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ORIGINAL RESEARCH article

Front. Phys., 23 June 2022
Sec. Social Physics
This article is part of the Research Topic Network Resilience and Robustness: Theory and Applications View all 21 articles

Results on Resistance Distance and Kirchhoff Index of Graphs With Generalized Pockets

Qun Liu
Qun Liu1*Jiaqi LiJiaqi Li2
  • 1School of Mathematics and Statistics, Hexi University, Zhangye, China
  • 2Institute of Intelligent Information, Hexi University, Zhangye, China

F, Hv are considered simple connected graphs on n and m + 1 vertices, and v is a specified vertex of Hv and u1, u2, … ukF. The graph G = G[F, u1, … , uk, Hv] is called a graph with k pockets, obtained by taking one copy of F and k copies of Hv and then attaching the ith copy of Hv to the vertex ui, i = 1, … , k, at the vertex v of Hv. In this article, the closed-form formulas of the resistance distance and the Kirchhoff index of G = G[F, u1, … , uk, Hv] are obtained in terms of the resistance distance and Kirchhoff index F and Hv.

1 Introduction

All graphs considered in this article are simple and undirected. The resistance distance between vertices u and v of G was defined by Klein and Randić [1] to be the effective resistance between nodes u and v as computed with Ohm’s law when all the edges of G are considered to be unit resistors. The Kirchhoff index Kf(G) was defined in Ref. 1 as Kf(G) = u<vruv, where ruv(G) denotes the resistance distance between u and v in G. Resistance distance are, in fact, intrinsic to the graph, with some nice purely mathematical interpretations and other interpretations. The Kirchhoff index was introduced in chemistry as a better alternative to other parameters used for discriminating different molecules with similar shapes and structures [1]. The resistance distance and Kirchhoff index have attracted extensive attention due to their wide applications in physics, chemistry, and other fields. Until now, many results on the resistance distance and Kirchhoff index are obtained. The references in [25] can be referred to know more. However, the resistance distance and Kirchhoff index of the graph is, in general, a difficult thing from the computational point of view. The bigger the graph, the more difficult it is to compute the resistance distance and Kirchhoff index; so a common strategy is to consider a complex graph as a composite graph and to find relations between the resistance distance and Kirchhoff index of the original graphs. Let G = (V(G), E(G)) be a graph with the vertex set V(G) and edge set E(G). Let di be the degree of vertex i in G and DG = diag (d1, d2, ⋯d|V(G)|) the diagonal matrix with all vertex degrees of G as its diagonal entries. For graph G, let AG and BG denote the adjacency matrix and vertex-edge incidence matrix of G, respectively. The matrix LG = DGAG is called the Laplacian matrix of G, where DG is the diagonal matrix of vertex degrees of G. We use μ1(G) ≥ u2(G) ≥⋯ ≥ μn(G) = 0 to denote the spectrum of LG. For other undefined notations and terminology from graph theory, the readers may refer to Ref. 6 and the references therein [723]. The computation of the resistance distance between two nodes in a resistor network is a classical problem in electric theory and graph theory. For certain families of graphs, it is possible to identify a graph by looking at the resistance distance and Kirchhoff index. More generally, this is not possible. In some cases, the resistance distance and Kirchhoff index of a relatively larger graph can be described in terms of the resistance distance and Kirchhoff index of some smaller (and simpler) graphs using some simple graph operations. There are results that discuss the resistance distance and Kirchhoff index of graphs obtained using some operations on graphs, such as join, graph products, corona, and many variants of corona, such as edge corona and neighborhood corona. For such operations, it is possible to describe the resistance distance and Kirchhoff index of the resulting graph using the resistance distance and Kirchhoff index of the corresponding constituting graph; Refs. 14 and 15 can be referred for reference. This article considers the resistance distance and Kirchhoff index of the graph operations as follows, obtained from Ref. 11.

Definition 1. [11]: Let F, Hv be connected graphs, v be a specified vertex of Hv and u1, u2, … , ukF. Let G = G[F, u1, u2, … , uk, Hv] be the graph obtained by taking one copy of F and k copies of Hv and then attaching the ith copy of Hv to the vertex ui, i = 1, 2, … , k, at the vertex v of Hv(identify ui with the vertex v of the ith copy). Then, the copies of the graph Hv that are attached to the vertices ui, i = 1, 2, … , k are referred to as pockets, and G is described as a graph with k pockets.Barik [11] has described the Laplacian spectrum of G = G [F, u1, u2, … , uk, Hv] using the Laplacian spectrum of F and Hv in a particular case when deg(v) = m. Recently, Barik and Sahoo [12] have described the Laplacian spectrum of more such graphs’ relaxing condition deg(v) = m. Let deg(v) = l, 1 ≤ lm. In this case, we denoted G = G [F, u1, u2, … , uk, Hv] more precisely by G = G [F, u1, u2, … , uk; Hv, l]. When k = n, we denoted simply by G = G [F; Hv, l]. If deg(v) = l, 1 ≤ lm, let N(v) = {v1, v2, … , vl} ⊂ V(Hv) be the neighborhood set of v in Hv. Let H1 be the subgraph of Hv induced by the vertices in N(v) and H2 be the subgraph of Hv induced by the vertices which are in V(Hv)\(N(v) ∪ {v}). When Hv = H1 ∨ (H2 + {v}), we described the resistance distance and Kirchhoff index of G = G[F, u1, u2, … , uk, Hv]. The graphs F = C4 and Hv = C3 are considered. Taking l = 1, 2 and 3, we obtained graphs G1 = G1 [F; Hv, 1], G2 = G2 [F; Hv, 2], and G3 = G3 [F; Hv, 3], respectively. Figure 1 is referred. In this case, we described the resistance distance and Kirchhoff index of G = G [F; Hv, l] in terms of the resistance distance and Kirchhoff index of F and Hv. The results are contained in Section 3 of this article. Furthermore, when F = F1F2, F1 is the subgraph of F induced by the vertices u1, u2, … , uk and F2 is the subgraph of F induced by the vertices uk+1, uk+2, … , un. The considered three graphs G2, G3, and G4 are shown in Figure 2, obtained from the two graphs F = K4 and Hv such that Hv \{v} = K3. It is observed that F = K1K3, G2, G3, and G4 are graphs with 2, 3, and 4 pockets, respectively. Figure 2 can be referred. In this case, we described the resistance distance and Kirchhoff index of G[F, u1, u2, … , uk; Hv, l] in terms of the resistance distance and Kirchhoff index of F and Hv. These results are contained in Section 4.

FIGURE 1
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FIGURE 1. [F; Hv, l] for different l.

FIGURE 2
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FIGURE 2. Graphs having different numbers of pockets.

2 Preliminaries

The {1}-inverse of M is a matrix X such that MXM = M. If M is singular, then it has infinite {1}-inverse [16]. For a square matrix M, the group inverse of M, denoted by M#, is the unique matrix X such that MXM = M, XMX = X, and MX = XM. It is known that M# exists if and only if rank(M) = rank(M2) [16, 17]. If M is really symmetric, then M# exists, and M# is a symmetric {1}-inverse of M. Actually, M# is equal to the Moore–Penrose inverse of M since M is symmetric [17].

It is known that the resistance distance in a connected graph G can be obtained from any {1}- inverse of G [13]. We used M(1) to denote any {1}-inverse of a matrix M, and (M)uv denotes the (u, v)-entry of M.

Lemma 2.1. [17]: Let G be a connected graph, then

ruvG=LG1uu+LG1vvLG1uvLG1vu=LG#uu+LG#vv2LG#uv.

Let 1n denote the column vector of dimension n with all the entries equal to one. We often use 1 to denote all-ones column vector if the dimension can be read from the context.

Lemma 2.2. [14]: For any graph, we have LG#1=0.

Lemma 2.3. [18]: Let

M=ABCD

be a nonsingular matrix. If A and D are nonsingular, then

M1=A1+A1BS1CA1A1BS1S1CA1S1=ABD1C1A1BS1S1CA1S1,

where S = DCA−1B.

Lemma 2.4. [15]: Let L be the Laplacian matrix of a graph of order n. For any a > 0, we have

L+aInanJn×n#=L+aI11anJn×n.

Lemma 2.5. [5]: Let G be a connected graph on n vertices, then

KfG=ntrLG11TLG11=ntrLG#.

Lemma 2.6. [19]: Let

L=ABBTD

be the Laplacian matrix of a connected graph. If D is nonsingular, then

X=H#H#BD1D1BTH#D1+D1BTH#BD1

is a symmetric {1}-inverse of L, where H = ABD−1BT.

3 The Resistance Distance and Kirchhoff Index of G [F; Hv, l]

Let F be a connected graph with the vertex set {u1, u2, … , un}. Let Hv be a connected graph on m + 1 vertices with a specified vertex v and V(Hv) = {v1, v2, … , vm, v}. Let G = G[F; Hv, l]. It is noted that G has n(m + 1) vertices. Let deg(v) = l, 1 ≤ lm. With loss of generality, it is assumed that N(v) = {v1, v2, … , vl}. Let H1 be the subgraph of Hv induced by the vertices in {v1, v2, … , vl} and H2 be the subgraph of Hv induced by the vertices {vl+1, vl+2, … , vm}. It is supposed that Hv = H1 ∨ (H2 + {v}). In this section, we focused on determining the resistance distance and Kirchhoff index of G[F; Hv, l] in terms of the resistance distance and Kirchhoff index of F, H1 and H2.

Theorem 3.1. Let G [F; Hv, l] be the graph, as described previously. It is supposed that Hv = H1 ∨ (H2 + {v}). Let the Laplacian spectrum of H1 and H2 be σ(H1) = (0 = μ1, μ2, … μl) and σ(H2) = (0 = ν1, ν2, … νml). Then, G [F; Hv, l] has the resistance distance and Kirchhoff index as follows:

(i) For any i, jV(F), we obtained

rijGF;Hv,l=L#Fii+L#Fjj2L#Fij=rijF.

(ii) For any iV(F) and jV(H1), we obtained

rijGF;Hv,l=L#Fii+LH1+ml+1IlmllJl×l1In+1lInL#F1lTInjj2L#F1lTInij.

(iii) For any iV(F) and jV(H2), we obtained

rijGF;Hv,l=L#Fii+LH2+lImllml+1Jml×ml1Injj2L#Fij.

(iv) For any iV(H1) and jV(H2), we obtained

rijGF;Hv,l=LH1+ml+1IlmllJl×l1Inii+LH2+lImllml+1Jml×ml1Injj2(LH1+ml+1IlmllJl×l)1Inij.

(v) For any iV(H2) and jV(H1), we obtained

rijGF;Hv,l=LH2+lImllml+1Jml×ml1Inii+LH1+ml+1IlmllJl×l1Injj2LH2+lImllml+1Jml×ml1Inij.

(vi) Let

KfGF;Hv,l=nm+1m+1nKfF+ni=2l1μiH1+ml+1+n+ni=2ml1νiH2+l+nlml+1ml2ml+1l+l2.

Proof: Let vji denote the jth vertex of H in the ith copy of Hv in G, for i = 1, 2, … , n; j = 1, 2, … , m, and let Vj(Hv)={vj1,vj2,,vjn}. Then, V(F)(j=1mVj(Hv)) is a partition of V(G). Using this partition, the Laplacian matrix of G = G[F; Hv, l] can be expressed as

LGF;Hv,l=LF+lIn1lTIn01lInLH1+ml+1IlInJl×mlIn0Jml×lInLH2+lImlIn.

We began with the computation of {1}-inverse of the Laplacian matrix L(G) of G = G[F; Hv, l]. Let A = L(F) + lIn, B=1lTIn0, BT=1lIn0 and

D=LH1+ml+1IlInJl×mlInJml×lInLH2+lImlIn.

First, we computed the D−1. By Lemma 2.3, we obtained

A1B1D11C1=LH1+ml+1IlInJl×mlInLH2+lIml1InJml×lIn=LH1+ml+1IlIn1l1mlTLH2+lIml11ml1lTIn=LH1+ml+1IlInmllJl×lIn=LH1+ml+1IlmllJl×lIn,

so

A1B1D11C11=LH1+ml+1IlmllJl×l1In.

By Lemma 2.3, we obtained

S1=D1C1A11B11=LH2+lImlInJml×lInLH1+ml+1Il1InJl×mlIn1=LH2+lImlInJml×lLH1+ml+1Il1Jl×mlIn1=LH2+lImllml+1Jml×ml1In.

By Lemma 2.3, we obtained

A11B1S1=LH1+ml+1Il1InJl×mlInLH2+lImllml+1Jml×ml1In=1ml+11lInml+1l1mlTIn=1lJl×mlIn.

Similarly, S1C1A11=(A11B1S1)T=1lJ(ml)×lIn. So

D1=P11lJl×mlIn1lJml×lInQ1,

where P1=[L(H1)+(ml+1)IlmllJl×l]1In, Q1=[(L(H2)+lImllml+1J(ml)×(ml))]1In. Now, we computed the {1}-inverse of G[F; Hv, l]. By Lemma 2.6, we obtained

H=ABD1BT=LF+lIn1lTIn0P11lJl×mlIn1lJml×lInQ11lIn0=LF+lIn1lTInLH1+ml+1IlmllJl×l1In1lIn=LF+lInlIn=LF,

so H# = L#(F). According to Lemma 2.6, we calculated − H#BD−1 and − D−1BTH#.

H#BD1=L#F1lTIn0P11lJl×mlIn1lJml×lInQ1=L#F1lTIn,L#F1mlTIn

and

D1BTH#=1lInL#F1mlInL#F.

We are ready to compute the D−1BTH#BD−1.

D1BTH#BD1=1lInL#F1mlInL#F1lTIn,1mlTIn=1lInL#F1lTIn1lInL#F1mlTIn1mlInL#F1lTIn1mlInL#F1mlTIn.

Let P=[L(H1)+(ml+1)IlmllJl×l]In, Q=(L(H2)+lImllml+1J(ml)×(ml))1In, and M=1lJl×(ml)In+(1lIn)L#(F)(1mlTIn); then, based on Lemma 2.6, the following matrix

N=L#FL#F1lTInL#F1mlTIn1lInL#FP1M1mlInL#FMTQ1,(1)

is a symmetric {1}-inverse of G[F; Hv, l], where P1=P1+(1lIn)L#(F)(1lTIn) and Q1=Q1+(1mlIn)L#(F)(1mlTIn). For any i, jV(F), by Lemma 2.1 and Eq. 1, we obtained

rijGF;Hv,l=L#Fii+L#Fjj2L#Fij=rijF,

as stated in (i). For any iV(F) and jV(H1), by Lemma 2.1 and Eq. 1, we obtained

rijGF;Hv,l=L#Fii+LH1+ml+1IlmllJl×l1In+1lInL#F1lTInjj2L#F1lTInij,

as stated in (ii). For any iV(F) and jV(H2), by Lemma 2.1 and Eq. 1, we obtained

rijGF;Hv,l=L#Fii+LH2+lImllml+1Jml×ml1Injj2L#Fij,

as stated in (iii). For any iV(H1) and jV(H2), by Lemma 2.1 and Eq. 1, we obtained

rijGF;Hv,l=LH1+ml+1IlmllJl×l1Inii+LH2+lImllml+1Jml×ml1Injj2LH1+ml+1IlmllJl×l1Inij,

as stated in (iv). For any iV(H2) and jV(H1), by Lemma 2.1 and Eq. 1, we obtained

rijGF;Hv,l=LH2+lImllml+1Jml×ml1Inii+LH1+ml+1IlmllJl×l1Injj2LH2+lImllml+1Jml×ml1Inij,

as stated in (v). Now, we computed the Kirchhoff index of G[F; Hv, l]. By Lemma 2.5, we obtained Kf(G[F; Hv, l])

=nm+1trN1TN1=nm+1trL#F+trLH1+ml+1Il+mllJl×l1In++trLH2+lIml+lml+1Jml×ml1In+tr1lInL#F1lTIn+tr1mlInL#F1mlTIn1TN1.

It is noted that the eigenvalues of (L(H2) + lIml) are 0 + l, ν2(H2) + l, … , νml(H2) + l and the eigenvalues of J(ml)×(ml) are (ml), 0(ml−1). Then,

trLH2+lImllml+1Jml1In=ni=2ml1νiH2+l+nml+1l.(2)

Similarly,

trLH1+ml+1IlmllJl×l1In=ni=2l1μiH1+ml+1+n.

It is easily obtained

tr1lInL#F1lTIn+tr1mlInL#F1mlTIn
=trJl×lL#F+trJml×mlL#F
=ltrL#F+mltrL#F=mtrL#F.(3)

Let P=L(H1)+(ml+1)IlmllJl×lIn, then

1TP11=1lT1lT1lTP10000P100000000P11l1l1l,(4)
=l1lTLH1+ml+1IlmllJl×l11l=l2.

Let Q=L(H2)+lImllml+1J(ml)×(ml)In, then

1TQ11=1mlT1mlT1mlTQ10000Q100000000Q11ml1ml1ml,(5)
=ml1mlTLH2+lImllml+1Jml×ml11ml
=ml2ml+1l.
1lnT1lInL#F1lTIn1ln=1nT1nT1nTInInIn,(6)
L#FInInIn1n1n1n
=n21nTL#F1n=0.

Similarly, 1T(1lIn)L#(F)(1mlTIn)1=0,1T(1mlIn)L#(F)(1lTIn)1=0 and 1T(1mlIn)L#(F)(1lTIn)1=0Plugging Eqs 26 and the aforementioned equations into Kf(G[F; Hv, l]), we obtained the required result in (vi).

4 Resistance Distance and Kirchhoff Index of G [F, u1, u2, … , uk; Hv, l]

In this section, we considered the case when F = F1F2, where F1 is the subgraph of F induced by the vertices u1, u2, … , uk and F2 is the subgraph of F induced by the vertices uk+1, uk+2, … , un. In this case, we indicated the explicit formulae of the resistance distance and Kirchhoff index of G = G[F, u1, u2, … , uk; Hv, l] in terms of the resistance distance and Kirchhoff index of G and Hv.

Theorem 4.1. Let G = G [F, u1, u2, … , uk; Hv, l] be the graph, as described previously. Let σ(F1) = (0 = α1, α2, … αk), σ(F2) = (0 = β1, β2, … βnk), σ(H1) = (0 = μ1, μ2, … μl), and σ(H2) = (0 = ν1, ν2, … νml). Then, G has the resistance distance and Kirchhoff index as follows:

(i) For any i, jV(F1), we obtained

rijG=LF1+nkIk1nkkii+LF1+nkIk1nkkjj2LF1+nkIk1nkkij.

(ii) For any i, jV(F2), we obtained

rijG=LF2+kInkii1+LF2+kInkjj12LF2+kInkij1.

(iii) For any i, jV(H1), we obtained

rijG=LH1+ml+1IlmllJl×lIkii+LH1+ml+1IlmllJl×lIkjj2LH1+ml+1IlmllJl×lIkij.

(iv) For any i, jV(H2), we obtained

rijG=LH2+lImllml+1Jml×mlIkii+LH2+lImllml+1Jml×mlIkjj2LH2+lImllml+1Jml×mlIkij.

(v) For any iV(F) and jV(H1), we obtained

rijG=L#Fii+LH1+ml+1IlmllJl×l1In2L#Fij.

(vi) For any iV(F) and jV(H2), we obtained

rijG=L#Fii+LH2+lImllml+1Jml×ml1In2L#Fij.

(vii) For any iV(H1) and jV(H2), we obtained

rijG=LH1+ml+1IlmllJl×l1Inii+LH2+lImllml+1Jml×ml1Injj2LH1+ml+1IlmllJl×l1Inij.

(viii) For any iV(H2) and jV(H1), we obtained

rijG=LH2+lImllml+1Jml×ml1Inii+LH1+ml+1Ilmlljl×l1Injj2LH2+lImllml+1Jml×ml1Inij.

(ix) Let

KfG=n+mk2i=1k1αi+nk1nk+i=1nk1βi+k+ki=2l1μi+ml+1+k+ki=2ml1νi+l+l2m2l+1ml+1+k+kmlll2+mlml+1l+2kml.

Proof: Let vji denote the jth vertex of H in the ith copy of Hv in G, for i = 1, 2, … , k, j = 1, 2, … , m, and let Vj(Hv)={vj1,vj2,,vjk}. Then, V(F1)V(F2)(j=1mVj(Hv)) is a partition of the vertex set of G = G[F, u1, u2, … , uk; Hv, l]. Using this partition, the Laplacian matrix of G can be expressed as

LG=L1Jk×nk1lTIk0Jnk×kL2001lIk0L3Jl×mlIk00Jml×lIkL4,

where L1 = L(F1) + (nk + l)Ik, L2 = L(F2) + kInk, L3 = (L(H1) + (ml + 1)Il) ⊗ Ik, and L4 = (L(H2) + lIml) ⊗ Ik. Let A = L1, B=Jk×(nk)1lTIk0, BT=J(nk)×k1lIk0, and

D=L2000L3Jl×mlIk0Jml×lIkL4.

First, we computed

D11=L3Jl×mlIkJml×lIkL41.

By Lemma 2.3, we obtained

A1B1D11C1=LH1+ml+1IlIkJl×mlIkLH2+lIml1IkJml×lIk=LH1+ml+1IlIk1l1mlTLH2+lIml11ml1lTIk=LH1+ml+1IlIkmllJl×lIk=LH1+ml+1IlmllJl×lIk,

so (A1B1D11C1)1=[L(H1)+(ml+1)IlmllJl×l]1Ik.By Lemma 2.3, we obtained

S1=D1C1A11B11=LH2+lImlIkJml×lIkLH1+ml+1Il1IkJl×mlIk1=LH2+lImlIkJml×lLH1+ml+1Il1Jl×mlIk1=LH2+lImllml+1Jml×ml1Ik.

By Lemma 2.3, we obtained

A11B1S1=LH1+ml+1Il1IkJl×mlIkLH2+lImllml+1Jml×ml1Ik=1ml+11l×ml+1l1mlTIk=1lJl×mlIk.

Similarly, S1C1A11=(A11B1S1)T=1lJ(ml)×lIk. So

D11=P11lJl×mlIk1lJml×lIkQ1,

where P1=[L(H1)+(ml+1)IlmllJl×l]1In, Q1=[(L(H2)+lImllml+1J(ml)×(ml))]1In. Now, we computed the {1}-inverse of G[F, u1, u2, … , uk; Hv, l]. Let P=[L(H1)+(ml+1)IlmllJl×l]Ik and Q=[(L(H2)+lImllml+1J(ml)×(ml))]Ik. By Lemma 2.6, we obtained

H=ABD1BT=LF1+nk+lIkJk×nk1lTIk0LF2+kInk1000P11lJl×mlIk01lJml×lIkQ1Jnk×k1lIk0=LF1+nk+lIknkkJk×klIk=LF1+nkIknkkJk×k,

so H#=(L(F1)+(nk)IknkkJk×k)#. By Lemma 2.4, we obtained H#=(L(F1)+(nk)Ik)11k(nk)Jk×k.According to Lemma 2.6, we calculated − H#BD−1 and − D−1BTH#.

H#BD1=H#Jk×nk1lTIk0LF2+kInk1000P11lJl×mlIk01lJml×lIkQ1=1kH#Jk×nkH#1lTIkH#1mlTIk

and

D1BTH#=1kJnk×kH#1lIkH#1mlIkH#.

We are ready to compute the D−1BTH#BD−1.

D1BTH#BD1=1kJnk×kH#1lIkH#1mlIkH#1kJk×nk1lTIk1mlTIk=1k2JH#J1kJH#1lTIk1k1lIkH#Jk×nk1lIkH#1lTIk1k1mlIkH#Jk×nk1mlIkH#1lTIk1kJH#1mlTIk1lIkH#1mlTIk1mlIkH#1mlTIk.

Let M=1mlTIk and N=1lTIk. Based on Lemma 2.6, the following matrix

T=H#1kH#JH#NH#M1kJH#LF2+kI100NTH#0P1+NTH#NNTH#M+1lJIkMTH#0MTH#N+1lJIkQ1+MTH#M

is a symmetric {1}-inverse of G = G[F, u1, u2, … , uk; Hv, l], where P=[L(H1)+(ml+1)IlmllJl×l]Ik and Q=[(L(H2)+lImllml+1J(ml)×(ml))]Ik. For any i, jV(F1), by Lemma 2.1 and Eq. 7, we obtained

rijG=LF1+nkIk11knkii+LF1+nkIk11knkjj2LF1+nkIk11knkij,

as stated in (i). For any i, jV(F2), by Lemma 2.1 and Eq. 7, we obtained

rijG=LF2+kInkii1+LF2+kInkjj12LF2+kInkij1,

as stated in (ii). For any i, jV(H1), by Lemma 2.1 and Eq. 7, we obtained

rijG=LH1+ml+1IlmllJl×lIkii1+LH1+ml+1IlmllJl×lIkjj12LH1+ml+1IlmllJl×lIkij1,

as stated in (iii). For any i, jV(H2), by Lemma 2.1 and Eq. 7, we obtained

rijG=LH2+lImllml+1Jml×mlIkii1+LH2+lImllml+1Jml×mlIkjj12LH2+lImllml+1Jml×mlIkij1,

as stated in (iv). For any iV(F) and jV(H1) by Lemma 2.1 and Eq. 7, we obtained

rijG=L#Fii+LH1+ml+1IlmllJl×l1Injj2L#Fij,

as stated in (v). For any iV(F) and jV(H2), by Lemma 2.1 and Eq. 7, we obtained

rijG=L#Fii+LH2+lImllml+1Jml×ml1Injj2L#Fij,

as stated in (vi). For any iV(H1) and jV(H2), by Lemma 2.1 and Eq. 7, we obtained

rijG=LH1+ml+1IlmllJl×l1Inii+LH2+lImllml+1Jml×ml1Injj2LH1+ml+1IlmllJl×l1Inij,

as stated in (vii). For any iV(H2) and jV(H1), by Lemma 2.1 and Eq. 7, we obtained

rijG=LH2+lImllml+1Jml×ml1Inii+LH1+ml+1IlmllJl×l1Injj2LH2+lImllml+1Jml×ml1Inij,

as stated in (viii). Now, we computed the Kirchhoff index of GF,u1,u2, uk;Hv,l as Kf(G[F, u1, u2, … , uk; Hv, l])

=n+mktrT1TT1=n+mktrLF1+nkIk11knkJk×k+trLF2+kInk1+ktrLH1+ml+1IlmllJl×l1+ktrLH2+lImllml+1Jml×ml1+1ltrJl×mlIk+1ltrJml×lIk+trNTH#N+trMTH#M1TT1.

It is noted that the eigenvalues of (L(F1) + (nk)Ik) are α1 + (nk), α2 + (nk), …, αk + (nk). Then,

trLF1+nkIk11knkJk×k
=i=1k1αi+nkkknk.

Similarly, tr(L(F2)+kInk)1=i=1nk1βi+k. It is noted that the eigenvalues of L(H1)+(ml+1)Il are 0 + (ml + 1), μ2(H1) + (ml + 1), …, μl(H1) + (ml + 1) and the eigenvalues of J(ml)×(ml) are (ml), 0(ml−1). Then,

trLH1+ml+1Il+mllJl×l1Ik1=ki=2l1μi+ml+1+k.

Similarly,

trLH2+lImllml+1Jml×mlIk1
=ki=2ml1νi+l+kl2m2l+1ml+1.

It is easily obtained that tr(Jl×(ml)Ik) = lk, tr(J(mllIk) = (ml)k and tr(NTH#N) + tr(MTH#M) = tr(Jl×lH#) + tr(J(ml)×(ml)H#) = ltr(H#) + (ml)tr(H#) = mtr(H#). Since 1kTH#=1kT[(L(F1)+(nk)Ik)11k(nk)Jk×k]=1nk1kT1k(nk)1kT=0, then

1TN1=1TLF2+kInk11+1TP11+1TQ11+1TNTH#N1+1TNTH#M1+1TMTH#N1+1TMTH#M1+1l1TJl×mlIk1+1l1TJml×lIk1.

By the process of Theorem 4.1, we obtained

1TP11=l2,1TQ11=mlml+1l.
1TNTH#N1=1lkT1lIkH#1lTIk1lk=1kT1kT1kTIkIkIkH#IkIkIk1k1k1k=k21kTH#1k=0.

Similarly, 1T(MTH#M)1 = 0, 1TNTH#M1 = 0, and 1TMTH#N1 = 0.

1TJl×mlIk1=1kT1kT1kTIkIkIkIkIkIkIkIkIk1k1k1k=lkml.

Similarly, 1T(J(mllIk) = lk(ml). Applying the aforementioned equations into KfGF,u1,u2,, uk;Hv,l, we obtained the required result in (ix).

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

Funding

This work was supported by the National Natural Science Foundation of China (no. 61963013), the Science and Technology Plan of Gansu Province(18JR3RG206), and the Research and Innovation Fund Project of President of Hexi University(XZZD2018003).

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.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: resistance distance, Kirchhoff index, generalized inverse, Schur complement, generalized pockets

Citation: Liu Q and Li J (2022) Results on Resistance Distance and Kirchhoff Index of Graphs With Generalized Pockets. Front. Phys. 10:872798. doi: 10.3389/fphy.2022.872798

Received: 10 February 2022; Accepted: 14 March 2022;
Published: 23 June 2022.

Edited by:

Yongxiang Xia, Hangzhou Dianzi University, China

Reviewed by:

Jia-Bao Liu, Anhui Jianzhu University, China
Yujun Yang, Yantai University, China

Copyright © 2022 Liu and Li. 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: Qun Liu, liuqun@fudan.edu.cn

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.