Abstract
A hypercube is a graph whose nodes can be labeled by binary vectors such that the distance between the binary addresses in the graph is the Hamming distance. Due to the symmetry of the hypercube, one usually considers the graph embedded in the hypercube proportionally in distance, meaning that the -graphs. In this paper, we determine the -embeddability of hypertrees and unicyclic hypergraphs.
1. Background
In many complex systems, the interaction between substances is collective, and this interaction between groups is ubiquitous in many fields. For example, joint procurement of goods, the interaction of proteins, labels posted on posts on the same website, cooperation between researchers, and so on. However, the interaction between these groups cannot be represented by vertices and edges in simple graphs. Suppose three or more researchers wrote a book together—this book cannot be represented by an edge in the simple graph. Furthermore, if an edge is created among all researchers, many papers jointly written by some researchers cannot be distinguished [1]. Hypergraphs can naturally represent the interaction between groups because they are composed of vertices and hyperedges, which solves the inherent limitations of a simple graph. Each hyperedge of a hypergraph can be a subset of the vertex set and it can represent the group interaction between vertices, so research on hypergraphs is also extremely necessary.
Hypergraphs can better represent the real world. Complex structures similar to a mesh in life can be represented by hypergraphs. In the paper [2], Claude Berge first mentioned the concept of the hypergraph. In 1973, Paul Seymour [3] discussed the related problems of minimal hypergraphs which are not 2-colourable. Claude Berge [4] described the related concepts of hypergraphs and the theory of hypergraphs in 1989. Up to the 21st century, the study of hypergraphs has remained a very hot topic. In recent years, Zikai Tang, Xiuping Fang, and Yaoping Hou [5] discussed and studied the spectral radii of the k-uniform linear hypergraphs in 2018. Furthermore, Geon Lee, Jihoon Ko, and Kijung Shin [1] investigate the local structures of real-world hypergraphs with the help of algorithms in 2020. Xiangxiang Liu, Ligong Wang, and Xihe Li [6] found the Wiener index of special hypergraphs in 2020. Mario Gionfriddo and others studied the relevant concepts of hypercycle systems in 2020 [7]. However, no one has studied the -embeddability of hypergraphs.
In the past half-century, people’s research on graph theory has shown an extremely active trend along with the rapid advancement of science and technology. The distance in a graph is a very important concept in graph theory, which is widely used in physics, chemistry, and computer information science. For example, when considering the distance between atoms in a chemical molecule, the distance between nodes in a traffic network, and the distance between nodes in a computer network, we only need to abstract the actual network into a graph, and then consider the distance between the vertices in the graph. A hypercube graph is a kind of graph with good symmetry, and the distance between any two vertices on it is the Hamming distance. In order to make the calculation of distance in the considered graph easier, people try to embed the considered graph into the hypercube graph proportionally. An -graph refers to a graph that can be embedded into a hypercube proportionally. In the past few decades, the -embeddability of graphs has been intensively studied. Assouad and Deza in [8,9] gave a judgment theorem on how to identify a graph as an -graph. According to this result, a graph is an -graph if and only if it can be embedded into a hypercube graph proportionally. Karzanov [10] proved that the identification problem for general -spaces is NP-complete. Surprisingly, Shpectorov [11] proved that an -graph can be recognized in polynomial time. Research on the -graph is also in full swing. It has extensive and profound applications in complex networks, information science, transportation, chemical graph theory, circuit communication, and other fields. For example, consider the Wiener index of a graph, that is, the sum of the distances between all pairs of vertices in the graph. If calculated directly using the defined formula, its complexity is the cubic order of vertices. However, if the graph is -embedded, its computational complexity can be reduced to the linear order of vertices.
To obtain more useful information or simpler algorithms, people usually put the studied complex objects into some well-studied mature space. Based on this, one usually considers putting the research objects into the -space. Studying the -embeddability of hypergraphs is of great significance to real life. For example, how connecting the particles of a molecule makes the molecular structure more stable; How connecting wires between the wiring ports of the circuit board makes the battery thinner and more practical. Therefore, it is necessary to study the -embeddability of hypergraphs. In this paper, we characterize the -embeddability of hypertrees and unicyclic hypergraphs.
2. Preliminaries
A hypergraph is an ordered pair of a finite set of vertices, the vertex set V, and a finite multiset of hyperedges, the edge set E, such that each hyperedge is a non-empty subset of V, i.e., for all . The number of vertices contained in the hypergraph is called the order of the hypergraph, which is denoted as . The number of hyperedges included in the hypergraph is called the size of the hypergraph, which is denoted as . Consequently, a graph is a hypergraph , where each hyperedge is a set of at most two vertices: for all [2,12].
A simple hypergraph is a hypergraph H such that . A simple graph is a simple hypergraph each of whose hyperedges has two vertices [4].
Throughout this article, we focus on simple hypergraphs, meaning that the number of vertices on each hyperedge is greater than or equal to 2 [12]. In this paper, the graphs we consider are simple graphs.
The maximum number of vertices contained in the hyperedges of the hypergraph is denoted by the rank of the hypergraph. The minimum number of vertices contained in the hyperedges of the hypergraph is denoted by the lower rank of the hypergraph. When each hyperedge of the hypergraph contains the same number of vertices (i.e., =), the hypergraph H is called a uniform hypergraph [4]. A simple uniform hypergraph of rank k is called a k-uniform hypergraph [4,12].
For any vertex v in the vertex set V, the number of hyperedges that contain v is called the degree of vertex v in the hypergraph H, denoted as .
In the hypergraph H, a vertex-hyperedge sequence is called a chain of length k [3], simply -chain, if it satisfies: (1) For any two vertices, ; (2) For any two hyperedges in the hypergraph ; (3) . In particular, if , then this chain is called a hypercycle of the hypergraph. If , the hypercycle is called significant [13]. Denotes a hypercycle of m hyperedges by . Accordingly, in a simple graph, a cycle is a hypercycle in which each hyperedge contains two vertices. In particular, the k cycle is denoted by .
If there is a - in a hypergraph, and are said to be connected. If there is a chain between any two vertices of the hypergraph, the hypergraph is said to be . A connected hypergraph with no hypercycle is called a , denoted by . If , then the vertex x is called the branch vertex of . If two hyperedges and share the same branch vertex x, they are said to be adjacent. In this case, and . If two vertices are in the same hyperedge, they are called adjacent.
Let be a subset of E and let S denote the subset of V consisting of all vertices in H of hyperedges in . Then the hypergraph is the subhypergraph of H induced by the hyperedge set of H. It is denoted by [14].
In a connected hypergraph, among all -chains, the least number of hyperedges contained in the - is called the distance between and , denoted as [3].
For a hypergraph H = , if , H is called a [4], whenever , , .
For a hyperedge of a hypergraph, if there is exactly one vertex whose degree is at least 2, is called a hanged hyperedge.
For , a superstar of H—with v as a center—is the set of hyperedges that contains v [15]. If each hyperedge in the superstar contains k vertices, it is called a k-uniform superstar. This denotes a k-uniform superstar with n vertices and m hyperedges by . It is clear that satisfies .
If the hypergraph is connected and it has only one hypercycle, then it is a unicyclic hypergraph. When a unicyclic hypergraph contains m hyperedges, it is denoted by .
Let X be the set of all real number sequences , where . For any , define the distance function . Then is a metric space, usually called the -space. If and Y is linear space, then the metric space is called the subspace of -space [16].
Let be a connected graph. For any two vertices u and v, represents the distance between u and v in graph G, that is, the length of the shortest path connecting u and v. Obviously is a metric on , and is a metric space, called the graphic metric space associated with G [17,18].
A graph G is an -graph [19] if the metric space is an isometric subspace of -space. If graph G is an -graph, then graph G has the -embeddability property. That is, there is a distance-maintaining mapping from to X, such that for any two vertices .
An n-dimensional hypercube or n-cube is defined as follows: the n-cube is a graph whose vertices are the ordered n-tuples of 0’s and 1’s, two vertices being joined if and only if they differ in exactly one coordinate [14,16].
In 1980, Assouad and Deza [8] proved that a graph G is an -graph if and only if there are two positive integers and n, the graph G can be scale--embedded into a hypercube . That is, for any two vertices , there is a mapping , which satisfies . Among them, is called the scale of G [20]. For convenience, we use to denote that graph G is scale--embeddable into the hypercube .
A subset S of vertices of a graph G is convex if for any two vertices u, v of S all vertices on shortest -paths belong to S. Divide the vertex set into two non-empty parts A and B, satisfying ; called a cut of G. If both A and B are convex, then the cut is a convex cut [21,22]. A cut of Gcuts an edge if and . It was known that -graphs can be recognized by convex cuts [21,22].
Theorem 1
([21,22]). A graph G is scale-λ-embeddable into a hypercube if and only if there exists a collection of convex cuts (not necessarily distinct) such that every edge of G is cut by exactly λ cuts from . Furthermore, if has n cuts, G can be scale-λ-embeddable into the hypercube .
3. -Embeddability of Hypertrees
Before discussing the -embeddability of hypergraphs, we must give several lemmas to facilitate the proof of the main theorems. Deza and Laurent proposed some examples of -graphs in [23]. They also presented some operations which preserve -embeddability such as “1-” and direct product of two -graphs. Here “1-” of two graphs means identifying a single vertex from two graphs. Let and be two disjoint graphs, where the vertex , vertex . Now identify vertex and vertex into a new vertex x, such that . We say that the resulting graph is obtained by identifying a single vertex x from and , and denote it by . This operation is called “1-” operation. At the same time, we denote that and .
Firstly, the definition of a complete graph is given. A simple graph G is said to be complete if every pair of distinct vertices of G are connected in G [14]. A complete graph with n vertices is often denoted by .
Lemma 1
([23]). .
Lemma 2
([23]). Let and be two -graphs. Then is an -graph.
Lemma 3.
Every hypertree with m hyperedges has at least two hanged hyperedges.
Proof.
Let be the longest chain in the hypertree . It can be assumed that is any 1-degree vertex in , and is any 1-degree vertex in . The hyperedge has no adjacent hyperedge at vertex . Similarly, the hyperedge has no adjacent hyperedge at vertex . Otherwise, either a hypercycle is formed, or a chain longer than P is formed, but this is clearly impossible. Therefore, the hyperedge and the hyperedge are two hanged hyperedges. Hence, every hypertree with m hyperedges has at least two hanged hyperedges. □
Lemma 4
([18]). For any nonnegative integer k, if , then .
Lemma 5.
If and , then .
Proof.
Let and be two positive integers. In addition, and . Let be obtained by identifying single vertices x from and . By Lemma 4, there are and . By Lemma 2, the graph is an -graph. Moreover, by Theorem 1, the convex cuts of and are still convex cuts in . That is, the graph was obtained by identifying vertex x with and and performing “1-” operation will not affect the convex cut division of and , then . □
To facilitate the proof of the principal theorem, we give a new definition of hypergraph H. Construct a simple graph as the accompanying base graph of H, denoted by . Such that , two vertices are joined by one edge if and only if they lie in the same hyperedge of H.
Note 1: A clique of G is a complete subgraph of G. For any hyperedge in H, the vertices in induce a clique in .
Note 2: Further, for any two vertices of H, .
Below are some of the theorems of the -embeddability of hypertrees.
Theorem 2.
Any hypertree is an -graph. In fact, a hypertree with n vertices and m hyperedges is scale-2-embedded into the hypercube .
Proof.
Denote the hypertree containing i hyperedges by , and denote the m hyperedges of hypertree by . Suppose that the cardinality of is .
When , the hypertree has exactly one hyperedge. Let be this hyperedge, and . It is obvious that the accompanying base graph of is a complete graph. By Lemma 1, is an -graph, and . Since , , the hypertree is scale-2-embeddable into a hypercube
The result is clearly true for . So assume that . We apply mathematical induction on m. Assume that the theorem is true for all hypertrees having fewer hyperedges than . If the hypertree contains hyperedges then . By Lemma 3, take one hanged hyperedge in hypertree as , such that . By the inductive hypothesis, the hypertree is an -graph, , and the hypertree can be scale-2-embeddable into the hypercube .
Suppose that the hypertree can be seen as a hypergraph obtained by identifying the branch vertex x from and . It is clear that . By the inductive hypothesis, , . By Lemma 2, the hypertree is an -graph. By Lemma 5, The proof is complete by the induction assumption. □
From the above theorem, we give the -embeddability of a special hypertree.
Corollary 1.
The k-uniform superstar is scale-2-embedded into the .
Proof.
It is sufficient to substitute into . □
The dimension of the hypercube also can be expressed in degrees as follows:
Theorem 3.
Any hypertree with m hyperedges can be scale-2-embeddable into the hypercube , where is the number of i-degree vertices .
Proof.
By induction on m. Let be a hypertree containing i hyperedges, and denote the m hyperedges of the hypertree by . Suppose that the cardinality of is , is the number of i-degree vertices of the hypertree .
When , the hypertree consists of only one hyperedge, say . Let be the number of i-degree vertices of the hypertree . Then . It is obvious that the accompanying base graph of is a complete graph, and by Lemma 1, is an -graph, . Hence, the hypertree is scale-2-embeddable into the hypercube .
Now assume that the result is true for the hypertree with hyperedges . Let be the number of i-degree vertices of the hypertree . By the inductive hypothesis, the hypertree is an -graph, and .
By Lemma 3, every hypertree with m hyperedges has at least two hanged hyperedges. Take one hanged hyperedge in hypertree as . Suppose that the branch vertex of is x. Then the hypertree can be seen as a hypergraph obtained by identifying x from and . It is clear that . Assume that , , then . By the inductive hypothesis, , . By Lemma 2, the hypertree is an -graph. Then by Lemma 5, , where Moreover,
Since contains only one hyperedge and all vertices of are 1-degree vertices, then . Due to containing hyperedges, there will be no m-degree vertices in , i.e., . This completes the proof of the theorem. □
4. -Embeddability of Unicyclic Hypergraphs
In this section, we will focus on the -embeddability of unicyclic hypergraphs. In particular, we also study the -embeddability of hypercycles.
In 2013, Guangfu Wang and Heping Zhang [16] introduced the gluing edge operation (“2-” operation) of two graphs. Let and be two disjoint graphs, where the edge in , edge in . Now identify edge with edge as a new edge , such that and or and . We say that the resulting graph is obtained by gluing and along the edge e and denote it by or . They get a sufficient condition of a graph obtained from two -graphs by gluing an edge is still an -graph, see Lemma 6.
Lemma 6
([16]). Let and be two -graphs. If at least one of them is bipartite, then is an -graph.
Before proving the main theorem, we introduce a special class of graphs. Let be a cycle of length n, where . Joining each vertex of with a new out of by an edge obtains a graph, called a denoted as . Furthermore, for integer , we join each vertex of with new vertices to produce a generalized sun graph, denoted by [24]. It is reasonable to allow some , that is, no joining the vertex of with any new vertex. For instance, the generalized sun graph is shown in Figure 1.
Figure 1.
Generalized sun graph .
The line graph of a graph G has vertices corresponding to the edges of G and two vertices are adjacent in if their corresponding edges of G have a common end-vertex.
From the definition of the line graph, we can know that the line graph of a generalized sun graph is the graph obtained from a cycle and n complete graphs by the “2-” operation at their corresponding positions gradually, denoted by , abbreviated as [17]. For instance, the line graph of generalized sun graph is shown in Figure 2.
Figure 2.
Line graph of generalized sun graph .
Lemma 7
([17]). An is an -graph.
Then, from the above lemma, we get the following theorem:
Theorem 4.
A hypercycle with n vertices and m hyperedges is an -graph and can scale-2-embeddable into a hypercube .
Proof.
Clearly, the accompanying base graph of hypercycle is isomorphic to the linear graph of generalized sun graph . By Lemma 7, we get that the is an -graph. Because for any two vertices v, u of , . Then the hypercycle is an -graph.
Next, we will prove that . Assume that the hypercycle contains n vertices and m hyperedges. The degree of a vertex of is either 1 or 2. Suppose that the hypercycle contains vertices with degree 1 and vertices with degree 2. It is clear that , . Let the hypercycle be , and , , …, , , where are the 2-degree vertices in and are the 1-degree vertices in . The hyperedge of a hypercycle corresponds to a complete graph of its accompanying underlying graph , denoted this complete graph by . Therefore, can be seen as the result obtained by the “2-sum” operation of a cycle and m complete graphs at corresponding positions m times. It is clear that is isomorphic to the linear graph of generalized sun graph .
We will prove the -embeddability of hypercycle by convex cuts. Convex cuts are constructed according to the degree of the vertices of . It is detailed in the following text.
Firstly, let’s discuss convex cuts of the first kind.
Take any vertex or of degree 1 of . Now we give a cut , which is the vertices division of the accompanying base graph , where , . As shown in Figure 3, let be the induced subgraph of the single vertex in , and let be the induced subgraph of the vertices in . In the vertex set , the shortest path from the to the is still in , then is convex. In the vertex set , for any two vertices , the shortest path from to is still in , because is still in the form of . The shortest path of any two vertices on the graph is still in , (If two vertices are in the same complete graph, the distance between the two vertices is 1. Otherwise, the shortest path between two vertices must follow the m-cycle . That is, the shortest path between any two vertices is still in ), then is convex. So the cut is a convex cut.
Figure 3.
Convex cuts of the first kind ( and ).
Therefore, there are cuts of the first kind in that are convex cuts. Denote these convex cuts by , , …, . Then there exists a collection of convex cuts of , such that . Moreover, the edge between and (or and ) is cut by 2 cuts from , and the edge between and (or and ) is cut by 1 cut from .
Secondly, let us discuss convex cuts of the second kind.
- (1)
- When m is even, see Figure 4a. A cut is given, which is the vertices division of the accompanying base graph , where , . Let be the induced subgraph of the vertex in . Let be the induced subgraph of the vertex in . Take any two vertices in , such as , or , or , or ,. The content is divided into the following two categories:
Figure 4. Convex cuts of the second kind ( and ). (a) A partition of convex cuts of the second kind; (b) Another partition of convex cuts of the second kind.- ➀
- If , we have ; ; ; , because for any graph or , these graphs are still complete graphs, in which the distance between any two different vertices is 1. Moreover, the shortest path between the two different vertices in graph is still in .
- ➁
- If , we haveThe shortest path of any two different vertices in graph must be along the m-cycle . So the shortest path between the two vertices of is still in , and is convex.
In the same way, the shortest path between any two vertices of is still in , so is convex. Then the cut is a convex cut. Since m-cycle is an even length cycle, the i-th convex cut is repeated with the -th convex cut. There are convex cuts like this. Similarly, another convex cuts as shown in Figure 4b will be obtained. In fact, these two types of convex cuts appear symmetrically.
Thus, when m is even, there are cuts of the second kind in that are convex cuts. Denote these convex cuts by , , …, . Then there exists a collection of convex cuts of , such that . Moreover, the edge between and (or and ) is cut by one cut from , and the edge between and is cut by two cuts from .
- (2)
- When m is odd, see Figure 5. A cut is given, which is the vertices division of the accompanying base graph , where , . Let be the induced subgraph of the vertex in . Let be the induced subgraph of the vertex in . Taking any two vertices in graph , such as , , or , , or , . The content is divided into the following two categories:
Figure 5. Convex cuts of the second kind ( and ).- ➀
- If , we have ; ; ; . Because for any graph or or , these graphs are still complete graphs, in which the distance between any two different vertices is 1. Moreover, the shortest path between the two different vertices in graph is still in .
- ➁
- If , we haveThe shortest path of any two different vertices in graph must be along the m-cycle . So the shortest path between the two vertices of is still in , then is convex. In the same way, the shortest path between any two vertices of is still in , so is convex. Then the cut is a convex cut.
Since m-cycle is an odd length cycle, there are convex cuts like this. So when m is odd, there are cuts of the second kind in that are convex cuts. Denote these convex cuts by , , …, . Then there exists a collection of convex cuts of , such that . In fact, these convex cuts all appear symmetrically. Moreover, the edge between and (or and ) is cut by one cut from , and the edge between and is cut by two cuts from .
Consequently, all the cuts of the second kind in are convex cuts.
Therefore, in the accompanying base graph of the hypercycle , there are convex cuts, which can form a convex cut cluster or . By Lemma 1, each edge of the accompanying base graph is cut by exactly two cuts from , so the graph can scale-2-embeddable into a hypercube . Because for any two vertices v, u of , . Then the hypercycle can scale-2-embeddable into a hypercube . □
Finally, we study the -embeddability of unicyclic hypergraphs. Given a unicyclic hypergraph , where n is the number of vertices, m is the number of hyperedges, is the number of vertices contained in a single cycle in the unicyclic hypergraph, is the number of edges contained in a single cycle in the unicyclic hypergraph, is the number of edges other than the number of edges contained in a single cycle. It is clear that . Then we have:
Theorem 5.
Any unicyclic hypergraph is an -graph. In fact, a unicyclic hypergraph with n vertices and m hyperedges is scale-2-embedded into a hypercube .
Proof.
The unicyclic hypergraph is obtained by gradually using “1-” operation between the hypercycle and some hyperedges. For any hyperedge in hypergraph H, the vertices in induce a clique in . By Lemma 1, is an -graph. Combining Theorem 4 and Lemma 2, we know that any unicyclic hypergraph is an -graph.
Next, we will prove that . Suppose that a unicyclic hypergraph with n vertices and m hyperedges is . Assume that the number of vertices contained in a single hypercycle is and the number of hyperedges is , where . We prove the result by mathematical induction on m.
- (1)
- Assume that a unicyclic hypergraph has no hanged hyperedges. Without loss of generality, at this time, any unicyclic hypergraph is a hypercycle , then , , . By Theorem 4, a unicyclic hypergraph is an -graph and . Hence, a unicyclic hypergraph without hanged hyperedges can be scale-2-embeddable into a hypercube .
- (2)
- When a unicyclic hypergraph contains hanged hyperedges. If the unicyclic hypergraph contains a hanged hyperedge. Let be the hanged hyperedge, and let be the unicyclic hypergraph. By Lemma 2, . Hence, the unicyclic hypergraph is scale-2-embedded into a hypercube .
The result can be verified for a unicyclic hypergraph containing a hanged hyperedge. Hence, suppose that the result is true for a unicyclic hypergraph containing more than one hanged hyperedges. Assume that a unicyclic hypergraph contains hanged hyperedges, then the unicyclic hypergraph is . By inductive assumptions, any unicyclic hypergraph is an -graph and .
When a unicyclic hypergraph contains hanged hyperedges, obviously, denoted this unicyclic hypergraph by . Denoted the hanged hyperedge added to unicyclic hypergraph by . By Lemma 2, . Moreover, . Hence, the result is true. □
5. Applications
According to the inspiration of applying graph theory knowledge to real life [25,26], the hypergraph studied in this paper also has many applications. The distance-based topological indices of many molecules (such as the Wiener index, Szeged index, PI index, etc.) are closely related to their physical and chemical properties [27,28]. We already know that the distance between any two vertices in a hypercube graph is exactly equal to the number of different positions representing the array of the two vertices [29]. If a hypergraph is an -graph, we can easily get the distance between any two vertices in the hypergraph, and then we can further calculate its various indices. Here is a simple example to find the Erds number for any author.
Now we give ten authors. If several authors work together to write an article, these authors will form a hyperedge. According to this principle, the relation of these authors is shown in Figure 6, forming a unicyclic hypergraph , where , , and . The question is to find the Erds number for any author.
Figure 6.
Unicyclic hypergraph .
By Theorem 5, this hypergraph is scale-2-embedded into a hypercube . Next, we get the accompanying base graph of this hypergraph, see Figure 7. According to the vertex label of the hypercube graph [14], each vertex of the accompanying base graph is labeled, as shown in Figure 7.
Figure 7.
The accompanying base graph .
By observing the vertex labels of Wang and Erds, it can be found that the labels of these two vertices are different in four positions, so the distance between Wang and Erds in is 4. Since this hypergraph , then the Erds number of Wang is .
By observing the vertex labels of Chen and Erds, it can be found that the labels of these two vertices are different in four positions, so the distance between Chen and Erds in is 2. Since this hypergraph , then the Erds number of Chen is . According to this method, we can find the Erds number of any author.
6. Conclusions
In this paper, we mainly examine the -embeddability of hypertrees and unicyclic hypergraphs. We found that a hypertree with n vertices and m hyperedges is scale-2-embedded into the hypercube . Considering the degree of the vertices, any hypertree with m hyperedges can be scale-2-embeddable into the hypercube . Specially, we show that a hypercycle with n vertices and m hyperedges is an -graph and can scale-2-embeddable into a hypercube . In addition, a unicyclic hypergraph with n vertices and m hyperedges is scale-2-embedded into a hypercube . It has a profound significance for simplifying the calculation of the distance between two vertices of a hypergraph, and it will also have a wide and profound impact on chemical, physical and electronic information.
Author Contributions
Methodology, G.W. and L.C.; validation, G.W. and L.C.; investigation, L.C. and Z.X.; resources, L.C. and Z.X.; writing—original draft preparation, L.C. and Z.X.; writing—review and editing, G.W. and L.C.; supervision, G.W.; project administration, G.W.; funding acquisition, G.W. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by the National Natural Science Foundation of China (Grant Nos. 11861032, 11961026) and the Natural Science Foundation of Jiangxi Province (Grant No. 20202BABL201010).
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Lee, G.; Ko, J.; Shin, K. Hypergraph motifs: Concepts, algorithms, and discoveries. Proc. Vldb. Endow. 2020, 13, 2256–2269. [Google Scholar] [CrossRef]
- Berge, C. Graphes et Hypergraphes; Monographes Universitaires de Mathémathiques; Dunod: Paris, France, 1970. [Google Scholar]
- Seymour, P.D. On the two-colouring of hypergraphs. Q. J. Math. 1974, 25, 303–311. [Google Scholar] [CrossRef]
- Berge, C. Hypergraphs, Combinatorics of Finite Sets; North-Holland Publishing: Amsterdam, The Netherlands, 1989; Volume 45, p. 267. [Google Scholar]
- Tang, Z.; Fang, X.; Hou, Y. On the spectral radii of k-uniform linear hypergraphs. J. Nat. Sci. Hunan Norm. Univ. 2018, 41, 87–94. [Google Scholar]
- Liu, X.; Wang, L.; Li, X. The wiener index of hypergraphs. J. Comb. Optim. 2020, 39, 351–364. [Google Scholar] [CrossRef]
- Gionfriddo, M.; Milazzo, L.; Tuza, Z. Hypercycle systems. Australas. J. Comb. 2020, 77, 336–354. [Google Scholar]
- Assouad, P.; Deza, M. Espaces métriques plongeables dans un hypercube: Aspects combinatoires, Ann. Discret. Math. 1980, 8, 197–210. (In French) [Google Scholar]
- Assouad, P.; Deza, M. Metric Subspaces of L1; Université de Paris-Sud, Département de Mathématique d’Orsay: Paris, France, 1982. [Google Scholar]
- Karzanov, A.V. Metrics and undirected cuts. Math. Program. 1985, 32, 183–198. [Google Scholar] [CrossRef]
- Shpectorov, S.V. On scale embeddings of graphs into hypercubes. Eur. J. Comb. 1993, 14, 117–130. [Google Scholar] [CrossRef]
- Berge, C. Graphs and Hypergraphs; North-Holland: Amsterdam, The Netherlands, 1973. [Google Scholar]
- Lewin, M. On hypergraphs without significant cycles. J. Comb. Theory Ser. B 1976, 20, 80–83. [Google Scholar] [CrossRef][Green Version]
- Bondy, J.A.; Murty, U.S.R. Graph Theory with Applications; Macmillan: London, UK; Elsevier: New York, NY, USA, 1976. [Google Scholar]
- Bretto, A.; Cherifi, H.; Ubéda, S. An efficient algorithm for helly property recognition in a linear hypergraph. Electron. Notes Theory Comput. Sci. 2001, 46, 177–187. [Google Scholar] [CrossRef][Green Version]
- Wang, G.; Zhang, H. l1-embeddability under the edge-gluing operation on graphs. Discret. Math. 2013, 313, 2115–2118. [Google Scholar] [CrossRef]
- Li, C.; Wang, G. The l1-embeddability of trees, unicyclic graphs and their line graphs. Math. Pract. Theory 2020, 50, 305–311. (In Chinese) [Google Scholar]
- Wang, G. l1-Embeddability of Graphs and Its Applications; Southeast University Press: Nanjing, China, 2017. (In Chinese) [Google Scholar]
- Deza, M.; Shpectorov, S.V. Polyhexes that are l1-graphs. Eur. J. Comb. 2009, 30, 1090–1100. [Google Scholar] [CrossRef][Green Version]
- Chepoi, V.; Deza, M.; Grishukhin, V.P. Clin d’oeil on L1-embeddable planar graphs. Discret. Appl. Math. 1997, 80, 3–19. [Google Scholar] [CrossRef]
- Bandelt, H.J.; Chepoi, V. Decomposition and l1-embedding of weakly median graphs. Eur. J. Comb. 2000, 21, 701–714. [Google Scholar] [CrossRef]
- Deza, M.; Grishukhin, V.; Shtogrin, M. Scale-Isometric Polytopal Graphs in Hypercubes and Cubic Lattices; Imperial College Press: London, UK, 2004. [Google Scholar]
- Deza, M.; Laurent, M. l1-rigid graphs. J. Algebr. Comb. 1994, 2, 153–175. [Google Scholar] [CrossRef]
- Yang, S.; Yao, B.; Yao, M. On felicitous character of generalized sun-graphs. Int. J. Math. 2015, 35, 318–326. [Google Scholar]
- Muhiuddin, G.; Takallo, M.M.; Jun, Y.B.; Borzooei, R.A. Cubic graphs and their application to a traffic flow problem. Int. J. Comput. Intell. Syst. 2020, 13, 1265–1280. [Google Scholar] [CrossRef]
- Qiang, X.; Kosari, S.; Chen, X.; Talebi, A.A.; Muhiuddin, G.; Sadati, S.H. A Novel Description of Some Concepts in Interval-Valued Intuitionistic Fuzzy Graph with an Application. Adv. Math. Phys. 2022, 2022, 2412012. [Google Scholar] [CrossRef]
- Balaban, A.T.; Motoc, I.; Bonchev, D.G.; Mekenyan, O.G. Topological indices for structure-activity correlations. Top. Curr. Chem. 1983, 114, 21–56. [Google Scholar]
- Wiener, H. Structural determination of paraffin boiling points. J. Am. Chem. Soc. 1947, 69, 17–20. [Google Scholar] [CrossRef] [PubMed]
- Imrich, W.; Klavžar, S. Product Graphs: Structure and Recognition; John Wiley & Sons: New York, NY, USA, 2000. [Google Scholar]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).