Structural Parameterizations of
Simultaneous Planarity
Abstract
Given a set of graphs on the same vertex set, the problem Simultaneous Embedding With Fixed Edges (SEFE) asks, whether there exist planar drawings of all input graphs, such that every pair of drawings coincides on their shared subgraph. It is known that SEFE is -complete [32], even in the so-called sunflower case, where all pairs of input graphs have the same shared graph [57]. Fink, Pfretzschner, and Rutter [26] recently initiated the study of the parameterized complexity of SEFE in the sunflower case, mainly focusing on structural parameters of . In this work, we shift the focus towards parameters of the union graph that contains the edges of all input graphs. On the positive side, we establish fixed-parameter tractability for the problem with respect to the feedback edge set number of . We complement this result by showing that it, surprisingly, remains -complete even if has constant vertex cover number. These results settle two open questions posed by Fink et al. [26].
Keywords and phrases:
SEFE, Simultaneous Planarity, Fixed-Parameter Tractability, NP-hardnessCopyright and License:
Ignaz Rutter; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Mathematics of computing Graph algorithmsFunding:
Thomas Depian, Simon D. Fink, Alexander Firbas, and Robert Ganian acknowledge support from the Vienna Science and Technology Fund (WWTF) [10.47379/ICT22029]. Simon D. Fink and Robert Ganian also acknowledge support from the Austrian Science Fund (FWF) [10.55776/Y1329 and 10.55776/COE12]. Matthias Pfretzschner and Ignaz Rutter acknowledge support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [541433306].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
The task of computing a plane drawing of a graph – or determining that none exists – has had a fundamental and broad impact on the field of theoretical computer science. An important reason why plane drawings are desirable is that they give rise to more easily readable visualizations of graphs [50, 51]. Nevertheless, in many scenarios we are faced with the issue that there isn’t a single graph we would need to visualize, but rather a (possibly small) set of planar graphs that do, however, share some of their edges and vertices. Examples where this occurs include, among others, the case of dynamic networks that change over time or can be the result of attempting to reconstruct the same underlying network using different methods. Our input is thus a sequence of graphs , for which we want to compute a corresponding sequence of planar drawings . It is, however, not enough to independently compute these drawings. In order to allow a user to compare the graphs by studying the sequence of drawings, it is important that the drawing is stable so that commonalities and difference can be easily observed. The problem Simultaneous Embedding with Fixed Edges models this by requiring that any vertex or edge that occurs in two of the graphs is represented in the same way (i.e., by the same point resp. by the same curve) in and . This problem is known to be -complete for [32] and despite significant research effort, the complexity of the problem is still open in the case .
An important special case of this problem is the sunflower case, where it is assumed that the intersection graph is the same for all . In this case, there is a single graph , called the shared graph, that is contained in each input graph , . Then, the vertices and edges of are called shared, whereas the vertices and edges that are contained in but do not belong to are called exclusive and they cannot occur in any input graph with . We refer to instances with this property as sunflower instances and to the corresponding problem as sunflower SEFE (or S-SEFE for short). Observe that for , all instances of SEFE are sunflower instances. Without loss of generality, the exclusive vertices can be added to the shared graph (by adding them as isolated vertices to all other input graphs). We thus assume throughout that all our input graphs share the same vertex set . A natural way to represent such sunflower instances of SEFE is by their union graph, , whose vertex set is and whose edge set is partitioned into sets , where contains the shared edges and , contains the exclusive edges of . It is readily seen that a sunflower instance of SEFE admits a solution if and only if its union graph admits a drawing such that for each , no pair of curves representing edges from crosses. An illustration of the problem is provided in Figure 1.
Jünger and Schulz [41] showed that, in this setting, the problem can be formulated purely combinatorially. Namely, it is equivalent to finding (combinatorial) planar embeddings of the input graphs that induce the same planar embedding on the shared graph. Here, two planar embeddings are considered the same if they have the same rotation system and the same relative positions of their connected components. This establishes a link to the partial drawing extension problem, which asks whether a given drawing (or equivalently a planar embedding) of a subgraph of an input graph can be extended to a planar drawing (or equivalently a planar embedding) of the complete graph without changing . In particular, S-SEFE is equivalent to deciding whether the shared graph admits a planar embedding that can be independently extended to each input graph .
The idea of simultaneous drawings and the extension of partial drawings readily generalize other types of graph representations such as geometric intersection and contact representations. This includes, among others, (several subclasses of) interval graphs [38, 54, 55, 56, 44, 43, 45], comparability and (circular) permutation graphs [39, 42, 49], circle graphs [19, 16], and circular-arc graphs [25], which have received considerable attention in the last years. Moreover, different drawing styles have been considered such as level-planar [3, 15] or orthogonal drawings [2, 6]. Moreover, fixed-parameter algorithms for drawing extension problems, often parameterized by the number of vertices and/or edges that still need to be added, have received considerable attention in recent years [23, 31, 9, 22] albeit the techniques developed there do not seem readily transferable to SEFE.
Since its introduction in 2005 [24], the SEFE problem has been the subject of substantial research efforts over the last two decades. SEFE is known to be -complete even for input graphs [32] and this extends to the sunflower case [57] even in the case where the shared graph is a tree [4]. The case is open and there is a plethora of work that aims at solving increasingly general special cases. Angelini, Di Battista, Frati, Jelínek, Kratochvíl, Patrignani and Rutter [5] show that S-SEFE can be solved in linear time if the embedding of the shared graph is fixed. For this case, also a full Kuratowski-type characterization of the positive instances has been given [40]. While there exist attempts to generalize such characterizations [36, 18], they seem to be inherently restricted to the biconnected case. More generally, when the embedding of the shared graph is not fixed, S-SEFE can be solved in linear time if the shared graph is biconnected [1, 35], if all connected components of the shared graph are cycles [14] and even if each connected component of the shared graph is biconnected or has maximum degree 3 [12, 57]. Most recently, it has been established that SEFE admits a polynomial-time algorithm for if the shared graph is connected [28, 10, 27]. We refer to the surveys [13, 53] for a more detailed overview.
In this work, we target instances of S-SEFE beyond the case of . A major motivation for our results is the work of Fink, Pfretzschner and Rutter [26], who initiated the study of parameterized algorithms capable of solving such instances. The central question underlying their work – as well as a plethora of other studies within the domain of parameterized algorithmics – is whether we can identify one or several parameters of the input such that every instance of S-SEFE can be solved in time . Algorithms exhibiting such runtime behavior are called fixed-parameter (with respect to )111We assume familiarity with the basic foundations of parameterized complexity theory, notably including the notions of fixed-parameter tractability, kernelization, and para-hardness [21].. Their main results included fixed-parameter algorithms for S-SEFE parameterized (1) by plus the vertex cover number (i.e., the minimum size of a vertex cover) of , and (2) by plus the feedback edge number (i.e., the minimum size of a feedback edge set) of . In spite of these results – and a number of supplementary results targeting the structure of the shared graph – many prominent gaps remain in our understanding of the parameterized complexity of SEFE. Two questions explicitly identified by Fink, Pfretzschner and Rutter were [26, Section 5]:
-
(A)
Can the parametric dependence on be avoided in fixed-parameter algorithm (1)?
-
(B)
Can the parametric dependence on be avoided in fixed-parameter algorithm (2)?
Contributions.
We expand our understanding of the complexity of S-SEFE by settling both open questions listed above. As our first result, we answer Question (A) in the negative and prove:
Theorem 1.
S-SEFE remains -complete even when restricted to instances where has vertex cover number at most .
The reduction underlying the proof of Theorem 1 is non-trivial and apart from a careful construction, it also relies on Vizing’s Theorem [58] and the edge coloring machinery introduced by Misra and Gries [48]. For our second result, we turn towards Question (B) which we answer positively:
Theorem 2.
S-SEFE is fixed-parameter tractable when parameterized by the feedback edge number of alone, and in particular admits a linear kernel under this parameterization.
We note that here a linear kernel means that we provide a polynomial-time procedure that reduces an instance of S-SEFE to an equivalent one whose size is linear in the feedback edge number of the union graph . The result strictly improves upon the previously established kernel of Fink, Pfretzschner and Rutter [26], whose size depended both on the feedback edge number and .
In our concluding discussion, we also provide new insights into the complexity-theoretic behavior of S-SEFE (and also SEFE) under other graph parameters. Notably, we rule out parameterized algorithms w.r.t. the graph degeneracy of the union graph, and establish an equivalence between treewidth and clique-width in the sense that algorithms and lower bounds for the considered problems transfer between these two parameters.
2 Preliminaries
Let be a simple graph. If there exists a path between every pair of vertices of , then is connected. A connected component of is a maximal induced subgraph of that is connected. A cut-vertex of is a vertex whose removal disconnects . A drawing of assigns every vertex to a coordinate and every edge to a simple arc between and . The drawing is planar if no two distinct arcs intersect at an interior point. A graph is planar if it admits a planar drawing. Every planar drawing of uniquely defines a rotation system, i.e., the clockwise circular ordering of the incident edges (and, hence, also of the adjacent vertices) for each vertex. Moreover, partitions the plane into regions called faces. If is disconnected, additionally defines relative positions for the connected components of , that is an assignment of each connected component to a unique face of every other connected component. A planar embedding of is an equivalence class of planar drawings of that induce the same rotation system and the same relative positions.
Let be an instance of S-SEFE. Recall that we consider the sunflower case, where all pairs of input graphs have the same shared graph . A tuple of planar drawings of is a simultaneous drawing of if each induces the same drawing on . Note that is a positive instance of S-SEFE if and only if admits a simultaneous drawing. We refer to a tuple of planar embeddings of as a simultaneous embedding of if each induces the same embedding on . Jünger and Schulz [41, Theorem 4] showed that, for , the existence of a simultaneous drawing is equivalent to the existence of a simultaneous embedding. This can be straightforwardly extended to in the sunflower case by successively applying their construction to each pair of input graphs. In this paper, we thus mainly work with simultaneous embeddings instead of drawings. We define and . For a (not necessarily induced) subgraph of , we define and .
For a graph , a set is a vertex cover of if every edge of is incident to a vertex in . The vertex cover number is the size of a minimum vertex cover of . A feedback edge set of is a set whose removal makes acyclic. The feedback edge set number is the size of a minimum feedback edge set of .
A directed graph is acyclic precisely when its vertices admit an ordering such that every arc satisfies . Such an ordering is referred to as a topological ordering of . The underlying undirected graph of a directed graph is the simple graph obtained by removing the direction of every edge of .
3 ParaNP-hardness w.r.t. Vertex Cover of the Union Graph
In this section, we derive Theorem 1, that is, S-SEFE remains -complete even when restricted to instances where has vertex cover number at most .
We achieve this via a reduction from 2-Digraph Coloring. The problem asks whether, for a directed graph , there exists a 2-partition of its vertices , such that both and are acyclic. The problem remains -complete even if has maximum degree 6 [37, Theorem 1]; this fact will be central to our construction. Let be such an instance; we compute our reduction as follows.
We aim to construct an instance of S-SEFE . We assume without loss of generality that contains no self-loops, for if contains a self-loop, is a trivial negative instance and we can output a trivial negative instance of S-SEFE. For each arc , contains a separate input graph. To simplify the presentation, we will index the input graphs with the arcs of rather than with the integers in this section.
To build our instance, we will first describe how to construct the shared graph and then describe, for each input graph, how to extend to form the completed instance . (Technically, as the symbol is only well defined if the underlying instance fulfills the sunflower property, we first define an auxiliary graph , extend this graph to obtain each input graph, and then argue that the so-obtained instance fulfills the sunflower property, where in particular, (Lemma 3)). Note that in our construction, we require the edge coloring algorithm of Misra and Gries [48] specifically to enable the proof of Lemma 3.
We let be a cycle of length 15 with vertices (which will form a vertex cover of size 15 of ), where has pendant vertices. The vertex set of the constructed instance is , where each identifies one pendant vertex of .
The intuition for our construction is as follows: Each pendant vertex of needs to be drawn either “inside” or “outside” the shared cycle. This models the 2-partition of 2-Digraph Coloring. Moreover, for each arc , we define an input graph extending that forces that, if and are drawn both “inside” or both “outside” the cycle, in the cyclic order of vertices around , going from “towards” the respective face (“inside” vs “outside”), needs to appear before , as otherwise this input graph would need to be drawn with a crossing. This models that the subgraphs induced by either partition can be sorted topologically, that is, they are acyclic. See Figure 2 for an example of the reduction and Figure 3 for an example of how a solution of 2-Digraph Coloring corresponds to a simultaneous embedding and vice versa.
Next, we construct the input graph for each . We first add all edges from , and then proceed to add two additional edges as follows. We select two cycle vertices and add the edges to , where is a map from to which we will define later. We call such an adjacent pair of cycle vertices, selected by , a register. Note that there are 7 registers in total: .
To compute , that is, assign each arc of a register, we compute an edge coloring (that is, an assignment of edges to colors such that adjacent edges are assigned different colors) of the undirected graph underlying , which we will call . In particular, this means that if two arcs share an endpoint, they are assigned different registers, except if they form a 2-cycle: then, they are assigned a common register.
As has a maximum degree of 6, so does . By Vizing’s theorem [58], admits an edge coloring using at most 7 colors. Using the algorithm of Misra and Gries [48], we can compute such a coloring in polynomial time. We identify each of the at most 7 colors with a unique register. Formally, if the edge coloring assigns arc register , we set .
This concludes the construction of our instance . Before we establish the correctness of our reduction, we show:
Lemma 3.
Instance obeys the sunflower property, where in particular, .
Proof.
We need to show that for each , implying that is well-defined and equal to . Suppose not.
By construction, as is a subgraph of and , and the codomain of consists of even integers, this means or .
First, consider the case where form a 2-cycle. Then, we have , and . In case we have , this means , i.e., arc is a self-loop. As does not have self-loops, this is a contradiction. Alternatively, in case we have , this means , which again means has a self-loop, a contradiction.
Otherwise do not form a 2-cycle. First, if , we have and . But then, both and are neighbors of in . Additionally, , since otherwise, the two arcs would form a 2-cycle. Thus the edge coloring assigns and different colors, which contradicts . The other case, , is symmetric.
To make the notion of how to “read off” a topological ordering of neighbors in a simultaneous embedding precise, we define:
Definition 4.
The -oriented, -delimited split of a cyclic permutation where is given by the left-face total order , and the right-face total order , where subscripts are interpreted modulo .
Next, we make an observation that will help us prove the correctness of our reduction. Essentially, we have that each possible embedding of tells us into which set of the 2-partition to assign and , and a guarantee that, if we assign them to the same set, the order in which we will “read off” their ordering will be consistent with there being an arc in the given 2-Digraph Coloring instance.
Observation 5.
Let . The set of planar embeddings of is given by the set specified in Figure 4. Furthermore, for all planar embeddings of , we have that in both the left-face as well as the right-face total order of the -oriented -delimited split of the rotation around , if both and are contained in the respective order, we have .
Now, we can show:
Lemma 6.
The reduction is correct, that is, is a positive instance of 2-Digraph Coloring if and only if is a positive instance of S-SEFE.
Proof.
Let be a partition of such that as well as are acyclic, and let and be a topological ordering of and , respectively, where we call the former the left order and the latter the right order.
Towards finding a simultaneous embedding of the S-SEFE instance, we first fix a planar embedding of . As is connected, it suffices to specify a rotation system. Note that, as is just a cycle with pendant vertices attached to , any rotation system for yields a planar embedding. For each where , has only two neighbors and hence, there is only one choice for ’s rotation. For , we define the following clockwise cyclic order of :
In other words, in the -oriented -delimited split of the rotation around , the left-face order equals , and the right-face order equals .
It remains to find a planar embedding for each input graph , such that each embedding induces the same embedding on . Consider for . We select a suitable embedding of ’s four embeddings listed in Figure 4 as follows: If and we have , we use embedding 1. ( is impossible since is a topological ordering of and ). If and we have , we use embedding 2. ( is impossible since is a topological ordering of and ). If and , we use embedding 3. Finally, if and , we use embedding 4.
In each case, it is easy to verify that the clockwise cyclic order of in is a sub-order of the clockwise cyclic order of in , the same holds for and , and that the rotations for the remaining vertices coincide in the embedding of and the embedding of . Thus, as required, we have constructed a simultaneous embedding of the S-SEFE instance.
Let a simultaneous embedding of the S-SEFE instance be given. Consider the -oriented -delimitted split of the clockwise order around in the planar embedding induced on by the simultaneous embedding. We denote the left-face order by (with vertex set ), and denote the right-face order by (with vertex set ). Observe that and form a partition of .
We claim that is a topological ordering of and that is a topological ordering of , that is, is a positive instance of 2-Digraph Coloring. For this to be the case, whenever and (resp. ), we need in (resp. ). Let and . Consider the planar embedding of given by the simultaneous embedding of the S-SEFE instance. By Observation 5, we have . The argument for the other order is symmetric. Hence, the proof is complete.
Finally, to obtain Theorem 1, we observe that the reduction can be performed in polynomial time, as the Misra–Gries edge-coloring algorithm is polynomial-time computable. Furthermore, by Lemma 3, the construction yields an S-SEFE instance satisfying the sunflower property. Moreover, the set forms a vertex cover of , so . Finally, S-SEFE is known to be in [32]. Thus, as our reduction is correct (Lemma 6), we obtain:
Theorem 1. [Restated, see original statement.]
S-SEFE remains -complete even when restricted to instances where has vertex cover number at most .
4 A Linear Kernel via the Feedback Edge Number of the Union Graph
In this section, we derive Theorem 2, i.e., a linear kernel for S-SEFE when parameterized by the feedback edge number of . To this end, let be an instance of S-SEFE and let be a minimum feedback edge set of of size . In the following, we discuss a series of reduction rules that, if applied exhaustively, transform into an instance of S-SEFE, such that the size of is bounded by a function in . Moreover, has a simultaneous embedding if and only if does.
Before we introduce said rules, let us first discuss some useful preprocessing steps that simplify the instance ; see also [26]. Clearly, if is disconnected, we can solve each of its connected components individually. Furthermore, Bläsius, Karrer, and Rutter showed that can be decomposed at the cut-vertices of into smaller, independent sub-instances, corresponding to the split components of [11, Lemma 1]. Observe that neither of these steps increases the size of . Therefore, we can assume, without loss of generality, that is biconnected. Consequently, is a tree with at most vertices of degree one or at least three. However, the number of degree 2 vertices is still unbounded.
In order to also bound the number of these, we introduce the concept of an internal-degree-2 path, or ID2-path for short, which is a maximal path in between two vertices and such that every internal vertex of has degree 2 in and and are not adjacent in . Note that this implies that has length at least three, i.e., consists of at least two edges. Our reduction rules that we introduce in the following kernel identify such ID2-paths and carefully replace them with a single edge. These rules are centered around the insight that, from the perspective of a single graph , , the path forces its endpoints and to share a face in if . However, we can also enforce this with a single edge . Otherwise, the path does not exist in , which removes the requirement for and to share a face in the embedding of . Hence, we can freely choose the placement of the internal vertices of and edges in .
Kernel 1.
Consider an instance of S-SEFE where is biconnected. We define the following rules, which, if applicable, map to a new instance of S-SEFE. Figure 5 visualizes the rules.
- Rule I:
-
If there exists an ID2-path in with endpoints , such that , then we remove all internal vertices of from and add the edge to every , .
- Rule II:
-
If Rule I is not applicable and there exists an ID2-path in with endpoints , and some , such that , then we remove all internal vertices of from and add the edge to .
- Rule III:
We can readily verify that each reduction rule produces a valid instance of S-SEFE with union graph and shared graph that obeys the sunflower property; recall that, by definition, the endpoints and of the ID-2 path are not adjacent in . In Lemmas 7, 8, and 9, we establish the correctness of the above-introduced reduction rules.
Proof.
Let be an instance of S-SEFE and the instance that we obtain after applying Rule I. Furthermore, let be the ID2-path identified when applying the rule. We now show that has a simultaneous embedding if and only if does.
Let be a simultaneous embedding of . As consists solely of edges from , it exists in every embedding , . We construct a simultaneous embedding of by contracting into a single edge in each embedding , . This way, we ensure that all the resulting embeddings agree on . Finally, since planarity is preserved under edge contraction, we conclude that is a simultaneous embedding of .
Let be a simultaneous embedding of . Recall that we introduced the edge in that connects the two endpoints of . Since , the edge exists in every embedding , . We now reintroduce in each by subdividing the edge sufficiently many times and updating the embeddings accordingly, i.e., to reflect the subdivision process. Since the induce the same embedding on before this operation, the obtained embeddings do so on afterwards. Furthermore, subdividing an edge cannot destroy planarity, i.e., each is a planar embedding and together they yield a simultaneous embedding of .
Proof.
Let be an instance of S-SEFE and the instance that we obtain after applying Rule II. Furthermore, let denote the ID2-path and let be the graph identified when applying the rule. We now show that has a simultaneous embedding if and only if does.
Let be a simultaneous embedding of . We now modify each embedding , and ensure that they yield the same embedding when restricted to . For the embedding , since , we can again contract the path into the edge to obtain an embedding of . For all other embeddings , , we obtain an embedding of by removing the internal vertices of . Since planarity is preserved under edge contraction and vertex deletion, each is a planar embedding of , . Furthermore, as we remove the same edges from from each embedding , all , , agree on and witness the existence of a simultaneous embedding of .
Let be a simultaneous embedding of . We now re-insert the ID2-path into each embedding , . For , we can re-insert by subdividing the edge sufficiently many times and updating the embedding to reflect the subdivision. This yields a planar embedding of , which induces a (new) embedding on . For all other embeddings , , the fact that we could not apply Rule I tells us that there is at least one edge . Hence, is not a single path in but a collection of paths and/or isolated vertices. Together with the fact that is an ID2-path in , this allows us to freely choose the embedding of the internal vertices of and edges of when we insert them into . In particular, we can choose the resulting embedding such that its restriction to coincides with . Moreover, to see that is a planar embedding, it suffices to observe that we can draw the internal vertices of and edges of arbitrarily close to or , respectively. We conclude that the obtained embeddings , , form a simultaneous embedding of .
Proof.
Let be an instance of S-SEFE and the instance that we obtain after applying Rule III. Furthermore, let be the ID2-path identified when applying the rule. We now show that has a simultaneous embedding if and only if does.
Let be a simultaneous embedding of . We now modify each , , to obtain a simultaneous embedding of . First, we remove the internal vertices of from each . If , i.e., if every edge of belongs to or , we can delete the entire embedding . Since we only deleted vertices (and their incident edges), the remaining embeddings yield a simultaneous embedding of the corresponding sub-instance of . Let be the resulting embedding of . What is missing from a simultaneous embedding of is the embedding of the graph . Recall that , where and are the end vertices of . We initialize . This ensures that all embeddings induce the same embedding when restricted to . What is missing from an embedding of is the edge . We now show that vertices and must share a face in , which allows us to insert the edge . Towards a contradiction, assume that this would not be the case. We recall that was obtained from by vertex deletion. Hence, and do not share a face in either. However, since is a simultaneous embedding of , and and are connected by the ID2-path in , there exists an edge for some such that and do not share a face in . Since is part of a simultaneous embedding of , this edge crosses another edge in any drawing represented by , a contradiction to the assumption that is a simultaneous embedding. Therefore, and share a face in , i.e., we can insert the edge in . This completes the construction of the simultaneous embedding of .
Let be a simultaneous embedding of and consider . As , the vertices and share a face in . Moreover, we can identify a face in which is shared by and and contains the edge (in ).
We now construct a simultaneous embedding of as follows. Consider an input graph , , and the embedding . For now, we assume that this embedding exists but note that our reduction rule could have removed entirely from . This case is handled at the end. Consider the face in the embedding when restricted to . Observe that by above arguments, the face contains both and . Recall that we apply Rule III only if Rules I and II are not applicable. Hence, similar to the proof of Lemma 8, we observe that when induced on , the ID2-path is not a single path between and but a collection of paths and/or isolated vertices. Hence, we can freely choose the embedding of the respective vertices and edges when extending into an embedding of . In particular, we can ensure that all internal vertices of are inside the face (when is restricted to ). Moreover, we can include the edges in the rotation around and , respectively, such that they lie between the same shared edges as the edge in ; see Figure 6. This way we ensure that the constructed embeddings will agree on . Furthermore, we can draw the internal vertices of and edges of arbitrarily close to or , i.e., is a planar embedding of .
Finally, recall that our reduction rule can remove a from . However, since this only happens if , we can initialize and proceed as above. Hence, we conclude that the constructed embeddings form a simultaneous embedding of .
Proof.
Let be an instance of S-SEFE. Recall that we can assume to be biconnected thanks to known steps that simplify instances of S-SEFE [11]. Let us exhaustively apply Reduction Rules I–III of Kernel 1 to to obtain , , with union graph . Note that the reduction rules maintain biconnectivity and the size of our parameter, i.e., the feedback edge number of – we only replace paths where every internal vertex is of degree 2 in by a single edge.
Let be a minimum feedback edge set of of size . We can compute in polynomial time by, for example, computing a spanning tree of and setting . As is biconnected, the graph is a tree. To ease argumentation, we assume to be rooted at an arbitrary leaf. Every leaf is incident to at least one edge of – otherwise the parent of this leaf would witness the existence of a cut vertex in which is not possible. The tree has therefore at most leaves and, consequently, at most internal vertices of degree at least three. Let denote the set of vertices such that is of degree at least three in or we have for some . Observe that contains all leaves of and, since , its size is in . It remains to bound the number of vertices of degree 2 in . We do that by bounding the length of a path in between a vertex and its (first) ancestor in . Let be such a path. We observe that can have length at most 4. Otherwise, i.e., if consists of 5 or more vertices, there are at least 3 consecutive internal vertices that have degree 2 in . These form a path whose endpoints are not connected in . In particular, they form an ID2-path, a contradiction to the fact that we exhaustively applied the reduction rules of Kernel 1. As there are at most such paths, one for each vertex in (as is a tree), each of which is of constant length, (and thus ) consists of at most vertices. Moreover, as is a tree on vertices and has the sunflower property, we have for each edge either or for a single . As has edges, , and since we delete input graphs whose edge set coincides with that of , the number of remaining input graphs is in . Finally, as S-SEFE is known to be in [32], it is decidable. With the safeness of the Rules I–III of Kernel 1 established in Lemmas 7, 8, and 9, the statement follows.
5 Discussion and Concluding Remarks
While Theorems 1 and 2 improve upon the previous state of the art, the parameterized complexity of S-SEFE remains wide open under other parameterizations. A key milestone left for future work is to settle whether S-SEFE is fixed-parameter tractable, -tractable or para-hard w.r.t. plus the treewidth [52] of the union graph, i.e., . Note that the question is only interesting if is included in the parameterization – otherwise, we immediately obtain intractability by Theorem 1.
As a stepping stone towards understanding the problem’s behavior on graphs of bounded treewidth, below we show that any treewidth-based algorithm for S-SEFE (or SEFE) would immediately also transfer to the graph parameter clique-width, even though on general graphs the latter can be arbitrarily smaller than the former. We remark that the formal definitions of these notions are rather technical and in fact not needed to establish the desired relationship.
Proposition 10.
(S-)SEFE parameterized by is in (in ) if and only if (S-)SEFE parameterized by is in (in , respectively).
Proof.
An (or ) algorithm parameterized by yields an (, respectively) algorithm parameterized by due to the well-known fact that for every graph [20]. Conversely, assume we have an (or ) algorithm for (S-)SEFE parameterized by . Consider an instance of (S-)SEFE parameterized by . If one of the input graphs is not planar, we can reject the instance. Otherwise, upper-bounds the thickness of , i.e., the edges of can be partitioned into at most edge sets such that each edge set induces a planar graph on .
It is known that for every graph of thickness there exists an integer which depends solely on the thickness of such that contains no as a subgraph [7]; notice here that depends solely on . This in turn ensures that is upper-bounded by a function of [34], and hence also by a function of . Therefore, the existing (or ) algorithm would imply fixed-parameter (or , respectively) tractability of the problem w.r.t. .
A different structural parameterization that has been successfully used for some other problems is graph degeneracy [17, 46, 8]. A graph is -degenerate if every subgraph of G contains a vertex of degree at most . The degeneracy of is then the smallest such that is -degenerate. Here, we provide a straightforward argument that rules out any parameterized algorithms w.r.t. graph degeneracy.
Proposition 11.
(S-)SEFE is -hard even when restricted to instances where the union graph has degeneracy at most 2 and .
Proof.
We recall that SEFE and S-SEFE are known to remain -hard when restricted to instances satisfying and, in particular, even . For each instance of (S-)SEFE, we construct a new instance by subdividing every edge of each input graph once. Since is a positive instance if and only if so is but the union graph of every constructed instance has degeneracy , the statement follows.
References
- [1] Patrizio Angelini, Giuseppe Di Battista, Fabrizio Frati, Maurizio Patrignani, and Ignaz Rutter. Testing the simultaneous embeddability of two graphs whose intersection is a biconnected or a connected graph. J. Discrete Algorithms, 14:150–172, 2012. doi:10.1016/J.JDA.2011.12.015.
- [2] Patrizio Angelini, Steven Chaplick, Sabine Cornelsen, Giordano Da Lozzo, Giuseppe Di Battista, Peter Eades, Philipp Kindermann, Jan Kratochvíl, Fabian Lipp, and Ignaz Rutter. Simultaneous orthogonal planarity. In Yifan Hu and Martin Nöllenburg, editors, Graph Drawing and Network Visualization - 24th International Symposium, GD 2016, Athens, Greece, September 19-21, 2016, Revised Selected Papers, volume 9801 of Lecture Notes in Computer Science, pages 532–545. Springer, 2016. doi:10.1007/978-3-319-50106-2_41.
- [3] Patrizio Angelini, Giordano Da Lozzo, Giuseppe Di Battista, Fabrizio Frati, Maurizio Patrignani, and Ignaz Rutter. Beyond level planarity: Cyclic, torus, and simultaneous level planarity. Theor. Comput. Sci., 804:161–170, 2020. doi:10.1016/J.TCS.2019.11.024.
- [4] Patrizio Angelini, Giordano Da Lozzo, and Daniel Neuwirth. Advancements on SEFE and partitioned book embedding problems. Theor. Comput. Sci., 575:71–89, 2015. doi:10.1016/J.TCS.2014.11.016.
- [5] Patrizio Angelini, Giuseppe Di Battista, Fabrizio Frati, Vít Jelínek, Jan Kratochvíl, Maurizio Patrignani, and Ignaz Rutter. Testing planarity of partially embedded graphs. ACM Trans. Algorithms, 11(4):32:1–32:42, 2015. doi:10.1145/2629341.
- [6] Patrizio Angelini, Ignaz Rutter, and T. P. Sandhya. Extending partial orthogonal drawings. J. Graph Algorithms Appl., 25(1):581–602, 2021. doi:10.7155/JGAA.00573.
- [7] Lowell W Beineke, Frank Harary, and John W Moon. On the thickness of the complete bipartite graph. In Mathematical Proceedings of the Cambridge Philosophical Society, volume 60(1), pages 01–05. Cambridge University Press, 1964.
- [8] Matthias Bentert, Till Fluschnik, André Nichterlein, and Rolf Niedermeier. Parameterized aspects of triangle enumeration. J. Comput. Syst. Sci., 103:61–77, 2019. doi:10.1016/J.JCSS.2019.02.004.
- [9] Sujoy Bhore, Robert Ganian, Liana Khazaliya, Fabrizio Montecchiani, and Martin Nöllenburg. Extending orthogonal planar graph drawings is fixed-parameter tractable. In Erin W. Chambers and Joachim Gudmundsson, editors, 39th International Symposium on Computational Geometry, SoCG 2023, June 12-15, 2023, Dallas, Texas, USA, volume 258 of LIPIcs, pages 18:1–18:16. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2023. doi:10.4230/LIPICS.SOCG.2023.18.
- [10] Thomas Bläsius, Simon D. Fink, and Ignaz Rutter. Synchronized planarity with applications to constrained planarity problems. ACM Trans. Algorithms, 19(4):34:1–34:23, 2023. doi:10.1145/3607474.
- [11] Thomas Bläsius, Annette Karrer, and Ignaz Rutter. Simultaneous embedding: Edge orderings, relative positions, cutvertices. In Stephen K. Wismath and Alexander Wolff, editors, Graph Drawing - 21st International Symposium, GD 2013, Bordeaux, France, September 23-25, 2013, Revised Selected Papers, volume 8242 of Lecture Notes in Computer Science, pages 220–231. Springer, 2013. doi:10.1007/978-3-319-03841-4_20.
- [12] Thomas Bläsius, Annette Karrer, and Ignaz Rutter. Simultaneous embedding: Edge orderings, relative positions, cutvertices. Algorithmica, 80(4):1214–1277, 2018. doi:10.1007/S00453-017-0301-9.
- [13] Thomas Bläsius, Stephen G. Kobourov, and Ignaz Rutter. Simultaneous embedding of planar graphs. In Roberto Tamassia, editor, Handbook on Graph Drawing and Visualization, pages 349–381. Chapman and Hall/CRC, 2013.
- [14] Thomas Bläsius and Ignaz Rutter. Disconnectivity and relative positions in simultaneous embeddings. Comput. Geom., 48(6):459–478, 2015. doi:10.1016/J.COMGEO.2015.02.002.
- [15] Guido Brückner and Ignaz Rutter. An spqr-tree-like embedding representation for level planarity. J. Comput. Geom., 14(1):48–77, 2023. doi:10.20382/JOCG.V14I1A3.
- [16] Guido Brückner, Ignaz Rutter, and Peter Stumpf. Extending partial representations of circle graphs in near-linear time. Algorithmica, 86(7):2152–2173, 2024. doi:10.1007/S00453-024-01216-5.
- [17] Austin Buchanan, Jose L. Walteros, Sergiy Butenko, and Panos M. Pardalos. Solving maximum clique in sparse graphs: an O(nm+n2) algorithm for d-degenerate graphs. Optim. Lett., 8(5):1611–1617, 2014. doi:10.1007/S11590-013-0698-2.
- [18] Johannes Carmesin and Will J. Turner. A graph minors approach to temporal sequences, 2025. arXiv:2504.00704.
- [19] Steven Chaplick, Radoslav Fulek, and Pavel Klavík. Extending partial representations of circle graphs. J. Graph Theory, 91(4):365–394, 2019. doi:10.1002/JGT.22436.
- [20] Derek G. Corneil and Udi Rotics. On the relationship between clique-width and treewidth. SIAM J. Comput., 34(4):825–847, 2005. doi:10.1137/S0097539701385351.
- [21] Marek Cygan, Fedor V. Fomin, Lukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michal Pilipczuk, and Saket Saurabh. Parameterized Algorithms. Springer, 2015. doi:10.1007/978-3-319-21275-3.
- [22] Thomas Depian, Simon D. Fink, Robert Ganian, and Martin Nöllenburg. The parameterized complexity of extending stack layouts. In Stefan Felsner and Karsten Klein, editors, 32nd International Symposium on Graph Drawing and Network Visualization, GD 2024, September 18-20, 2024, Vienna, Austria, volume 320 of LIPIcs, pages 12:1–12:17. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2024. doi:10.4230/LIPICS.GD.2024.12.
- [23] Eduard Eiben, Robert Ganian, Thekla Hamm, Fabian Klute, and Martin Nöllenburg. Extending partial 1-planar drawings. In Artur Czumaj, Anuj Dawar, and Emanuela Merelli, editors, 47th International Colloquium on Automata, Languages, and Programming, ICALP 2020, July 8-11, 2020, Saarbrücken, Germany (Virtual Conference), volume 168 of LIPIcs, pages 43:1–43:19. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2020. doi:10.4230/LIPICS.ICALP.2020.43.
- [24] Cesim Erten and Stephen G. Kobourov. Simultaneous embedding of planar graphs with few bends. J. Graph Algorithms Appl., 9(3):347–364, 2005. doi:10.7155/JGAA.00113.
- [25] Jirí Fiala, Ignaz Rutter, Peter Stumpf, and Peter Zeman. Extending partial representations of circular-arc graphs. In Michael A. Bekos and Michael Kaufmann, editors, Graph-Theoretic Concepts in Computer Science - 48th International Workshop, WG 2022, Tübingen, Germany, June 22-24, 2022, Revised Selected Papers, volume 13453 of Lecture Notes in Computer Science, pages 230–243. Springer, 2022. doi:10.1007/978-3-031-15914-5_17.
- [26] Simon D. Fink, Matthias Pfretzschner, and Ignaz Rutter. Parameterized complexity of simultaneous planarity. In Michael A. Bekos and Markus Chimani, editors, Graph Drawing and Network Visualization - 31st International Symposium, GD 2023, Isola delle Femmine, Palermo, Italy, September 20-22, 2023, Revised Selected Papers, Part II, volume 14466 of Lecture Notes in Computer Science, pages 82–96. Springer, 2023. doi:10.1007/978-3-031-49275-4_6.
- [27] Simon Dominik Fink and Ignaz Rutter. Constrained planarity in practice - engineering the synchronized planarity algorithm. J. Graph Algorithms Appl., 29(1):91–123, 2025. doi:10.7155/JGAA.V29I1.2923.
- [28] Radoslav Fulek and Csaba D. Tóth. Atomic embeddability, clustered planarity, and thickenability. J. ACM, 69(2):13:1–13:34, 2022. doi:10.1145/3502264.
- [29] Robert Ganian. Twin-cover: Beyond vertex cover in parameterized algorithmics. In Dániel Marx and Peter Rossmanith, editors, Parameterized and Exact Computation - 6th International Symposium, IPEC 2011, Saarbrücken, Germany, September 6-8, 2011. Revised Selected Papers, volume 7112 of Lecture Notes in Computer Science, pages 259–271. Springer, 2011. doi:10.1007/978-3-642-28050-4_21.
- [30] Robert Ganian. Improving vertex cover as a graph parameter. Discret. Math. Theor. Comput. Sci., 17(2):77–100, 2015. doi:10.46298/DMTCS.2136.
- [31] Robert Ganian, Thekla Hamm, Fabian Klute, Irene Parada, and Birgit Vogtenhuber. Crossing-optimal extension of simple drawings. In Nikhil Bansal, Emanuela Merelli, and James Worrell, editors, 48th International Colloquium on Automata, Languages, and Programming, ICALP 2021, July 12-16, 2021, Glasgow, Scotland (Virtual Conference), volume 198 of LIPIcs, pages 72:1–72:17. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2021. doi:10.4230/LIPICS.ICALP.2021.72.
- [32] Elisabeth Gassner, Michael Jünger, Merijam Percan, Marcus Schaefer, and Michael Schulz. Simultaneous graph embeddings with fixed edges. In Fedor V. Fomin, editor, Graph-Theoretic Concepts in Computer Science, 32nd International Workshop, WG 2006, Bergen, Norway, June 22-24, 2006, Revised Papers, volume 4271 of Lecture Notes in Computer Science, pages 325–335. Springer, 2006. doi:10.1007/11917496_29.
- [33] Tatsuya Gima, Tesshu Hanaka, Masashi Kiyomi, Yasuaki Kobayashi, and Yota Otachi. Exploring the gap between treedepth and vertex cover through vertex integrity. Theor. Comput. Sci., 918:60–76, 2022. doi:10.1016/J.TCS.2022.03.021.
- [34] Frank Gurski and Egon Wanke. The tree-width of clique-width bounded graphs without K. In Ulrik Brandes and Dorothea Wagner, editors, Graph-Theoretic Concepts in Computer Science, 26th International Workshop, WG 2000, Konstanz, Germany, June 15-17, 2000, Proceedings, volume 1928 of Lecture Notes in Computer Science, pages 196–205. Springer, 2000. doi:10.1007/3-540-40064-8_19.
- [35] Bernhard Haeupler, Krishnam Raju Jampani, and Anna Lubiw. Testing simultaneous planarity when the common graph is 2-connected. J. Graph Algorithms Appl., 17(3):147–171, 2013. doi:10.7155/JGAA.00289.
- [36] Lukas Hartmann. Charakterisierung simultaner Planarität mittels verbotener Substrukturen. Master’s thesis, Karlsruhe Institute of Technolgy, 2013. URL: https://i11www.iti.kit.edu/_media/teaching/theses/da-hartmann-13.pdf.
- [37] Ararat Harutyunyan, Michael Lampis, and Nikolaos Melissinos. Digraph coloring and distance to acyclicity. Theory Comput. Syst., 68(4):986–1013, 2024. doi:10.1007/S00224-022-10103-X.
- [38] Krishnam Raju Jampani and Anna Lubiw. Simultaneous interval graphs. In Otfried Cheong, Kyung-Yong Chwa, and Kunsoo Park, editors, Algorithms and Computation - 21st International Symposium, ISAAC 2010, Jeju Island, Korea, December 15-17, 2010, Proceedings, Part I, volume 6506 of Lecture Notes in Computer Science, pages 206–217. Springer, 2010. doi:10.1007/978-3-642-17517-6_20.
- [39] Krishnam Raju Jampani and Anna Lubiw. The simultaneous representation problem for chordal, comparability and permutation graphs. J. Graph Algorithms Appl., 16(2):283–315, 2012. doi:10.7155/JGAA.00259.
- [40] Vít Jelínek, Jan Kratochvíl, and Ignaz Rutter. A kuratowski-type theorem for planarity of partially embedded graphs. Comput. Geom., 46(4):466–492, 2013. doi:10.1016/J.COMGEO.2012.07.005.
- [41] Michael Jünger and Michael Schulz. Intersection graphs in simultaneous embedding with fixed edges. J. Graph Algorithms Appl., 13(2):205–218, 2009. doi:10.7155/JGAA.00184.
- [42] Pavel Klavík, Jan Kratochvíl, Tomasz Krawczyk, and Bartosz Walczak. Extending partial representations of function graphs and permutation graphs. In Leah Epstein and Paolo Ferragina, editors, Algorithms - ESA 2012 - 20th Annual European Symposium, Ljubljana, Slovenia, September 10-12, 2012. Proceedings, volume 7501 of Lecture Notes in Computer Science, pages 671–682. Springer, 2012. doi:10.1007/978-3-642-33090-2_58.
- [43] Pavel Klavík, Jan Kratochvíl, Yota Otachi, Ignaz Rutter, Toshiki Saitoh, Maria Saumell, and Tomás Vyskocil. Extending partial representations of proper and unit interval graphs. Algorithmica, 77(4):1071–1104, 2017. doi:10.1007/S00453-016-0133-Z.
- [44] Pavel Klavík, Jan Kratochvíl, Yota Otachi, Toshiki Saitoh, and Tomás Vyskocil. Extending partial representations of interval graphs. Algorithmica, 78(3):945–967, 2017. doi:10.1007/S00453-016-0186-Z.
- [45] Pavel Klavík and Maria Saumell. Minimal obstructions for partial representations of interval graphs. Electron. J. Comb., 25(4):4, 2018. doi:10.37236/5862.
- [46] Michal Kotrbcík, Rastislav Královic, and Sebastian Ordyniak. Edge-editing to a dense and a sparse graph class. In Evangelos Kranakis, Gonzalo Navarro, and Edgar Chávez, editors, LATIN 2016: Theoretical Informatics - 12th Latin American Symposium, Ensenada, Mexico, April 11-15, 2016, Proceedings, volume 9644 of Lecture Notes in Computer Science, pages 562–575. Springer, 2016. doi:10.1007/978-3-662-49529-2_42.
- [47] Michael Lampis and Valia Mitsou. Fine-grained meta-theorems for vertex integrity. Log. Methods Comput. Sci., 20(4), 2024. doi:10.46298/LMCS-20(4:18)2024.
- [48] Jayadev Misra and David Gries. A constructive proof of vizing’s theorem. Inf. Process. Lett., 41(3):131–133, 1992. doi:10.1016/0020-0190(92)90041-S.
- [49] Miriam Münch, Ignaz Rutter, and Peter Stumpf. Partial and simultaneous transitive orientations via modular decompositions. Algorithmica, 86(4):1263–1292, 2024. doi:10.1007/S00453-023-01188-Y.
- [50] Helen C. Purchase. Effective information visualisation: a study of graph drawing aesthetics and algorithms. Interact. Comput., 13(2):147–162, 2000. doi:10.1016/S0953-5438(00)00032-1.
- [51] Helen C. Purchase, David A. Carrington, and Jo-Anne Allder. Empirical evaluation of aesthetics-based graph layout. Empir. Softw. Eng., 7(3):233–255, 2002.
- [52] Neil Robertson and Paul D. Seymour. Graph minors. III. planar tree-width. J. Comb. Theory B, 36(1):49–64, 1984. doi:10.1016/0095-8956(84)90013-3.
- [53] Ignaz Rutter. Simultaneous embedding. In Seok-Hee Hong and Takeshi Tokuyama, editors, Beyond Planar Graphs, Communications of NII Shonan Meetings, pages 237–265. Springer, 2020. doi:10.1007/978-981-15-6533-5_13.
- [54] Ignaz Rutter, Darren Strash, Peter Stumpf, and Michael Vollmer. Simultaneous representation of proper and unit interval graphs. In Michael A. Bender, Ola Svensson, and Grzegorz Herman, editors, 27th Annual European Symposium on Algorithms, ESA 2019, September 9-11, 2019, Munich/Garching, Germany, volume 144 of LIPIcs, pages 80:1–80:15. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2019. doi:10.4230/LIPICS.ESA.2019.80.
- [55] Ignaz Rutter, Darren Strash, Peter Stumpf, and Michael Vollmer. Simultaneous representation of proper and unit interval graphs. Algorithmica, 87(5):783–811, 2025. doi:10.1007/S00453-025-01296-X.
- [56] Ignaz Rutter and Peter Stumpf. Simultaneous representation of interval graphs in the sunflower case. In Inge Li Gørtz, Martin Farach-Colton, Simon J. Puglisi, and Grzegorz Herman, editors, 31st Annual European Symposium on Algorithms, ESA 2023, September 4-6, 2023, Amsterdam, The Netherlands, volume 274 of LIPIcs, pages 90:1–90:15. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2023. doi:10.4230/LIPICS.ESA.2023.90.
- [57] Marcus Schaefer. Toward a theory of planarity: Hanani-tutte and planarity variants. In Walter Didimo and Maurizio Patrignani, editors, Graph Drawing - 20th International Symposium, GD 2012, Redmond, WA, USA, September 19-21, 2012, Revised Selected Papers, volume 7704 of Lecture Notes in Computer Science, pages 162–173. Springer, 2012. doi:10.1007/978-3-642-36763-2_15.
- [58] V. G. Vizing. On an estimate of the chromatic class of a p-graph. Diskret. Analiz, 3:25–30, 1964. in Russian.
