In recent years, the research of autonomous driving and mobile robot technology is a hot research direction. The ability of simultaneous positioning and mapping is an important prerequisite for unmanned systems. Lidar is widely used as the main sensor in SLAM (Simultaneous Localization and Mapping) technology because of its high precision and all-weather operation. The combination of Lidar and IMU (Inertial Measurement Unit) is an effective method to improve overall accuracy. In this paper, multi-line Lidar is used as the main data acquisition sensor, and the data provided by IMU is integrated to study robot positioning and environment modeling. On the one hand, this paper proposes an optimization method of tight coupling of lidar and IMU using factor mapping to optimize the mapping effect. Use the sliding window to limit the number of frames optimized in the factor graph. The edge method is used to ensure that the optimization accuracy is not reduced. The results show that the point plane matching mapping method based on factor graph optimization has a better mapping effect and smaller error. After using sliding window optimization, the speed is improved, which is an important basis for the realization of unmanned systems. On the other hand, on the basis of improving the method of optimizing the mapping using factor mapping, the scanning context loopback detection method is integrated to improve the mapping accuracy. Experiments show that the mapping accuracy is improved and the matching speed between two frames is reduced under loopback mapping. However, it does not affect real-time positioning and mapping, and can meet the requirements of real-time positioning and mapping in practical applications.
Citation: Minghe Liu, Ye Tao, Zhongbo Wang, Wenhua Cui, Tianwei Shi. Research on Simultaneous localization and mapping Algorithm based on Lidar and IMU[J]. Mathematical Biosciences and Engineering, 2023, 20(5): 8954-8974. doi: 10.3934/mbe.2023393
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In recent years, the research of autonomous driving and mobile robot technology is a hot research direction. The ability of simultaneous positioning and mapping is an important prerequisite for unmanned systems. Lidar is widely used as the main sensor in SLAM (Simultaneous Localization and Mapping) technology because of its high precision and all-weather operation. The combination of Lidar and IMU (Inertial Measurement Unit) is an effective method to improve overall accuracy. In this paper, multi-line Lidar is used as the main data acquisition sensor, and the data provided by IMU is integrated to study robot positioning and environment modeling. On the one hand, this paper proposes an optimization method of tight coupling of lidar and IMU using factor mapping to optimize the mapping effect. Use the sliding window to limit the number of frames optimized in the factor graph. The edge method is used to ensure that the optimization accuracy is not reduced. The results show that the point plane matching mapping method based on factor graph optimization has a better mapping effect and smaller error. After using sliding window optimization, the speed is improved, which is an important basis for the realization of unmanned systems. On the other hand, on the basis of improving the method of optimizing the mapping using factor mapping, the scanning context loopback detection method is integrated to improve the mapping accuracy. Experiments show that the mapping accuracy is improved and the matching speed between two frames is reduced under loopback mapping. However, it does not affect real-time positioning and mapping, and can meet the requirements of real-time positioning and mapping in practical applications.
Topological indices have become an important research topic associated with the study of their mathematical and computational properties and, fundamentally, for their multiple applications to various areas of knowledge (see, e.g., [1,2,3]). Within the study of mathematical properties, we will contribute to the study of inequalities and optimization problems associated with topological indices. Our main goals are the Sombor indices, introduced by Gutman in [4].
In what follows, G=(V(G),E(G)) will be a finite undirected graph, and we will assume that each vertex has at least a neighbor. We denote by dw the degree of the vertex w, i.e., the number of neighbors of w. We denote by uv the edge joining the vertices u and v (or v and u). For each graph G, its Sombor index is
SO(G)=∑uv∈E(G)√d2u+d2v. |
In the same paper is also defined the reduced Sombor index by
SOred(G)=∑uv∈E(G)√(du−1)2+(dv−1)2. |
In [5] it is shown that these indices have a good predictive potential.
Also, the modified Sombor index of G was proposed in [6] as
mSO(G)=∑uv∈E(G)1√d2u+d2v. | (1.1) |
In addition, two other Sombor indices have been introduced: the first Banhatti-Sombor index [7]
BSO(G)=∑uv∈E(G)√1d2u+1d2v | (1.2) |
and the α-Sombor index [8]
SOα(G)=∑uv∈E(G)(dαu+dαv)1/α, | (1.3) |
here α∈R∖{0}. In fact, there is a general index that includes most Sombor indices listed above: the first (α,β)–KA index of G which was introduced in [9] as
KAα,β(G)=KA1α,β(G)=∑uv∈E(G)(dαu+dαv)β, | (1.4) |
with α,β∈R. Note that SO(G)=KA2,1/2(G), mSO(G)=KA2,−1/2(G), BSO(G)=KA−2,1/2(G), and SOα(G)=KAα,1/α(G). Also, we note that KA1,β(G) equals the general sum-connectivity index [10] χβ(G)=∑uv∈E(G)(du+dv)β. Reduced versions of SO(G), mSO(G) and KAα,β(G) were also introduced in [4,6,11], e.g., the reduced (α,β)–KA index is
redKAα,β(G)=∑uv∈E(G)((du−1)α+(dv−1)α)β. |
If α<0, then redKAα,β(G) is just defined for graphs without pendant vertices (recall that a vertex is said pendant if its degree is equal to 1).
Since I. Gutman initiated the study of the mathematical properties of Sombor index in [4], many papers have continued this study, see e.g., [12,13,14,15,16,17,18].
Our main aim is to obtain new bounds of Sombor indices, and to characterize the graphs where equality occurs. In particular, we have obtained bounds for Sombor indices relating them with the first Zagreb index, the forgotten index and the first variable Zagreb index. Also, we solve some extremal problems for Sombor indices.
The following inequalities are known for x,y>0:
xa+ya<(x+y)a≤2a−1(xa+ya)if a>1,2a−1(xa+ya)≤(x+y)a<xa+yaif 0<a<1,(x+y)a≤2a−1(xa+ya)if a<0, |
and the second, third or fifth equality is attained for each a if and only if x=y. These inequalities allow to obtain the following result relating KA indices.
Theorem 1. Let G be any graph and α,β,λ∈R∖{0}.Then
KAαβ/λ,λ(G)<KAα,β(G)≤2β−λKAαβ/λ,λ(G)if β>λ,βλ>0,2β−λKAαβ/λ,λ(G)≤KAα,β(G)<KAαβ/λ,λ(G)if β<λ,βλ>0,KAα,β(G)≤2β−λKAαβ/λ,λ(G)if β<0,λ>0,KAα,β(G)≥2β−λKAαβ/λ,λ(G)if β>0,λ<0, |
and the second, third, fifth or sixth equality is attained for each α,β,λ if and only if all the connected components of G are regular graphs.
Proof. If a=β/λ, x=dαu and y=dαv, then the previous inequalities give
dαβ/λu+dαβ/λv<(dαu+dαv)β/λ≤2β/λ−1(dαβ/λu+dαβ/λv)if β/λ>1,2β/λ−1(dαβ/λu+dαβ/λv)≤(dαu+dαv)β/λ<dαβ/λu+dαβ/λvif 0<β/λ<1,(dαu+dαv)β/λ≤2β/λ−1(dαβ/λu+dαβ/λv)if β/λ<0, |
and the second, third or fifth equality is attained if and only if du=dv.
Hence, we obtain
(dαβ/λu+dαβ/λv)λ<(dαu+dαv)β≤2β−λ(dαβ/λu+dαβ/λv)λif β/λ>1,λ>0,2β−λ(dαβ/λu+dαβ/λv)λ≤(dαu+dαv)β<(dαβ/λu+dαβ/λv)λif β/λ>1,λ<0,2β−λ(dαβ/λu+dαβ/λv)λ≤(dαu+dαv)β<(dαβ/λu+dαβ/λv)λif 0<β/λ<1,λ>0,(dαβ/λu+dαβ/λv)λ<(dαu+dαv)β≤2β−λ(dαβ/λu+dαβ/λv)λif 0<β/λ<1,λ<0,(dαu+dαv)β≤2β−λ(dαβ/λu+dαβ/λv)λif β<0,λ>0,(dαu+dαv)β≥2β−λ(dαβ/λu+dαβ/λv)λif β>0,λ<0, |
and the equality in the non-strict inequalities is tight if and only if du=dv.
If we sum on uv∈E(G) these inequalities, then we obtain (1).
Remark 2. Note that the excluded case β=λ in Theorem 1 is not interesting, since KAαβ/λ,λ(G)=KAα,β(G) if β=λ.
The argument in the proof of Theorem 1 also allows to obtain the following result relating reduced KA indices.
Theorem 3. Let G be any graph and α,β,λ∈R∖{0}.If α<0 or αβλ<0, we also assume that G does not have pendant vertices.Then
redKAαβ/λ,λ(G)<redKAα,β(G)≤2β−λredKAαβ/λ,λ(G)if β>λ,βλ>0,2β−λredKAαβ/λ,λ(G)≤redKAα,β(G)<redKAαβ/λ,λ(G)if β<λ,βλ>0,redKAα,β(G)≤2β−λredKAαβ/λ,λ(G)if β<0,λ>0,redKAα,β(G)≥2β−λredKAαβ/λ,λ(G)if β>0,λ<0, |
and the second, third, fifth or sixth equality is attained for each α,β,λ if and only if all the connected components of G are regular graphs.
If we take β=1/α and μ=1/λ in Theorem 1, we obtain the following inequalities for the α-Sombor index.
Corollary 4. Let G be any graph and α,μ∈R∖{0}.Then
SOμ(G)<SOα(G)≤21/α−1/μSOμ(G)if μ>α,αμ>0,21/α−1/μSOμ(G)≤SOα(G)<SOμ(G)if μ<α,αμ>0,SOα(G)≤21/α−1/μSOμ(G)if α<0,μ>0, |
and the second, third or fifth equality is attained for each α,μ if and only if all the connected components of G are regular graphs.
Recall that one of the most studied topological indices is the first Zagreb index, defined by
M1(G)=∑u∈V(G)d2u. |
If we take μ=1 in Corollary 4, we obtain the following result.
Corollary 5. Let G be any graph and α∈R∖{0}.Then
M1(G)<SOα(G)≤21/α−1M1(G)if 0<α<1,21/α−1M1(G)≤SOα(G)<M1(G)if α>1,SOα(G)≤21/α−1M1(G)if α<0, |
and the second, third or fifth equality is attained for each α if and only if all the connected components of G are regular graphs.
If we take α=2, β=−1/2 and λ=1/2 in Theorem 1, we obtain the following inequality relating the modified Sombor and the first Banhatti-Sombor indices.
Corollary 6. Let G be any graph.Then
mSO(G)≤12BSO(G) |
and the bound is tight if and only if all the connected components of G are regular graphs
In [19,20,21], the first variable Zagreb index is defined by
Mα1(G)=∑u∈V(G)dαu, |
with α∈R.
Note that Mα1 generalizes numerous degree–based topological indices which earlier have independently been studied. For α=2, α=3, α=−1/2, and α=−1, Mα1 is, respectively, the ordinary first Zagreb index M1, the forgotten index F, the zeroth–order Randić index 0R, and the inverse index ID [2,22].
The next result relates the KAα,β and Mα+11 indices.
Theorem 7. Let G be any graph with maximum degree Δ, minimum degree δ and m edges, and α∈R∖{0}, β>0.Then
KAα,β(G)≥(Mα+11(G)+2Δα/2δα/2m√2(Δα/2+δα/2))2βif 0<β<1/2,KAα,β(G)≥(Mα+11(G)+2Δα/2δα/2m√2(Δα/2+δα/2))2βm1−2βif β≥1/2, |
and the second equality is attained for some α,β if and only if G is a regular graph.
Proof. If uv∈E(G) and α>0, then
√2δα/2≤√dαu+dαv≤√2Δα/2. |
If α<0, then the converse inequalities hold. Hence,
(√dαu+dαv−√2δα/2)(√2Δα/2−√dαu+dαv)≥0,√2(Δα/2+δα/2)√dαu+dαv≥dαu+dαv+2Δα/2δα/2. |
Since
∑uv∈E(G)(dαu+dαv)=∑u∈V(G)dudαu=∑u∈V(G)dα+1u=Mα+11(G), |
If 0<β<1/2, then 1/(2β)>1 and
∑uv∈E(G)√dαu+dαv=∑uv∈E(G)((dαu+dαv)β)1/(2β)≤(∑uv∈E(G)(dαu+dαv)β)1/(2β)=KAα,β(G)1/(2β). |
Consequently, we obtain
KAα,β(G)1/(2β)≥Mα+11(G)+2Δα/2δα/2m√2(Δα/2+δα/2). |
If β≥1/2, then 2β≥1 and Hölder inequality gives
∑uv∈E(G)√dαu+dαv=∑uv∈E(G)((dαu+dαv)β)1/(2β)≤(∑uv∈E(G)(dαu+dαv)β)1/(2β)(∑uv∈E(G)12β/(2β−1))(2β−1)/(2β)=m(2β−1)/(2β)KAα,β(G)1/(2β). |
Consequently, we obtain
KAα,β(G)1/(2β)≥Mα+11(G)+2Δα/2δα/2m√2(Δα/2+δα/2)m(1−2β)/(2β). |
If G is regular, then
(Mα+11(G)+2Δα/2δα/2m√2(Δα/2+δα/2))2βm1−2β=(2Δαm+2Δαm√22Δα/2)2βm1−2β=(√2Δα/2m)2βm1−2β=(2Δα)βm=KAα,β(G). |
If the second equality is attained for some α,β, then we have dαu+dαv=2δα or dαu+dαv=2Δα for each uv∈E(G). Also, the equality in Hölder inequality gives that there exists a constant c such that dαu+dαv=c for every uv∈E(G). Hence, we have either dαu+dαv=2δα for each edge uv or dαu+dαv=2Δα for each edge uv, and hence, G is regular.
If we take α=2 and β=1/2 in Theorem 7 we obtain:
Corollary 8. Let G be any graph with maximum degree Δ and minimum degree δ, and m edges.Then
SO(G)≥F(G)+2Δδm√2(Δ+δ), |
and the bound is tight if and only if G is regular.
In order to prove Theorem 10 below we need an additional technical result. A converse of Hölder inequality appears in [23,Theorem 3], which, in the discrete case, can be stated as follows [23,Corollay 2].
Proposition 9. Consider constants 0<α≤β and 1<p,q<∞ with 1/p+1/q=1.If wk,zk≥0 satisfy αzqk≤wpk≤βzqk for 1≤k≤n, then
(n∑k=1wpk)1/p(n∑k=1zqk)1/q≤Cp(α,β)n∑k=1wkzk, |
where
Cp(α,β)={1p(αβ)1/(2q)+1q(βα)1/(2p),when 1<p<2,1p(βα)1/(2q)+1q(αβ)1/(2p),when p≥2. |
If (w1,…,wn)≠0, then the bound is tight if and only if wpk=αzqkfor each 1≤k≤n and α=β.
Recall that a bipartite graph with X and Y partitions is called (a,b)-biregular if all vertices of X have degree a and all vertices of Y have degree b.
The next result relates several KA indices.
Theorem 10. Let G be any graph, α,β,μ∈R and p>1.Then
DppKAα,p(β−μ)(G)KAα,pμ/(p−1)(G)p−1≤KAα,β(G)p≤KAα,p(β−μ)(G)KAα,pμ/(p−1)(G)p−1 |
where
Dp={Cp((2δα)p(β−μpp−1),(2Δα)p(β−μpp−1))−1,if α(β−μpp−1)≥0,Cp((2Δα)p(β−μpp−1),(2δα)p(β−μpp−1))−1,if α(β−μpp−1)<0, |
and Cp is the constant in Proposition 9. The equality in the upper(lower) bound is tight for each α,β,μ,p if G is a biregular graph (with α(β−μpp−1)≠0 if and only if G is a regular graph.)
Proof. Hölder inequality gives
KAα,β(G)=∑uv∈E(G)(dαu+dαv)β−μ(dαu+dαv)μ≤(∑uv∈E(G)(dαu+dαv)p(β−μ))1/p(∑uv∈E(G)(dαu+dαv)pμ/(p−1))(p−1)/p,KAα,β(G)p≤KAα,p(β−μ)(G)KAα,pμ/(p−1)(G)p−1. |
If G is a biregular graph with m edges, we obtain
KAα,p(β−μ)(G)KAα,pμ/(p−1)(G)p−1=(Δα+δα)p(β−μ)m((Δα+δα)pμ/(p−1)m)p−1=(Δα+δα)p(β−μ)(Δα+δα)pμmp=((Δα+δα)βm)p=KAα,β(G)p. |
Since
(dαu+dαv)p(β−μ)(dαu+dαv)pμ/(p−1)=(dαu+dαv)p(β−μpp−1), |
if αp(β−μpp−1)≥0, then
(2δα)p(β−μpp−1)≤(dαu+dαv)p(β−μ)(dαu+dαv)pμ/(p−1)≤(2Δα)p(β−μpp−1), |
and if αp(β−μpp−1)<0, then
(2Δα)p(β−μpp−1)≤(dαu+dαv)p(β−μ)(dαu+dαv)pμ/(p−1)≤(2δα)p(β−μpp−1). |
Proposition 9 gives
KAα,β(G)=∑uv∈E(G)(dαu+dαv)β−μ(dαu+dαv)μ≥Dp(∑uv∈E(G)(dαu+dαv)p(β−μ))1/p(∑uv∈E(G)(dαu+dαv)pμ/(p−1))(p−1)/p,KAα,β(G)p≥DppKAα,p(β−μ)(G)KAα,pμ/(p−1)(G)p−1. |
Proposition 9 gives that the equality is tight in this last bound for some α,β,μ,p with α(β−μpp−1)≠0 if and only if
(2δα)p(β−μpp−1)=(2Δα)p(β−μpp−1)⇔δ=Δ, |
i.e., G is regular.
If we take β=0 in Theorem 10 we obtain the following result.
Corollary 11. Let G be any graph with m edges, α,μ∈R and p>1.Then
KAα,−pμ(G)KAα,pμ/(p−1)(G)p−1≥mp. |
The equality in the bound is tight for each α,μ,p if G is a biregular graph.
If we take α=2, β=0, p=2 and μ=1/4 in Theorem 10 we obtain the following result.
Corollary 12. Let G be any graph with maximum degree Δ, minimum degree δ and m edges, then
m2≤mSO(G)SO(G)≤(Δ+δ)24Δδm2. |
The equality in the upper bound is tight if and only if G is regular.The equality in the lower bound is tight if G is a biregular graph.
Note that the following result improves the upper bound in Corollary 5 when α>1.
Theorem 13. Let G be any graph with minimum degree δ, and α≥1.Then
21/α−1M1(G)≤SOα(G)≤M1(G)−(2−21/α)δ, |
and the equality holds for some α>1 in each bound if and only if G is regular.
Proof. The lower bound follows from Corollary 5. Let us prove the upper bound.
First of all, we are going to prove that
(xα+yα)1/α≤x+(21/α−1)y | (2.1) |
for every α≥1 and x≥y≥0. Since (2.1) is direct for α=1, it suffices to consider the case α>1.
We want to compute the minimum value of the function
f(x,y)=x+(21/α−1)y |
with the restrictions g(x,y)=xα+yα=1, x≥y≥0. If (x,y) is a critical point, then there exists λ∈R such that
1=λαxα−1,21/α−1=λαyα−1, |
and so, (y/x)α−1=21/α−1 and y=(21/α−1)1/(α−1)x; this fact and the equality xα+yα=1 imply
(1+(21/α−1)α/(α−1))xα=1,x=(1+(21/α−1)α/(α−1))−1/α,y=(21/α−1)1/(α−1)(1+(21/α−1)α/(α−1))−1/α,f(x,y)=(1+(21/α−1)α/(α−1))−1/α+(21/α−1)(21/α−1)1/(α−1)(1+(21/α−1)α/(α−1))−1/α=(1+(21/α−1)α/(α−1))−1/α+(21/α−1)α/(α−1)(1+(21/α−1)α/(α−1))−1/α=(1+(21/α−1)α/(α−1))(α−1)/α>1. |
If y=0, then x=1 and f(x,y)=1.
If y=x, then x=2−1/α=y and
f(x,y)=2−1/α+(21/α−1)2−1/α=1. |
Hence, f(x,y)≥1 and the bound is tight if and only if y=0 or y=x. By homogeneity, we have f(x,y)≥1 for every x≥y≥0 and the bound is tight if and only if y=0 or y=x. This finishes the proof of (2.1).
Consequently,
(dαu+dαv)1/α≤du+(21/α−1)dv=du+dv−(2−21/α)dv |
for each α≥1 and du≥dv. Thus,
(dαu+dαv)1/α≤du+dv−(2−21/α)δ |
for each α≥1 and uv∈E(G), and the equality holds for some α>1 if and only if du=dv=δ. Therefore,
SOα(G)≤M1(G)−(2−21/α)δ, |
and the equality holds for some α>1 if and only if du=dv=δ for every uv∈E(G), i.e., G is regular.
Corollary 14. Let G be any graph with minimum degree δ.Then
2−1/2M1(G)≤SO(G)≤M1(G)−(2−√2)δ, |
and the equality holds in each bound if and only if G is regular.
The upper bound in Corollary 14 appears in [14,Theorem 7]. Hence, Theorem 13 generalizes [14,Theorem 7].
A family of topological indices, named Adriatic indices, was put forward in [24,25]. Twenty of them were selected as significant predictors in Mathematical Chemistry. One of them, the inverse sum indeg index, ISI, was singled out in [25] as a significant predictor of total surface area of octane isomers. This index is defined as
ISI(G)=∑uv∈E(G)dudvdu+dv=∑uv∈E(G)11du+1dv. |
In the last years there has been an increasing interest in the mathematical properties of this index. We finish this section with two inequalities relating the Sombor, the first Zagreb and the inverse sum indeg indices.
Theorem 15. Let G be any graph, then
√2(M1(G)−2ISI(G))≥SO(G)>M1(G)−2ISI(G) |
and the upper bound is tight if and only if all the connected components of G are regular graphs.
Proof. It is well-known that for x,y>0, we have
x2+y2<(x+y)2≤2(x2+y2),√x2+y2<x+y≤√2√x2+y2, |
and the equality
√d2u+d2v√d2u+d2v+2dudv=(du+dv)2 |
give
(du+dv)√d2u+d2v+2dudv>(du+dv)2,√d2u+d2v+2dudvdu+dv>du+dv,SO(G)+2ISI(G)>M1(G). |
In a similar way, we obtain
1√2(du+dv)√d2u+d2v+2dudv≤(du+dv)2,√d2u+d2v+√22dudvdu+dv≤√2(du+dv),SO(G)+2√2ISI(G)≤√2M1(G). |
The equality in this last inequality is tight if and only if 2(d2u+d2v)=(du+dv)2 for each edge uv, i.e., du=dv for every uv∈E(G), and this happens if and only if all the connected components of G are regular graphs.
We start this section with a technical result.
Proposition 16. Let G be any graph, u,v∈V(G) with uv∉E(G), and α,β∈R∖{0} with αβ>0.Then KAα,β(G∪{uv})>KAα,β(G).If α>0, then redKAα,β(G∪{uv})>redKAα,β(G).Furthermore, if α<0 and G does not have pendant vertices, then redKAα,β(G∪{uv})>redKAα,β(G).
Proof. Let {w1,…,wdu} and {w1,…,wdv} be the sets of neighbors of u and v in G, respectively. Since αβ>0, the function
U(x,y)=(xα+yα)β |
is strictly increasing in each variable if x,y>0. Hence,
KAα,β(G∪{uv})−KAα,β(G)=((du+1)α+(dv+1)α)β++du∑j=1(((du+1)α+dαwj)β−(dαu+dαwj)β)+dv∑k=1(((dv+1)α+dαwk)β−(dαv+dαwk)β)>((du+1)α+(dv+1)α)β>0. |
The same argument gives the results for the redKAα,β index.
Given an integer number n≥2, let Γ(n) (respectively, Γc(n)) be the set of graphs (respectively, connected graphs) with n vertices.
We study in this section the extremal graphs for the KAα,β index on Γc(n) and Γ(n).
Theorem 17. Consider α,β∈R∖{0} with αβ>0, and an integer n≥2.
(1) The complete graph Kn is the unique graph that maximizes KAα,β on Γc(n) or Γ(n).
(2) Any graph that minimizes KAα,β on Γc(n) is a path.
(3) If n is even, then the union of n/2 paths P2 is the unique graph that minimizes KAα,β on Γ(n).If n is odd, then the union of (n−3)/2 paths P2 with a path P3 isthe unique graph that minimizes KAα,β on Γ(n).
(4) Furthermore, if α,β>0, then the three previous statements hold if we replace KAα,β with redKAα,β.
Proof. Let G be a graph with order n, minimum degree δ and m edges.
Items (1) and (2) follow directly from Proposition 16.
(3) Assume that n is even. It is well known that the sum of the degrees of a graph is equal to twice the number of edges of the graph (handshaking lemma). Thus, 2m≥nδ≥n. Since αβ>0, the function
U(x,y)=(xα+yα)β |
is strictly increasing in each variable if x,y>0. Hence, for any graph G∈Γ(n), we have
KAα,β(G)=∑uv∈E(G)(dαu+dαv)β≥∑uv∈E(G)(1α+1α)β=2βm≥2βn2=2β−1n, |
and the equality is tight in the inequality if and only if du=1 for all u∈V(G), i.e., G is the union of n/2 path graphs P2.
Finally, assume that n is odd. Fix a graph G∈Γ(n). If du=1 for every u∈V(G), then handshaking lemma gives 2m=n, a contradiction (recall that n is odd). Therefore, there exists a vertex w with dw≥2. By handshaking lemma we have 2m≥(n−1)δ+2≥n+1. Recall that the set of neighbors of the vertex w is denoted by N(w). Since U(x,y) is a strictly increasing function in each variable, we obtain
KAα,β(G)=∑u∈N(w)(dαu+dαw)β+∑uv∈E(G),u,v≠w(dαu+dαv)β≥∑u∈N(w)(1α+2α)β+∑uv∈E(G),u,v≠w(1α+1α)β≥2(1+2α)β+2β(m−2)≥2(1+2α)β+2β(n+12−2)=2(1+2α)β+2βn−32, |
and the bound is tight if and only if du=1 for all u∈V(G)∖{w}, and dw=2. Hence, G is the union of (n−3)/2 path graphs P2 and a path graph P3.
(4) If α,β>0, then the same argument gives the results for the redKAα,β index.
We deal now with the optimization problem for redKAα,β when α,β<0.
Given an integer number n≥3, we denote by Γwp(n) (respectively, Γwpc(n)) the set of graphs (respectively, connected graphs) with n vertices and without pendant vertices.
Theorem 18. Consider α,β<0, and an integer n≥3.
(1) The cycle graph Cn is the unique graph that minimizes redKAα,β on Γwpc(n).
(2) The union of cycle graphs are the only graphs that minimize redKAα,β on Γwp(n).
(3) The complete graph Kn is the unique graph that maximizes redKAα,β on Γwpc(n) or Γwp(n).
Proof. Let G be a graph with order n, minimum degree δ and m edges. Since a graph without pendant vertices satisfies δ≥2, handshaking lemma gives 2m≥nδ≥2n. Since α,β<0, the function
U(x,y)=(xα+yα)β |
is strictly increasing in each variable if x,y>0. Hence, for any graph G∈Γwp(n), we have
KAα,β(G)=∑uv∈E(G)(dαu+dαv)β≥∑uv∈E(G)(2α+2α)β=2(α+1)βm≥2(α+1)βn, |
and the inequality is tight if and only if du=2 for all u∈V(G), i.e., the graph G is the union of cycle graphs. If G is connected, then it is the cycle graph Cn.
Item (3) follows from Proposition 16.
In this paper, we contributed to the study of inequalities and optimization problems associated with topological indices. In particular, we obtained new lower and upper optimal bounds of general Sombor indices, and we characterized the graphs where equality occurs.
Specifically, we have obtained inequalities for these indices relating them with other indices: the first Zagreb index, the forgotten index and the first variable Zagreb index. Finally, we solve some extremal problems for general Sombor indices
We would like to thank the reviewers by their careful reading of the manuscript and their suggestions which have improved the presentation of this work. The research of José M. Rodríguez and José M. Sigarreta was supported by a grant from Agencia Estatal de Investigación (PID2019-106433GB- ´ I00/AEI/10.13039/501100011033), Spain. The research of Jose M. Rodríguez is supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M23), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).
All authors declare no conflicts of interest in this paper.
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