Finding -Cuts in Claw-Free Graphs
Abstract
The Matching Cut problem is to decide if the vertex set of a connected graph can be partitioned into two non-empty sets and such that the edges between and form a matching, that is, every vertex in has at most one neighbour in , and vice versa. If for some integer , we allow every vertex in to have at most neighbours in , and vice versa, we obtain the more general problem -Cut. It is known that -Cut is NP-complete for every . However, for claw-free graphs, it is only known that -Cut is polynomial-time solvable for and NP-complete for . We resolve the missing case by proving NP-completeness. This follows from our more general study, in which we also bound the maximum degree. That is, we prove that for every , -Cut, restricted to claw-free graphs of maximum degree , is constant-time solvable if and NP-complete if . Moreover, in the former case, we can find a -cut in linear time. We also show how our positive results for claw-free graphs can be generalized to -free graphs where is the graph obtained from a star on vertices by subdividing one of its edges exactly times.
Keywords and phrases:
matching cut, -cut, claw-free, maximum degreeFunding:
Jungho Ahn: supported by Leverhulme Trust Research Project Grant RPG-2024-182 and INHA UNIVERSITY Research Grant.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:
The authors thank Ali Momeni and Hyunwoo Lee for providing some helpful insights about the proofs of Lemma 9 and Theorem 10, respectively.Editors:
Ho-Lin Chen, Wing-Kai Hon, and Meng-Tsung TsaiSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik
1 Introduction
In this paper, we determine new complexity results for finding -cuts, which form a natural generalization of matching cuts. The latter form a well-studied notion that combines two classic concepts in graph theory: matchings and edge cuts. Namely, a matching cut in a connected graph is a set of edges that is both a matching (i.e., no two edges in share an end-vertex) and an edge cut (i.e., can be partitioned into two non-empty sets and such that consists of all the edges between and ). The Matching Cut problem is to decide if a connected graph has a matching cut.
Already in 1984, Chvátal [9] proved that Matching Cut is NP-complete even for -free graphs of maximum degree . Here, the graph denotes the star on vertices, that is, the graph with vertices and edges , for , and a graph is -free if it does not contain as an induced subgraph. In contrast, Chvátal [9] also showed that Matching Cut is polynomial-time solvable for graphs of maximum degree at most . In 2009, Bonsma [6] proved the same for -free graphs (of arbitrary degree), which are also known as claw-free graphs. Since then a growing sequence of papers appeared in which the computational complexity of Matching Cut for various special graph classes was determined, often in a systematic way (e.g., [8, 11, 18, 22, 23]) and also from a parameterized complexity perspective (e.g. [1, 12, 13, 16, 17]) and for many closely related problem variants, such as the problems of finding perfect matching cuts [5, 15, 19], maximum matching cuts [24], minimum matching cuts [20], matching multicuts [14] and disconnected perfect matchings [7]. We refer to Section 5 for a summary of the complexity results for Matching Cut restricted to -free graphs as part of a summary for a more general notion, namely -cuts, the topic of our paper. For an integer and a connected graph , a set is a -cut of if can be partitioned into two non-empty sets and such that:
-
the set is the set of all edges between and ; and
-
every vertex in has at most neighbours in , and vice versa.
See Figure 1 for some examples. We note that a -cut is a matching cut and vice versa. For a fixed integer , the -Cut problem is to decide if a connected graph has a -cut. Hence, Matching Cut and -Cut are the same problems.
The -Cut problem was introduced by Gomes and Sau [13]. Apart from several parameterized complexity results (see also [2]), they showed the following two results. The first result is a structural result (shown for in [9, 25]), which immediately implies the first statement of the second result (shown for in [9]).
Theorem 1 (Gomes and Sau [13]).
For , every graph with maximum degree and has a -cut, which can be found in polynomial time.
Theorem 2 (Gomes and Sau [13]).
For , -Cut is constant-time solvable for graphs with maximum degree but NP-complete for -regular graphs (that is, graphs in which every vertex has degree ).
For , the results in Theorem 2 are currently the best results for -Cut of bounded maximum degree, so for we have a complexity gap. Gomes and Sau [13] argued that it is unlikely that the maximum degree bound of in Theorem 2 can be lowered, as that would disprove a conjecture about the existence of so-called internal partitions of -regular graphs for odd ; see [3].
In particular, Theorem 2 shows that -Cut is constant-time solvable for graphs of maximum degree and NP-complete for graphs of maximum degree . Gomes and Sau [13] showed that all maximum degree- graphs on vertices without a -cut have some specific structure: they are -regular or have exactly two vertices of degree , which are adjacent. Interestingly, they mentioned in [13] that they were unable to find a maximum degree- graph on more than 18 vertices without a -cut.
The -Cut problem has also been studied for -free graphs. As mentioned, we summarize these results in Section 5. For now, we focus on the case for the following reason. It is known that for all , -Cut is NP-complete for claw-free graphs. This was shown in [21] (the gadget constructed in the proof of Theorem 2 is not claw-free). The result for contrasts the case due to the aforementioned result of Bonsma [6] that -Cut (Matching Cut) is polynomial-time solvable on claw-free graphs and leaves open exactly the case . The authors of [21] could prove that -Cut is NP-complete for -free graphs and asked about the case in the following open problem:
Open Problem 1 (Lucke et al. [21]).
What is the complexity of -Cut for claw-free graphs?
Our Results
Inspired by Theorems 1 and 2 of Gomes and Sau [13] and motivated by Open Problem 1, we consider claw-free graphs of bounded maximum degree. In Sections 3 and 4, respectively, we show the following two results for , the second of which solves Open Problem 1.
Theorem 3.
Let . Every claw-free graph with maximum degree and has a -cut, which can be found in linear time. Moreover, there exist arbitrarily large claw-free -regular graphs with no -cut.
Theorem 4.
For , -Cut is constant-time solvable for claw-free graphs with maximum degree but NP-complete for claw-free graphs with maximum degree .
The first statement of Theorem 3 is the analogue of Theorem 1 for claw-free graphs (for which we can find the -cut even in linear time). We show how this statement follows from a corresponding stronger statement on -free graphs, where is the graph obtained from a star on vertices by subdividing one of its edges exactly times, see Figure 2 for the case where and . The second statement of Theorem 3 not only shows that the bound in the first statement is best possible, but also relates to Theorem 2: it shows that for every , there exists an infinite number of -regular no-instances of -Cut that are also claw-free.
The first statement of Theorem 3 immediately implies the constant-time part of Theorem 4, as is a constant. We use the graph in the second statement of Theorem 3 as part of our hardness gadget in the NP-completeness part of Theorem 4.
Theorem 4 shows in particular that -Cut is constant-time solvable for claw-free graphs of maximum degree but NP-complete for claw-free graphs of maximum degree , which solves Open Problem 1. Moreover, the gadget used in the reduction for -Cut ) for claw-free graphs in [21] contains vertices of arbitrarily large degree. Theorem 4 strengthens this result by adding a maximum degree bound that is only one higher than the maximum degree bound in Theorem 2.
Note that is at least in both Theorems 3 and 4, which can be explained as follows. We first recall that for , Bonsma [6] proved that -Cut is polynomial-time solvable even for claw-free graphs with arbitrarily large maximum degree . Second, for , Theorem 3 would not hold: take, for example, a chain of graphs isomorphic to (complete graph minus an edge) which we obtain from copies of , for , by identifying a pair of degree vertices between consecutive copies. That is, where , is the pair of degree vertices of the th copy, we identify vertices and , for all . The resulting chain is an arbitrarily large claw-free graph of arbitrarily large maximum degree but with no -cut, see Figure 3 for the case where .
2 Preliminaries
In this paper, we only consider finite, undirected graphs without multiple edges and self-loops. For every integer , let .
Let be a graph and let be a vertex of . We denote by the (open) neighbourhood of and by the closed neighbourhood of . The degree of is the size of , and we denote by the maximum degree of . For a set , we denote by the set of edges of with exactly one end-vertex in .
A complete graph is a graph whose vertex set is a clique, which is a set of pairwise adjacent vertices. For , we let denote the complete graph on vertices. A vertex set is an independent set of if no two vertices of are adjacent in . In addition, is bipartite if we can partition the vertex set into (possibly empty) sets and such that and and are each an independent set.
The chromatic number of a graph is the smallest integer such that has a -colouring, which is a mapping with for every . The set of all vertices that are mapped to the same colour is called a colour class of . For , a graph is -degenerate if every subgraph of contains a vertex of degree at most . It is well known and readily seen that every -degenerate graph is -colourable. The degeneracy of is the smallest integer such that is -degenerate. The following observation holds (we give a proof for completeness).
Observation 5.
Let and let be a graph. If has no independent set of size , then has a subgraph of minimum degree at least
Proof.
Assume has no independent set of size . Let be the degeneracy of , so has a subgraph of minimum degree at least . Consider a -colouring of . As every colour class of is an independent set, we have and thus . Let be an integer. A red-blue colouring of gives each vertex of either colour red or blue. A red-blue -colouring of is a red-blue colouring where every vertex has at most neighbours of the other colour and both colours, red and blue, are used at least once. See Figure 1 for an example of a red-blue -colouring (left figure) and a red-blue -colouring (right figure). In our proofs, we use the following well-known observation; see e.g. [21].
Observation 6.
For every integer , has a red-blue -colouring with sets and if and only if the set of edges between and form a -cut of .
Let be a graph with a red-blue -colouring for some . We say that a set is monochromatic if all vertices in have the same colour.
We will also use the following observations, which can be readily seen.
Observation 7.
Let . Let be a graph and let with . For every red-blue colouring of , in which is monochromatic, each vertex in with at least neighbours in has the same colour as the vertices of .
Observation 8.
Let . Let be a graph with a clique on at least vertices. Then is monochromatic in every red-blue -colouring of .
3 The Proof of Theorem 3
In this section, we prove Theorem 3, which states that for all , every claw-free graph with maximum degree and has a -cut, which we can find in linear time, and moreover, that there exist arbitrarily large claw-free -regular graphs with no -cut.
We start with a lemma. In its proof, we extend the argument that Chvátal [9] used to observe that -Cut is constant-time solvable for graphs of maximum degree at most .
Lemma 9.
Let . Let be a graph with , and let be a non-empty set of vertices with . If each vertex in is incident to at most edges in , then has a -cut, which can be found in linear time.
Proof.
Assume that each vertex in is incident to at most edges in . We will now construct a red-blue -colouring of , which, by Observation 6, gives that has a -cut. We first colour every vertex in blue and recursively colour an uncoloured vertex blue if it has at least blue neighbours. Note that this takes time, as . We colour all remaining vertices of red. See also Figure 4.
Let and be the sets of red and blue vertices, respectively. Note that . By construction, every vertex in has at most neighbours in . As we assume that each vertex in is incident to at most edges in , each vertex in has at most neighbours in . Since and each vertex in has at least neighbours in , each vertex in has at most neighbours in . Hence, every vertex in has at most neighbours in . It remains to show that , or equivalently, that , which we will do below.
Let denote the vertices in in the order they are coloured blue. For an arbitrary , let . Recall that by construction, each vertex has at least neighbours in and at most neighbours not in . So when we colour blue, that is, add to , we lose at least edges with exactly one blue end-vertex and gain at most new edges with exactly one blue end-vertex. In other words, . This implies , and thus . We use this and our assumption that to deduce that
and thus . Hence, we obtained a red-blue -colouring of . To prove the first part of Theorem 3, we prove a stronger statement in Theorem 10 and afterwards we show how Theorem 10 implies the first part of Theorem 3. For every positive integer and , we recall that is the graph obtained from by replacing one edge with a path of length , see Figure 2. Note that contains exactly edges. In addition, is the graph .
Theorem 10.
For , and , every -free graph with either maximum degree , or and has a -cut, which can be found in linear time.
Proof.
Let , and . Let be an -free graph. If , then has a -cut: take all edges between any vertex of and its neighbours. From now on, assume and and .
We choose an arbitrary vertex of and let . For each , we denote by the set of vertices which are at distance exactly from in . Note that and for each , . Thus,
Let be the set of vertices in which are incident to at least edges in . For each , we denote by the set of neighbours of not in and by the subgraph of induced on .
We first show that , for , has no independent set of size . Suppose not. By the definition of , there is an induced path of length between and . Together with this path and the independent set in , we can find as an induced subgraph, a contradiction. Thus, has no independent set of size .
For each , since has no independent set of size , by Observation 5, has a subgraph whose minimum degree is at least
We remark that can be found in constant time as , which is a constant. Now, we let
Note that can be found in constant time as , which is a constant.
We are going to apply Lemma 9 to . Since , we have , and therefore
To apply Lemma 9 to , we first show that every vertex in is incident to at most edges in . By construction, this holds for every vertex in . Let be a vertex in and let be a vertex in . Note that and might be the same. Since the minimum degree of is at least
and is adjacent to every vertex in , there are at least
neighbours of in . Then is incident to at most
edges in . That is, is incident to at most edges in . Hence, every vertex in is incident to at most edges in .
We now show that . Since , we have
Since every vertex in is incident to at most edges in , we have . Thus,
Hence, by Lemma 9, we can find a -cut of in linear time.
Theorem 3 (first part, restated). For , every claw-free graph with maximum degree and has a -cut, which can be found in linear time.
Proof.
Let be a claw-free graph. If , then we can apply Theorem 10 directly. Assume . Theorem 10 with and implies the first part of Theorem 3. In order to see this, let be a claw-free graph with maximum degree and . As if , we obtain . We also observe:
where the last inequality holds from the fact that and the function is increasing for . Hence, the conditions in Theorem 10 are satisfied, and we may conclude that has a -cut, which can be found in linear time.
We now prove the second part of Theorem 3, which shows that the bound given in the first part of Theorem 3 is best possible. We slightly reformulate the statement as follows.
Theorem 11.
For every integer , , and , there exists a claw-free -regular graph on vertices that has no -cut.
Proof.
Let be pairwise disjoint cliques of size . For each , let be a partition of such that . Note that
Let be the graph obtained from by adding new vertices such that for each , is equal to where , see Figure 5. Note that has vertices.
We first show that is claw-free and -regular. Let be an arbitrary integer in . Since the neighbourhood of is the disjoint union of two cliques and , has no claw centred at . Note further that has degree . Consider now a vertex in . The neighbourhood of consists of all other vertices in and some vertex , where . Hence, has degree and since is a clique, has no claw centred at . We conclude that is claw-free and -regular.
It remains to show that has no -cut. Note that in any red-blue -colouring of , , for , is monochromatic by Observation 8, since it is a clique of size at least . We claim that
is monochromatic in every red-blue -colouring of . Suppose for a contradiction that has a red-blue -colouring where is not monochromatic. Then there exists such that and have different colours, where . Without loss of generality, assume that is coloured red. Consequently, is coloured blue. Since has at least red neighbours in , it is coloured red. However, has blue neighbours in , contradicting the fact that we considered a red-blue -colouring. Hence, if has a red-blue -colouring, then is monochromatic.
Thus, if has a red-blue -colouring, then is monochromatic and hence, , for , is coloured the same as since has at least neighbours in . Therefore, there is no red-blue -colouring of . By Observation 6, has no -cut.
4 The Proof of Theorem 4
In this section we prove Theorem 4. We first recall that the first statement of Theorem 3 immediately implies the constant-time part of Theorem 4, as is a constant. Hence, it remains to show the NP-completeness part of Theorem 4, that is, that for every integer , -Cut is NP-complete for claw-free graphs of maximum degree . To do this, we will reduce from NAE -Sat -, which is a variant of Not-All-Equal -Satisfiability (NAE -Sat). An instance of NAE -Sat consists of a set of clauses , each containing three variables. The problem is to decide whether there is an assignment of the variables such that every clause contains both a true and a false literal. Such an assignment is called an NAE-satisfying assignment.
An instance of the problem we will reduce from NAE -Sat - is an instance of NAE -Sat that is satisfied both by the assignment where every variable is true and the assignment where every variable is false. In other words, given an instance of NAE -Sat -, every clause contains a positive literal and a negative literal. Additionally, since the clause has the same set of NAE-satisfying assignments as the clause , we may assume that each clause contains exactly one negative literal.
The problem NAE -Sat - is to decide whether an instance has a third NAE-satisfying assignment. That is, we must decide whether there exists an assignment of variables such that at least one variable is true, at least one variable is false, and each clause contains both a true and a false literal. The next result was shown in [10].
Proposition 12 (Eagling-Vose et al. [10]).
NAE -Sat - is NP-complete.
We remark that it is possible to combine the reduction from Matching Cut to NAE -Sat - given in [10] with the reduction given here from the latter problem to -Cut to obtain a reduction directly from Matching Cut to -Cut. However, we separate the two reductions for ease of explanation.
For the reduction in the proof of our NP-hardness result, we use a lemma that is based on the class of graphs from Theorem 11. For all integers , , and , let be the graph obtained from the graph in Theorem 11, with respect to the same integers, by adding new vertices such that for each , the neighbourhood of in is equal to where . See also Figure 6.
Lemma 13.
For all integers , , and , the graph is a claw-free graph with maximum degree on vertices which has no -cut. In particular, each of has degree , and the other vertices have degree at least .
Proof.
Let be the graph in Theorem 11, with respect to the same integers, and let . Note that
Since is -regular and have pairwise disjoint neighbourhoods, each of has degree , and the other vertices have degree either or .
We show that is claw-free. Suppose that has a claw centred at a vertex . Since is claw-free, contains for some . As is a clique, . So is the union of two cliques, contradicting that is a claw. Hence, is claw-free.
It remains to show that has no -cut. By Observation 6, has a -cut if and only if has a red-blue -colouring. By Theorem 11, we know that is monochromatic in every red-blue -colouring. Further, , for , has neighbours in . Thus, by Observation 7, is coloured the same as . This implies that is monochromatic in every red-blue -colouring and hence has no red-blue -colouring. It follows that has no -cut.
We are now ready to prove the remaining part of Theorem 4, which we restate below.
Theorem 4 (NP-completeness part, restated). For , -Cut is NP-complete for claw-free graphs with maximum degree .
Proof.
We reduce from NAE -Sat -. Let be an instance of NAE -Sat - with variables and clauses . In the following, we construct an instance of -Cut which is claw-free and has maximum degree . For each , let be the number of occurrences of in and let be a copy of . We say that a vertex of is free if it has degree in . Note that has exactly free vertices. We remark that these free vertices will play the role of variable vertices for .
For each clause , for , we add two disjoint cliques of size and of size . In addition, we add a vertex . We let and call a clause gadget. We add all edges between and and between and . For each , we choose some free vertex of and call this vertex . We add edges between and each vertex in , edges between and each vertex in , and we also add an edge between and , see Figure 7. We choose these free vertices in such a way that every free vertex has neighbours in exactly one clause gadget. This is possible as, for every , has free vertices and appears times in . Let be the resulting graph.
We first show that is a claw-free graph of maximum degree . Let be an arbitrary integer in . Let be a vertex that is not free. Then, by Lemma 13, has degree at most and further, since has neighbours only in , has no claw centred at . Let be a free vertex of . Recall that has a neighbour in a clause gadget for some . Note that has degree at most since it has neighbours within and at most neighbours in . In addition, the neighbours of in form a clique of size or . Thus, the neighbourhood of in is the union of this clique in and some clique in , so has no claw centred at .
Finally, we consider the clause gadget . Recall that is a fixed vertex with neighbourhood . Thus, it has degree . Since is complete to , the neighbourhood of is the union of two cliques. Hence, the vertex is not the centre of a claw of . Let be a vertex in . The closed neighbourhood of is , which is the union of the two cliques and . Hence, is not the centre of a claw in . Since , has degree . Now, let be a vertex in . The closed neighbourhood of is , which is the union of the two cliques and . So is not the centre of a claw in . Again, as , the vertex has degree . It follows that is a claw-free graph of maximum degree at most .
We show that has a -cut if and only if has an NAE-satisfying assignment with both a true and a false variable. By Observation 6, this is equivalent to showing that has a red-blue -colouring if and only if has an NAE-satisfying assignment with both a true and a false variable.
We assume first that has a red-blue -colouring and show that has an NAE-satisfying assignment with both a true and a false variable. Recall that by Lemma 13, is monochromatic for each . We set a variable to true if is coloured blue and to false otherwise.
We first show that the resulting assignment contains both a true and a false variable. Suppose for a contradiction that this is not the case. We may assume without loss of generality that all variables are true. This implies that for every , is coloured blue. Note that , for , is a clique of size and thus monochromatic by Observation 8. As , it is coloured blue. Further, has neighbours in . Hence, since is monochromatic, is coloured blue. It follows that is blue as well and, since has blue neighbours in , it is coloured blue. Thus, the whole graph is coloured blue, contradicting the fact that we considered a red-blue -colouring. Therefore, the assignment contains both a true and a false variable.
We now show that the assignment is NAE-satisfying for . Suppose for a contradiction that the assignment is not NAE-satisfying. Then there exists a clause , for some , such that all literals have the same value. Note that this implies that both and take the opposite value of . Without loss of generality, assume that is true and and are both false. That is, is coloured blue while and are coloured red. Recall that is monochromatic. Since has neighbours in , is coloured the same as and is thus coloured red. This implies that the blue vertex has red neighbours in , so its neighbour is coloured blue. However, as is coloured red, has red neighbours in , contradicting the fact that we considered a red-blue -colouring. Hence, the assignment is NAE-satisfying for .
For the other direction, we now assume that has an NAE-satisfying assignment with both a true and a false variable. We construct a red-blue -colouring of as follows. For each , we colour blue if it corresponds to a true variable and red otherwise. For each , we colour the same as . In addition, we colour the same as .
We show that this colouring is indeed a red-blue -colouring of . Note first that since the assignment contains both a true and a false variable, we have both red and blue vertices. It remains to show that every vertex has at most neighbours of the other colour. Let be an arbitrary integer in . Note that every vertex of which is not a free vertex has no neighbour of the other colour. Let be a free vertex of . Recall that there is exactly one clause , for , such that is adjacent to the corresponding clause gadget . That is, . We distinguish between these cases:
-
If , then it has one neighbour outside of and thus at most one neighbour of the other colour.
-
If , then, by construction, it has no neighbour of the other colour.
-
If , then it has neighbours outside of and, by construction, at least one of them, namely , has the same colour as .
Thus, has at most neighbours of the other colour.
Now, let be a vertex in . If , then its closed neighbourhood is , which is monochromatic by construction. Thus, has no neighbour of the other colour. If , then, since is monochromatic, the only neighbours of which may be coloured with the other colour are and . Since , it follows that has at most neighbours of the other colour. Thus, we may assume that . Recall that the neighbourhood of is and that is coloured the same as . Assume without loss of generality that is coloured blue. Suppose for a contradiction that has at least red neighbours. That is, and are coloured red. Since is monochromatic by construction, this implies that and thus are coloured red as well. Hence, and are both coloured red, while is coloured blue, a contradiction to the assumption that the assignment is NAE-satisfying. Thus, has at most neighbours of the other colour. Hence, the colouring is indeed a red-blue -colouring of . This completes the proof. We remark that for every , -Cut is still NP-complete on claw-free graphs with maximum degree : after replacing each as a copy of , instead of , the same hardness proof works.
5 Conclusions
We proved both constant-time and NP-completeness results for -Cut restricted to claw-free graphs of bounded maximum degree, leaving open only one case, which replaces Open Problem 1:
Open Problem 2.
For every integer , what is the computational complexity of -Cut on claw-free graphs of maximum degree ?
Recall that we showed in Theorem 3 that there are many claw-free -regular graphs with no -cut and also that every claw-free graph of maximum degree has a -cut. This shows that our bound is best possible. On the other hand, our construction used in the proof of Theorem 4 for graphs of maximum degree cannot easily be modified to work for graphs of maximum degree . The variable gadget is based on our construction for -regular graphs without a -cut. We modify the construction such that it contains vertices of degree that can be used to connect the gadget to the rest of the construction. However, to make sure that we do not get a -cut by partitioning the graph into a variable gadget and the rest, there has to be a vertex in the variable gadget that has at least neighbours outside the gadget. This leads to vertices of degree in the construction. Hence, reducing the degree in this construction requires us to construct a variable gadget containing some vertices of degree smaller than . If we want the gadget to be monochromatic, this implies we need a gadget with vertices of degree . However, finding such a gadget seems to be a challenging task.
In our paper we also showed that our positive results for -Cut on claw-free graphs can be generalized to even -free graphs. A natural question, which we leave for future work, is whether our results can also be generalized to -free graphs. Here, is the graph obtained from the claw by subdividing two of its edges exactly once. In order to answer this question, we need some new arguments as our current proof techniques cannot be applied immediately. For instance, in the proof of Theorem 10, a key observation is that for each , has no independent set of size , as otherwise we can find an induced by combining such an independent set with the path of length between and . This observation no longer holds for the case.
We recall that in particular, our results imply that -Cut, restricted to claw-free graphs of maximum degree , is constant-time solvable if and NP-complete if . The latter result resolved an open case in the complexity classification of -Cut on -free graphs, as the complexity of -Cut for claw-free graphs was not previously known. This brings us to the state-of-the-art summary for -Cut on -free graphs, which we update below.
We first give some more terminology. For , we denote by and , respectively, a path and a cycle on vertices. For , we denote by the disjoint union of copies of . We denote by the graph obtained from a claw by subdividing one edge once, so that it has four edges. Let be a graph that looks like the letter “H”. It is obtained by taking the graph and making the middle vertices, say and , of each adjacent to each other. We obtain the graph , for , by subdividing exactly times, see Figure 8. The girth of a graph that is not a forest is the length of a shortest cycle in it.
We now present the updated state-of-the-art summary. For every , -Cut is NP-complete for graphs of girth at least for every fixed [11], and thus for -free graphs for every . It is also known that -Cut is NP-complete for -free graphs for every [11], -free graphs [9], -free graphs [23] and -free graphs [18]. On the positive side, -Cut is polynomial-time solvable for -free graphs [20], -free graphs [20] and -free graphs [20] for every .
We summarize the above results and our new result for -Cut on claw-free graphs in the following theorem, in which all unreferenced results for -Cut are shown in [21]. For two graphs and , we write if is an induced subgraph of , and denote by the disjoint union of a copy of and a copy of .
Theorem 14.
Let and let be a graph.
-
If , then -Cut (Matching Cut) on -free graphs is
-
–
polynomial-time solvable if , , or for some ;
-
–
NP-complete if , , , , for some , or for some .
-
–
-
If , then -Cut on -free graphs is
-
–
polynomial-time solvable if or for some ;
-
–
NP-complete if , , for some .
-
–
It is known that for , -Cut is polynomial-time solvable on -free graphs whenever -Cut is polynomial-time solvable for -free graphs. This means that the cases are all polynomially equivalent. Hence, for , there are, due to our new result, now only three non-equivalent open cases left, namely when .
Finally, we are currently exploring the consequences of our results and proofs for finding internal partitions of graphs. To explain, a partition of the vertex set of a graph is an internal partition of if for every , every vertex in has at least half of its neighbours in . Internal partitions are well studied; see, for example, the survey of Bazgan, Tuza and Vanderpooten [4]. The corresponding decision problem that asks whether a graph has an internal partition is known as Satisfactory Partition. As we briefly mentioned in Section 1, there are connections between -cuts and internal partitions [13].
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