry over to partitioned probe -free graphs. However, it also leads to the following research question:
If an -complete problem is polynomial-time solvable on -free graphs for some graph , is also polynomial-time solvable on (partitioned) probe -free graphs?
Our Focus.
To investigate our research question, we consider Colouring and -Colouring for (partitioned) probe -free graphs. For some graphs , such as [22], probe -free graphs can be recognized in polynomial time. However, for most graphs , including , the recognition of probe -free graphs and the distinction between probes and non-probes are open problems. Hence, we usually require the sets of probes and non-probes to be part of the input, i.e., we must consider partitioned probe -free graphs. Note that we can colour a probe -free graph with one extra colour (assigned to each vertex in ) than the number of colours used for . The challenge is to determine if we need that extra colour.
Related Work.
So far, most previous work on probe graphs focused on characterising and recognising classes of probe graphs [42, 22, 20, 4, 43, 5, 55]. However, recently, the first systematic studies of optimisation problems on partitioned probe -free graphs were undertaken. Brettell et al. [15] considered Vertex Cover on partitioned probe -free graphs and Dabrowski et al. [31] did the same for Matching Cut and some of its variants. A takeaway from [15, 31] is that determining the complexity of Vertex Cover for (partitioned) probe -free graphs seems challenging, whereas Matching Cut is -complete on partitioned probe -free graphs, even though they are both polynomial-time solvable on -free graphs [58, 38].
Helpful for algorithmic studies as [15, 31] is that probe graphs inherit some properties from the graph class they are based on. This is also true when studying Colouring. For example, Golumbic and Lipshteyn [42] proved that probe chordal graphs are perfect. Hence, we obtain that Colouring is polynomial-time solvable for probe chordal graphs, as Colouring is so for perfect graphs [45, 46]. In 2012, Chandler et al. [21] conjectured that this holds even for Colouring on partitioned probe perfect graphs. Moreover, the following is known:
Proposition 1 ([22, 15]).
Let be a class of graphs and let be a fixed integer.
-
(i)
If has clique-width at most , then has clique-width at most .
-
(ii)
If has mim-width at most , then has mim-width at most .
Hence, as holds for every graph class , we obtain that a graph class has bounded mim-width (clique-width) if and only if has bounded mim-width (clique-width). However, if the yes-instances for some problem in have bounded width, this may no longer hold for the yes-instances for in . If we can still solve on , this means there might be a deeper reason for the polynomial-time behaviour of on . We will also research this.
Our Results.
As mentioned, we focus on Colouring and -Colouring for probe -free graphs. Our first result is a full dichotomy of Colouring on partitioned probe -free graphs (for two graphs and , we write if is an induced subgraph of ).
Theorem 2.
For a graph , Colouring is polynomial-time solvable for probe -free graphs if , and else it is -complete even for partitioned probe -free graphs.
By Theorem 2, Colouring is -complete for partitioned probe -free graphs, while Colouring is even polynomial-time solvable on -free graphs [54]. It is known that the class of -free graphs has bounded mim-width [13] if and and only if it has bounded clique-width (see e.g. [33]) if and only if is an induced subgraph of . Hence, Theorem 2 also implies, together with Proposition 1, that Colouring on (not necessarily partitioned) probe -free graphs is solvable in polynomial time exactly when the mim-width or clique-width is bounded. In fact, we apply Proposition 1 to show the first part of Theorem 2, while for the second part we modify a known hardness reduction for Colouring [6]; see Section 3.
Our second result is a full dichotomy for -Colouring on partitioned probe -free graphs:
Theorem 3.
For an integer , -Colouring on partitioned probe -free graphs is polynomial-time solvable if and -complete if .
In Section 4 we prove the polynomial part of Theorem 3 by giving our main result: a polynomial-time algorithm for -Colouring for partitioned probe -free graphs. The class of -free graphs has been extensively studied for many well-known graph problems, yielding polynomial-time algorithms not only for -Colouring for any [49], but also Vertex Cover [58], Feedback Vertex Set [1], Independent Feedback Vertex Set [8] and very recently, Odd Cycle Transversal [2], or more generally, Maximum Partial List -Coloring for every fixed graph [57]. Our polynomial-time result for -Colouring on partitioned probe -free graphs is the first result that generalizes a known polynomial-time result for a (classical) graph problem on -free graphs to partitioned probe -free graphs.
In Section 5 we prove the second part of Theorem 3. In fact, we show that -Colouring is -complete even on partitioned probe -free graphs. In contrast, -Colouring is polynomial-time solvable even on -free graphs [9] and -free graphs for all [32].
In Section 6, we point out many natural directions for future research. In particular, we determine all (disconnected) graphs for which -Colouring on probe partitioned -free graphs is still open and solve one such open case, namely when . Moreover, we consider -Colouring for and solve one open case, namely when for , by proving that for every , all probe -free graphs are -free.
Proof Ideas behind Our Main Result.
As evidenced by the , there are -free graphs that are not perfect, and there exist three different proofs for showing that -Colouring is polynomial-time solvable on -free graphs. As discussed below, these proofs are not applicable to probe -free graphs, even though two of them provide good starting points.
First, in the proof of Brettell et al. [14], it was shown that -colourable -free graphs have bounded mim-width for all , directly implying that -Colouring becomes polynomial-time solvable [17]. However, bipartite graphs are even -colourable and readily seen to be even probe -free (as shown below explicitly for paths) while already chordal bipartite graphs have not only unbounded mim-width [12] but even unbounded sim-width [10]. This also shows that probe -colourable -free graphs, which have bounded mim-width due to Proposition 1, are only a small subclass of the class of -colourable probe -free graphs.
Second, in the proof of Randerath, Schiermeyer and Tewes [62], a connected -colourable -free graph is shown to have a dominating set of constant size. By precolouring in every possible way, polynomially many instances of -List Colouring (i.e., where all lists of admissible colours have size ) are obtained. As -List Colouring can be formulated as -SAT, it is polynomial-time solvable [36]. This approach fails for probe -free graphs. To see this, let be a path . Let and . Note that and are independent. Hence, making a clique yields a split graph, which is -free, so is even probe -free. However, for large , has no small dominating set.
Finally, in the proof of Woeginger and Sgall [63], it is first shown that every -free graph is -colourable. Next, the case where contains at least one triangle (which may not be dominating) is considered. After colouring , the following rule is applied exhaustively: whenever a vertex has two neighbours not coloured alike, give the third colour. Afterwards, it is again shown that an instance of -List Colouring is obtained. Also this approach does not work for probe -free graphs due to their more intricate structure. By extending the arguments as in [63], we can show that even all -free probe -free graphs, which include all (probe) -free graphs, are -colourable (see Section 4). However, -free probe -free graphs form only a small subclass of -colourable probe -free graphs.
As we explain below, our proof for partitioned probe -free graphs turns out to be substantially more involved than the second and third proofs for -free graphs and does not rely on the boundedness of some width parameter.
First, if all connected components of the subgraph induced by the probes are bipartite, we can colour the probes with colours and and use colour for the non-probes (as the non-probes form an independent set). Next, we show that at most one connected component of the subgraph induced by the set of probes can be non-bipartite. Then, by -freeness, we find that has a short odd cycle . The fact that in general, is not a dominating cycle of the graph causes several complications. To overcome these complications, we branch on the colours of and then just like [63], we try to extend the colouring as much as possible using propagation rules, with the aim to reduce eventually to polynomially many instances of -List Colouring. We show that the latter is possible via (i) a new decomposition of probe -free graphs, which carefully takes into account the fact that we do not know the missing edges between the non-probes that make the graph -free (as illustrated in Figure 3) and (ii) an adaptation of the standard 2-SAT formula for -List Colouring.
2 Preliminaries
Let be a graph, and be a positive integer. The order of is its number of vertices, and the size of is its number of edges. For a vertex of , we denote its (open) neighbourhood by , and its closed neighbourhood by . For a set of vertices of , let , and . A vertex is complete to a set of vertices if is adjacent to every vertex of , and is anticomplete to if is not adjacent to any vertex of . Let be another set of vertices of that is disjoint to . If every vertex of is complete (anticomplete) to , then is complete (anticomplete) to . We write for the subgraph of induced by . For two vertex-disjoint graphs and , we let denote their disjoint union, which is the graph . For a graph and integer , denotes the disjoint union of copies of .
For a graph , we say that is -free if there is no set of vertices such that is isomorphic to . We say that is probe -free if there is a partition of the vertices of into a set of probes and a set of non-probes , such that is independent in , and there is a set of edges such that is -free. Note that is -free if is probe -free. A partitioned probe -free graph is a triple , where is a probe -free graph with as the probes and as the non-probes, that is, the sets of probes and non-probes are given. For a set of graphs, a graph is -free if is -free for every . A graph is probe -free if there is an independent set of non-probes in and a set of edges such that is -free. In a partitioned probe -free graph , the graph is probe -free with set of probes and set of non-probes .
We define . A partial -colouring of is a function such that, if with , then . If is a vertex of with , then is coloured (under ). Let be another partial -colouring of . Then is an extension of if implies that . A -colouring of is a partial -colouring under which every vertex of is coloured. For , we define .
Algorithm 1 is a simple colour propagation algorithm that is essential to the proof of Theorem 3. The following properties of Algorithm 1 are easy and their proofs are omitted:
Lemma 4.
Let be a partial -colouring of a graph .
We use the following well-known lemma, which is due to Edwards [36]. We provide a proof to adapt it later.
Lemma 5.
Given a graph and a partial -colouring of , for every uncoloured vertex , define the set of available colours of as . If for every uncoloured vertex , then deciding if there is a -colouring that is an extension of is possible in polynomial time.
Proof.
Let the SAT formula in conjunctive normal form have variables for every uncoloured vertex and every , and clauses
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for every uncoloured vertex (i.e., if , then is not satisfiable) and
-
for every with uncoloured vertices and and .
According to the assumptions is a 2-SAT formula. By construction, there is a -colouring of that is an extension of if and only if is satisfiable. This completes the proof since deciding the satisfiability of a 2-SAT formula is possible in polynomial time [3].
3 The Proof of Theorem 2
In this section we show Theorem 2. The proof of our next result is based on an existing construction from [6], and we omit the proof details.
Proposition 6.
Colouring is -complete on partitioned probe -free graphs.
We combine Proposition 6 with the -completeness part of the dichotomy of KrĂĄl et al. [54], the fact that -free graphs have clique-width [30] and Proposition 1 to obtain Theorem 2 (proof details omitted):
Theorem 2. [Restated, see original statement.]
For a graph , Colouring is polynomial-time solvable for probe -free graphs if , and else it is -complete even for partitioned probe -free graphs.
4 The Proof of the Polynomial Part of Theorem 3
In this section we prove the main result of our paper, namely that -Colouring is polynomial-time solvable for partitioned probe -free graphs.
We first show the following independent result (Proposition 7) in more or less the same way as done in [63] for showing that -free graphs are -colourable. The main difference is that we must take into account the probes and non-probes. As such, the proof of this result serves as warm-up exercise illustrating some of the arguments we will use in a more involved way in the proof of our main result. Note that probe -free graphs form a subclass of -free probe -free graphs. This containment is proper, as
- (i)
-
(ii)
chordal bipartite graphs, which are -free probe -free, have unbounded mim-width [12].
Proposition 7.
All -free probe -free graphs, and thus all probe -free graphs, are -colourable.
Proof.
Let be a -free probe -free graph. Let be the set of probes and be the set of non-probes, so is an independent set. By definition, there exists a set of edges with both end-vertices in such that is -free. We may assume without loss of generality that is connected, as otherwise we consider every connected component of separately.
If is bipartite, then we colour with colours and , and as is independent, we can use colour for the vertices of . Now suppose that is not bipartite. This means that has an odd cycle . As is -free and probe -free, must be -free. Hence, has length . Let in that order. We will now use, with a little bit of extra care, the same arguments as in [63].
We first claim that every vertex not on has a neighbour on . Else, as is connected, there exists a vertex that is anti-complete to and that has a neighbour that is adjacent to at least one vertex on , say . If is an induced in , then is also an induced in . The reason is that contains no edge that is incident with a vertex from , because all belong to . As is -free and is -free, this means that must be adjacent to in . By applying the same arguments on the path , we find that must be adjacent to in as well. However, now form a triangle in , contradicting the -freeness of .
We now claim that every vertex not on has exactly two neighbours and on for some , where we write and . Let . By the above, has a neighbour on , say is adjacent to . Recall that does not contain any edges incident to vertices of , as . Hence, if is an induced in , then is also an induced in . As is -free and is -free, this means that is either adjacent to (take ) or to (take ). Due to the above, we can decompose as
where for , the set consist of all vertices of whose neighbours on are exactly and . We give colours , respectively. Moreover, we colour all the vertices of , , , and with colours , respectively. As is -free, the five sets are all independent. Therefore, the only potential conflicts could be between vertices from and , which are all coloured , or between vertices from and , which are all coloured . However, the former vertices are all incident to , and thus form an independent set in , and similarly, the latter vertices are all adjacent to , and thus als form an independent set in . We conclude that we have indeed constructed a -colouring of , completing the proof. We are now ready to show the main result of our paper, which we prove in the way as outlined at the end of Section 1.
Theorem 8.
-Colouring is polynomial-time solvable for partitioned probe -free graphs.
Proof.
Let be a partitioned probe -free graph. We may assume that is connected; otherwise, we execute the given algorithm for every connected component of . Let be such that is -free. We define only for verifying correctness; the polynomial-time algorithm does not use . If is -free, then it is possible in polynomial time to determine whether is 3-colourable [49]. Therefore, we may assume that is not -free and, in particular, and . We may also assume that does not contain a clique of order at least ; otherwise, is not -colourable. Let be the connected components of that contain at least one edge. We may assume at least one such connected component exists; else is bipartite with partite sets and , and thus clearly 3-colourable in polynomial time.
Getting initial structure.
We begin by proving two claims that describe the structure of edges between and .
Claim 9.
Every vertex of that is neither complete nor anticomplete to for some is complete or anticomplete to for every with .
Proof.
Let be neither complete nor anticomplete to . Suppose that has a neighbour in , where . It suffices to prove that is complete to . Assume, for a contradiction, that is not adjacent to . By assumption, there exists that is not adjacent to . A shortest --path with internal vertices in followed by a shortest --path with internal vertices in is induced in and has length at least 4; see Figure 1. Since such a path exists, there is an induced in , a contradiction.
If are all bipartite, then is clearly 3-colourable, since is independent in . Therefore, we may assume that and is not bipartite. This implies that contains an induced odd cycle and, since is -free because of , such a cycle has length or length . We now pick an induced odd cycle in as follows. If contains an induced , then let be any such . If does not contain an induced , but contains an induced that dominates , then let be any such . Otherwise, we pick to be an arbitrary . Note that computing is possible in polynomial time.
If a single vertex of dominates , then is clearly not 3-colourable. Hence, we may assume from here that this is not the case. This fact (that we often use implicitly) has important implications. In particular, no vertex of dominates . But also:
Claim 10.
Let be a vertex with no neighbour in . If has a neighbour in with , then a vertex of with a neighbour in is complete to .
Proof.
Consider a shortest --path in . As has no neighbour in , has length at least . Let be the vertex of where ends and let be the vertex on preceding . Using the observation preceding the claim, is not complete to . We may thus assume that was chosen such that there exists a vertex . If , then as does not neighbour , the path has length at least , a contradiction to the fact that is -free. Hence, and is neither complete nor anticomplete to . If is not a neighbour of in , then is an induced path in of length at least , a contradiction. Let be a neighbour of in . If is not a neighbour of in , then the path is an induced in , a contradiction; see Figure 1 right. Hence, has a neighbour in , and the claim follows from Claim 9.
Claim 11.
The connected components are all bipartite or is not 3-colourable.
Proof.
Assume (without loss of generality) is not bipartite and is -colourable. From our earlier observation, if some vertex is complete to or to , then is not -colourable, a contradiction. As is connected, has a neighbour . Hence, is neither complete or anticomplete to . As cannot be complete to , by Claim 9, is anticomplete to . Then, by Claim 10, there is a vertex in that is complete to , a contradiction. We can check in linear time whether are all indeed bipartite.
Colouring .
Let for brevity and . Note that consists only of isolated vertices and bipartite connected components. We branch on all partial 3-colourings that only colour every vertex of . There are constantly many branches, as there are only constantly many such partial 3-colourings. We propagate the colours through by executing Algorithm 1 on . If an error occurred, then there is no 3-colouring of that is an extension of by Lemma 4 (ii), and we backtrack. So we may assume that no error occurred, and for simplicity we denote the returned extension of by again.
We explicitly only propagated the colours through . We now partition of . Let
-
be the set of vertices of with colour for ,
-
,
-
be the set of uncoloured vertices of with a neighbour of colour for ,
-
, and
-
consist of the remaining vertices of .
Note that is connected, because is connected, and we assign colours to uncoloured vertices only with the Propagation Rule in Algorithm 1. Also note that the vertices of have only neighbours of colour since they are uncoloured.
Our ultimate goal is to apply Lemma 5. So far we are not in a position to apply it, since there may be vertices (for example in ) that do not have a coloured neighbour. In the remaining proof, we distinguish two cases, depending on the length of .
Case 1: has length 5.
We show that all vertices already have a coloured neighbour.
Claim 12.
Every vertex of has a neighbour in .
Proof.
Assume, for a contradiction, that has no neighbour in . Consider a shortest --path in . Let be the vertex of that has a neighbour in . Note that is not complete to ; otherwise, we would have concluded that is not 3-colourable. If is in itself, then has length at least 3, and there would be an induced in with vertices in ; see Figure 2 left. Hence, is not in . Then has at most two neighbours in , and has length at least 2, and there would be an induced in with vertices in , a contradiction; see Figure 2 right.
Case 2: has length 3.
First, note that for every vertex , we have that has two neighbours with two distinct colours in , since is a clique and we assign colours to uncoloured vertices only through the Propagation Rule in Algorithm 1. We now give a more precise partition of ; see Figure 3. Let and . Let
-
and be the set of vertices of and , respectively, that have two neighbours in with two distinct colours,
-
and be the set of vertices of and , respectively, with a neighbour in for ,
-
, ,
-
, and .
Let be the set of vertices of with no neighbour in . Note that no vertex of , , , and has a coloured neighbour. We now show how in the end we can apply Lemma 5.
Handling and .
Since is independent in and is connected, every vertex of has a neighbour in . If, in , a vertex has only neighbours in for one , then a 3-colouring of that extends can be extended to a 3-colouring of by assigning colour to . We remove any such from and continue. Now, every vertex of has neighbours in for at least two distinct , or has a neighbour in . We prove two claims, one for each of the two described types of vertices in .
Claim 13.
For with , if has a neighbour in , and has a neighbour in , then and have the same neighbours in .
Proof.
Assume, for a contradiction, that is a neighbour of , but not a neighbour of . Let be a neighbour of . Consider a shortest --path in with internal vertices in . As is not an induced in , we must have . Let be the neighbour of in , and let be a neighbour of that is adjacent to neither nor . Note that exists since every vertex of has two neighbours of two distinct colours. Now, is an induced in , a contradiction; see Figure 4 left.
Let be the set of vertices of with a neighbour in .
Claim 14.
A single vertex of dominates the vertices of .
Proof.
If , then and the statement is trivial. Hence, . As is a connected -free graph, contains a connected dominating set that induces a -free graph or a [19]. As we are in Case 2, cannot be a . Hence, is a clique.
If , then contains a clique of order at least , which we already excluded. If , then contains a that dominates . By the choice of and the fact that we are in Case 2, dominates . Hence, our application of the Propagation Rule ensures that , a contradiction. If and the vertex of is in , then we arrive at a contradiction as before. If and the vertex of is not in , then this vertex and form a clique of order at least , which we already excluded. It remains that . In other words, contains a dominating edge .
We must have that and are disjoint; otherwise, there would be a dominating triangle in , which we can exclude as before. Without loss of generality, let contain at least two vertices of . This implies . As there is no edge between and by definition of , dominates .
It remains to show that is complete to . Suppose exists. Let be a neighbour of . As neighbours two vertices of and , vertex is in a cycle of length , which is contained in (possibly ). Let . As and are disjoint, is not adjacent to . Also, is not adjacent to as and , and is not adjacent to , as and . As is not an induced in , we obtain , a contradiction; see Figure 4 right. Hence, dominates .
Claim 15.
is dominated by a set of at most two vertices of .
Handling and .
We now describe the structure of the edges between and .
Claim 16.
(i) Every vertex of has no neighbour in , and (ii) For every , is complete to .
Proof.
We first prove (i). Suppose, for the sake of contradiction, that there exists a vertex that has a neighbour in . Since , has a neighbour . By definition of , has no neighbour in . Let be a shortest --path in with internal vertices in . The path must contain a vertex of for some by assumption and therefore has length at least 2. Then there is an induced in with vertices in , a contradiction; see Figure 5 left.
We continue with (ii). For some , let such that is not complete to . Since , has a neighbour . Since , has a neighbour in . Let be a non-neighbour of . Let be a neighbour of that is closest to in . Let be a shortest --path in , which exists since is connected. As , they are not adjacent. Thus, has length at least 2, and contains an induced in , a contradiction; see Figure 5 right. Hence, for every , is complete to .
We continue with two claims describing the structure of the edges between and .
Claim 17.
Every vertex of has a neighbour in .
Proof.
Assume, for a contradiction, that the vertex only has neighbours in . Since every vertex of has no neighbours in by Claim 16 (i), a shortest --path in has length at least 3. This implies that there is an induced in with vertices in , a contradiction; see Figure 6 left. The claim follows.
Claim 18.
If , then every vertex of has the same neighbours in .
Proof.
Note that by Claim 16 (i) and since is independent. Let . Assume, for a contradiction, that the vertex is a neighbour of , but not a neighbour of . By considering a shortest --path in containing the vertices and , we see that . Let be a vertex that is not adjacent to in , which exists, or would not be -colourable. Therefore, together with a shortest --path with internal vertices in contains an induced in , a contradiction; see Figure 6 right. As were arbitrary, the proof is complete.
Claim 19.
If there is 3-colouring of that is an extension of , then there is a 3-colouring of that is an extension of .
Proof.
Assume, for a contradiction, that for a vertex , there exist vertices with for every . Note that by Claim 16 (i). By Claim 17 and Claim 18, there exists a vertex that is adjacent to , , and , a contradiction to the fact that is a -colouring of . Therefore, for every vertex , there is a colour such that no neighbour of in has colour under . At this point, choosing any such colour for every vertex of gives a 3-colouring of that is an extension of . Claim 19 implies that it suffices to decide if there is a 3-colouring that is an extension of . Hence, from now on, assume that . Recall that is the set of vertices of with no neighbour in . Consequently, by Claim 17, every vertex of has a neighbour in . Claim 9 implies that every vertex of is either complete or anticomplete to each connected component of . It follows that, if , then contains all vertices of the connected component of in . We prove one more claim about the structure of the edges between and .
Claim 20.
If is nonempty for at least two , then the bipartite subgraph of spanned by the edges of with one end in and the other end in is complete.
Proof.
Let be an arbitrary connected component of . Keep in mind that is a connected component of too. Let with be such that is nonempty, and has a neighbour in . Note that such and exist by assumption and Claim 17, and is complete to by Claim 9. We prove that is complete to .
Assume, for a contradiction, that has no neighbour in . Let be an arbitrary neighbour of in . Consider a shortest --path with internal vertices in , which exists since is connected. As , the path has length at least 3, and, by Claim 16 (ii), the path has length exactly 3. Since is not an induced in , we have . Let be the neighbour of in , let , and let be a neighbour of in with colour . Note that exists since every vertex of has two neighbours in with two distinct colours. Now is an induced in , a contradiction; see Figure 7. So has a neighbour in . Claim 9 implies that is complete to . Since was chosen arbitrarily, this proves that is complete to .
A similar argument shows that for , if is nonempty, then is complete to too. By interchanging the roles of and , we see that is complete to . Since was chosen arbitrarily, and since every such connected component of has a neighbour in by Claim 17, this completes the proof.
Colouring .
At this point, we are in a position to decide if there is a -colouring of that is an extension of . First, Claim 15 implies that is dominated by a set of at most two vertices of . We branch on the (constantly many) consistent extensions of into -colourings that additionally colour every vertex of , which we call again for simplicity.
Observe that every vertex of has a coloured neighbour now. As , we now only need to achieve the same for in order to apply Lemma 5. If , then Lemma 5 is directly applicable. Therefore, we decide in polynomial time if there is a 3-colouring of that is an extension of . If there is no such 3-colouring, then we backtrack.
We now assume that . Since vertices in are not adjacent to by definition and , . If is nonempty for at least two , then we choose a vertex . We branch on the extensions of that additionally colour . Observe that now every vertex of has a coloured neighbour under by the definition of and Claim 20. Now, Lemma 5 is applicable. Therefore, we decide in polynomial time if there is a 3-colouring of that is an extension of . If there is no such 3-colouring, then we backtrack.
It remains the case that there is exactly one such that is nonempty. Every vertex in has neighbours only in . In particular, for each connected component of , which is a connected component of , the colour may be used without creating conflicts outside of . Recall that is bipartite by Claim 11. Hence, we wish to extend by, for each connected component of , colouring one of its partite set by colour . However, we cannot immediately decide which partite set, and make a small detour.
Let be a connected component of that contains an edge. Let be a neighbour of in . Since , it is adjacent to , and thus neither complete nor anticomplete to . Hence, is complete to by Claim 9. Thus, is complete to . Therefore, all vertices of must receive the same colour in any -colouring of that extends . We ensure this first, for each such connected component , and then extend the colouring to .
We apply the formula of Lemma 5 to , adapted as follows. For every connected component in that contains an edge, and for every two distinct vertices , we add the clauses to for every . These clauses ensure that two such vertices and receive the same colour. (Alternatively we could identify these vertices. At this point it does not matter that this does not preserve probe -freeness.) After that, we resolve the satisfiability of the 2-SAT formula in polynomial time [3]. If is not satisfiable, then there is no 3-colouring of that is an extension of , and we backtrack. Otherwise, let be a 3-colouring of obtained from a satisfying assignment of . We can extend to a -colouring of by assigning colour to isolated vertices in , and by assigning the remaining two colours to the nontrivial bipartite connected components of , which is possible due to the extra clauses we added to . This completes the proof of Theorem 8.
5 The Proof of the NP-Completeness Part of Theorem 3
Theorem 3 states that for , -Colouring on partitioned probe -free graphs is polynomial-time solvable if and -complete if . In Section 4 we showed the polynomial part of Theorem 3. We now show the -completeness part by reducing from 1-Precolouring Extension, which has as input: an integer , a graph with at least vertices, and a partial -colouring of that assigns vertices colours , respectively. Can be extended to a -colouring of ? Bodlaender et al. [7] proved that this problem is -complete, even if , is bipartite and the precoloured vertices all belong to the same partition set of . Cai [18] used this result to prove that -Colouring is -complete for graphs that become bipartite by deleting three edges. We use the gadget of [18] to show the following, which implies the -completeness part of Theorem 3.
Theorem 21.
-Colouring is -complete on partitioned probe -free graphs.
Proof.
We reduce an instance of 1-Precolouring Extension, where is a bipartite graph with bipartition and , and the precoloured vertices belong to without loss of generality, to an instance of -Colouring. As mentioned, this variant of 1-Precolouring Extension is still -complete [7]. The bipartition of can be computed in polynomial time. Let be the graph from [18], which is obtained in polynomial-time from by turning into a clique. The graph is probe -free, which is witnessed by the fact that the graph obtained from by turning the independent set into a clique is -free. It is easy to see that is a yes-instance of 1-Precolouring Extension if and only if is a yes-instance of -Colouring. This proves that -Colouring is -hard on partitioned probe -free graphs.
6 Additional Results and Concluding Remarks
In our paper, we considered the probe graph model introduced by Zhang et al. [64]. Our aim was to research to what extent polynomial-time results for -free graphs can be extended to probe -free graphs. We first gave a dichotomy for Colouring restricted to (partitioned) probe -free graphs and then showed our main result, which states that the known polynomial-time result for -Colouring for -free graphs (whose yes-instances all have bounded mim-width) can be extended to partitioned probe -free graphs (whose yes-instances even have unbounded sim-width). We also proved that this result cannot be generalized to partitioned probe -free graphs unless by showing -completeness even for partitioned -free graphs. As -Colouring is polynomial-time solvable even for -free graphs [9] and -free graphs for all [32], our results give a clear indication of the difference in computational complexity if not all edges of the input graph are known, under the probe graph model. They also lead to a range of natural directions for future work, as we discuss below.
First, the dichotomy for -Colouring for partitioned probe -free graphs has not been fully settled. We are able to prove the following additional result (proof omitted):
Theorem 22.
For every , -Colouring is polynomial-time solvable on partitioned probe -free graphs.
Theorem 3, Theorems 21â22 and the result that -Colouring is -complete on -free graphs if is not a linear forest [37, 50] leave only the following open cases:
Problem 23.
Determine the complexity of 3-Colouring on partitioned probe -free graphs when is (), (), (), (), or ().
Second, since -Colouring is polynomial on -free graphs [49] even for all , we ask:
Problem 24.
For , determine the complexity of -Colouring on partitioned probe -free graphs.
Crucial properties in our proof for -Colouring on partitioned probe -free graphs, such as the fact that there is a single non-bipartite connected component and that no vertex is complete to the cycle we pick in it, no longer hold if . We do note that probe -free graphs have bounded mim-width for every , due to -free graphs having bounded mim-width for every [14] and Proposition 1. Hence, as we may assume that an input graph for -Colouring is -free, a good starting point is to consider -Colouring for -free partitioned probe -free graphs, or even for -free partitioned probe -free graphs.
We recall that for solving -Colouring on probe -free graphs, we only need the partition into and . To solve Problem 24, it would also be interesting to research if the problem becomes easier under the assumption that we also know the set of edges .
As another starting point for solving Problem 24, we can show the following result (proof omitted):
Theorem 25.
For every and , -Colouring is polynomial-time solvable on (not necessarily partitioned) probe -free graphs.
We note that for , Theorem 25 does not need the partition , whereas Theorem 22 does, so the two theorems are not comparable.
We could prove Theorem 25 by showing that for all , every probe -free graphs is -free, and we ask:
Problem 26.
Are there other sets , for which there exists a finite set such that every probe -free graph is -free?
An inclusion as in Problem 26 is in general strict, e.g., probe -free graphs form a hereditary graph class that is not finitely defined. To explain this, as probe -free graphs are closed under vertex deletion, there is a unique minimal set of graphs such that a graph is probe -free if and only if it is -free. We can show that (proof omitted). So, in particular, probe -free graphs form a proper subclass of -free graphs, that is, graphs with no odd hole of length at least . This leads to the following natural question:
Problem 27.
Determine the complexity of -Colouring for -free graphs.
It is known that -Colouring is polynomial-time solvable for odd-hole free graphs, i.e., -free graphs (see [59]) and -free graphs are -bounded [27].
Knowing more about would help solving the following open problem, which is solved for in polynomial time [22] and which in turn might help solving -Colouring on probe -free graphs without a given partition of their vertex set.
Problem 28.
Determine the complexity of recognizing probe -free graphs.
We also ask for which other graph classes , are Colouring and -Colouring polynomially solvable on the class of (partitioned) probe graphs ? Recall from Section 1 that Colouring is polynomial-time solvable for probe chordal graphs (as these graphs are perfect) and that in 2012, Chandler et al. [21] conjectured the same for partitioned probe perfect graphs.
We finish with two other, broader directions for future work. First, we recall our result (Proposition 7) that -free probe -free graphs (and thus all probe -free graphs) are -colourable, which generalizes the same result for -free graphs [63]. There is a long history for obtaining constant (tight) bounds on the chromatic number of -free graphs; see also the recent survey [24]. In particular, for all , every -free graph can be coloured with at most colours [44], improving an older result in [47]. It is also known e.g. that every -free graph is -colourable for all [11], and that every -free graph [61], every -free graph [16] and every -free graph [40] is -colourable. In particular, subclasses of -free graphs are well studied; see [23, 34, 35] for several of such results. To what extent can all these results be extended to the probe version? Proposition 7 illustrates there exist graph classes with a positive answer.
Second, our results indicate that the reason for polynomial-time solvability of -Colouring for -free graphs goes beyond boundedness of mim-width. The question, which may also be asked for other problems, is if we can push further in this direction. So far, we assumed that the set of non-probes is an independent set. This is an extreme case in a more general model in which we assume that we do know some of the edges in .
Problem 29.
Determine if -Colouring is polynomially solvable on graphs that can be made -free by adding new edges to , which may have some initial edges.
If we allow an arbitrary initial set of edges in , then the problem is already -complete on graphs that can be made -free: take the graph used in any -hardness reduction for -Colouring; set ; and let be the set of all edges that are not already in (so is complete, that is, is -free).
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