Abstract
A graph of order n is called pancyclic if it contains a cycle of length y for every . The connectivity of an incomplete graph G, denoted by , is . A graph G is said to be ℓ-connected if the connectivity . The Wiener-type indices of a connected graph G are , where is a function and is the distance in G between s and t. In this note, we first determine the minimum and maximum values of for ℓ-connected graphs. Then, we use the Wiener-type indices of graph G, the Wiener-type indices of complement graph with minimum degree or to give some sufficient conditions for connected graphs to be pancyclic. Our results generalize some existing results of several papers.
MSC:
05C45; 05C09; 05C92
1. Introduction
The graphs considered here are undirected, finite and simple. Following the convention, we use G to denote a graph (undirected, finite, simple), use to represent the vertex set (it must be a finite set) of the graph, use to represent the edge set of the graph and use to denote that there exists an edge between u and v. Furthermore, we use to denote an n-cycle (a graph in which all its vertices form a single closed loop, with each vertex connected to exactly two other vertices), to denote a complete bipartite graph of order n (a graph with a partition of its vertex set such that each vertex of is connected to each vertex of , and the subgraphs induced by and contain no edges) and to denote a complete graph of order n. Clearly, in a simple graph, a complete graph possesses the highest possible number of edges.
Let . The neighbor of u is a vertex subset , denoted by , and the size of the vertex subset is called the degree of vertex u, denoted by . Examining the degrees of vertices in graph theory has considerable significance. The degree of vertices is closely linked to the connectivity, Hamiltonian properties and sparsity of a graph. Under certain given conditions, by calculating the degree of the graph, we can determine whether it belongs to a certain class of graphs and whether there exists a cycle of a certain size, and so on. Moreover, in graph algorithms, the degree of vertices is often used as the basis for the algorithm design, as a range of graph parameters are associated with vertex degrees.
The complement graph of G is the graph with the same vertex set of G but its edge set is , denoted by . Therefore, for , there either exists an edge in the graph or in its complement graph, but not both. Regarding complement graphs, a famous result is that either a graph or its complement graph must be connected. Let and be two graphs that are disjoint from each other. Now, we introduce the union and the joint of two distinct graphs. The union of and , denoted by , is the graph with and . It is easy to see that the union is not connected if and are not empty graphs. The joint of and , denoted by , is the graph with and . It is easy to see that the joint is connected if and are not empty graphs (by the famous result of complement graphs mentioned above).
Let Y be a vertex subset of G. Then, we call Y a vertex cut if is not connected. Let G be a graph such that and it is not isomorphic to , and W be the set consisting of all vertex cuts of the graph G. The connectivity of G, denoted by , is . The minimum cut set is widely applied in network flow problems. A graph G is said to be ℓ-connected if , where is an integer. In other words, there does not exist a vertex subset of size such that the graph G becomes disconnected after removing this subset. Clearly, if G is -connected, then it is m-connected. For convenience, we introduce some notations here. We use to denote the set consisting of all the graphs which are connected and have n vertices, use to denote the set consisting of all the graphs which are connected, have connectivity and n vertices and use to denote the set consisting of all connected bipartite graphs with n vertices.
The distance between s and t is the value of the length of a shortest path in a graph G for vertex s and vertex t, denoted by ( for short). The distance is a core concept in this paper. Clearly, the distances are all equal to 1 in a complete graph. The eccentricity of vertex u in a graph G, denoted by , is , and the diameter of a graph G, denoted by , is defined as , or equivalently, is . Typically, a graph with a smaller diameter implies that the vertices in the graph are more easily accessible to each other.
A graph G is called pancyclic if the graph G contains a cycle of length y for every , where . Clearly, if a graph has the pancyclic property, then this graph is connected (since it includes a cycle whose length is equal to its number of vertices). For other undefined terminologies and notations, we refer readers to [1].
Topological indices are mathematical invariants derived from the structure of a graph. These indices can be categorized into several types based on their computational principles and applications, including the distance-based indices, the counting-based indices, the shape-based indices, the degree-based indices, the spectral indices and the information-theoretic indices. The distance-based indices are calculated based on the distances between vertices, the counting-based indices involve counting specific subgraphs, the shape-based indices capture the topological shape and measure the structural characteristics, the degree-based indices are calculated using the degrees of the vertices, the spectral indices are based on the spectrum of matrices (adjacency matrix, normalized Laplacian matrix) associated with the graph and the information-theoretic indices utilize concepts from information theory in the context of graphs, frequently involving the measurement of entropy or mutual information. Next, we introduce several distance-based indices: Wiener-type indices, which are a widely studied class of distance-based indices.
Let . The Wiener index of G, denoted by , was defined as [2]
Clearly, the value of the Wiener index depends only on the distances. Consequently, this characteristic of the calculation makes the Wiener index highly sensitive to the shape and size of the graph.
The Wiener-type indices of a connected graph G with respect to a function , denoted by , was defined as
Wiener-type indices are generalizations of the Wiener index. By introducing different functions , Wiener-type indices provide a broader range of tools and methods for studying and describing the structural characteristics of graphs. Now, we introduce some Wiener-type indices.
- is the Wiener index [2] when , denoted by .
- is the modified Wiener index [3] when for , denoted by .
- is the hyper-Wiener index [4] when , denoted by .
- is the Harary index [5] when , denoted by .
The above Wiener-type indices are important distance-based indices with significant applications in various scientific disciplines, particularly in chemistry. They are widely used topological indices in chemical graph theory. The Wiener index is closely linked to the molecular branching and structural properties of chemical compounds. The modified Wiener index refines the original Wiener index by assigning weights or emphasizing specific graph characteristics, making it more suitable for analyzing complex molecular systems. The hyper-Wiener index incorporates both the distances and their squared values, offering a more sensitive measure for highly branched or cyclic structures. The Harary index focuses on the reciprocal of the shortest distances, capturing the overall connectivity and robustness of a molecular structure. These indices play a crucial role in modeling and predicting physical, chemical and biological properties of molecules. For more advances on Wiener-type indices and the latest work on related topics, we refer readers to [6,7,8,9,10].
The study of finding some sufficient condition for a graph to have a particular property has attracted the attention of many researchers. The Zagreb index is a graph-theoretical index used in mathematical chemistry to study molecular structures. It quantifies the connectivity of atoms in chemical molecules, which provides insights into molecular stability and reactivity. In [11], Liu et al. gave some sufficient conditions on the connective eccentricity index, difference of Zagreb indices and some other indices for a graph to be k-leaf-connected. Liu et al. [12] obtained some sufficient conditions, in terms of the difference of Zagreb indices, for graphs to be traceable, Hamilton-connected, k-edge-Hamiltonion, k-Hamiltonion, k-path-coverable and k-connected. Others see [13,14,15,16,17] and the references within.
Determining whether a graph has the Hamiltonian property is a famous problem. In [18], Kuang et al. used the Wiener-type invariants to show some sufficient conditions for Hamiltonian property of graphs. It is worth considering the use of the Wiener-type indices to derive other properties. Motivated by this, we consider the pancyclic property of graphs. The pancyclic property of a graph has a wide range of applications in combinatorial optimization, network design, theoretical research and algorithm design. It provides a useful tool for understanding the connectivity of graphs and solving problems related to cycle structures.
In this paper, we first determine the extreme values of for ℓ-connected graphs. Then, we use the Wiener-type indices of graph G, the Wiener-type indices of complement graph with or to give some sufficient conditions for a graph to have the pancyclic property. Our results generalize some existing results of several papers.
The outline of this paper is given below.
- In Section 2, the necessary preliminaries are introduced.
- In Section 3, we show the main results, including some extremal conclusions on ℓ-connected graphs with respect to Wiener-type indices and some conditions that ensure graphs to have the pancyclic property with respect to Wiener-type indices.
- In Section 4, we summarize the main findings of this paper, and pose a problem for future work.
2. Preliminaries
For convenience, we use to represent . Clearly, if , then . Moreover, if for any , then the count of vertex pairs that are separated by a distance of 2 is equivalent to minus the count of vertex pairs that are directly connected (i.e., have a distance of 1), where .
Lemma 1.
Let with diameter . Then, iff .
Proof.
Let . If , then for two vertices . Thus, . Conversely, if , then for . Thus, . □
Lemma 2
([19]). If with , then the diameter .
Combining Lemmas 1 and 2, the Wiener-type index of a graph is determined by and if is greater than .
Lemma 3
([19]). Let , , the graph . Then, , where
Let , be the ℓ-th power of G, which is the graph with and iff . It is clear that . The following lemma represents this fact.
Lemma 4
([19]). Let and . Then, .
For these graphs in , the following lemma provides an upper bound for their diameter:
Lemma 5
([19]). Let . Then, the diameter .
For connected graphs with minimum degree greater than 2 or 3, the following two lemmas show that, as long as their number of edges is sufficiently large, these graphs have pancyclic property, except for bipartite graphs and those in the set or the set (the sets and will be introduced in next section).
Lemma 6
([20]). Let , with edges and . If , then G has pancyclic property unless or .
Lemma 7
([21]). Let , with edges and . If , then G has pancyclic property unless or .
Let , where is a function. Double counting is a combinatorial technique used to count the same set of objects in two different ways for deriving certain results. This technique is widely used in graph theory. The following lemma can be directly obtained by using double counting:
Lemma 8.
Let , , . Then, , where .
Proof.
By the fact that , we have . □
3. Main Results
3.1. Results on ℓ-Connected Graphs
In this subsection, we show the results on ℓ-connected graphs.
For these graphs in with the connectivity ℓ, the following theorem provides a lower bound for their Wiener-type indices with a monotone increasing function and identifies the extremal graph where the equality holds.
Theorem 1.
Let , and with connectivity ℓ. If has monotonic increasing property, then
with equality iff .
Proof.
Let with connectivity ℓ and minimum Wiener-type indices. Then, there is a vertex cut Y of with . Let be the components of the graph .
Claim 1.
For , is a complete graph.
Suppose that there exists such that is not a complete graph and . Let . Then with connectivity ℓ. Since is strictly increasing, then , which is a contradiction.
By a similar analysis, we have
Claim 2.
is a complete graph.
Claim 3.
.
Suppose that . Let , where , and . Then, with connectivity ℓ. Since is strictly increasing, then , which is a contradiction.
Combining Claims 1–3, we have that , where .
When or , we obtain the minimum value of , i.e., and .
By the above arguments, the conclusion holds. □
In Theorem 1, let (where ). Then, we can derive the minimal values of these Wiener-type indices for ℓ-connected graphs (it should be noted that is a monotone increasing function when ). The results are shown below.
When , we have . The corresponding result on the Wiener index is as follows:
Corollary 1
([22]). Let , , and with connectivity ℓ. Then,
the equality holds iff .
When , we have . The corresponding result on the modified Wiener index is as follows:
Corollary 2.
Let , , , and with connectivity ℓ. Then,
the equality holds iff .
When , we have . The corresponding result on the hyper-Wiener index is as follows:
Corollary 3.
Let , , and with connectivity ℓ. Then,
the equality holds iff .
For graphs in , the following theorem provides an upper bound for their Wiener-type indices with a monotone increasing function and gives some graphs that make the equality hold.
Theorem 2.
Let , and . When is a monotone increasing function, then
The bound is the best possible when , and
Proof.
Let and . Since , by Lemma 5, diameter . Since , then for . Since is strictly increasing, we have . Therefore, by Lemma 8, .
Now, we show that, when , the bound can be obtained by giving an example. It is obvious that
Then, by Lemma 4, when , we have ; when , since ℓ is even, we have .
Let and . Let for . Then, we have for . Therefore, for , , and if , if . Then, .
This concludes the proof. □
In Theorem 2, let (where ). Then, we can derive the maximal values of these Wiener-type indices for ℓ-connected graphs. The results are shown below.
When , we have . The corresponding result on the Wiener index is as follows:
Corollary 4
([19]). Let , , and . Then,
The bound is the best possible when , and
When , we have . The corresponding result on the modified Wiener index is as follows:
Corollary 5.
Let , , , and . Then,
The bound is the best possible when , and
When , we have . The corresponding result on the hyper-Wiener index is as follows:
Corollary 6.
Let , , and . Then,
The bound is the best possible when , and
Theorem 3.
Let such that , . When is a monotone increasing function, then
where
Proof.
Let . Then, it is well known that . Since , then . By Lemma 2, we have . By Lemma 1, . By Lemma 3 and the monotonicity of , we have , where
Based on the above arguments, the conclusion holds. □
For graphs in where ℓ and n satisfy that n is even, and , the following theorem provides an upper bound for their Wiener-type indices with a monotone increasing function and gives some graphs that make the equality hold.
Theorem 4.
Let , , , and . If has monotonic increasing property, then
the bound is obtained if , where is a perfect matching in the graph .
Proof.
Let and . Since , then by Lemma 5. By and the monotonicity of , we have . Thus, we have . If , then the equality holds. □
3.2. Results on Pancyclic Graphs
In this subsection, we show the results on pancyclic graphs.
For graphs in , the following theorem provides a lower bound (or an upper bound) for their Wiener-type indices with a monotone increasing (or decreasing) function and identifies the extremal graph where the equality holds.
Lemma 9.
Let .
(i) When has monotonic increasing property, then
with equality iff .
(ii) When has monotonic decreasing property, then
with equality iff .
Proof.
Let have two disjoint independent sets, denoted by and such that , and . If is strictly increasing, then we have
with equality iff .
The proof for the case where is strictly decreasing is similar, and thus it is omitted here. This completes the proof. □
Let [20].
Yu et al. showed Lemma 6 in [20]. Based on Lemmas 6 and 9, we show the following results.
Theorem 5.
Let , and .
(i) If has monotonic increasing property, and
then the graph G has pancyclic property if it is not an element of the set .
(ii) If has monotonic decreasing property, and
then the graph G has pancyclic property if it is not an element of the set .
Proof.
Let , and . If is strictly increasing, then
Since , then . By Lemma 6, G is pancyclic unless or G is a graph in the set .
If G is a pancyclic graph, the conclusion holds. Otherwise, we have or . By Lemma 9, we have if G is a bipartite graph. Since , then G is not a bipartite graph. For all , we can easily verify that .
The proof for the case where is strictly decreasing is similar, and thus it is omitted here.
By the above arguments, we have completed the proof. □
In Theorem 5, let (where ). Then, we can derive some conditions that ensure graphs to have the pancyclic property with respect to these Wiener-type indices. The results are shown below.
When , we have . The corresponding result on the Wiener index is as follows.
Corollary 7
([23]). Let , and . If
then the graph G has pancyclic property if it is not an element of the set .
When , we have . The corresponding result on the modified Wiener index is as follows.
Corollary 8.
Let , , and .
(i) If and
then the graph G has pancyclic property if it is not an element of the set .
(ii) If and
then the graph G has pancyclic property if it is not an element of the set .
When , we have . The corresponding result on the hyper-Wiener index is as follows.
Corollary 9.
Let , and . If
then the graph G has pancyclic property if it is not an element of the set .
When , we have . The corresponding result on the Harary index is as follows.
Corollary 10
([23]). Let , and . If
then the graph G has pancyclic property if it is not an element of the set .
For convenience, we say G is an NCB-graph if G is a non-complete bipartite graph.
Theorem 6.
Let , and .
(i) If has monotonic increasing property, and
then the graph G has pancyclic property if it is not an NCB-graph.
(ii) If has monotonic decreasing property, and
then the graph G has pancyclic property if it is not an NCB-graph.
Proof.
For convenience, let and . Then, .
Let and . If has monotonic increasing property, then
Since , then . By Lemma 6, G has the pancyclic property unless it is in the set or the set .
If G is a pancyclic graph, the conclusion holds. Otherwise, we have or . If or G is a complete bipartite graph, then . Hence, G is an NCB-graph.
The proof for the case where is strictly decreasing is similar, and thus it is omitted here.
The proof is complete by the above arguments. □
In Theorem 6, let (where ). Then, we can derive some conditions that ensure graphs to have the pancyclic property with respect to these Wiener-type indices of complement graphs. The results are shown below.
When , we have . The corresponding result on the Wiener index is as follows.
Corollary 11
([23]). Let , and . If and
then the graph G has pancyclic property if it is not an NCB-graph.
When , we have . The corresponding result on the modified Wiener index is as follows.
Corollary 12.
Let , and .
(i) If , and
then the graph G has pancyclic property if it is not an NCB-graph.
(ii) If , and
then the graph G has pancyclic property if it is not an NCB-graph.
When , we have . The corresponding result on the hyper-Wiener index is as follows.
Corollary 13.
Let , and . If and
then the graph G has pancyclic property if it is not an NCB-graph.
When , we have . The corresponding result on the Harary index is as follows.
Corollary 14
([23]). Let , and . If and
then the graph G has pancyclic property if it is not an NCB-graph.
Let [21].
Xu et al. showed Lemma 7 in [21]. Based on Lemmas 7 and 9, we show the following results.
Theorem 7.
Let , and .
(i) If has monotonic increasing property and
then the graph G has pancyclic property if it is not an element of the set .
(ii) If has monotonic decreasing property and
then the graph G has pancyclic property if it is not an element of the set .
Proof.
Let , and . If is strictly increasing, then
Since , then . By Lemma 7, G is pancyclic unless G is a graph in the set or .
If G is a pancyclic graph, the conclusion holds. Otherwise, we have or G is a bipartite graph. By Lemma 9, we have if G is a bipartite graph. Since , then G is not a bipartite graph. For all , we can easily verify that .
The proof for the case where is strictly decreasing is similar, and thus it is omitted here.
Based on the above arguments, the proof is complete. □
In Theorem 7, let (where ). Then, we can derive some conditions that ensure graphs to have the pancyclic property with respect to these Wiener-type indices. The results are shown below.
When , we have . The corresponding result on the Wiener index is as follows.
Corollary 15.
Let , and . If
then the graph G has pancyclic property if it is not an element of the set .
When , we have . The corresponding result on the modified Wiener index is as follows.
Corollary 16.
Let , and .
(i) If and
then the graph G has pancyclic property if it is not an element of the set .
(ii) If and
then the graph G has pancyclic property if it is not an element of the set .
When , we have . The corresponding result on the hyper-Wiener index is as follows.
Corollary 17.
Let , and . If
then the graph G has pancyclic property if it is not an element of the set .
When , we have . The corresponding result on the Harary index is as follows.
Corollary 18.
Let , and . If
then the graph G has pancyclic property if it is not an element of the set .
Example 1.
Let , , , , where and . Then, if is a monotone increasing function, and if is a monotone decreasing function.
Proof.
Clearly, G is connected, and .
Let . Clearly, . Since there exists exactly one edge between and , G contains no . Let be a monotone increasing function. If , then by Theorem 5, G is pancyclic, a contradiction. Hence, .
Similarly, if is strictly decreasing, we have . □
Example 2.
Let , , , , where and . Then, G has the pancyclic property if .
Proof.
Clearly, and . Let . Then, . If , then . If , then . By Corollaries 7 and 15, G has the pancyclic property if . □
4. Conclusions and Future Work
In this paper, we introduce several Wiener-type indices, whose corresponding functions are monotonically increasing or monotonically decreasing. Based on these Wiener-type indices and the monotonicity of their corresponding functions , we show some extremal conclusions on ℓ-connected graphs and some conditions that ensure graphs to have the pancyclic property. Moreover, we give some examples (see Examples 1 and 2) to support our findings.
Wiener-type indices are important and widely studied in chemical graph theory. They can be used to describe molecular structures and determine certain properties of graphs. The pancyclic property of a graph can be used to analyze complex networks. Our findings provide some upper and lower bounds for Wiener-type indices and offer a numerical computation method to determine whether a graph is pancyclic, which will assist in deriving the structure and properties of certain graphs by utilizing Wiener-type indices in practical applications. However, what we explore in this paper is the sufficient condition for a graph to be pancyclic based on the Wiener-type indices. Naturally, one may ask about the necessary conditions, which we believe are worth considering for future work.
Problem 1.
Find some necessary conditions for a graph G to be pancyclic with respect to , where is a monotonic function.
Author Contributions
Conceptualization, J.Z., H.L. and L.Y.; Methodology, J.Z., H.L. and L.Y.; Validation, J.Z. and H.L.; Formal analysis, J.Z., H.L. and L.Y.; Writing—original draft, J.Z. and H.L.; Writing—review & editing, J.Z.; Supervision, L.Y.; Funding acquisition, H.L. and L.Y. All authors have read and agreed to the published version of the manuscript.
Funding
Supported by the National Natural Science Foundation of China (Grant No. 12371347), the Foundation of Hubei Provincial Department of Education (Grant Nos. Q20232505, Q20232513).
Data Availability Statement
The data will be made available by the authors on request.
Conflicts of Interest
The authors declare that there are no conflicts of interest.
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