On embedding degree sequences
B\'ela Csaba, B\'alint V\'as\'arhelyi

TL;DR
This paper investigates conditions under which one graphic degree sequence can be embedded as a subgraph within any realization of another degree sequence, advancing understanding of graph embedding properties.
Contribution
It introduces new criteria for embedding degree sequences, providing a deeper theoretical understanding of subgraph realizability within degree sequence constraints.
Findings
Established sufficient conditions for degree sequence embedding
Characterized when one degree sequence can always be realized as a subgraph
Extended existing theories on graphic sequences and subgraph realizations
Abstract
Assume that we are given two graphic sequences, and . We consider conditions for and which guarantee that there exists a simple graph realizing such that is the subgraph of any simple graph that realizes .
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On embedding degree sequences
Béla Csaba, Bálint Vásárhelyi Bolyai Institute, Interdisciplinary Excellence Centre, University of Szeged, Hungary, email: [email protected]. Partially supported by Ministry of Human Capacities, Hungary, Grant 20391-3/2018/FEKUSTRAT, NKFIH Fund No. KH 129597 and by the NKFIH Fund No. SNN 117879.Bolyai Institute, University of Szeged, Hungary, email: [email protected]. Supported by TÁMOP-4.2.2.B-15/1/KONV-2015-0006.
Abstract
Assume that we are given two graphic sequences, and . We consider conditions for and which guarantee that there exists a simple graph realizing such that is the subgraph of any simple graph that realizes .
1 Introduction
All graphs considered in this paper are simple. We use standard graph theory notation, see for example [16]. Let us provide a short list of a few perhaps not so common notions, notations. Given a bipartite graph we call it balanced if . This notion naturally generalizes for -partite graphs with .
If for some graph then the subgraph spanned by is denoted by . Moreover, let so that then denotes the bipartite subgraph of on vertex classes and having every edge of that connects a vertex of with a vertex of . The number of vertices in is denoted by the number of its edges is denoted by . The degree of a vertex is denoted by or if is clear from the context, by . The number of neighbors of in a subset is denoted by and and denote the minimum and maximum degree of respectively. The complete graph on vertices is denoted by the complete bipartite graph with vertex class sizes and is denoted by .
A finite sequence of natural numbers is a graphic sequence or degree sequence if there exists a graph such that is the (not necessarily) monotone degree sequence of . Such a graph realizes . For example, the degree sequence can be realized only by vertex-disjoint union of cycles.
The largest value of is denoted by . Often the positions of will be identified with the elements of a vertex set . In this case, we write for the corresponding component of .
The degree sequence is a bigraphic sequence if there exists a simple bipartite graph with , realizing such that the degrees of vertices in are and the degrees of the vertices of are .
Let and be two graphs on vertices. We say that is a subgraph of if we can delete edges from so that we obtain an isomorphic copy of . We denote this relation by . In the literature the equivalent complementary formulation can be found as well: we say that and pack if there exist edge-disjoint copies of and in . Here denotes the complement of .
Two classical results in this field are the following theorems.
Theorem 1** (Dirac, [6]).**
Every graph with vertices and minimum degree has a Hamilton cycle.
Theorem 2** (Corrádi-Hajnal, [3]).**
Let , , and let be an -vertex graph with . Then contains vertex-disjoint cycles.
It is an old an well-understood problem in graph theory to tell whether a given sequence of natural numbers is a degree sequence or not. We consider a generalization of it, which is remotely related to the so-called discrete tomography111In the discrete tomography problem we are given two degree sequences of length , and and the questions is whether there exists a graph on vertices with a red-blue edge coloration so that the following holds: for every vertex the red degree of is and the blue degree of is . (or degree sequence packing) problem (see e.g. [5]) as well. The question whether a sequence of numbers is a degree sequence can also be formulated as follows: Does have a subgraph such that the degree sequence of is The question becomes more general if is replaced by some (simple) graph on vertices. If the answer is yes, we say that can be embedded into or equivalently, packs with .
One of our main results is the following.
Theorem 3**.**
For every and there exists an such that for all if is a graph on vertices with and is a degree sequence of length with , then is embeddable into .
It is easy to see that Theorem 3 is sharp up to the additive term. For that let be an even number, and suppose that every element of is 1. Then the only graph that realizes is the union of vertex disjoint edges. Let be the complete bipartite graph with vertex class sizes and . Clearly does not have vertex disjoint edges.
In order to state the other main result of the paper we introduce a new notion.
Definition 4**.**
Let be an integer. A bipartite graph with vertex classes and is -unbalanced, if . The degree sequence is -unbalanced, if it can be realized by a -unbalanced bipartite graph.
Theorem 5**.**
Let be an integer. For every and there exist an and an such that if is a -unbalanced degree sequence of length with is a graph on vertices with , then can be embedded into .
Hence, if is unbalanced, the minimum degree requirement of Theorem 3 can be substantially decreased, what we pay for this is that the length of has to be slightly smaller than the number of vertices in the host graph.
2 Proof of Theorem 3
Proof.
First, we find a suitable realization of our will consists of components of bounded size. Second, we embed into using a theorem by Chvátal and Szemerédi, and a result on embedding so called well-separable graphs. The details are as follows.
We construct in several steps. At the beginning, let be the empty graph and let all degrees in be active. While we can find active degrees of with value (for some ) we realize them with a (that is, we add this complete bipartite graph to , and the degrees are “inactivated”). When we stop we have at most active degrees. This way we obtain several components, each being a balanced complete bipartite graph. These are the type 1 gadgets. Observe that if a vertex belongs to some type 1 gadget, then its degree is exactly
Let be the vertex set that is identified with the active vertices ( if and only if the assigned active degree is odd). Since must be an even number we have that is even. Add a perfect matching on to . With this we achieved that every vertex of misses an even number of edges.
Next we construct the type 2 gadgets using the following algorithm. In the beginning every type 1 gadget is unmarked. Suppose that is an active vertex. Take a type 1 gadget mark it, and let denote an arbitrarily chosen perfect matching in ( exists since is a balanced complete bipartite graph). Let be an arbitrary edge in . Delete the edge and add the new edges and . While is missing edges repeat the above procedure with edges of until becomes empty. If becomes empty, take a new unmarked type 1 gadget and repeat the method with . It is easy to see that in steps reaches its desired degree and gets inactivated. Clearly, the degrees of vertices in the marked type 1 gadgets have not changed.
Figure 1 shows examples of type 2 gadgets. In the upper one two vertices of were first connected by an edge and then two type 1 gadgets were used so that they could reach their desired degree, while in the lower one we used three type 1 gadgets for a vertex of The numbers at the vertices indicate the colors in the 3-coloring of
Let denote the set of vertices containing the union of all type 2 gadgets. Observe that type 2 gadgets are 3-colorable and all have less than vertices. Let us summarize our knowledge about for later reference.
Claim 6**.**
- (1)
** 2. (2)
the components of are balanced complete bipartite graphs, each having size at most 3. (3)
* and* 4. (4)
.
We are going to show that . For that we first embed the possibly 3-chromatic part using the following strengthening of the Erdős–Stone theorem proved by Chvátal and Szemerédi [2].
Theorem 7**.**
Let and assume that is a graph on vertices where is sufficiently large. Let . If
[TABLE]
then contains a , i.e. a complete -partite graph with vertices in each class, such that
[TABLE]
Since the conditions of Theorem 7 are satisfied with and hence, contains a balanced complete tripartite subgraph on vertices. Using Claim LABEL:HSzerk and the 3-colorability of this implies that .
Observe that after embedding into every uncovered vertex of still has at least uncovered neighbors. Denoting the subgraph of the uncovered vertices of by we obtain that
In order to prove that we first need a definition.
Definition 8**.**
A graph on vertices is well-separable if it has a subset of size such that all components of are of size .
We need the following theorem.
Theorem 9** ([4]).**
For every and positive integer there exists an such that for all if is a bipartite well-separable graph on vertices, and for a graph of order , then .
Since has bounded size components, we can apply Theorem 9 for and with parameter . With this we finished proving what was desired.
∎
3 Further tools for Theorem 5
When proving Theorem 3, we used the Regularity Lemma of Szemerédi, but implicitly, via the result on embedding well-separable graphs. When proving Theorem 5 we will apply this very powerful result explicitly, hence, below we give a very brief introduction to the area. The interested reader may consult with the original paper by Szemerédi [15] or e.g. with the survey paper [10].
3.1 Regularity Lemma
The density between disjoint sets and is defined as:
[TABLE]
We will need the following definition to state the Regularity Lemma.
Definition 10** (Regularity condition).**
Let . A pair of disjoint vertex-sets in is -regular if for every and , satisfying
[TABLE]
we have
[TABLE]
This definition implies that regular pairs are highly uniform bipartite graphs; namely, the density of any reasonably large subgraph is almost the same as the density of the regular pair.
We will use the following form of the Regularity Lemma:
Lemma 11** (Degree Form).**
For every there is an such that if is any graph and is any real number, then there is a partition of the vertex set into clusters , and there is a subgraph of with the following properties:
,
,
all clusters , , are of the same size ,
* for all ,*
* ( is an independent set in ) for all ,*
all pairs , , are -regular, each with density either 0 or greater than in .
We call the exceptional cluster, are the non-exceptional clusters. In the rest of the paper we will assume that . Here means that * is sufficiently smaller than .*
Definition 12** (Reduced graph).**
Apply 11 to the graph with parameters and , and denote the clusters of the resulting partition by ( being the exceptional cluster). We construct a new graph , the reduced graph of in the following way: The non-exceptional clusters of are the vertices of the reduced graph (hence ). We connect two vertices of by an edge if the corresponding two clusters form an -regular pair with density at least .
The following corollary is immediate:
Corollary 13**.**
Apply 11 with parameters and to the graph satisfying for some . Denote the reduced graph of . Then , where .
The (fairly easy) proof of the lemma below can be found in [10].
Lemma 14**.**
Let be an -regular–pair with density for some . Let be a constant such that . We arbitrarily divide and into two parts, obtaining the non-empty subsets and , respectively. Assume that and . Then the pairs and are all –regular pairs with density at least .
3.2 Blow-up Lemma
Let and be two graphs on vertices. Assume that we want to find an isomorphic copy of in . In order to achieve this one can apply a very powerful tool, the Blow-up Lemma of Komlós, Sárközy and Szemerédi [8, 9]. For stating it we need a new notion, a stronger one-sided property of regular pairs.
Definition 15** (Super-Regularity condition).**
Given a graph and two disjoint subsets of its vertices and , the pair is -super-regular, if it is -regular and furthermore,
[TABLE]
and
[TABLE]
Theorem 16** (Blow-up Lemma).**
Given a graph of order and positive integers there exists a positive such that the following holds: Let be arbitrary positive parameters and let us replace the vertices of with pairwise disjoint sets of sizes (blowing up ). We construct two graphs on the same vertex set . The first graph is obtained by replacing each edge with the complete bipartite graph between and . A sparser graph is constructed by replacing each edge arbitrarily with an -super-regular pair between and . If a graph with is embeddable into then it is already embeddable into .
4 Proof of Theorem 5
Let us give a brief sketch first. Recall, that is a -unbalanced and bounded degree sequence with . In the proof we first show that there exists a -unbalanced bipartite graph that realizes such that is the vertex disjoint union of the graphs where each graph is a bipartite -unbalanced graph having bounded size. We will apply the Regularity lemma to and find a special substructure (a decomposition into vertex-disjoint stars) in the reduced graph of . This substructure can then be used to embed the union of the graphs, for the majority of them we use the Blow-up lemma.
4.1 Finding
The goal of this subsection is to prove the lemma below.
Lemma 17**.**
Let be a -unbalanced degree sequence of positive integers with . Then can be realized by a -unbalanced bipartite graph which is the vertex disjoint union of the graphs such that for every we have that is -unbalanced, moreover, .
Before starting the proof of 17, we list a few necessary notions and results.
We call a finite sequence of integers a zero-sum sequence if the sum of its elements is zero. The following result of Sahs, Sissokho and Torf plays an important role in the proof of 17.
Proposition 18**.**
[14]** Assume that is a positive integer. Then any zero-sum sequence on having length at least contains a proper nonempty zero-sum subsequence.
The following result, formulated by Gale [7] and Ryser [13], will also be useful. We present it in the form as discussed in Lovász [11].
Lemma 19**.**
[11*]**
Let be a bipartite graph and be a nonnegative integer function on with . Then has a subgraph such that for all if and only if*
[TABLE]
for any and , where .
We remark that such a subgraph is also called an -factor of .
Lemma 20**.**
If is a sequence of positive integers with , where is the maximum of , and with and then is bigraphic.
Proof.
All we have to check is whether the conditions of 19 are met if .
Suppose indirectly that there is an pair for which (2) does not hold. Choose such a pair with minimal . Then or are impossible, as in those cases (2) trivially holds. Hence, . Assuming that (2) does not hold, we have that
[TABLE]
which is equivalent to
[TABLE]
as is a complete bipartite graph. Furthermore, using the minimality of , we know that
[TABLE]
for any . (5) is equivalent to
[TABLE]
[TABLE]
for any , which implies
[TABLE]
The same reasoning also implies that whenever is a counterexample. Therefore we only have to verify that (2) holds in case and . Recall that , as all elements of are positive. Hence, , and and we get that
[TABLE]
holds, since . ∎
Proof.
(17) Assume that J=\big{(}S,T;E(J)\big{)} is a -unbalanced bipartite graph realizing . Hence, . Moreover, since . We form vertex disjoint tuples of the form such that and the collection of these tuples contains every vertex of exactly once. We define the bias of the tuple as
[TABLE]
Obviously, . The conditions of 18 are clearly met with . Hence, we can form groups of size at most in which the sums of biases are zero. This way we obtain a partition of into -unbalanced set pairs which have zero bias. While these sets may be small, we can combine them so that each combined set is of size at least and has zero bias. By 20 these are bigraphic sequences. The realizations of these small sequences give the graphs . It is easy to see that for every . Finally, we let . ∎
4.2 Decomposing
Let us apply the Regularity lemma with parameters . By 13 we have that .
Let be an integer. An -star is a . The center of an -star is the vertex of degree the other vertices are the leaves. In case we pick one of the vertices of the 1-star arbitrarily to be the center.
Lemma 21**.**
The reduced graph has a decomposition into vertex disjoint stars such that each star has at most leaves.
Proof.
Take a partial star-decomposition of that is as large as possible. Assume that there are uncovered vertices in . Let denote those vertices that are covered (so we assume that has maximal cardinality), and let be an uncovered vertex. Observe that has neighbours only in otherwise, if with , then we can simply add to the star-decomposition, contradicting to the maximality of . See Figure 2 for the possible neighbors of .
- a)
If is connected to a 1-star, then we can replace it with a 2-star. 2. b)
If is connected to the center of an -star, where , then we can replace this star with an -star by adding the edge to the -star. 3. c)
If is connected to a leaf of an -star, where , then replace the star with the edge and an -star (i.e., delete from it).
We have not yet considered one more case: when is connected to the center of a -star. However, simple calculation shows that for every vertex at least one of the above three cases must hold, using the minimum degree condition of . Hence we can increase the number of covered vertices. We arrived at a contradiction, has the desired star-decomposition. ∎
4.3 Preparing for the embedding
Consider the -star-decomposition of as in 21. Let denote the number of -stars in the decomposition for every . It is easy to see that
[TABLE]
First we will make every -regular pair in super-regular by discarding a few vertices from the non-exceptional clusters. Let for example be a star in the decomposition of with center cluster and leaves where . Recall that the pairs has density at least . We repeat the following for every if such that has at most neighbors in then discard from put it into . Similarly, if has at most neighbors in then discard from put it into . Repeat this process for every star in . We have the following:
Claim 22**.**
We do not discard more than vertices from any non-exceptional cluster.
Proof.
Given a star in the decomposition assume that its center cluster is and let be one of its leaves. Since the pair is -regular with density at least neither nor can have more than vertices that have at most neighbors in the opposite cluster. Hence, during the above process we may discard up to vertices from . Next, we may discard vertices from the leaves, but since no leaf had more than vertices with less than neighbors in even after discarding at most vertices of there can be at most vertices in that have less than neighbors in . Using that we have that . We obtained what was desired. ∎
By the above claim we can make every -regular pair in a -super-regular pair so that we discard only relatively few vertices. Notice that we only have an upper bound for the number of discarded vertices, there can be clusters from which we have not put any points into . We repeat the following for every non-exceptional cluster: if vertices were discarded from it with then we take arbitrary vertices of it, and place them into . This way every non-exceptional cluster will have the same number of points, precisely . For simpler notation, we will use the letter for this new cluster size. Observe that has increased by vertices, but we still have since and . Since in the resulting pairs the minimum degree will be at least .
Summarizing, we obtained the following:
Lemma 23**.**
By discarding a total of at most vertices from the non-exceptional clusters we get that every edge in represents a -super-regular pair, and all non-exceptional clusters have the same cardinality, which is denoted by . Moreover, .
Since is bounded above by a constant, when embedding we need almost every vertex of in particular those in the exceptional cluster . For this reason we will assign the vertices of to the stars in . This is not done in an arbitrary way.
Definition 24**.**
Let be a vertex and be an -regular pair. We say that has large degree to if has at least neighbors in . Let be a star in where is the center of and are the leaves, here . If has large degree to any of then can be assigned to . If and has large degree to then can be assigned to any of the leaves.
Observation 25**.**
If we assign new vertices to a -star, then we necessarily assign them to the center. Since before assigning, the number of vertices in the leaf-clusters is exactly times the number of vertices in the center cluster, after assigning new vertices to the star, times the cardinality of the center will be larger than the total number of vertices in the leaf-clusters. If is a -star with and we assign up to vertices to any of its clusters, where then even after assigning new vertices we will have that times the cardinality of the center is larger than the total number of vertices in the leaf-clusters.
The following lemma plays a crucial role in the embedding algorithm.
Lemma 26**.**
Every vertex of can be assigned to at least non-exceptional clusters.
Proof.
Suppose that there exists a vertex that can be assigned to less than clusters. If cannot be assigned to any cluster of some -star with then the total degree of into the clusters of is at most . If cannot be assigned to any cluster of some -star then the total degree of into the clusters of is at most since every vertex of the center cluster could be adjacent to . Considering that can be assigned to at most clusters and that we obtain the following inequality:
[TABLE]
Using and we get
[TABLE]
Dividing both sides by and cancellations give
[TABLE]
Noting that one can easily see that we arrived at a contradiction. Hence every vertex of can be assigned to several non-exceptional clusters. ∎
26 implies the following:
Lemma 27**.**
One can assign the vertices of so that at most vertices are assigned to non-exceptional clusters.
Proof.
Since we have at least choices for every vertex, the bound follows from the inequality where we used and . ∎
Observation 28**.**
A key fact is that the number of newly assigned vertices to a cluster is much smaller than their degree into the opposite cluster of the regular pair since .
4.4 The embedding algorithm
The embedding is done in two phases. In the first phase we cover every vertex that belonged to together with some other vertices of the non-exceptional clusters. In the second phase we are left with super-regular pairs into which we embed what is left from using the Blow-up lemma.
4.4.1 The first phase
Let be an -regular cluster-edge in the -star . We begin with partitioning and randomly, obtaining and with . For every (except those that came from ) flip a coin. If it is heads, we put into otherwise we put it into . Similarly, we flip a coin for every (except those that came from ) and depending on the outcome, we either put the vertex into or into . The proof of the following lemma is standard, uses Chernoff’s bound (see in [1]), we omit it.
Lemma 29**.**
With high probability, that is, with probability at least we have the following:
\big{|}|A^{\prime}|-|A^{\prime\prime}|\big{|}=o(n)* and \big{|}|B^{\prime}|-|B^{\prime\prime}|\big{|}=o(n)*
* for every *
* for every *
the density
it is easy to see that 29 implies that is a -super-regular pair having density at least with high probability.
Assume that was an element of before we assigned it to the cluster and assume further that . Since is an edge of the star-decomposition, either or must be the center of .
Let be one of the -unbalanced bipartite subgraphs of that has not been embedded yet. We will use to cover . Denote and the vertex classes of where . Let and .
If is the center of then the vertices of will cover vertices of and the vertices of will cover vertices of . If is the center, and will switch roles. The embedding of is essentially identical in both cases, so we will only discuss the case when is the center.222Recall that if then we may assigned to a leaf, so in such a case could be the center.
In order to cover we will essentially use a well-known method called Key lemma in [10]. We will heavily use the fact that
[TABLE]
The details are as follows. We construct an edge-preserving injective mapping . In particular, we will have and . First we let . Set . Using 29 we have that .
Next we find . Since by -regularity the majority of the vacant vertices of will have at least neighbors in . Pick any of these, denote it by and let . Also, set .
In general, assume that we have already found the vertices their common neighborhood in is and
[TABLE]
By -regularity, this implies that the majority of the vacant vertices of has large degree into at least and this, as above, can be used to find . Then we set . Since and is large compared to even into the last set many vacant vertices will have large degrees.
As soon as we have it is easy to find the images for . Since we can arbitrarily choose vacant points from for the images.
Note that we use less than vertices from and during this process. We can repeat it for every vertex that were assigned to and still at most vertices will be covered from and from .
Another observation is that every -star in the decomposition before this embedding phase was -unbalanced, now, since we were careful, these have become -balanced with .
Of course, the above method will be repeated for every edge of the decomposition for which we have assigned vertices of .
4.4.2 The second phase
In the second phase we first unite all the randomly partitioned clusters. For example, assume that after covering the vertices that were coming from the set of vacant vertices of is denoted by . Then we let and using analogous notation, let .
Claim 30**.**
All the pairs are -super-regular with density at least .
Proof.
The -regularity of these pairs is easy to see, like the lower bound for the density, since we have only covered relatively few vertices of the clusters. For the large minimum degrees note that by 29 every vertex of had at least neighbors in hence, in as well, and analogous bound holds for vertices of . ∎
At this point we want to apply the Blow-up lemma for every star of individually. For that we first have to assign those subgraphs of to stars that were not embedded yet. We need a lemma.
Lemma 31**.**
Let be a complete bipartite graph with vertex classes and where and . Assume that where . Let be the vertex disjoint union of -unbalanced bipartite graphs:
[TABLE]
such that for every . If then .
Observe that if we have 31, we can distribute the subgraphs among the stars of and then apply the Blow-up lemma. Hence, we are done with proving Theorem 5 if we prove 31 above.
Proof.
The proof is an assigning algorithm and its analysis. We assign the vertex classes of the subgraphs to and one-by-one. Before assigning the th subgraph the number of vacant vertices of is denoted by and the number of vacant vertices of is denoted by .
Assume that we want to assign . If then the larger vertex class of is assigned to the smaller is assigned to . Otherwise, if then we assign the larger vertex class to and the smaller one to . Then we update the number of vacant vertices of and . Observe that using this assigning method we always have .
The question is whether we have enough room for . If then we must have enough room, since and every has at most vertices. Hence, if the algorithm stops, we must have . Since must hold, we have . From this the lemma follows. ∎
5 Remarks
One can prove a very similar result to Theorem 5, in fact the result below follows easily from it. For stating it we need the notion of graph edit distance which is detailed e.g. in [12]: the edit distance between two graphs on the same labeled vertex set is defined to be the size of the symmetric difference of the edge sets
Theorem 32**.**
Let be an integer. For every and there exists an and a such that if , is a -unbalanced degree sequence of length with , is a graph on vertices with , then there exists a graph on vertices such that the edit distance of and is at most , and can be embedded into .
Here is an example showing that Theorem 5 and 32 are essentially best possible.
Example 33**.**
Assume that has only odd numbers and has at least one odd sized component. The embedding is impossible. Indeed, any realization of has only even sized components, hence cannot contain it as a spanning subgraph.
Note that this example does not work in case is connected. In Theorem 3 the minimum degree hence, is connected, and in this case we can embed into .
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