Abstract
The orbit polynomial is a new graph counting polynomial which is defined as where , …, are all vertex orbits of the graph G. In this article, we investigate the structural properties of the automorphism group of a graph by using several novel counting polynomials. Besides, we explore the orbit polynomial of a graph operation. Indeed, we compare the degeneracy of the orbit polynomial with a new graph polynomial based on both eigenvalues of a graph and the size of orbits.
1. Introduction
In quantum chemistry, the early Hückel theory computes the levels of -electron energy of the molecular orbitals in conjugated hydrocarbons, as roots of the characteristic/spectral polynomial which are called the eigenvalues of a molecular graph, see [1]. This concept was generalized by Hosoya [2] and the others [3,4,5] by changing the adjacency matrix with other matrices based on graph invariants. In the mathematical chemistry literature, the counting polynomials have first been introduced by Hosoya, see [6]. Other counting polynomials have later been proposed: Matching polynomial [7,8], independence [9,10], king [11,12], color [12], star or clique polynomials [13,14], etc. An overview of graph polynomials is provided in reference [15].
In the current work, we introduce a novel graph polynomial based on orbit-partitions of regarding graph, see [16,17]. It is derived from the concept of orbit polynomial. The typical terms of the orbit polynomial is of the form , where is the number of orbits of the automorphism group of size n. It should be noted that the characteristic polynomials do not characterize graphs due to several isospectral graphs, see [18].
We proceed as follows. In Section 2, the definitions used in the present work are introduced and known results needed are given. Section 3, contains the main results of this paper based on the orbit structure of a graph. Finally, in Section 4, by using the concept of graph spectra, we define a new version of orbit polynomial whose unique positive root is a measure that discriminate all graphs of order six, uniquely.
2. Preliminaries
In this research, and indicates the vertex and edge sets of the graph G, respectively. We assume that all graphs are simple, connected and finite.
In this paper, the automorphism group of a graph as well as the vertex-orbits are needed to infer the orbit polynomial. The automorphism group is a collection of all permutations on the set of vertices that preserves the adjacency between vertices of a graph, namely is an edge of graph G if and only if is an edge. We denote the automorphism group of a graph G by Aut().
For the vertex u, an orbit containing u is the collection of all ’s in which is an automorphism element of G. The graph G is said to be vertex-transitive, if it has exactly one orbit. This means that in a vertex-transitive all vertices can be mapped to each other, namely for two elements a and b, there is at least an automorphism that . An edge-transitive graph can be defined similarly.
Let be a group acting on the set X. The stabilizer of element is defined as The orbit-stabilizer theorem implies that , see [19].
3. The Orbit and the Modified Orbit Polynomials
The orbit polynomial was defined by Dehmer et al. in [16] as
where are all vertex-orbits of G. Moreover, the the modified version of orbit polynomial, is defined as
Many structural properties of a graph can be derived from the orbit polynomial. Let G be a graph of order n. From the definition, it is clear that if , then and thus . Moreover, a graph is vertex-transitive if and only if and consequently .
Example 1.
The cycle graph is vertex-transitive and by the above discussion and .
Example 2.
For the path graph we obtain
and
From the orbit polynomial , one can easily see that if n is even then has a pendant edge and if n is odd then has a central vertex, since each tree has a central vertex or a central edge, see [20]. We also explore that in the case that n is even (n is odd), then has () orbits of length two.
3.1. Orbit Polynomial of Line Graphs
An edge-automorphism of graph G is a bijection on such that two edges are adjacent if and only if and are adjacent in G. The set of all edge-automorphisms of graph G is also a group under the composition of functions and we denote it by .
Any automorphism of G induces a bijection on , defined by . It is clear that is an edge-automorphism. The set
is a subgroup of induced by edge-automorphisms of G.
Theorem 3
([20]). Assume that G is a graph of order . Then .
For a graph G, its line graph is a new graph with the vertex set is and two vertices are adjacent in if and only if the corresponding edges are adjacent in G. An automorphism of is an edge-automorphism of G. Suppose are the set of graphs as depicted in Figure 1. Then we have the following theorem.
Figure 1.
Three graphs , and of order 4.
Theorem 4
([1]). For a connected graph G, where , we have
Consider two graphs and in Figure 2. Both of them have the same orbit polynomial while for two graphs and in Figure 3, we have and . Finally, consider the graph and its line graph as depicted in Figure 4. The automorphism group of both of them is isomorphic with symmetric group but and .
Figure 2.
A graph with its line graph, both of order 5.
Figure 3.
A graph of order 6 whose line graph is of order 5.
Figure 4.
A graph and its line graph which have the same automorphism group.
The distance between two vertices x and y a graph G is the length of the shortest path between them and we denote it by . For the vertex u of graph G, suppose is the number of vertices at distance i from u. If for two vertices u and v, we have () then they are Hosoya-equivalent or H-equivalent, see [21,22,23,24,25,26,27,28,29,30].
The set of H-equivalent vertices is called an H-partition of G. Moreover, the Hosoya polynomial is defined as , where are all H-partitions of G and . The modified Hosoya polynomial is also .
Theorem 5.
Suppose are all orbits of graph G. If for any pair of vertices and , we have , then ’s are all H-partitions of G.
Proof.
It is clear that two vertices in the same orbit have the same degree. Moreover, two vertices u and v in a same H-partition have the same degree, since yields that . Thus, if vertices of different orbits have different degrees, then they are in different H-partitions. This completes the proof. □
Corollary 6.
If the degrees of orbit vertices are distinct, then the orbit and Hosoya polynomials are the same, namely
By considering the definition of action of automorphism group of graph G on the set of edges, the edge version of orbit polynomial can be defined as follows.
Definition 7.
Let are all edge-orbits under the action of on the set of edges. Then
For example, the star graph is edge-transitive; hence and . On the other hand, if T is a tree on n vertices with , then T is edge-transitive and so T is a bi-regular graph, which means that all vertices of T are of degrees r and s for some . If T is regular, then which confirms our claim. If T is a bi-regular tree, then , since the pendant vertices compose an orbit and the central vertex is a singleton orbit. Notice that if , then an edge-transitive tree has not a central edge. Hence, we proved the following theorem.
Theorem 8.
The edge-orbit polynomial if and only if .
In continuing this section, we prove that the cycle graph can be characterized by its edge-orbit polynomial.
Theorem 9.
Let G be a graph without a pendant edge. Then if and only if .
Proof.
If , then we are done. Conversely, by , one can immediately conclude that the number of edges and the number of vertices of graph G are the same and thus G is a unicycle graph. If G has a vertex of degree greater than two, then G has at least two cycles, a contradiction. Hence, G is a connected regular graph of degree 2 and the assertion follows. □
Suppose G is a graph with k orbits of equal sizes. Then and thus zero is the only root of . On the other hand, if is the only root of , then , for some . However, the set of orbits of a graph is a partition of the vertex set and thus , which means that . In particular, if then G is vertex-transitive and if then G is asymmetric graph. Hence, we proved the following theorem.
Theorem 10.
The integer is a root of if and only if G is vertex-transitive.
Proof.
If G is vertex-transitive, then and clearly is a zero of it. Conversely, if is a zero of , then . Since, , necessarily and which yields that G is vertex-transitive as desired. □
3.2. Graph Classification with Respect to Orbit Polynomial
One of the classical problem in algebraic graph theory is characterizing the graphs in terms of the graph polynomials. Here, we introduce three classes of trees that can be characterized by their orbit polynomials.
Theorem 11.
If G is a graph with orbit polynomial , then G is a graph on 6 vertices. Moreover, if G has a pendant edge, then it has three pendant edges.
Proof.
Clearly, G has 6 vertices, since the set of orbits is a partition for the vertex set. If G has only one pendant edge, then its endpoints compose two different singleton orbits, a contradiction. If G has two pendant edges, then necessarily they compose an orbit of size two. These edges share a common vertex, because in other case either we have two orbits of sizes 2 and 4 or three orbits of size two or there are two orbits of size 2, all of them are contradictions. Hence, three other vertices are in the same orbit and they have the same degree. If they are of degree 2, then or . If , then , a contradiction. □
Example 12.
All graphs on six vertices with the orbit polynomial are as depicted in Figure 5. They have different automorphism groups while their orbit polynomials are the same.
Figure 5.
All graphs on six vertices with orbit polynomial .
Example 13.
Suppose . Then , and thus . All graphs with this property have at least six and at most 18 vertices. The problem is solved completely for . If , then necessarily and . Hence, . This means that the related graph has two orbits of size 1, an orbit of size 2 and an orbit of size 3. There are 39 graphs of order 7 by this property. Some of them are depicted in Figure 6.
Figure 6.
Examples of graphs of order 7 with orbit polynomial .
If , then or , see Figure 7. Since the orbit sizes are , then by orbit-stabilizer theorem, we obtain
and thus . On the other hand, G has no a permutation of order 6, since otherwise we have a singleton orbit. Moreover, by a similar argument, we can show that there is no permutation of order 5 or 4. This means that G is a group and thus , since all orbits are of sizes 1, 2, 3. If for example, we have only one orbit of each size 1, 2 and 3, then , where and . This means that by applying Equation (1), 6 or 12 and thus or or . Hence, we proved the following theorem.
Figure 7.
Two graphs of order 8 with three distinct orbit sizes.
Theorem 14.
Let G be a graph of order 6. Then if and only if or or .
4. Orbit-Entropy Polynomial
The characteristic polynomial [1] of a graph G with adjacency matrix is
The roots of this polynomial are eigenvalues of G and form the spectrum of G as
where () is the multiplicity of eigenvalue and .
Here, consider all graphs of order six and their orbit polynomials as reported in Table 1 and Table 2. There are 13 graphs with the same orbit polynomial . This means that the orbit polynomial has not a power discrimination to characterize all graphs of the same order. In [16], it is claimed that the degeneracy of roots of the modified version of orbit polynomial is less than orbit polynomial, but for the 13 mentioned graph of order 6, we obtain which implies that the modified orbit polynomial is not also a powerful discrimination to capture structural information for these graphs. Here, we introduce a new polynomial with more powerful discrimination than orbit polynomial, to capture structural information.
Table 1.
All graphs of order six together with their unique positive roots of and .
Table 2.
(Continuation of Table 1).
A number of measures using Shannon’s entropy function have been introduced and investigated since the fifties, see [31,32,33,34]. The discrete form of this well-known function is defined for a probability vector and has the form ; see [35,36].
Let be all non-zero eigenvalues of a graph G. Then is called the eigenvalue-entropy based on ’s, where
If , then the Equation (2) can be reformulated as follows:
where is the adjacency energy of graph G, see [5,37].
The degeneracy problem of orbit polynomial can be overcome, by constructing the so-called super polynomial which is defined by subtracting the orbit polynomial from eigenvalue entropy:
The unique positive roots () of the orbit-entropy polynomials for all graphs of order six is reported in the third column of Table 1. Comparing these quantities with the orbit polynomial roots, we obtain that ’s are distinct, for all these 13 graphs.
Bear in mind that two vertex-transitive graphs of the same order have the same orbit polynomials and thus the same modified orbit polynomials. However, in general, their orbit-entropy polynomials are not equal. For example, consider two graphs and in Figure 8. The spectrum of these graphs are
and
Figure 8.
Two vertex-transitive graphs of order 6 with distinct orbit-entropy polynomials.
Then and . Hence, and while the orbit polynomial of both of them is .
5. Summary and Conclusions
The Hosoya partition and the orbit polynomials of several kinds of graphs were investigated. Moreover, a relation between the orbit and Hosoya partition polynomials was explored. We also defined a new polynomial based on both orbit sizes and eigenvalues of a graph, and it was shown that the degeneracy of new polynomial relative to the orbit polynomial is quite low. Applying the theory of groups, especially the automorphism group approach used in this paper, enables one to analyze networks and we capture information about the number of interconnections of components. Finally, a characterization for all graphs with orbit polynomial is given.
Author Contributions
M.G., M.D. and F.E.-S. wrote the paper. All authors have read and agreed to the published version of the manuscript.
Funding
Matthias Dehmer thanks the Austrian Science Funds for supporting this work (project P30031).
Conflicts of Interest
The authors declare no conflict of interest.
References
- Cvetković, D.; Doob, M.; Sachs, H. Spectra of Graphs Theory and Applications; Academic Press: Heidelberg, Germany, 1995. [Google Scholar]
- Hosoya, H. On some counting polynomials in chemistry. Applications of graphs in chemistry and physics. Discret. Appl. Math. 1988, 19, 239–257. [Google Scholar] [CrossRef]
- Gutman, I.; Harary, F. Generalizations of the matching polynomial. Util. Math. 1983, 24, 97–106. [Google Scholar]
- Gutman, I.; Bonchev, D.; Rouvray, D.H. Polynomials in Graph Theory. Chemical Graph Theory, Introduction and Fundamentals; Abacus Press: New York, NY, USA, 1991; pp. 133–176. [Google Scholar]
- Gutman, I.; Furtula, B.; Katanić, V. Randić index and information. AKCE Int. J. Graphs Comb. 2018, 15, 307–312. [Google Scholar] [CrossRef]
- Hosoya, H. Topological index, A newly proposed quantity characterizing the topological nautre of structural isomers of saturated hydrocarbons. Bull. Chem. Soc. Jpn. 1971, 44, 2332–2339. [Google Scholar] [CrossRef]
- Hosoya, H. Clar’s aromatic sextet and sextet polynomial. Top. Curr. Chem. 1990, 153, 255–272. [Google Scholar]
- Farrell, E.J. An introduction to matching polynomials. J. Comb. Theory 1979, 27, 75–86. [Google Scholar] [CrossRef]
- Gutman, I.; Hosoya, H. Molecular graphs with equal Zcounting and independence polynomials. Z. Naturforsch. 1990, 45, 645–648. [Google Scholar]
- Gutman, I. Some analytical properties of the independence and matching polynomials. Match Commun. Math. Comput. Chem. 1992, 28, 139–150. [Google Scholar]
- Stevanović, D.; Motoyama, A.; Hosoya, H. King and domino polynomials for polyomino graphs, Graph Theory Notes. J. Math. Phys. 1977, 34, 31–36. [Google Scholar]
- Balasubramanian, K.; Ramaraj, R. Computer generation of king and color polynomials of graphs and lattices and their applications to statistical mechanics. J. Comput. Chem. 1985, 6, 447–454. [Google Scholar] [CrossRef]
- Farrell, E.J.; De Matas, C.M. On star polynomials of complements of graphs. Ark. Mat. 1988, 26, 85–190. [Google Scholar] [CrossRef]
- Farrell, E.J.; De Matas, C.M. Star polynomials of some families of graphs with small cyclomatic numbers. Util. Math. 1988, 33, 33–45. [Google Scholar]
- Balasubramanian, K. On Graph Theoretical Polynomials in Chemistry. In Mathematical and Computational Concepts in Chemistry; Trinastic, N., Ed.; Ellis Horwood Ltd.: New York, NY, USA, 1986; pp. 20–33. [Google Scholar]
- Dehmer, M.; Chen, Z.; Emmert-Streibd, F.; Mowshowitz, A.; Varmuzag, K.; Jodlbauer, H.; Shih, Y.; Tripathi, S.; Tao, J. The orbit-polynomial: A novel measure of symmetry in graphs. IEEE Access 2020, 8, 36100–36112. [Google Scholar] [CrossRef]
- Dehmer, M.; Chen, Z.; Emmert-Streib, F.; Shi, Y.; Tripathi, S. Graph measures with high discrimination power revisited: A random polynomial approach. Inform. Sci. 2018, 467, 407–414. [Google Scholar] [CrossRef]
- Balasubramanian, K.; Basak, S.C. Characterization of isospectral graphs using Ggraph invariants and derived orthogonal parameters. J. Chem. Inf. Comput. Sci. 1998, 38, 367–373. [Google Scholar] [CrossRef]
- Dixon, J.D.; Mortimer, B. Permutation Groups; Springer: New York, NY, USA, 1996. [Google Scholar]
- Harary, F. Graph Theory; Addison-Wesley Publishing Company: Boston, MA, USA, 1969. [Google Scholar]
- Dehmer, M.; Mowshowitz, A.; Shi, Y. Structural differentiation of graphs using Hosoya-based indices. PLoS ONE 2014, 7, e102459. [Google Scholar] [CrossRef] [PubMed]
- Dehmer, M.; Emmert-Streib, F.; Shi, Y. Graph distance measures based on topological indices revisited. Appl. Math. Comput. 2015, 266, 623–633. [Google Scholar] [CrossRef]
- Mowshowitz, A.; Dehmer, M. The Hosoya entropy of a graph. Entropy 2015, 17, 1054–1062. [Google Scholar] [CrossRef]
- Ghorbani, M.; Dehmer, M.; Rajabi-Parsa, M.; Emmert-Streib, F.; Mowshowitz, A. Hosoya entropy of fullerene graph. Appl. Math. Comput. 2019, 352, 88–98. [Google Scholar]
- Ghorbani, M.; Dehmer; Mowshowitz, A.; Emmert-Streib, F. The Hosoya entropy of graphs revisited. Symmetry 2019, 11, 1013. [Google Scholar] [CrossRef]
- Ghorbani, M.; Dehmer, M.; Cao, S.; Feng, L.; Tao, J.; Emmert-Streib, F. On the zeros of the partial Hosoya polynomial of graphs. Inf. Sci. 2020, 524, 199–215. [Google Scholar] [CrossRef]
- Jachiymski, J. The contraction principle for mappings on a metric space with a graph. Proc. Am. Math. Soc. 2008, 136, 1359–1373. [Google Scholar] [CrossRef]
- Eskandar, A.; Aydi, H.; Arshad, M.; De la Sen, M. Hybrid Ćirić type graphic (Υ,Λ)-contraction mappings with applications to electric circuit and fractional differential equations. Symmetry 2020, 12, 467. [Google Scholar]
- Afshari, H.; Aydi, H.; Karapinar, E. On generalized α-ψ-Geraghty contractions on b-metric spaces. Georg. J. Math. 2020, 27, 9–21. [Google Scholar] [CrossRef]
- Karapinar, E.; Czerwik, S.; Aydi, H. (α,ψ)-Meir-Keeler contraction mappings in generalized b-metric spaces. J. Funct. Spaces 2018. [Google Scholar] [CrossRef]
- Bollobás, B. Random Graphs, 2nd ed.; Cambridge Studies in Advanced Mathematics; Cambridge University Press: Cambridge, UK, 2001. [Google Scholar]
- Bonchev, D.; Trinajestić, N. Information theory, distance matrix and molecular branching. J. Chem. Phys. 1977, 67, 4517–4533. [Google Scholar] [CrossRef]
- Bonchev, D.; Rouvray, D.H. Introduction and Fundamentals. In Chemical Graph Theory; Abacus Press: New York, NY, USA, 1991. [Google Scholar]
- Dehmer, M. Information processing in complex networks: Graph entropy and information functionals. Appl. Math. Comput. 2008, 201, 82–94. [Google Scholar] [CrossRef]
- Rashevsky, N. Life, information theory, and topology. Bull. Math. Biophys. 1955, 17, 229–235. [Google Scholar] [CrossRef]
- Mowshowitz, A. Entropy and the complexity of graphs: I. An index of the relative complexity of a graph. Bull. Math. Biophys. 1968, 30, 175–204. [Google Scholar] [CrossRef]
- Gutman, I. The Energy of a Graph: Old and New Results. In Algebraic Combinatorics and Applications; Betten, A., Kohnert, A., Laue, R., Wassermann, A., Eds.; Springer: Berlin, Germany, 2001; pp. 196–211. [Google Scholar]
© 2020 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 (http://creativecommons.org/licenses/by/4.0/).