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BRIEF RESEARCH REPORT article

Front. Phys., 12 January 2021
Sec. Statistical and Computational Physics
This article is part of the Research Topic Mathematical Treatment of Nanomaterials and Neural Networks View all 28 articles

Resistance Distances in Linear Polyacene Graphs

Dayong WangDayong Wang1Yujun Yang
Yujun Yang2*
  • 1Business School, Hohai University, Nanjing, China
  • 2School of Mathematics and Information Sciences, Yantai University, Yantai, China

The resistance distance between any two vertices of a connected graph is defined as the net effective resistance between them in the electrical network constructed from the graph by replacing each edge with a unit resistor. In this article, using electric network approach and combinatorial approach, we derive exact expression for resistance distances between any two vertices of polyacene graphs.

1 Introduction

Let G=(V(G),E(G)) be a connected graph. It is interesting to consider distance functions on G. The most natural and best-known distance function is the shortest path distance. For any two vertices i,jV(G), the shortest path distance between i and j, denoted by dG(i,j), is defined as the length of a shortest path connecting i and j. Two decays ago, another novel distance function, named resistance distance, was identified by Klein and Randić [1]. The concept of resistance distance originates from electrical circuit theory. If we view G as an electrical network N by replacing each edge of G with a unit resistor, then the resistance distance [1] between i and j, denoted by ΩG(i,j), is defined as the net effective resistance between the corresponding nodes in the electrical network N. In contrast to the shortest path distance, the resistance distance has a notable feature that if i and j are connected by more than one path, then they are closer than they are connected by the only shortest path. So it is suggested that resistance distance is more appropriate to deal with wave-like motion in the network, like the communication in chemical molecules. In addition, it turns out that the resistance distance has some pure mathematical interpretations, which could be expressed in terms of the generalized inverse of the Laplacian matrix [1], the number of spanning trees and spanning bi-trees [2], and random walks on graphs [3, 4].

Besides being an intrinsic graph metric and an important component of electrical circuit theory, resistance distance also turns out to have important applications in chemistry. For this reason, resistance distance has been widely studied in the mathematical, chemical, and physical literature. In the study of resistance distance, the main focus is placed on the problem of computation of resistance distance. This problem has been a classical problem in electrical network theory studied by numerous researchers for a long time. Besides, it is also relevant to a wide range of problems ranging from random walks, the theory of harmonic functions, to lattice Green’s functions. Consequently, this problem has attracted much attention, and many researchers have devoted themselves to it. Up to now, resistance distances have been computed for many interesting (classes of) graphs, with emphasis being placed on some highly concerned electrical networks and chemical interesting graphs. For example, resistance distances have been computed for Platonic solids [5], and for some fullerene graphs including buckminsterfullerene [6], circulant graphs [7], distance-regular graphs [8, 9], pseudo–distance-regular graphs [10], wheels and fans [11], Cayley graphs over finite abelian groups [12], complete graph minus N edges [13], resistor network embedded on a globe [14], Möbius ladder [15], m×n cobweb network [16], complete n-partite graphs [17], m×n resistor network [18], ladder graph [19], n-step network [20], Cayley graphs on symmetric groups [21], Apollonian network [22], Sierpinski Gasket Network [23], generalized decorated square and simple cubic network lattices [24], self-similar (x,y) -flower networks [25], almost complete bipartite graphs [26], straight linear 2-trees [27], and path networks [28].

It is interesting to note that a good deal of attention has been paid on resistance distances in plane networks, such as Platonic solids, fullerene graphs, wheels, fans, ladder graphs, Apollonian network, Sierpinski Gasket Network, m×n resistor network, and straight linear 2-tree. Motivated by this fact, we are devoted to considering other interesting plane networks. In this article, we take the linear polyacene graphs into consideration. It is well known that the linear polyacene graphs are graph representations of an important class of benzenoid hydrocarbons, and it is an interesting class of plane hexagonal networks. We use Ln to denote the linear polyacene graph with n1 benzenoid rings (i.e., hexagons), as shown in Figure 1. Using electrical network approach and resistance distance local rules, we derive exact expression for resistance distances between any two vertices of Ln.

FIGURE 1
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FIGURE 1. Linear polyacne graph Ln and its vertex labeling.

2 Resistance Distances in Linear Polyacene Graphs

Let Ln be the linear polyacene graph with n1 benzenoid rings. Obviously, Ln has 4n2 vertices and 5n4 edges. For convenience, we label the vertices in Ln as in Figure 1. We partite the vertex set of Ln into two classes: V1={p1,p2,,pn,q1,q2,,qn} and V2={s1,s2,,sn1,t1,t2,,tn1}. To compute resistance distances between any two vertices of Ln, we take two steps. In the first step, we compute resistance distances between vertices in V1. To this end, we first view Ln as a weighted ladder graph Ln* by simply replacing all the paths pisipi+1 and qitiqi+1(1in1) by edges of resistance 2. Then, by making use of the electric network approach as inspired in [19], we obtain resistance distances between vertices in V1. Next, for the second step, using the results obtained in the first step together with resistance distance local rules, we derive expressions for resistance distances between the remaining pairs of vertices.

Before stating the main result, we introduce the elegant resistance distance local rules, which will be frequently used later. For any vertex aV(G), we use nG(a) to denote the set of neighbors of a. Then, we have the following sum rules for resistance distances.

Lemma 2.1 [29]. Let G=(V(G),E(G)) be a connected graph with n(n2) vertices. Then,

1)  Foranya,bV(G)(ab)(ab)
ΔaΩG(a,b)+inG(a)(ΩG(i,a)ΩG(i,b))=2,(1)

where Δa denotes the degree of the vertex a.

2) For any three different vertices a,b,cV,

Δc(ΩG(c,a)ΩG(c,b))+inG(c)(ΩG(i,b)ΩG(i,a))=0.(2)

Now, we are ready for the main theorem. For simplicity, we let α=322, and define f(x,y) and g(x,y) as follows:

f(x,y)=(1αxy)(2αx+y1+α2y1+α2n2x+1(1αxy2αx+y1)),g(x,y)=(1+αxy)(2+αx+y1+α2y1+α2n2x+1(1+αxy+2αx+y1)).

Then, the main result is given in the following.

Theorem 2.2. The resistance distances between any two vertices in the linear polyacene graph Ln can be computed as follows.

ΩLn(pi,pj)=ij+f(i,j)42(1α2n),(2.1)
ΩLn(qi,pj)=ij+g(i,j)42(1α2n),(2.2)
ΩLn(si,pj)=ij+34f(i+1,i)162(1α2n)+f(i,j)+f(i+1,j)82(1α2n),(2.3)
ΩLn(si,qj)=ji14+f(j+1,j)162(1α2n)+g(j,i)+g(j,i+1)82(1α2n),(2.4)
ΩLn(si,sj)=12i+jf(i+1,i)+f(j+1,j)+f(j,i)+f(j+1,i)+f(j,i+1)+f(j+1,i+1)162(1α2n),(2.5)
ΩLn(si,tj)=12+ij+g(i,j)+g(i,j+1)+g(i+1,j)+g(i+1,j+1)f(i+1,i)162(1α2n)f(i+1,i)+f(i+2,i+1)322(1α2n).(2.6)

Proof. We divide the proof into two steps.

Step 1. Computation of resistance distances between any two vertices in V1.

To compute resistance distances between vertices in V1, we view Ln as a weighted ladder graph Ln* by simply replacing all the paths pisipi+1 and qitiqi+1(1in1) by edges of resistance 2, see Figure 2 (left). Clearly, ΩLn*(p,q)=ΩLn(p,q) holds for all p,qV(Ln*).

FIGURE 2
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FIGURE 2. Weighted ladder graph Ln* (left) and the circuit reduction of Ln1* with respect to pn1 and qn1 (right).

First, we compute resistance distances between the end vertices p1, pn, q1, and qn. let xn:=ΩLn*(pn,p1), yn:=ΩLn*(pn,q1), and zn:=ΩLn*(pn,qn). Clearly, Ln* can be obtained from Ln1* by adding two vertices pn and qn, and the three edges with end vertices {pn1,pn}, {pn,qn}, and {qn,qn1}, as shown in Figure 2 (right). Hence, according to rules for series and parallel circuits, zn could be expressed in term of zn1 as

zn=zn1+4zn1+5,n2,(2.7)

with initial condition z1=1. Solving the recurrence relation by Mathematica [30], we obtain

zn=2(1+2)+421(322)2n,n1.(2.8)

Specially, we have z1=1, z2=56, z3=2935, and z4=169204. It is easily checked that zn can also be expressed as

zn=2(1+2)+42(3+22)n(3+22)n(322)n,n1.(2.9)

We proceed to use zn to find explicit formulas for xn and yn. To this end, we make circuit reduction to the subgraph Ln* of Ln+1* with respect to pn, qn, and p1, where n1. Precisely speaking, we reduce Ln* to a Y-shaped graph which has outer vertices pn, qn, and p1. We use A, B, and C to denote the effective resistances between end vertices of those edges of the Y-shaped graph. Then, we have B+C=yn, A+C=xn, and A+B=zn. Solving these equations, we get

A=xnyn+zn2,B=xn+yn+zn2,C=xn+ynzn2.

On the other hand, by parallel and series connection rules, we have xn+1=(A+2)(B+3)zn+5+C and yn+1=(B+2)(A+3)zn+5+C. So, it follows that

xn+1=(xnyn+zn+4)(xn+yn+zn+6)4(zn+5)+xn+ynzn2,n1,(2.10)
yn+1=(xn+yn+zn+4)(xnyn+zn+6)4(zn+5)+xn+ynzn2,n1,(2.11)

with initial conditions x1=0 and y1=1. Eq. 2.10 minus Eq. 2.11 yields

xn+1yn+1=xnynzn+5.

Set tn:=xnyn. It follows that

tn+1=tnzn+5,n1 and t1=1.(2.12)

Thus, we have

tn+1=k=1n1zk+5.(2.13)

Since 1zk+5=(3+22)k(322)k(3+22)k+1(322)k+1, using Eq. 2.9 and doing some algebraic calculations, we get

tn=42(3+22)n(322)n,n1.(2.14)

This could also be rewritten as tn=42(322)n1(322)2n, for all n1. Now, we come back to solve xn and yn. By using xn=tn+yn, Eqs 2.82.14 and doing some algebra, Eq. 2.11 becomes

yn+1=yn+221(322)n+1221(322)n+1,n1 and y1=1.(2.15)

Solving the recursion relation, we get

yn=n22+221(322)n,n1.(2.16)

Now, by Eqs 2.142.16, together with the relation xn=tn+yn, we get

xn=n22+221+(322)n,n1.(2.17)

Next, we proceed to compute ΩLn*(pn,pi), ΩLn*(pn,qi), and ΩLn*(pi,qi), where n>i>1. To achieve our goal, we consider Ln* as the union of three graphs: the upper part of pi+1 and qi+1, the lower part of pi and qi, and the middle part consisting of pi+1, qi+1, pi, and qi, as shown in Figure 3. Note that the upper and the lower graphs are corresponding to the graphs Lni* and Li*, respectively. We make circuit reductions as illustrated in Figure 3. First, make the circuit reduction of the upper part with respect to pn, pi+1, and qi+1 to obtain a Y-shaped graph, and assume that resistances along its edges are M, N, and K. Then, reduce the lower part of pi and qi to be edge with resistance ΩLn*(pi,qi)=zi. We could find that

M+N=xni,M+K=yni,N+K=zni.(2.18)

Note that

xn+ynzn=2n2,xnyn+zn=222+421+(322)n,xn+yn+zn=222+421(322)n.(2.19)

Solving M, N, and K, we obtain

M=xni+ynizni2=ni1,N=xniyni+zni2=12+221+(322)ni,K=xni+yni+zni2=12+221(322)ni.(2.20)

Then, applying parallel and series connection rules to the reduced circuit in Figure 3, we obtain

ΩLn*(pn,pi)=(N+2)(K+zi+2)zni+zi+4+M,ΩLn*(pn,qi)=(K+2)(N+zi+2)zni+zi+4+M,ΩLn*(pi,qi)=zi(zni+4)zni+zi+4.(2.21)

Substituting Eqs 2.82.20 into Eq. 2.21, we have

ΩLn*(pn,pi)=ni+(1αni)(22αn+iαn+i1αni+1+α2i1+α)42(1α2n),ΩLn*(pn,qi)=ni+(1+αni)(2+2αn+i+αn+i1+αni+1+α2i1+α)42(1α2n),ΩLn*(pi,qi)=1+α2i1+α2n2i+1+α2n2(1α2n).(2.22)

Finally, we compute ΩLn*(pi,pj) and ΩLn*(qi,pj) (n>ij1). To this end, we consider Ln* as the union of two graphs: the upper part and the lower part with respect to pi and qi, as illustrated in Figure 4. Note the lower part is the graph Li*, and the upper part is the graph Lni*. Next, we make circuit reduction to Lni* so that it is reduced to an edge pi+1qi+1 with resistance zni. Then, we reduce Li* to a Y-shaped graph with end vertices pi, qi, and pj, and resistances D, E, and F along its edges. These reductions are illustrated in Figure 4. Then, we have

D+E=ΩLi*(pi,pj),D+F=ΩLi*(pi,qi)=zi,E+F=ΩLi*(qi,pj).(2.23)

It follows that

D=ΩLi*(pi,pj)+ziΩLi*(qi,pj)2,E=ΩLi*(pi,pj)zi+ΩLi*(qi,pj)2,F=ΩLi*(pi,pj)+zi+ΩLi*(qi,pj)2.(2.24)

On the other hand, by the series and parallel connection rules, we have

ΩLn*(pi,pj)=D(zni+F+4)zni+zi+4+E,ΩLn*(qi,pj)=F(zni+D+4)zni+zi+4+E.(2.25)

By Eqs. (2.8), Eqs 2.222.25, and doing some algebra using Mathematica [30], we obtain

ΩLn*(pi,pj)=ij+(1αij)(2αi+j1+α2j1+α2n2i+1(1αij2αi+j1))42(1α2n),(2.26)
ΩLn*(qi,pj)=ij+(1+αij)(2+αi+j1+α2j1+α2n2i+1(1+αij+2αi+j1))42(1α2n).(2.27)

It is easily verified that Eq. 2.27 is valid for i=j.

FIGURE 3
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FIGURE 3. Ln* and circuit reduction to find ΩLn*(pn,pi), ΩLn*(qn,pi), and ΩLn*(pi,qi).

FIGURE 4
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FIGURE 4. Ln* and circuit reductions to find ΩLn*(pi,pj) and ΩLn*(qi,pj).

Step 2. Computation of resistance distances between p,qV2 and between pV1 and qV2.

First, we compute ΩLn(si,pi) and ΩLn(si,pi+1). Applying Lemma 2.1 to pairs of vertices {si,pi} and {si,pi+1}, we obtain

2ΩLn(si,pi)+ΩLn(pi,si)ΩLn(pi,pi)+ΩLn(pi+1,si)ΩLn(pi+1,pi)=2,(2.28)
2ΩLn(si,pi+1)+ΩLn(pi,si)ΩLn(pi,pi+1)+ΩLn(pi+1,si)ΩLn(pi+1,pi+1)=2.(2.29)

Multiplying Eq. 2.28 by 3 and then minus Eq. 2.29, we get

ΩLn(si,pi)=18(4+2ΩLn(pi,pi+1)).(2.30)

Then, substituting the value of ΩLn(pi,pi+1) as obtained in Step 1 into Eq. 2.30, we could obtain

ΩLn(pi+1,pi)=1+(1α)(2α2i+α2i1+α2n2i1(1α2α2i))42(1α2n).(2.31)

Substituting Eq. 2.31 into Eq. 2.30, we have

ΩLn(si,pi)=34+(1α)(2α2i+α2i1+α2n2i1(1α2α2i))162(1α2n).(2.32)

In the same way, we could obtain that

ΩLn(si,pi+1)=34+(1α)(2α2i+α2i1+α2n2i1(1α2α2i))162(1α2n).(2.33)

Second, we calculate the resistance distance between si and pj. Again, applying Lemma 2.1 to {si,pj}, we obtain

2ΩLn(si,pj)+ΩLn(pi,si)ΩLn(pi,pj)+ΩLn(pi+1,si)ΩLn(pi+1,pj)=2.(2.34)

By Eqs 2.32, 2.33, it follows that

ΩLn(pi,si)+ΩLn(pi+1,si)=32+(1α)(2α2i+α2i1+α2n2i1(1α2α2i))82(1α2n).(2.35)

For the sake of simplicity, we define

f(x,y)=(1αxy)(2αx+y1+α2y1+α2n2x+1(1αxy2αx+y1)).(2.36)

Then, Eq. 2.35 can be rewritten as

ΩLn(pi,si)+ΩLn(pi+1,si)=32+f(i+1,i)82(1α2n).(2.37)

On the other hand, by Eq. 2.26, we have

ΩLn(pi,pj)+ΩLn(pi+1,pj)=2i2j+1+f(i,j)+f(i+1,j)42(1α2n).(2.38)

Substituting Eqs. 2.37, 2.38 into Eq. 2.34, we draw the conclusion that

ΩLn(si,pj)=ij+34f(i+1,i)162(1α2n)+f(i,j)+f(i+1,j)82(1α2n).(2.39)

Third, we calculate the resistance distance between sj and qi. Apply Lemma 2.1 to {sj,qi} to obtain

2ΩLn(sj,qi)+ΩLn(pj,sj)ΩLn(pj,qi)+ΩLn(pj+1,sj)ΩLn(pj+1,qi)=2.(2.40)

By Eq. 2.37, we have

ΩLn(pj,sj)+ΩLn(pj+1,sj)=32+f(j+1,j)82(1α2n).(2.41)

For simplicity, we define

g(x,y)=(1+αxy)(2+αx+y1+α2y1+α2n2x+1(1+αxy+2αx+y1)).(2.42)

On the other hand, by Eq. 2.27, we have

ΩLn(qi,pj)+ΩLn(qi,pj+1)=2i2j1+g(i,j)+g(i,j+1)42(1α2n).(2.43)

Substituting Eqs. 2.412.43 into Eq. 2.40, we get

ΩLn(sj,qi)=ij14+f(i+1,i)162(1α2n)+g(i,j)+g(i,j+1)82(1α2n).(2.44)

Fourth, we calculate the resistance distance between si and sj. Applying Lemma 2.1 to {si,sj}, we have

2ΩLn(si,sj)+ΩLn(pi,si)ΩLn(pi,sj)+ΩLn(pi+1,si)ΩLn(pi+1,sj)=2.(2.45)

As ΩLn(pi,si), ΩLn(pi,sj), ΩLn(pi+1,si), and ΩLn(pi+1,sj) have been given by Eq. 2.39, simple calculation leads to

ΩLn(si,sj)=12i+jf(i+1,i)+f(j+1,j)+f(j,i)+f(j+1,i)+f(j,i+1)+f(j+1,i+1)162(1α2n).

Fifth and finally, we calculate the resistance between si and tj. Applying Lemma 2.1 to {si,tj}, we have

2ΩLn(si,tj)+ΩLn(pi,si)ΩLn(pi,tj)+ΩLn(pi+1,si)ΩLn(pi+1,tj)=2(2.46)

Note by the symmetry of Ln that we have ΩLn(pi,tj)=ΩLn(qi,sj) and ΩLn(pi+1,tj)=ΩLn(qi+1,sj). Using the results obtained in Eqs. 2.392.44, simple algebraic calculation yields

ΩLn(si,tj)=12+ij+g(i,j)+g(i,j+1)+g(i+1,j)+g(i+1,j+1)f(i+1,i)162(1α2n)f(i+1,i)+f(i+2,i+1)322(1α2n).(2.47)

3 Conclusion

The computation of resistance distances is a classical problem in electrical circuit theory, which has attracted much attention. It is of special interest to investigate resistance distances in plane networks. Along this line, we have considered the linear polyacene network, with exact expression for resistance distances in this network being given. It is a primary attempt for the computation of resistance distances in plane hexagonal lattice. Resistance distances in more and more plane hexagonal lattices are greatly anticipated.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Funding

This research was funded by the National Natural Science Foundation of China through grant number 116711347, and project ZR2019YQ02 by Shandong Provincial Natural Science Foundation.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank the anonymous reviewers for their useful comments.

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Keywords: hexagonal lattice, local rules, polyacene graph, resistance distance, circuit reduction

Citation: Wang D and Yang Y (2021) Resistance Distances in Linear Polyacene Graphs. Front. Phys. 8:600960. doi: 10.3389/fphy.2020.600960

Received: 31 August 2020; Accepted: 24 November 2020;
Published: 12 January 2021.

Edited by:

Andre P. Vieira, University of São Paulo, Brazil

Reviewed by:

Zhibin Du, South China Normal University, China
Mohammad Reza Farahani, Iran University of Science and Technology, Iran

Copyright © 2021 Wang and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yujun Yang, yangyj@yahoo.com

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