
Citation: Jianwei Du, Xiaoling Sun. On the graph connectivity and the variable sum exdeg index[J]. AIMS Mathematics, 2021, 6(1): 607-622. doi: 10.3934/math.2021037
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In this paper, we are concerned with undirected simple connected graphs only. Let G=(V(G),E(G)) denote a graph with vertex set V(G) and edge set E(G). The degree of a vertex u∈V(G) is denoted by dG(u).
Topological indices are numbers reflecting certain structural features of organic molecules that are obtained from the molecular graph, and they play an important role in chemistry, pharmacology, etc. (see [1,2,3]). The Randić index [4] (devised in 1975 for measuring the branching of molecules) and Zagreb indices [5] (appeared in 1972 within the study of total π-electron energy on molecular structure) are among the most studied topological indices. The variable sum exdeg index (denoted by SEIa) was introduced by Vukičević [6] in 2011 and is defined as:
SEIa(G)=∑uv∈E(G)(adG(u)+adG(v))=∑v∈V(G)dG(v)adG(v), |
where a≠1 is an arbitrary positive real number. This graph invariant is very well correlated with octanol-water partition coefficient of octane isomers [6], and was be used to analyze the octane isomers given by the International Academy of Mathematical Chemistry (IAMC) [7,8,9]. Yarahmadi and Ashrafi [10] presented a polynomial form of this descriptors with some applications in nanoscience. Applying the majorization technique, Ghalavand and Ashrafi [11] obtained the maximum and minimum values of variable sum exdeg index of trees, unicyclic, bicyclic and tricyclic graphs for a>1. Recent results can be found in [12,13,14,15].
Denote by G−uv and G+uv the graph that obtained from G by deleting the edge uv∈E(G) and the graph that obtained from G by adding an edge uv∉E(G) (u,v∈V(G)), respectively. For E′⊂E(G), let G−E′ be the subetaaph of G obtained by deleting the edges of E′. Let W⊂V(G), we use G−W to denote the subetaaph of G obtained by deleting the vertices of W and the edges incident with them. A cut edge of a graph is an edge whose deletion breaks the graph into two components. A cut vertex in a connected graph is a vertex whose deletion increases the number of components of the graph. A block of a graph is a maximum connected subetaaph without cut vertices. We also call a block an endblock of a graph if it has at most one cut vertex in the graph as a whole. The vertex connectivity (respectively, edge connectivity) of a graph is the minimum number of vertices (respectively, minimum number of edges) whose deletion yields the resulting graph disconnected or a singleton. A clique of a graph G is a subset S of V such that any two vertices in G[S] (the subetaaph of G induced by S) are adjacent. As usual, we use Pn, Sn, Cn and Kn to denote the n-vertex path, the n-vertex star, the n-vertex cycle and the n-vertex complete graph, respectively.
Let Pr=x0x1⋯xr (r≥1) be a path of graph G with dG(x1)=⋯=dG(xr−1)=2 (unless r=1). If dG(x0),dG(xr)≥3, then Pr is called an internal path of G; if dG(x0)≥3,dG(xr)=1, then Pr is called a pendant path of G. The vertex-disjoint union of the graphs G1 and G2 is denoted by G1∪G2. Let G1∨G2 be the graph obtained from G1∪G2 by adding all possible edges from vertices of G1 to vertices of G2. The cyclomatic number of a connected graph G is defined as γ(G)=|E(G)|−|V(G)|+1. A k cyclic graph is a graph whose cyclomatic number is k. For γ(G)=0, G is a tree.
Let Kkn (as shown in Figure 1) be the graph obtained by identifying one vertex of Kn−k with the central vertex of star Sk+1 and Ckn (as shown in Figure 1) be the graph obtained by attaching a pendant path Pk+1 to one vertex of Cn−k. Obviously, the graph Kkn and Ckn are two special graphs of order n with k cut edges.
The graph G1n,k of order n with k cut vertices (as shown in Figure 2) is obtained from Kn−k by attaching at most one pendant edge to each vertex of Kn−k, where 0<k≤n2.
The graph G2n,k of order n with k cut vertices (as shown in Figure 2) is obtained from Kn−k by attaching exactly one pendant path (with length equal or greater than one) to each vertex of Kn−k, where n2<k≤n−3, l1+l2+⋯+lm=n−k and l1+2l2+⋯+mlm=k (lt is the number of path with length t, t=1,2,⋯,m). We can see [16] for other notations.
Lemma 2.1. [7] Let fa(x)=xax, where x≥1,a>1. Then
(i)fa(x) is an increasing function for each a>1;
(ii)f″a(x)>0 and fa(x) is a convex function for each a>1.
By Lemma 2.1 and the definition of variable sum exdeg index, the following Lemma 2.2 is obvious.
Lemma 2.2. Let G=(V,E) be a simple connected graph. Then
(i) If e=uv∉E(G), u,v∈V(G), SEIa(G)<SEIa(G+e) for a>1;
(ii) If e∈E(G), SEIa(G)>SEIa(G−e) for a>1.
Lemma 2.3. Let
f(x,y)=(x+y−1)ax+y−1+a−xax−yay, |
where x,y≥2 and a>1. Then f(x,y)>0.
Proof. If y≥2 is fixed, by Lemma 2.1, we have
∂f(x,y)∂x=ax+y−1−ax+[(x+y−1)ax+y−1−xax]lna>0. |
So f(x,y) is strictly monotone increasing in x. By symmetry, if x≥2 is fixed, then f(x,y) is strictly monotone increasing in y. Thus, by Jensen inequality for the function xax, which is strictly convex for a>1, we have f(x,y)≥f(2,2)=3a3+a−2⋅2a2>0.
Lemma 2.4. Let
g(x)=fa(x+r)−fa(x)=(x+r)ax+r−xax, |
where x≥2, r≥1 and a>1. Then g(x) is strictly monotone increasing in x.
Proof. Note that for a>1,
g′(x)=ax+r−ax+[(x+r)ax+r−xax]lna>0. |
So g(x) is strictly monotone increasing in x.
Lemma 2.5. Let
g(x,y)=(x−1)[(x+y−3)ax+y−3−(x−1)ax−1]+a−(y−1)ay−1+(y−2)[(x+y−3)ax+y−3−(y−1)ay−1], |
where x≥2, y≥3 and a>1. Then g(x,y)≥0.
Proof. Since for a>1,
∂g(x,y)∂x=[(x+y−3)ax+y−3−(x−1)ax−1]+(x−1){ax+y−3−ax−1+[(x+y−3)ax+y−3−(x−1)ax−1]lna}+(y−2)[ax+y−3+(x+y−3)ax+y−3lna]>0. |
So g(x,y) is strictly monotone increasing in x. Thus, g(x,y)≥g(2,y)=0.
Lemma 2.6. Let
h(x,y)=(x−1)[(x+y−3)ax+y−3−(x−1)ax−1]+2a2−yay+(y−2)[(x+y−3)ax+y−3−(y−1)ay−1], |
where x,y≥3 and a>1. Then h(x,y)>0.
Proof. Note that
∂h(x,y)∂x=∂g(x,y)∂x>0. |
So h(x,y) is strictly monotone increasing in x. Thus, h(x,y)≥h(3,y)=yay−2a2+(y−2)[yay−(y−1)ay−1]>0.
Lemma 2.7. Let
l(x,y)=(x−1)[(x+y−3)ax+y−3−(x−1)ax−1]+(x+y−2)ax+y−2+4a2+(y−2)[(x+y−3)ax+y−3−(y−1)ay−1]−xax−2yay, |
where x,y≥3 and a>1. Then l(x,y)>0.
Proof. It can be seen that
∂l(x,y)∂x=[(x+y−3)ax+y−3−(x−1)ax−1]+(x−1){ax+y−3−ax−1+[(x+y−3)ax+y−3−(x−1)ax−1]lna}+(y−2)[ax+y−3+(x+y−3)ax+y−3lna]+ax+y−2+(x+y−2)ax+y−2lna−ax−xaxlna>ax+y−2−ax+[(x+y−2)ax+y−2−xax]lna>0. |
So l(x,y) is strictly monotone increasing in x. Thus, l(x,y)≥l(3,y)=(y−2)[yay−(y−1)ay−1]+(y+1)ay+1−3a3>0.
We use GE(n,k) to denote the set of graphs on n vertices with k cut edges. If k=n−1, GE(n,n−1) is a tree and trees with extremal variable sum exdeg index had been obtained in [7] and [11]. For a connected graph on n vertices having the cyclomatic number at least one, the number of its cut edges is at most n−3. Therefore, in this section, we always assume that G has k cut edges with 1≤k≤n−3.
First, we provide some graph transformations on graphs with given number of cut edges which will increase the variable sum exdeg index for a>1.
Transformation A1: Suppose G1 is a graph with n1≥3 vertices and G2 is a graph with n2≥2 vertices, where G1 is 2-edge connected. Let G be a graph obtained from G1 and G2 by adding an edge between a vertex x of G1 and a vertex y of G2, as shown in Figure 3. Then xy be a non-pendant cut edge of G. Let G′ be the graph obtained by identifying x of G1 to y of G2 and adding a pendant edge to x(y), as shown in Figure 3.
Lemma 3.1. Let G and G′ be graphs in Figure 3. Then SEIa(G′)>SEIa(G) for a>1.
Proof. Let dG(x)=r and dG(y)=s. By the definition of variable sum exdeg index and Lemma 2.3, we have
SEIa(G′)−SEIa(G)=(r+s−1)ar+s−1+a−rar−sas>0. |
The proof is completed.
Remark 3.2. For any G∈GE(n,k), if necessary, by repeating the graph transformation A1, any cut edge (non-pendant cut edge) of G can changed into pendant edge. That is, if necessary, by a series of transformation A1, we can change G to G∗ (as shown in Figure 4), where Si (1≤i≤r) are 2-edge-connected graphs.
Transformation A2: Let G be a graph as shown in Figure 5, x,y∈V(G1), x1,x2,⋯,xr are pendant vertices adjacent to x, and y1,y2,⋯,ys are pendant vertices adjacent to y, where dG(y)≤dG(x). Let G′=G−{yy1,yy2,⋯,yys}+{xy1,xy2,⋯,xys}, as shown in Figure 5.
Lemma 3.3. Let G and G′ be graphs in Figure 5. Then SEIa(G′)>SEIa(G) for a>1.
Proof. In view of the definition of variable sum exdeg index and Lagrange mean value theorem, for a>1, we have
SEIa(G′)−SEIa(G)=fa(dG(x)+s)+fa(dG(y)−s)−[fa(dG(x))+fa(dG(y))]=fa(dG(x)+s)−fa(dG(x))−[fa(dG(y))−fa(dG(y)−s)]=s(f′a(ξ)−f′a(η)), |
where dG(x)<ξ<dG(x)+s, dG(y)−s<η<dG(y).
Since dG(y)≤dG(x), by Lemma 2.1, then SEIa(G′)−SEIa(G)>0, i.e., SEIa(G′)>SEIa(G) for a>1.
Remark 3.4. For any G∈GE(n,k), if necessary, by repeating graph transformation A1 and A2, all the pendant edges are attached to the same vertex. That is, if necessary, by a series of transformation A1 and A2, we can change G to H1 or H2 (as shown in Figure 6), where Si (1≤i≤r) are 2-edge-connected graphs.
By Lemmas 3.1, 3.3 and Remarks 3.2, 3.4, we have the following Lemma 3.5.
Lemma 3.5. Let G∈GE(n,k). Then SEIa(G)≤SEIa(Hi)(i=1 or 2) for a>1, where H1 or H2 is a graph as shown in Figure 6, Si(1≤i≤r) are 2-edge-connected graphs.
Denoted Kni(1≤i≤r) to be a clique which is obtained by adding edges in Si(1≤i≤r) and changing Si into complete sub-graphs, where Si(1≤i≤r) in H1 or H2 are 2-edge-connected graphs.
Lemma 3.6. Suppose H′1 or H′2 is a graph as shown in Figure 7, where Kni(1≤i≤r) is a clique as above. Then SEIa(H′i)≥SEIa(Hi)(i=1 or 2) for a>1.
Proof. By Lemma 2.2, the result holds obviously.
Theorem 3.7. Let G∈GE(n,k), where 1≤k≤n−3. Then
SEIa(G)≤(n−k−1)2an−k−1+(n−1)an−1+ka |
for a>1, with equality holding if and only if G≅Kkn.
Proof. Choose G∈GE(n,k) such that G has the maximum variable sum exdeg index for a>1. By Lemma 3.5 and 3.6, we have SEIa(G)≤SEIa(H′1) or SEIa(G)≤SEIa(H′2) for a>1.
Next, we prove that r=1. By contradiction, assume that r≥2. Without loss of generality, suppose that there exists an edge e=uv∉E(G), u∈V(Kni), v∈V(Knj), 1≤i,j≤r, i≠j, and u,v is not the common vertex of Kni and Knj. By Lemma 2.2, we have SEIa(G+e)>SEIa(G) for a>1, a contradiction to the choice of G. So r=1, i.e., G≅Kkn.
First, we provide some transformations on graphs with cut edges which will decrease the variable sum exdeg index for a>1.
Transformation A3: Let Cp=u0u1u2⋯up−1 and Cq=v0v1v2⋯vq−1 be two cycles in G (as shown in Figure 8) such that Cp connects Cq by a path Pl (with l≥2 vertices) whose end vertices are u0, v1, and the vertex, say ut (resp. vs), on the cycle Cp (resp. Cq) in G either is of degree 2 or has subetaaph Gt (resp. Hs) attached, 0≤t≤p−1, 0≤s≤q−1. G′=G−{u0u1,v1v0,v1v2}+{u0v2,u1v0}, as shown in Figure 8.
Lemma 3.8. Let G and G′ be graphs in Figure 8. Then SEIa(G)>SEIa(G′) for a>1.
Proof. It is easy to see that dG′(u0)=dG(u0), dG′(u1)=dG(u1), dG′(v0)=dG(v0), dG′(v2)=dG(v2), dG′(v1)=dG(v1)−2, and dG′(w)=dG(w) for w∈V(G)∖{u0,u1,v0,v1,v2}. Thus, for a>1,
SEIa(G)−SEIa(G′)=fa(dG(v1))−fa(dG(v1)−2)>0. |
The proof is completed.
Transformation A4: Let G be a graph as shown in Figure 9, where G1≆K1 and y∈V(G1). That is, we use G to denote the graph obtained from G1 by identifying y with the vertex xr of a path x1x2⋯xr−1xr⋯xn, 1<r<n. Let G′=G−xr−1xr+xnxr−1, as shown in Figure 9.
Lemma 3.9. Let G and G′ be graphs in Figure 9. Then SEIa(G)>SEIa(G′) for a>1.
Proof. By Lemma 2.1 and the definition of variable sum exdeg index, we have
SEIa(G)−SEIa(G′)=fa(dG1(y)+2)−fa(dG1(y)+1)−(fa(2)−fa(1))=f′a(ξ)−f′a(η)>0, |
where dG1(y)+1<ξ<dG1(y)+2, 1<η<2.
Remark 3.10. By repeating Transformation A5, any tree T attached to a graph G can be changed into a path as showed in Figure 10.
Transformation A5: Let G be a graph as shown in Figure 11, where x,y∈V(G1) and dG1(x),dG1(y)≥2. That is, we use G to denote the graph obtained from identifying x with the vertex x0 of a path x0x1⋯xr and identifying y with the vertex y0 of a path y0y1⋯ys, where r,s≥1. G′=G−xx1+ysx1, as shown in Figure 11.
Lemma 3.11. Let G and G′ be graphs in Figure 11. Then SEIa(G)>SEIa(G′) for a>1.
Proof. The proof is similar to Lemma 3.9, omitted.
Theorem 3.12. Let G∈GE(n,k), where 1≤k≤n−3. Then
SEIa(G)≥2(n−2)a2+3a3+a |
for a>1, with equality holding if and only if G≅Ckn.
Proof. Choose connected graph G∈GE(n,k) such that it has the smallest variable sum exdeg index for a>1. Let E′={e1,e2,⋯,ek} be the set of the cut edges of G∈GE(n,k). By Lemma 2.2, it can be seen that each component of G−E′ is either a cycle or an isolated vertex.
Next, we prove that G contains exactly one cycle of length n−k. By contradiction, assume that G contains at least two cycles. Then by Lemma 3.8, we can obtain a graph G′∈GE(n,k) such that SEIa(G′)<SEIa(G) for a>1, a contradiction to the choice of G. Furthermore, G has k cut edges, so the length of the cycle contained in G is of n−k. By Lemmas 3.9, 3.11 and Remark 3.10, we have G≅Ckn.
Let GV(n,k) be the set of graphs on n vertices with k cut vertices. If k=n−2, then the only graph in GV(n,n−2) is the path. Therefore, in this section, we always assume that G has k cut vertices with 1≤k≤n−3.
Transformation B1: Let G be a graph as shown in Figure 12, Kp and Kq be two cliques of G, where p≥2, q≥3 and Kq is an endblock. V(Kp) and V(Kq) have one cut vertex, say u, in common. V(Kp)={u1,u2,⋯,up−1,u}, V(Kq)={v1,v2,⋯,vq−1,u}. Gi(1≤i≤p−1) is the subetaaph attached to ui(1≤i≤p−1). Let G′=G−{uu1,uu2,⋯,uup−1,uv2,uv3,⋯,uvq−1}+{u1v1,u1v2,⋯,u1vq−1}+⋯+{up−1v1,up−1v2,⋯,up−1vq−1}, as shown in Figure 12.
Lemma 4.1. Let G and G′ be graphs in Figure 12. Then SEIa(G′)>SEIa(G) for a>1.
Proof. Note that dG(u)=p+q−2, dG′(u)=1, dG(v1)=q−1, dG′(v1)=p+q−2, dG′(ui)=dG(ui)+q−2 (i=1,2,⋯,p−1), dG′(vj)=p+q−3 (j=2,3,⋯,q−1), and the degrees of other vertices in Gi(1≤i≤p−1) are unchanged. By the definition of variable sum exdeg index and Lemma 2.4, 2.5, for a>1, we have
SEIa(G′)−SEIa(G)=p−1∑i=1fa(dG(ui)+q−2)+q−1∑j=2fa(dG(vj)+p−2)+fa(dG(v1)+p−1)+fa(1)−fa(dG(u))−p−1∑i=1fa(dG(ui))−q−1∑j=1fa(dG(vj))=p−1∑i=1[fa(dG(ui)+q−2)−fa(dG(ui))]+q−1∑j=2[fa(p+q−3)−fa(q−1)]+fa(p−q−2)+fa(1)−fa(p−q−2)−fa(q−1)>(p−1)[(p+q−3)ap+q−3−(p−1)ap−1]+a−(q−1)aq−1+(q−2)[(p+q−3)ap+q−3−(q−1)aq−1]>0. |
This completes the proof.
Transformation B2: Let G be a graph as shown in Figure 13, Kp be a clique of G, where p≥3. V(Kp)={u0,u1,⋯,up−1}. P=u1w1⋯wt (t≥2) is a path attached to u1. NG(u0)={u1,u2,⋯,up−1}, NG(u1)={u0,u2,⋯,up−1,w1}. Gi(2≤i≤p−1) is the subetaaph attached to ui(2≤i≤p−1). Let G′=G−wt−1wt+u0wt, as shown in Figure 13.
Lemma 4.2. Let G and G′ be graphs in Figure 13. Then SEIa(G′)>SEIa(G) for a>1.
Proof. By the definition of variable sum exdeg index and Lemma 2.4, for a>1, we have
SEIa(G′)−SEIa(G)=fa(dG(u0)+1)+fa(dG(wt−1)−1)−fa(dG(u0))−fa(dG(wt−1))=pap−(p−1)ap−1+a−2a2≥3a3+a−2⋅2a2>0. |
The proof is completed.
Transformation B3: Let G be a graph as shown in Figure 14, Kp and Kq be two cliques of G, where p,q≥3. V(Kp) and V(Kq) have one cut vertex, say u, in common. V(Kp)={u1,u2,⋯,up−1,u}, V(Kq)={v1,v2,⋯,vq−1,u}. P=v1w1⋯wt (t≥1) is a path attached to v1 and NG(v1)={u,v2,⋯,vq−1,w1}. Gi(1≤i≤p−1) is the subetaaph attached to ui(1≤i≤p−1) and Hj(2≤j≤q−1) is the subetaaph attached to vj(2≤j≤q−1). Let G′=G−{uu1,uu2,⋯,uup−1,uv1,uv2,⋯,uvq−1}+{wtu}+{u1v1,u1v2,⋯,u1vq−1}+⋯+{up−1v1,up−1v2,⋯,up−1vq−1}, as shown in Figure 14.
Lemma 4.3. Let G and G′ be graphs in Figure 14. Then SEIa(G′)>SEIa(G) for a>1.
Proof. It can be seen that dG(u)=p+q−2, dG′(u)=1, dG(wt)=1, dG′(wt)=2, dG(v1)=q, dG′(v1)=p+q−2, dG′(ui)=dG(ui)+q−2 (i=1,2,⋯,p−1), dG′(vj)=dG(vj)+p−2 (j=2,⋯,q−1), and the degrees of other vertices are unchanged. By the definition of variable sum exdeg index and Lemma 2.4, 2.6, for a>1, we have
SEIa(G′)−SEIa(G)=p−1∑i=1[fa(dG(ui)+q−2)−fa(dG(ui))]+q−1∑j=2[fa(dG(vj)+p−2)−fa(dG(vj))]+fa(p+q−2)−fa(q)−fa(p+q−2)+fa(2)≥(p−1)[(p+q−3)ap+q−3−(p−1)ap−1]+2a2−qaq+(q−2)[(p+q−3)ap+q−3−(q−1)aq−1]>0. |
The proof is completed.
Transformation B4: Let G be a graph as shown in Figure 15, Kp and Kq be two cliques of G, where p,q≥3. Kp connects Kq by an internal path P=u⋯u′ of length s≥1. V(Kp)={u1,u2,⋯,up−1,u}, V(Kq)={v1,v2,⋯,vq−1,u′}. Pt+1=v1w1⋯wt (t≥1) is a path attached to v1 and NG(v1)={u′,v2,⋯,vq−1,w1}. Gi(1≤i≤p−1) is the subetaaph attached to ui(1≤i≤p−1) and Hj(2≤j≤q−1) is the subetaaph attached to vj(2≤j≤q−1). Let G′=G−{uu1,uu2,⋯,uup−1,u′v1,u′v2,⋯,u′vq−1}+{wtu}+{u1v1,u1v2,⋯,u1vq−1}+⋯+{up−1v1,up−1v2,⋯,up−1vq−1}, as shown in Figure 15.
Lemma 4.4. Let G and G′ be graphs in Figure 15. Then SEIa(G′)>SEIa(G) for a>1.
Proof. We notice that dG(u)=p, dG′(u)=2, dG(u′)=q, dG′(u′)=1, dG(wt)=1, dG′(wt)=2, dG(v1)=q, dG′(v1)=p+q−2, dG′(ui)=dG(ui)+q−2 (i=1,2,⋯,p−1), dG′(vj)=dG(vj)+p−2 (j=2,⋯,q−1), and the degrees of other vertices are unchanged. By the definition of variable sum exdeg index and Lemma 2.4, 2.7, for a>1, we have
SEIa(G′)−SEIa(G)=p−1∑i=1[fa(dG(ui)+q−2)−fa(dG(ui))]+q−1∑j=2[fa(dG(vj)+p−2)−fa(dG(vj))]+fa(p+q−2)−fa(q)+2fa(2)−fa(p)−fa(q)≥(p−1)[(p+q−3)ap+q−3−(p−1)ap−1]+(p+q−2)ap+q−2+4a2+(q−2)[(p+q−3)ap+q−3−(q−1)aq−1]−pap−2qaq>0. |
This finishes the proof.
Lemma 4.5. Choose G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. Then each cut vertex of G connects exactly two blocks and each of the blocks contained in G is a clique.
Proof. We shall prove by contradiction. Let u be a cut vertex in G. Assume that u connects at least three connected components, say G1,G2,⋯,Gr(r≥3), of G. Let G′=G+xy, where x∈V(G2)∖{u} and y∈V(G3)∖{u}. Clearly, G′∈GV(n,k) and by Lemma 2.2, we have SEIa(G′)>SEIa(G) for a>1, a contradiction. Thus, we get that each cut vertex connects exactly two blocks. Moreover, by Lemma 2.2, we can conclude that each block is a clique.
In order to determine the maximum variable sum exdeg index of GV(n,k), we choose connected graph G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. By Lemma 4.5, each cut vertex of G connects exactly two cliques. We define two cliques Kp, Kq (p,q≥3) of G are adjacent, if Kp connects Kq by a path P such that P does not intersect some other clique with at least 3 vertices. By Lemma 4.5, the following Lemma 4.6 is obtained.
Lemma 4.6. Choose G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. If two cliques Kp, Kq with p,q≥3 in G are adjacent, then the path connecting Kp and Kq is either of length 0 or an internal path.
Lemma 4.7. Choose G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. If Kq is an endblock of G, then q=2.
Proof. We prove this lemma by contradiction. Suppose that q≥3, let Kp(p≥2) be a clique such that V(Kp), V(Kq) have one cut vertex, say u, in common. By Lemma 4.5, u is not a cut vertex of some other clique. From Lemma 4.1, G can be changed to G′ by transformation B1 with a larger variable sum exdeg index for a>1, which contradicts the choice of G. Hence, q=2.
Choose G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. By Lemma 4.5, we assume that Kn1,Kn2,⋯,Knr are all cliques of G.
Lemma 4.8. Choose G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. Let Kn1,Kn2,⋯,Knr are all of the cliques contained in G. Then there is only one clique Kni with ni≥3.
Proof. To the contrary, suppose that there are two cliques Kp, Kq(p≠q and p,q∈{n1,n2,⋯,nr}) such that Kp is adjacent to Kq, where p,q≥3. By Lemma 4.7, it can be seen that Kp and Kq are not endblocks. Furthermore, by Lemma 4.5, we can choose two such blocks such that at least one of them have a pendant path attached to one of its vertices. Without loss of generality, we assume that Kq is one of such cliques and v1 is attached by one pendant path, say Pt+1=v1w1⋯wt(t≥1). By Lemma 4.6, we can see that Kp and Kq have exactly one cut vertex in common or Kp connects Kq by an internal path P of length s≥1. Next, We discuss in two cases.
Case 1. Kp and Kq have exactly one cut vertex, say u, in common.
By Lemma 4.3, G can be changed to G′ by transformation B3 with a larger variable sum exdeg index for a>1, which is a contradiction to the choice of G.
Case 2. The internal path P=u⋯u′ is of length s≥1.
By Lemma 4.4, G can be changed to G′ by transformation B4 with a larger variable sum exdeg index for a>1, which contradicts the assumption of G.
The proof is completed.
Lemma 4.9. Choose G∈GV(n,k) such that SEIa(G) is as large as possible for a>1. Let Kp be the only clique with p≥3. Then p=n−k.
Proof. In view of Lemma 4.5 and 4.8, it can be concluded that in G, there are k+1 cliques and k of them are isomorphic to K2. Since G has k cut vertices, and each cut vertex belongs to two cliques, then 2k+p−k=n. Thus, p=n−k.
Denote Gn,k={G|G∈GV(n,k) is obtained by attaching at most one pendant path to each vertex of Kn−k}. Then it is not difficult to see that {G1n,k,G2n,k}⊂Gn,k.
Lemma 4.10. Let H∈Gn,k. Then for a>1, the maximum value of SEIa(H) is obtained at the graph in G1n,k or G2n,k.
Proof. Choose H∈Gn,k such that SEIa(H) is as large as possible for a>1. If H≅G1n,k or G2n,k, the lemma holds. Otherwise, H∈Gn,k∖{G1n,k,G2n,k}. Let P, which is attached to u0, be the shortest path of all the pendant paths in H and P′, which is attached to u1, be the longest one in H. Since H∉{G1n,k,G2n,k}, then we have |E(P)|=0 (H has no pendant path attached to u0) and |E(P′)|≥2. By Lemma 4.2, H can be changed to H′ by transformation B2 with a larger variable sum exdeg index for a>1, which contradicts the assumption of H.
Theorem 4.11. Let G∈GV(n,k), where 1≤k≤n−3. Then
(i) if 1≤k≤n2, SEIa(G)≤(n−2k)(n−k−1)an−k−1+k(n−k)an−k+ka for a>1, with equality holding if and only if G≅G1n,k;
(ii) if n2<k≤n−3, SEIa(G)≤(n−k)2(n−k−1)an−k−1+2(2k−n)a2+a(n−k) for a>1, with equality holding if and only if G≅G2n,k.
Proof. By Lemma 4.8 and 4.9, we have G∈Gn,k. By Lemma 4.10, for a>1, we have SEIa(G)≤SEIa(G1n,k) when 1≤k≤n2 and SEIa(G)≤SEIa(G2n,k) when n2<k≤n−3.
The proof is finished.
Lemma 5.1. Let G be a graph of order n with vertex connectivity κ<n−1. Then there exist positive integers n1 and n2 such that n1+n2=n−κ and for a>1,
SEIa(G)≤SEIa(Kκ∨(Kn1∪Kn2)). |
Proof. Assume that X is a vertex cut of G with κ vertices such that G−X has l components, say G1,G2,⋯,Gl, where l≥2. Let n1=|V(G1)| and n2=|V(G2∪⋯∪Gl)|. Then G is a spanning subetaaph of Kκ∨(Kn1∪Kn2). By Lemma 2.2, the lemma holds immediately.
Lemma 5.2. Let G be a n-vertex graph with edge connectivity λ<n−1. Then there exist positive integers n1 and n2 such that n1+n2=n−κ, κ≤λ and for a>1,
SEIa(G)≤SEIa(Kκ∨(Kn1∪Kn2)). |
Proof. Let κ be the vertex connectivity of G. Then κ≤λ<n−1. From Lemma 5.1, the conclusion holds clearly.
Lemma 5.3. Let G=Ks∨(Kn1∪Kn2) and G′=Ks∨(Kn1−1∪Kn2+1), where 2≤n1≤n2, n1+n2=n−s. Then for a>1,
SEIa(G′)>SEIa(G). |
Proof. In view of the definition of variable sum exdeg index, for a>1, we have
SEIa(G′)−SEIa(G)=(n1−1)fa(n1+s−2)+(n2+1)fa(n2+s)−n1fa(n1+s−1)−n2fa(n2+s−1)=n2(fa(n2+s)−fa(n2+s−1))−n1(fa(n1+s−1)−fa(n1+s−2))+fa(n2+s)−fa(n1+s−2)>n2f′a(ξ)−n1f′a(η)≥n1(f′a(ξ)−f′a(η)), |
where n2+s−1<ξ<n2+s, n1+s−2<η<n1+s−1. By Lemma 2.1, we have SEIa(G′)−SEIa(G)>0 for a>1, i.e., SEIa(G′)>SEIa(G) for a>1.
Theorem 5.4. Let G be a graph of order n with vertex connectivity κ(κ<n−1). Then
SEIa(G)≤κ(n−1)an−1+(n−κ−1)(n−2)an−2+κaκ |
for a>1, with equality if and only if G≅Kκ∨(K1∪Kn−κ−1).
Proof. Choose G such that G has the maximum variable sum exdeg index (for a>1) among all graphs of order n with vertex connectivity κ. By Lemma 2.2 and 5.1, there exist positive integers n1 and n2 such that n1+n2=n−κ and G≅Kκ∨(Kn1∪Kn2). Moreover, by Lemma 5.3, G≅Kκ∨(K1∪Kn−κ−1).
Theorem 5.5. Let G be a n-vertex graph with edge connectivity λ(λ<n−1). Then
SEIa(G)≤λ(n−1)an−1+(n−λ−1)(n−2)an−2+λaλ |
for a>1, with equality if and only if G≅Kλ∨(K1∪Kn−λ−1).
Proof. Choose G such that G has the maximum variable sum exdeg index (for a>1) among all n-vertex graphs with edge connectivity λ. By Lemma 2.1 and 5.2, there exist positive integers κ≤λ such that n1+n2=n−κ and G≅Kκ∨(Kn1∪Kn2). By Lemma 5.3, we have G≅Kκ∨(K1∪Kn−κ−1). Furthermore, Kκ∨(K1∪Kn−κ−1) is a spanning subetaaph of Kλ∨(K1∪Kn−λ−1) for κ≤λ, by Lemma 2.2, the result holds obviously.
In [7], Vukičević think that mathematical properties of the variable sum exdeg index deserves further study since it can be used for the detection of chemical compounds that may have desirable properties. Inspired by [17,18,19,20,21,22,23,24], we continue to study the mathematical properties of the variable sum exdeg index and the connectivity of a graph. In this work, we present the extremal value of the variable sum exdeg indices (for a>1) in terms of the number of cut edges, or the number of cut vertices, or the vertex connectivity, or the edge connectivity of a graph. Furthermore, the corresponding extremal graphs are characterized.
The authors would like to thank the referees for their careful reading and helpful suggestions. This work was supported by the Shanxi Province Science Foundation for Youths [grant number 201901D211227].
The authors declare no conflict of interest.
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