The expected values and variances for Sombor indices in a general random chain

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Abstract

This article is devoted to establish the distributions for Sombor indices in a general random chain, in which their explicit analytical expressions of the expected values and variances are obtained. As applications, these results for random hexagonal, random phenylene, random polyphenyl and random spiro chains are given. Finally, the distributions for the Sombor indices in these four random chains are asymptotic to normal distributions is shown.

Introduction

In this paper, we always suppose that a graph means a finite simple connected graph unless otherwise specified, and refer to Bondy and Murty [3] for the notations and terminologies freely used but not defined here.

Let G=(V(G),E(G)) be a graph, where V(G) and E(G) are the vertex set and the edge set of G, respectively. It is a famous fact that chemical molecules can conveniently be described by a graph if we associate vertices with the atoms and edges with covalent bonds between atoms. Theoretical chemists focus on predicting physicochemical properties of chemical molecules by means of their structures. The topological indices play an important role in the prediction. For more details on topological indices, see [17], [25] and the references cited therein.

Inspired by Euclidean metrics, a class of novel topological indices, known as Sombor indices, is recently introduced by Gutman [11], including the (ordinary) Sombor index, the reduced Sombor index and the average Sombor index.

For a graph G, the Sombor index SO(G), the reduced Sombor SOred(G) and the average Sombor index SOavr(G) are defined as follows:SO(G)=uvE(G)dG2(u)+dG2(v),SOred(G)=uvE(G)(dG(u)1)2+(dG(v)1)2,SOavr(G)=uvE(G)(dG(u)d¯)2+(dG(v)d¯)2,where d¯=2|E(G)||V(G)| is the average degree of G.

In the following, we consider the general Sombor index, see [10], defined asSOa(G)=uvE(G)(dG(u)a)2+(dG(v)a)2,where a is a constant or a parameter of G. It is obvious that we can get the Sombor index, the reduced Sombor index and the average Sombor index by setting a=0,1,d¯, respectively.

Sombor indices have been the subject of intense scholarly debate because of their good chemical applicability. In [12], some basic properties of Sombor indices are presented. In [7], Sombor indices of chemical graphs is studied. In [19], the chemical graphs ordered by Sombor indices are given. For more results of Sombor indices, we refer the reader to see [[1], [2], [5], [8], [9], [13], [18], [23], [24]].

Currently, many researchers concentrate on the expected value of some indices. In [14], the expected values of the first Zagreb and Randić indices in random polyphenyl chains are given. In [21], [22], Raza determines the expected values for arithmetic, geometric indices, the sum-connectivity, harmonic, symmetric division, variable inverse sum degree and general Randic indices in random phenylene chains. In [26], [27], the expected values and variances for the Gutman index, Schultz index, multiplicative degree-Kirchhoff index and additive degree-Kirchhoff index in a random polyphenyl chain are presented. In [20], the expected value for the reduced Sombor index in a random polyphenyl chain are given. In [10], the expected values for the Sombor indices in random hexagonal chains and random phenylene chains are obtained. Motivated by [10], [14], [20], [21], [22], [26], [27], we make researches on the expected values and variances for Sombor indices in a general random chain, defined in Definition 2.1.

This paper is organized as follows. In Section 2, we introduce the definition of general random chain and briefly recall some of the basic facts from probability theory. Section 3 is devoted to establish the distributions for Sombor indices in a general random chain. Based on the distributions, we obtain their explicit analytical expressions of the expected values and variances in Section 4. In Section 5, the asymptotic behaviors of the distributions for Sombor indices in random hexagonal, random phenylene, random polyphenyl and random spiro chains are presented.

Section snippets

Preliminaries

In this section, we start with some definitions of random hexagonal, random phenylene, random polyphenyl and random spiro chains.

The random hexagonal chain RHCn=RHC(n,p1,p2,p3) with n hexagons is constructured by the following way:

  • (1)

    RHC1 is a hexagon and RHC2 contains two hexagons, see Fig. 1.

  • (2)

    For every n>2, RHCn is constructured by attaching one hexagon to RHCn1 in three ways, resulted in RHCn1,RHCn2,RHCn3 with probability p1,p2,p3 respectively, where p1+p2+p3=1, see Fig. 2.

The random phenylene

The distribution for SOa(Gn)

This section devotes to establish the distrbution for SOa(Gn). As applications, the distributions for SOa(RHCn), SOa(RPCn), SOa(PPCn) and SOa(RSCn) are obtained.

Theorem 3.1

Let Gn(n>2) be a general random chain in Definition 2.1 with the link constants {Ai}i=1t for Sombor indices. ThenSOa(Gn)=ATX+SOa(G2),where AT=(A1,A2,,At) and XM(n2,p), p=(p1,p2,,pt).

Proof

By (2.3), SOa(Gn) can be quantified asSOa(Gn)=(SOa(Gn1),SOa(Gn2),,SOa(Gnt))Zn,and by (2.1), we haveSOa(Gni)=SOa(Gn1)+Ai,i=1,2,,t.

Associated (3.1)

The expected value and variance for SOa(Gn)

In this section, we present the explicit analytical expressions of the expected value and variance for SOa(Gn). In particular, the explicit analytical expressions of the expected values and variances for SOa(RHCn), SOa(RPCn), SOa(PPCn) and SOa(RSCn) are given.

Theorem 4.1

Let Gn(n>2) be a general random chain in Theorem 3.1. Then the expected value and variance for SOa(Gn) are given byE(SOa(Gn))=(i=1tAipi)(n2)+SOa(G2), Var(SOa(Gn))=(i=1tAi2pi(i=1tAipi)2)(n2).

Proof

By Theorem 3.1, we haveSOa(Gn)=ATX+SOa(G2),X

Asymptotic behaviors

In Section 3, the distrubutions for Sombor indices in random hexagonal, random phenylene, random polyphenyl and random spiro chains are presented, see Corollaries 3.3–3.6, respectively. In this section, we study the asymptotic behaviors for Sombor indices in these four random chains.

In probability theory and statistics, the binomial distribution can be approximated by normal distribution under certain conditions, known as De Moivre-Laplace Theorem.

Lemma 5.1

De Moivre-Laplace Theorem [6]

Let XnB(n,p). Then for each real number x, we

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    This work is supported by the National Nature Science Foundation of China (Grant No. 11971180, 12071156), the Guangdong Provincial Natural Science Foundation (Grant No. 2019A1515012052).

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