The complexity of recognizing minimally tough graphs
Gyula Y Katona, Istv\'an Kov\'acs, Kitti Varga

TL;DR
This paper proves that recognizing minimally t-tough graphs is DP-complete for any positive rational t, introducing weighted toughness as a key concept in the proof.
Contribution
It establishes the DP-completeness of recognizing minimally t-tough graphs for all positive rational t and introduces weighted toughness to aid the proof.
Findings
Recognition problem is DP-complete for all positive rational t.
Introduces weighted toughness as a new concept.
Provides complexity classification for minimally t-tough graphs.
Abstract
A graph is called -tough if the removal of any vertex set that disconnects the graph leaves at most components. The toughness of a graph is the largest for which the graph is -tough. A graph is minimally -tough if the toughness of the graph is and the deletion of any edge from the graph decreases the toughness. The complexity class DP is the set of all languages that can be expressed as the intersection of a language in NP and a language in coNP. In this paper, we prove that recognizing minimally -tough graphs is DP-complete for any positive rational number . We introduce a new notion called weighted toughness, which has a key role in our proof.
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The complexity of recognizing minimally tough graphs
Gyula Y Katona [email protected] Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Hungary
MTA-ELTE Numerical Analysis and Large Networks Research Group, Hungary
István Kovács [email protected] Shapr3D, Hungary
Kitti Varga [email protected] Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Hungary
HAS Alfréd Rényi Institute of Mathematics, Hungary
Abstract
A graph is called -tough if the removal of any vertex set that disconnects the graph leaves at most components. The toughness of a graph is the largest for which the graph is -tough. A graph is minimally -tough if the toughness of the graph is and the deletion of any edge from the graph decreases the toughness. The complexity class DP is the set of all languages that can be expressed as the intersection of a language in NP and a language in coNP. In this paper, we prove that recognizing minimally -tough graphs is DP-complete for any positive rational number . We introduce a new notion called weighted toughness, which has a key role in our proof.
1 Introduction
All graphs considered in this paper are finite, simple and undirected. Let denote the number of components and denote the independence number of a graph . (Using to denote the number of components may be confusing, however, most of the literature on toughness uses this notation.) For a graph and a vertex set , let denote the subgraph of induced by . For a connected graph , a vertex set is called a cutset if its removal disconnects the graph.
The notion of toughness was introduced by Chvátal [toughness_intro].
Definition 1.1**.**
Let be a real number. A graph is called -tough if holds for any vertex set that disconnects the graph (i.e. for any with ). The toughness of , denoted by , is the largest for which is -tough, taking for all .
We say that a cutset is a tough set if .
It follows directly from the definition of toughness that every -tough noncomplete graph is -connected; therefore, the minimum degree of any -tough noncomplete graph is at least .
Clearly, the more edges a graph has, the larger its connectivity can be, so the graphs whose toughness decreases whenever one of their edges are removed might have some interesting properties.
Definition 1.2**.**
A graph is minimally -tough if and for all .
The motivation for our research is the following conjecture.
Conjecture 1.3** (Kriesell [kriesell]).**
Every minimally -tough graph has a vertex of degree .
The above conjecture can be naturally generalized to any positive rational number as follows: every minimally -tough graph has a vertex of degree . Note that this conjecture is an analogue of a theorem of Mader stating that for any positive integer , every minimally -connected graph has a vertex of degree , see [ende].
Kriesell’s conjecture is still open, but in [min1tough_article] we presented some related results, in particular that in the class of claw-free graphs the conjecture is true in a very strong sense, namely, the only minimally 1-tough, claw-free graphs are cycles of length at least four. On the other hand, we also proved that the class of minimally -tough graphs is large for any positive rational number : any graph can be embedded as an induced subgraph into a minimally -tough graph.
Therefore it is natural to ask, how “large” the set of minimally -tough graphs is for different values and for various graph classes. In the present paper we investigate the first question from a complexity theoretical viewpoint. Similar results for the second question are presented in [spec_graphclasses].
Let be an arbitrary positive rational number and consider the following problem.
-Tough
Instance: a graph .
Question: is it true that ?
Note that in this problem, is not part of the input.
It is easy to see that for any positive rational number , the problem -Tough is in coNP: a witness is a vertex set S whose removal disconnects the graph and leaves more than components. By reducing a variant of the independent set problem to the complement of -Tough, Bauer et al. proved the following.
Theorem 1.4** ([recognize_toughness]).**
For any positive rational number , the problem -Tough is coNP-complete.
However, in some graph classes the toughness can be computed in polynomial time, for instance, in the class of split graphs.
Theorem 1.5** ([split_general]).**
For any rational number , the class of -tough split graphs can be recognized in polynomial time.
The focus of our investigation is on the critical version of the problem -Tough. Let be an arbitrary positive rational number and consider the following problem.
Min--Tough
Instance: a graph .
Question: is it true that is minimally -tough?
Since extremal problems usually seem not to belong to , the complexity class called DP was introduced by Papadimitriou and Yannakakis in [dp_intro].
Definition 1.6**.**
A language is in the class DP if there exist two languages and such that .
A language is called DP-hard if all problems in DP can be reduced to it in polynomial time. A language is DP-complete if it is in DP and it is DP-hard.
It should be emphasized that if . Moreover, .
To prove that Min--Tough is DP-complete for any positive rational number , we use the following problem for reduction.
-Critical
Instance: a graph and a positive integer .
Question: is it true that , but for any edge ?
Note that, unlike in -tough or Min--Tough, in this problem is part of the input. The DP-completeness of the problem -Critical is a trivial consequence of the following theorem.
Theorem 1.7** ([crit_clique]).**
The following problem is DP-complete.
CriticalClique* *
*Instance: a graph and a positive integer . *
Question: is it true that has no clique of size , but adding any missing edge to , the resulting graph has a clique of size ?
Corollary 1.8**.**
The problem -Critical is DP-complete.
Our main result is the following.
Theorem 1.9**.**
The problem Min--Tough is DP-complete for any positive rational number .
Note that since the toughness of any noncomplete graph is a rational number, there exist no minimally tough graphs with irrational toughness.
To prove the case , we introduce a new notion called weighted toughness. However, we believe that this might be an interesting idea on its own.
Definition 1.10**.**
Let be a positve real number. Given a graph and a positive weight function on its vertices, we say that the graph is weighted -tough with respect to the weight function if
[TABLE]
holds for any vertex set whose removal disconnects the graph, where
[TABLE]
The weighted toughness of a noncomplete graph (with respect to the weight function ) is the largest for which the graph is weighted -tough, and we define the weighted toughness of complete graphs (with respect to ) to be infinity.
Note that the weighted toughness of a graph with respect to the weight function that assigns 1 to every vertex is the toughness of the graph.
The paper is organized as follows. Section 2 gathers the properties of minimally tough graphs and -critical graphs that are needed to prove Theorem 1.9. Since the proof of this theorem is fairly complicated, Section 3 discusses some of its special cases in the hope of fostering a better understanding. The proof of Theorem 1.9 considers three cases: when , when , and when ; they are proved in Sections 4, 5 and 6, respectively.
2 Preliminaries
In this section we collect some useful properties of minimally tough graphs and -critical graphs.
2.1 Minimally tough graphs
Proposition 2.1**.**
Let be a positive rational number and a graph with . Then
[TABLE]
for any nonempty proper subset of .
Proof.
If is a cutset in , then by the definition of toughness holds.
If is not a cutset in , then (since ). On the other hand, since and . Therefore holds in this case as well. ∎
As is clear from its proof, the above proposition holds even if is not a cutset. However, it does not hold if and is not a cutset: if , then the graph cannot contain a cut-vertex; therefore for any subset with , while .
Proposition 2.2**.**
Let be a connected noncomplete graph on vertices. Then is a positive rational number, and if , where are relatively prime positive integers, then .
Proof.
By definition,
[TABLE]
for a noncomplete graph . Since is connected and noncomplete, for every with . Obviously, , and since is connected, . ∎
Corollary 2.3**.**
Let and be two connected noncomplete graphs on vertices. If , then
[TABLE]
Proof.
Let and be two pairs of relative prime positive integers such that and . Proposition 2.2 implies that . Since ,
[TABLE]
∎
Proposition 2.4**.**
For every positive rational number , the problem Min--Tough belongs to DP.
Proof.
For any positive rational number ,
[TABLE]
Let
[TABLE]
[TABLE]
and
[TABLE]
Notice that L_{2}=\text{{\mbox{t-Tough}}} and it is known to be in coNP: if a graph is not -tough, then a witness is a vertex set whose removal disconnects and leaves more than components. Similarly, , since a witness is a set of vertex sets \big{\{}S_{e}\subseteq V(G)\bigm{|}e\in E(G)\big{\}}, where for any the removal of disconnects and leaves more than components.
Now we show that , i.e. we can express in the form
[TABLE]
which is the complement of a language belonging to coNP. Let be an arbitrary graph on vertices. If is disconnected, then , and if is complete, then , so in both cases if and only if for any positive number . If is connected and noncomplete, then from Corollary 2.3 it follows that if and only if . Therefore
[TABLE]
so .
Since and and \text{{Min-\mbox{t-Tough}}}=\left(L_{1,1}\cap L_{1,2}\right)\cap L_{2}, we can conclude that \text{{Min-\mbox{t-Tough}}}\in\text{DP}. ∎
Proposition 2.5**.**
Let be a positive rational number and a minimally -tough graph. For every edge of ,
the edge is a bridge in , or 2. 2.
there exists a vertex set with
[TABLE]
and the edge is a bridge in .
In the first case, we define .
Proof.
Let be an arbitrary edge of which is not a bridge. Since is minimally -tough, . Since is not a bridge, is still connected, so there exists a cutset in satisfying \omega\big{(}(G-e)-S\big{)}>|S|/t.
By Proposition 2.1, if , then . So assume that . Now there are two cases.
Case 1: ( and) is a cutset in .
Since and is a cutset, . This is only possible if connects two components of .
Case 2: ( and) is not a cutset in .
Then . Since is a cutset in , the edge must connect two components of , so
[TABLE]
Now we show that . Suppose to the contrary that . Since , this implies that . Moreover, since , the graph is -connected, and thus it has at least vertices. From this it follows that and one of the endpoints of form a cutset in , otherwise would only have
[TABLE]
vertices (where the latter inequality is valid since ). Let denote this cutset. Since is -tough and is a cutset in ,
[TABLE]
so . Therefore
[TABLE]
which implies that and that is a contradiction. ∎
2.2 Almost minimally 1-tough graphs
The graphs and behave similarly as minimally 1-tough graphs: they are 1-tough, and the removal of any of their edges decreases their toughness below 1. However, they are not minimally 1-tough since their toughness is infinity. To handle these kinds of graphs, we introduce the following definition.
Definition 2.6**.**
A graph is almost minimally -tough if and for all .
In fact, the only almost minimally 1-tough graphs are minimally 1-tough graphs and the graphs and .
Claim 2.7**.**
For a graph the following are equivalent.
The graph is almost minimally 1-tough. 2.
The graph is 1-tough and for every , the edge is a bridge or there exists a vertex set with
[TABLE]
(If is a bridge, we define .) 3.
The graph is either minimally 1-tough or or .
Proof.
Let be an arbitrary edge of , and let us assume that it is not a bridge. Since and is still connected, there exists a cutset in satisfying \omega\big{(}(G-e)-S\big{)}>|S|.
Now there are two cases.
Case 1: is a cutset in .
Since and is a cutset, . This is only possible if connects two components of , which means that
[TABLE]
Case 2: is not a cutset in .
Then . On the other hand,
[TABLE]
since is a cutset in . This is only possible if connects two components of , which means that
[TABLE]
Since
[TABLE]
this implies that . Moreover, since is not a bridge in . Hence,
[TABLE]
Then and for every . Let us assume that is not minimally 1-tough, i.e. . We need to show that or .
Suppose to the contrary that has at least 4 vertices. Let be an arbitrary edge, and let be a vertex set for which
[TABLE]
Since and , the vertex set cannot be a cutset in , so must hold. Since has at least 4 vertices, and one of the endpoints of form a cutset of size at most 2, so , which is a contradiction. This means that or , since there are no other 1-tough graphs on at most 3 vertices with at least one edge.
Trivial. ∎
Proposition 2.8**.**
Let be an almost minimally 1-tough graph. Then for any nonempty proper subset of .
Proof.
By Claim 2.7, the graph is either minimally 1-tough or or . If is minimally 1-tough, then , and we already covered this case in Proposition 2.1. If or , then and hold for any nonempty proper subset of . ∎
2.3 -critical graphs
First, we cite some results on -critical graphs.
Proposition 2.9** (Problem of §8 in [lovasz]).**
If is an -critical graph without isolated vertices, then every point is contained in at least one maximum independent vertex set.
Lemma 2.10** (Problem of §8 in [lovasz]).**
If we replace a vertex of an -critical graph with a clique, and connect every neighbor of the original vertex with every vertex in the clique, then the resulting graph is still -critical.
Lemma 2.11** ([lovasz_matching]).**
Let be an -critical graph and an arbitrary vertex of degree at least 2. Split into two vertices and , each of degree at least 1, add a new vertex and connect it to both and . Then the resulting graph is -critical, and .
For one of our proofs we also need the following observation, which is a straightforward consequence of Corollary 1.8 and Lemmas 2.10 and 2.11.
Proposition 2.12**.**
For any positive integers and , the following variant of the problem -Critical is DP-complete.
Instance: an -connected graph and a positive integer that is divisible by .
Question: is it true that , but for any edge ?
3 On some special cases of Theorem 1.9
This section aims to highlight the key steps of the proof of Theorem 1.9 by considering some simpler cases of it. In the view of this intention, technical details are omitted here.
Let be an integer and let be a complete graph of size on the vertex set . Add the vertices and to , and for all connect and , and also and , and let denote the obtained graph. (For an example see Figure 10 in the Appendix.) It is easy to see that is a minimally 1-tough graph, and it is due to the fact that complete graphs are -critical. This plain construction inspires all the others proposed in this paper. This construction can be generalized for -critical graphs in general to obtain a minimally 1-tough graph. (See Figure 11.) The construction for minimally integer-tough graphs can be seen as a “blow-up” of the minimally 1-tough construction. (See Figure 12.) These constructions are described in details in the following subsection.
3.1 On the case of minimally -tough graphs, where is a positive integer
Let , and be positive integers, let be an arbitrary \big{\lceil}(t+1)/2\big{\rceil}-connected graph on the vertices , and let be defined as follows. For all and let
[TABLE]
For all let
[TABLE]
and place a complete graph on its vertices. For all if , then place a complete bipartite graph on . For all and add the vertex set
[TABLE]
to the graph and place a complete graph on the vertices of . For all connect to . For all add the vertex set
[TABLE]
to the graph and for all place a complete bipartite graph on . Let
[TABLE]
See Figure 1. (For examples see Figures 11 and 12.)
Claim 3.1**.**
Let be an arbitrary \big{\lceil}(t+1)/2\big{\rceil}-connected graph. Then is -critical with if and only if is minimally 1-tough.
Proof.
The cases and should be handled separately, but since the main steps of the proofs are similar, only the (easier) case is presented here.
The proof of the following lemma is omitted now. (In Section 5 a similar lemma is proved, but for a more complex graph, see Lemma 5.6.)
Lemma 3.2**.**
If , then .
Accepting this lemma, all we have left to show is that
- –
if is -critical with , then holds for any , 2. –
if , then , and 3. –
if either but the graph is not -critical or , then there exists an edge for which .
Assume first that is -critical with . Let be an arbitrary edge. If is incident to one of the vertices of , i.e., to a vertex of degree 2, then clearly . If is not incident to any of the vertices of , then it connects two vertices of . By Lemma 2.10, the subgraph is -critical, so in there exists an independent vertex set of size . Let
[TABLE]
Then it is easy to see that
[TABLE]
hold, so .
Now assume . Then let be an independent vertex set of size in , and let
[TABLE]
Then
[TABLE]
hold, so .
Finally, assume that either but the graph is not -critical or . Then there exists an edge such that . By Lemma 3.2, the graph is 1-tough, but we can obtain from by edge-deletion, which means that is not minimally 1-tough. ∎
Corollary 3.3**.**
For any positive integer , the problem Min--Tough is DP-complete.
Proof.
In Proposition 2.4 we already proved that the problem Min--Tough is in DP, and it follows from Claim 3.1 that we can reduce -Critical to it, but for this it should be also noted that can be constructed from in polynomial time. ∎
The above construction works only in the case when is a positive integer for the simple reason that the sets , and consist of vertices.
3.2 On the case of minimally -tough graphs, where is an integer
Up to this point, we only handled the case when is a positive integer. To prove Theorem 1.9 for the noninteger cases, we modify the previous constructions and here we illustrate these modifications with the following simple example.
Let be an integer, let , let be an arbitrary connected graph, and let be defined as follows. Add independent vertices for each original vertex to the graph , and connect them to (see Figure 2). (For an example see Figure 13.)
Claim 3.4**.**
Let be an arbitrary connected graph. Then is minimally -tough if and only if is almost minimally 1-tough.
Similarly as before, we can conclude the following.
Corollary 3.5**.**
For every integer , Min--Tough is DP-complete.
In Section 6, this latter idea is extended to the case when by “gluing” some other graph to the vertices of the original graph . (See Figure 14.) It is worth noting that in the case when for some integer , the obtained graph in Section 6 is exactly the same as the graph constructed here. After this “gluing”, the vertices of become cut-vertices in the obtained graph , thus the toughness of can be at most 1/2. The plan for the cases when is to perform this so called “gluing” by identifying not only one, but vertices of a smaller and a larger graph, where the larger graph resembles a minimally -tough graph and the “gluing” procedure aims to decrease its toughness to the desired value . In fact, in Sections 4 and 5 this larger graph is chosen to be a slight modification of .
4 Minimally -tough graphs, where
Before proving Theorem 1.9 for any positive rational number , we need some preparation. First, we construct some auxiliary graphs.
4.1 The auxiliary graph when
Let be a rational number such that . Let be relatively prime positive integers such that . Let be a positive integer, and let
[TABLE]
Place a clique on the vertices of and a complete bipartite graph on . Obviously, the toughness of this complete split graph is . Deleting an edge may decrease the toughness, and now we delete edges incident to until the toughness remains at least but the deletion of any other such edge would result in a graph with toughness less than . Let denote the obtained split graph. Then , and for any edge incident to , i.e. there exists a vertex set whose removal disconnects and
[TABLE]
Now delete all the edges induced by , and let denote the obtained bipartite graph.
4.2 The auxiliary graph when
Let be a rational number such that . Let be relatively prime positive integers such that and let be constructed as follows. Let
[TABLE]
For any and connect to , and connect to and . (In other words, can be obtained from the complete bipartite graph by deleting edges incident to one vertex of the color class of size . See Figure 3.)
Claim 4.1**.**
Let be a rational number such that . Then .
Proof.
Let and let be an arbitrary cutset in . Now we show that .
Case 1: .
Then and . Since , it follows that
[TABLE]
Case 2: .
If as well, then and . Since , it follows that
[TABLE]
If , then and . Since , it follows that
[TABLE]
Case 3: and .
Then , but since is a cutset, . Obviously, there is no cut-vertex in , thus . Since , it follows that
[TABLE]
Hence . On the other hand, the vertex set is a cutset in with and , so .
Therefore, . ∎
By repeatedly deleting some edges of , eventually we obtain a minimally -tough graph, let us denote it with (i.e. if there exists an edge whose deletion does not decrease the toughness, then we delete it). Obviously, we could not delete the edges incident to , so the vertex still has degree 2. Let denote the edge connecting and and let . Note that is a bipartite graph with color classes and .
4.3 The proof of Theorem 1.9 when
Theorem 4.2**.**
For any rational number with , the problem Min--Tough is DP-complete.
Proof.
Let be a rational number such that . In Proposition 2.4 we already proved that the problem Min--Tough is in DP. To show that it is DP-hard, we reduce -Critical to it.
Let be relatively prime positive integers such that , let be an arbitrary 2-connected graph on the vertices and let be defined as follows. For all let
[TABLE]
and place a clique on the vertices of . For all if , then place a complete bipartite graph on . (This subgraph is denoted by in Figure 4.) For all “glue” the graph to the vertex by identifying with the vertex of and let denote the -th copy of and let denote the -th copy of its color class , and let and denote the -th copies of the vertices and , respectively. Let
[TABLE]
[TABLE]
and
[TABLE]
Add the vertex sets
[TABLE]
and
[TABLE]
to the graph and place the bipartite graph on . For all and connect to . See Figure 4. (For an example see Figure 15.) Now is part of the input of the problem -Critical, therefore the graph must be constructed in polynomial time and by Theorem 1.5, this can be done. On the other hand, is not part of the input of the problem Min--Tough, therefore the graph can be constructed in advance. Hence, can be constructed from in polynomial time.
To show that is -critical with if and only if is minimally -tough, first we prove the following lemma.
Lemma 4.3**.**
Let be a 2-connected graph with . Then is -tough.
Proof.
Let be a cutset in . We need to show that .
First, we show that the following assumption can be made for .
(1) .
Suppose that for some . If , then after the removal of , the vertex has degree , so there is no need to remove it. Similarly, if , then we can also assume that . If , then considering instead of decreases the number of components only by one, meaning that if is a cutset in , then it is enough to show that since it implies
[TABLE]
where the last inequality is valid since . If is not a cutset in , then and since has degree 2 and is not a cut-vertex in , i.e.
[TABLE]
where again the last inequality is valid since . This completes the validation of assumption (1).
Now there are two cases.
Case 1: .
After the removal of , the vertices of are isolated; therefore we can assume that .
To write up a formula for and , we need to introduce some notations. Let
[TABLE]
[TABLE]
for all , and
[TABLE]
for all (i,j)\in\big{(}[n]\times[ak]\big{)}\setminus C. Finally, let
[TABLE]
Using these notations it is clear that
[TABLE]
By the assumption that , in the vertices of are isolated. Since \alpha\big{(}G_{t,k}[V]\big{)}=\alpha(G), the removal of from leaves at most components. By Claim 4.1 and Proposition 2.1, for any the removal of from leaves at most components. By Proposition 2.1, for any the removal of from leaves at most components, but the component of has been already counted. Hence
[TABLE]
using that .
Case 2: .
Assume that for some . In this case, using assumption (1), we can also assume the following.
(2) There exists at most one for which .
Suppose that for some . By assumption (1), the component of contains all of the vertices . Now considering the cutset instead of increases the number of components by at least two: it disconnects both and from the vertices \big{\{}u_{i,j_{0}}\bigm{|}i\in[n]\setminus\{i_{1},i_{2}\}\big{\}}, and it also disconnects from (and of course it can also disconnect other vertices of \big{\{}u_{i,j_{0}}\bigm{|}i\in[n]\big{\}} from each other). Then it is enough to show that since it implies
[TABLE]
where the last inequality is valid since . Proceeding further, we can obtain a cutset for which holds; and such sets were already handled in Case 1.
(3) is connected.
By assumption (2), there exists at most one for which . Since is 2-connected, this implies that is connected.
(4) There exists at most one for which and belong to different components in .
Suppose that belong to different components in , and so do for some . Similarly as in the proof of assumption (2), considering the cutset instead of increases the number of components by at least two, so it is enough to show that .
(5) In all the remaining vertices of \big{\{}v_{i,j_{0}},u_{i,j_{0}}\bigm{|}i\in[n]\big{\}} belong to the component of .
It follows directly from assumptions (1), (2) and (3).
(6) In all the remaining vertices of belong to the component of .
It follows directly from assumptions (3) and (5).
(7) In all the remaining vertices of belong to the same component.
It follows directly from assumptions (5) and (6).
By assumption (7), in there is a component containing all the remaining vertices of , and every other component is either an isolated vertex of (since is a bipartite graph) or a component of H^{i,j}-\big{(}V(H^{i,j})\cap S\big{)} for some . Hence we can also assume the following.
(8) .
By assumption (5) and Proposition 2.1 and the properties of , the removal of from leaves at most components, but the component of has been already counted.
Using the previous notations,
[TABLE]
and
[TABLE]
This means that . ∎
Now we return to the proof of Theorem 4.2 and we show that is -critical with if and only if is minimally -tough.
Let us assume that is -critical with . By Lemma 4.3, the graph is -tough, i.e. .
Let be an independent vertex set of size in .
Recall the definition of from the beginning of the proof: it is the color class in the corresponding copy of . Let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and
[TABLE]
so .
Therefore, .
Let be an arbitrary edge. We need to show that . Now we have four cases.
Case 1: has an endpoint in .
Then this endpoint has degree 2, so .
Case 2: has an endpoint in .
By the properties of , there exists a cutset in for which
[TABLE]
Note that is also a cutset in and
[TABLE]
so .
Case 3: is induced by for some .
By Proposition 2.5, there exists a vertex set for which
[TABLE]
Consider the -th copy of the vertex set in ; let us denote it with . If , then is a cutset in and
[TABLE]
so . Now assume that . Let be an independent vertex set of size in that contains (by Proposition 2.9, such an independent vertex set exists). Let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and
[TABLE]
so .
Case 4: connects two vertices of .
By Lemma 2.10, the graph is -critical, so in there exists an independent vertex set of size . Let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and
[TABLE]
so .
Therefore, if is -critical with , then is minimally -tough.
Now let us assume that is not -critical with , i.e. either or even though , the graph is not -critical.
Case I: .
Let be an independent vertex set of size in and let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and
[TABLE]
so , which means that is not minimally -tough.
Case II: .
Since is not -critical with , there exists an edge such that . By Lemma 4.3, the graph is -tough, but it can be obtained from by edge-deletion, which means that is not minimally -tough. ∎
5 Minimally -tough graphs, where
This whole section resembles the previous one in structure. However, it requires some additional ideas that make the proofs more complicated. First, again, we construct some auxiliary graphs.
Let be a rational number. It is easy to see that either or . Let ,
[TABLE]
and
[TABLE]
Let be the smallest positive integers such that and .
5.1 The auxiliary graph when
Let be a positive integer that is divisible by . Note that in this case
[TABLE]
is a positive integer. Let
[TABLE]
and
[TABLE]
Place a clique on the vertices of and a complete bipartite graph on . Obviously, the toughness of this complete split graph is
[TABLE]
Deleting an edge may decrease the toughness, and now we delete edges incident to until the toughness remains at least but the deletion of any other such edge would result in a graph with toughness less than . Let denote the obtained split graph. Then , and for any edge incident to , i.e. there exists a vertex set whose removal disconnects and
[TABLE]
Now delete all the edges induced by , and let denote the obtained bipartite graph.
5.2 The auxiliary graph when
Let be constructed as follows. Let
[TABLE]
[TABLE]
[TABLE]
[TABLE]
and
[TABLE]
Place a clique on the vertices of , , , and . For all connect to and to , and connect to . Connect all the vertices of to all the vertices of , and connect all the vertices of to all the vertices of . Finally, add a new vertex to the graph and connect it to all the vertices of . See Figure 5.
Claim 5.1**.**
For any rational number the graph has weighted toughness with respect to the weight function that assigns weight 1 to all the vertices of except for the vertex , to which it assigns weight .
Proof.
Let be an arbitrary cutset of . We need to show that .
We can assume that either or since removing only a proper subset of does not disconnect anything from the graph. Similarly, we can also assume that either or .
Case 1: and .
Then has at most 2 components, and to obtain 2 components, the following must hold:
- –
or for all , and 2. –
or .
Hence and
[TABLE]
Case 2: and .
Now we can assume that since after the removal of removing does not disconnect anything from the graph. Similarly, we can also assume that . Then has at most 3 components. To obtain three components, the following must hold:
- (i)
or for all (but ), and 2. (ii)
.
Hence and
[TABLE]
To obtain two components, either (i) or (ii) must hold; in both cases and
[TABLE]
Case 3: .
First we show that the following assumptions can be made for .
(1) .
After the removal of , removing any of the vertices of does not disconnect anything from the graph.
(2) There exists at most one for which , i.e. .
Suppose that there exist for which and . By assumption (1), considering the cutset instead of increases both the number of components and the weight of the removed vertex set by 1. Hence it is enough to show that
[TABLE]
since it implies
[TABLE]
where the last inequality is valid since .
(3) For all if , then .
After the removal of and removing does not disconnect anything from the graph.
(4) For all if , then .
Suppose that there exists for which . By assumption (1), considering the cutset instead of increases both the number of components and the weight of the removed vertex set by 1. Hence, similarly as in assumption (2), it is enough to show that
[TABLE]
(5) \big{|}(V^{\prime}_{1}\cup V^{\prime\prime})\cap S\big{|}=T.
It follows directly from assumptions (3) and (4).
Case 3.1: ( and) .
Now we can assume that since after the removal of removing does not disconnect anything from the graph. Similarly, by assumption (2), we can also assume that , i.e. . Hence
[TABLE]
and every component of contains exactly one of the vertices , i.e.
[TABLE]
Case 3.2: ( and) .
In this case we can make some further assumptions for .
(6) If , then .
After the removal of removing does not disconnect anything from the graph.
(7) If , then .
Suppose that . Then considering the cutset instead of increases the number of components by 1 and the weight of the removed vertex set by . Hence it is enough to show that since it implies
[TABLE]
(8) .
Suppose that . Then by assumption (2), there exists for which . But by assumption (1), considering the cutset instead of increases both the number of components and the weight of the removed vertex set by 1. Then, similarly as in assumption (2), it is enough to show that .
Case 3.2.1: (, and) .
Hence
[TABLE]
and
[TABLE]
Case 3.2.2: (, and) .
Hence
[TABLE]
and
[TABLE]
Therefore is weighted -tough with respect to (meaning that the weighted toughness of is at least ).
Consider the cutset
[TABLE]
Since and
[TABLE]
the weighted toughness of with respect to is at most .
Thus the weighted toughness of with respect to is exactly . ∎
Deleting an edge may decrease the weighted toughness, and now we delete edges not induced by until the weighted toughness with respect to the weight function remains at least but the deletion of any other edge not induced by would result in a graph with weighted toughness less than . Let denote the obtained graph.
According to the following claim we could not delete the edges induced by or incident to any of the vertices of .
Claim 5.2**.**
Let be a rational number. For any edge induced by or incident to any of the vertices of , there exists a cutset in for which
[TABLE]
Proof.
Let be an arbitrary edge induced by or incident to any of the vertices of .
Case 1: is incident to a vertex of .
Let denote one of the endpoints of , and let denote the other one. Let be the neighborhood of the vertex except for . Since has degree and all of its neighbors have weight 1,
[TABLE]
Since the removal of from leaves the vertex isolated,
[TABLE]
Case 2: is incident to a vertex of .
If is incident to a vertex of , then either it is incident to a vertex of and this case was already settled in Case 1, or it is induced by and therefore it was not allowed to be deleted.
Case 3: is induced by , i.e. for some , .
Then
[TABLE]
is a cutset in such that
[TABLE]
and
[TABLE]
∎
Claim 5.3**.**
Let be a rational number and . Then the following hold.
- (i)
The graph is connected. 2. (ii)
For any cutset of ,
[TABLE] 3. (iii)
If holds for a cutset of , then
[TABLE] 4. (iv)
For any edge not induced by there exists a vertex set whose removal from disconnects the graph and
[TABLE]
Proof.
- (i)
Suppose to the contrary that is not connected. Then is a cut-vertex in . Since the weighted toughness of with respect to is ,
[TABLE]
which is a contradiction. 2. (ii)
Let be an arbitrary cutset of . Since is a cutset in , the vertex set is a cutset in , and
[TABLE] 3. (iii)
Let be a cutset of for which . We can assume that since removing any of the vertices of from does not disconnect anything from the graph. Then all the neighbors of the vertex belong to the same component in , so is a cutset in as well and
[TABLE]
where the last equality is valid since . 4. (iv)
Let be an arbitrary edge not induced by . Then by the properties of , there exists a vertex set whose removal from disconnects the graph and
[TABLE]
where the last inequality is valid since . Let . Then
[TABLE]
∎
5.3 The cutsets and in when
Let
[TABLE]
and for all let
[TABLE]
Proposition 5.4**.**
The sets and are all cutsets in and
[TABLE]
and
[TABLE]
for all .
Proof.
It is easy to see that
[TABLE]
and
[TABLE]
∎
5.4 The proof of Theorem 1.9 when
Theorem 5.5**.**
For any rational number , the problem Min--Tough is DP-complete.
Proof.
Let be a rational number. In Proposition 2.4 we already proved that the problem Min--Tough is in DP. To show that it is DP-hard, we reduce the variant of -Critical defined in Proposition 2.12 to it.
Let , and , and M=\big{\lceil}2\lceil t\rceil/\lceil 2t\rceil\big{\rceil} as before. Let be the smallest positive integers such that and , let be an arbitrary -connected graph on the vertices with , let be a positive integer that is divisible by and let be defined as follows. For all let
[TABLE]
For all let
[TABLE]
and place a clique on the vertices of . For all if , then place a complete bipartite graph on . (This subgraph is denoted by in Figure 6.) For all “glue” the graph to the vertex set by identifying with the vertex of for all . For all let , and denote the -th copies of , and , respectively. For all let denote the -th copy of , and for all let denote the -th copy of . For all add the vertex set
[TABLE]
to the graph and for all connect to . Let
[TABLE]
and let
[TABLE]
Add the vertex set
[TABLE]
to the graph and place the bipartite graph on . See Figure 6. Now is part of the input of the problem -Critical, therefore the graph must be constructed in polynomial time and by Theorem 1.5, this can be done. On the other hand, is not part of the input of the problem Min--Tough, therefore the graph can be constructed in advance. Hence, can be constructed from in polynomial time.
To show that is -critical with if and only if is minimally -tough, first we prove the following lemma.
Lemma 5.6**.**
Let be an arbitrary -connected graph on vertices with . Then is -tough.
Proof.
Let be a cutset in . We need to show that .
Case 1: .
After the removal of , the vertices of are isolated, therefore we can assume that .
Let
[TABLE]
[TABLE]
for all , and
[TABLE]
for all (i,j,m)\in\big{(}[n]\times[k]\times[M]\big{)}\setminus C. Let
[TABLE]
Using these notations it is clear that
[TABLE]
By the assumption that , in the vertices of are isolated. Since \alpha\big{(}G_{t,k}[V]\big{)}=\alpha(G), the removal of from leaves at most components. By Claim 5.3, for any the removal of from leaves at most
[TABLE]
components. By Claim 5.3, for any the removal of from leaves at most
[TABLE]
components, but the component of the remaining vertices of has been already counted. Hence
[TABLE]
Case 2: .
There are four types of components in :
- (a)
components containing at least one vertex of , 2. (b)
components containing at least one vertex of but no vertices of , 3. (c)
components containing at least one vertex of but no vertices of , 4. (d)
isolated vertices of .
Let be fixed. First we show that the following assumptions can be made for .
(1) .
Obviously, the number of vertices of that belong to a component of type (c) is at most . Since the neighborhood of any vertex of spans a clique in , considering the cutset
[TABLE]
instead of can only increase the number of components of types (a), (b) and (d), while it decreases the number of components of type (c) to 0, i.e., by at most . Hence,
[TABLE]
and
[TABLE]
Then it is enough to prove that since it implies
[TABLE]
where the last inequality is valid since .
(2) There are no components of type (c) in .
It follows directly from assumption (1).
(3) \big{|}\{i\in[n]\mid V_{i,j_{0},m_{0}}\subseteq S\}\big{|}\leq\lceil T^{\prime}/t\rceil.
Let
[TABLE]
and suppose that . By assumption (1), the component of contains every vertex of and therefore all the remaining vertices of . Now considering the cutset
[TABLE]
instead of increases the number of removed vertices by at most , and it increases the number of components by at least since it disconnects the vertex sets , from each other. Then it is enough to show that since it implies
[TABLE]
Proceeding further, we can obtain a cutset for which holds; and such sets were already handled in Case 1.
(4) is connected, i.e. there is only one component of type (a).
Since ,
[TABLE]
Since is 3-connected, assumption (2) implies that is connected.
Using the previous notations,
[TABLE]
By assumption (2), there are no components of type (c), and by assumption (4), there is only one component of type (a). By the properties of , the removal of from leaves at most
[TABLE]
components, one of them is the component of , hence there are at most
[TABLE]
components of type (d). Similarly as before, for any the removal of from leaves at most
[TABLE]
components, all of which can be of type (b). For any the removal of from leaves at most
[TABLE]
components; the component of the remaining vertices of is of type (a), all the others can be of type (b). By assumption (1), all the vertices of belong to the component of , hence the component of has been counted multiple times (more than once). Therefore,
[TABLE]
Thus, . ∎
Now we return to the proof of Theorem 5.5 and we show that is -critical with if and only if is minimally -tough.
Let us assume that is -critical with . By Lemma 5.6, the graph is -tough, i.e. .
Let be an independent vertex set of size in , and recall the definition of the sets and constructed in Subsection 5.3. Let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and after the removal of from , the vertices of are isolated and the other components of are exactly the components of H^{i,j,m}-\big{(}S\cap V(H^{i,j,m})\big{)} for all . By Proposition 5.4,
[TABLE]
and
[TABLE]
for all . Since and
[TABLE]
it follows that
[TABLE]
so .
Therefore, .
Let be an arbitrary edge. We need to show that . Now we have four cases.
Case 1: has an endpoint in .
Then this endpoint has degree in , so
[TABLE]
Case 2: has an endpoint in .
By the properties of , there exists a cutset in for which
[TABLE]
Note that is also a cutset in and
[TABLE]
so .
Case 3: is induced by for some .
The case when is induced by was already covered in Case 1. So assume that is not induced by . Then by Claim 5.3, there exists a vertex set for which
[TABLE]
Consider the -th copy of the vertex set in ; let us denote it with . If , then is a cutset in and
[TABLE]
so . Assume that . Let be an independent vertex set of size in that contains (by Proposition 2.9, such an independent vertex set exists). Let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and similarly as before,
[TABLE]
so .
Case 4: connects two vertices of .
Since the case when is induced by for some was settled in Case 3, we can assume that there do not exist for which is induced by . By Lemma 2.10, the graph is -critical, so in there exists an independent vertex set of size . Let
[TABLE]
[TABLE]
and
[TABLE]
By the assumption that there do not exist for which is induced by ,
[TABLE]
so
[TABLE]
is a (well-defined) cutset in . Then
[TABLE]
and similarly as before,
[TABLE]
so .
Now let us assume that is not -critical with , i.e. either or even though , the graph is not -critical.
Case I: .
Let be an independent vertex set of size in . Let
[TABLE]
and
[TABLE]
Then is a cutset in with
[TABLE]
and similarly as before,
[TABLE]
so , which means that is not minimally -tough.
Case II: .
Since is not -critical with there exists an edge such that . By Lemma 5.6, the graph is -tough, but it can be obtained from by edge-deletion, which means that is not minimally -tough. ∎
Therefore the problem Min--Tough is DP-complete, so by Claim 2.7, we can conclude the following.
Corollary 5.7**.**
Recognizing almost minimally 1-tough graphs is DP-complete.
Let Almost-Min--Tough denote the problem of determining whether a given graph is almost minimally 1-tough.
6 Minimally -tough graphs with
The case when is special in some sense: graphs with toughness at most can have cut-vertices. Unlike in the previous cases, we reduce Almost-Min--Tough to this problem. But first, again, we construct an auxiliary graph.
6.1 The auxiliary graph when
Let be a positive rational number. Let be relatively prime positive integers such that and let be constructed as follows. Let
[TABLE]
Place a clique on the vertices of , connect every vertex of to every vertex of , and connect to for all . See Figure 7.
Proposition 6.1**.**
Let be a positive rational number. Then .
Proof.
Let be an arbitrary cutset of . We can assume that since removing any of the vertices of does not disconnect anything in the graph. Then , so
[TABLE]
which implies that
[TABLE]
∎
By repeatedly deleting some edges of , eventually we obtain a minimally -tough graph; let us denote it with (i.e. if there exists an edge whose deletion does not decrease the toughness, then we delete it). Obviously, we could not delete the edges between and , so the vertices of still have degree 1 in .
Note that is a tough set of . For further reference (to avoid confusion with other sets denoted by ), we introduce a new name for it.
Notation 6.2**.**
Let denote the tough set in .
6.2 “Gluing”
Definition 6.3**.**
Let be a graph with a vertex of degree 1, and let be the neighbor of . Let be an arbitrary graph, and “glue” separately to all vertices of by identifying each vertex of with . Let denote the obtained graph. (See Figure 8.)
6.3 The proof of Theorem 1.9 when
Theorem 6.4**.**
For any positive rational number , the problem Min--Tough is DP-complete.
Proof.
Let be a positive rational number. In Proposition 2.4 we already proved that the problem Min--Tough is in DP. To show that it is DP-hard, we reduce Almost-Min--Tough to it.
Let be an arbitrary graph and . Consider the graph and let be an arbitrary vertex of having degree 1, and let be its neighbor. Let
[TABLE]
and let denote the -th copy of “glued” to the vertex for all . (For examples see Figures 13 and 14.)
Now we show that is almost minimally 1-tough if and only if is minimally -tough.
First, let be almost minimally 1-tough. We need to show that is minimally -tough.
Let be an arbitrary cutset of . Let
[TABLE]
[TABLE]
for all , and
[TABLE]
for all (see Figure 9). Finally, let
[TABLE]
Using these notations it is clear that
[TABLE]
By Proposition 2.8, the removal of from leaves at most components. By Proposition 2.1, the removal of from leaves at most components. But for all we have already counted the component of which contains , and for all we do not need to count the component of . Hence
[TABLE]
which means that .
Now let be a tough set of . Since has degree 1, we can assume that . Let be the first copy of . Obviously, is a cutset in , and
[TABLE]
which means that .
Therefore, .
Let be an arbitrary edge. We need to show that for all . Now we have two cases.
Case 1: .
If is a bridge in , then . So assume that is not a bridge in . Let be a vertex set in guaranteed by Claim 2.7, and for all let be the -th copy of the tough set defined in Notation 6.2. (Note that and .) Let
[TABLE]
and consider the vertex set
[TABLE]
Then is a cutset in with
[TABLE]
and
[TABLE]
which means that .
Case 2: for some .
If is a bridge in , then . So assume that is not a bridge in and let be a vertex set in guaranteed by Proposition 2.5. Again, since has degree 1, we can assume that . Let be the -th copy of . Obviously, is a cutset in and
[TABLE]
which means that .
Therefore, the graph is minimally -tough.
Now we show that if is minimally -tough, then is almost minimally 1-tough.
First, we prove that . Suppose to the contrary that . Obviously, must be connected (otherwise ), so there exists a cutset in satisfying
[TABLE]
For all let be the -th copy of the tough set defined in Notation 6.2. (Note that and .) Let
[TABLE]
and consider the vertex set
[TABLE]
Then is a cutset in with
[TABLE]
and
[TABLE]
which means that and that is a contradiction. So .
Now we prove that for all . Let be an arbitrary edge. If is a bridge in , then . Let us assume that is not a bridge in . Then is not a bridge in either. Let be a vertex set guaranteed by Proposition 2.5. Consider the vertex set . Since is a bridge in as well, is a cutset in . Let
[TABLE]
[TABLE]
for all and
[TABLE]
for all . Let
[TABLE]
Then
[TABLE]
must hold, otherwise, similarly as before,
[TABLE]
which is a contradiction. So .
Therefore, is almost minimally 1-tough. ∎
7 Conclusion
In this paper we proved that recognizing minimally -tough graphs is DP-complete for any positive rational number . On the other hand, in [spec_graphclasses] we proved that in some special graph classes, this problem belongs to P:
- –
in the class of split graphs, 2. –
in the class of claw-free graphs when , and 3. –
in the class of -free graphs.
These results are not really surprising since the toughness of split, or claw-free, or -free graphs can be computed in polynomial time, see [split_general], [clawfree], and [2K2], respectively.
It is also known that recognizing -tough bipartite graphs is coNP-complete for any positive rational number , see [recognize_toughness_bipartite] and [exact_toughness], but determining the complexity of recognizing minimally -tough, bipartite graphs is still open.
Acknowledgment
The research of the first author was supported by National Research, Development and Innovation Office NKFIH, K-116769 and K-124171, by the National Research, Development and Innovation Fund (TUDFO/51757/2019-ITM, Thematic Excellence Program), and by the Higher Education Excellence Program of the Ministry of Human Capacities in the frame of Artificial Intelligence research area of Budapest University of Technology and Economics (BME FIKP-MI/SC). The research of the second author was supported by National Research, Development and Innovation Office NKFIH, K-111827. The research of the third author was supported by National Research, Development and Innovation Office NKFIH, K-124171.
Appendix
References
