2320213106896
Five results on maximizing topological indices in graphs
Abstract
In this paper, we prove a collection of results on graphical indices. We determine the extremal graphs attaining the maximal generalized Wiener index (e.g. the hyper-Wiener index) among all graphs with given matching number or independence number. This generalizes some work of Dankelmann, as well as some work of Chung. We also show alternative proofs for two recent results on maximizing the Wiener index and external Wiener index by deriving it from earlier results. We end with proving two conjectures. We prove that the maximum for the difference of the Wiener index and the eccentricity is attained by the path if the order is at least and that the maximum weighted Szeged index of graphs of given order is attained by the balanced complete bipartite graphs.
keywords:
topological indices, average distance, Wiener index, eccentricity, Szeged index, extremal graphs1 Introduction
Let be a simple connected graph, as we only work with connected graphs in this paper. We denote its vertex set by and its edge set by The independence number of a graph , denoted by , is the size of the largest independent vertex set. The matching number of a graph is the size of a maximum independent edge subset of , we will denote it by or . We will denote by the set of all trees with vertices and matching number . A path is a path of order .
Let denote the distance between vertices and in a graph . The diameter of a graph equals The eccentricity of a vertex , equals The eccentricity of a graph is the sum of the eccentricities over all vertices, i.e.
The degree of the vertex will be denoted . For an edge , will be equal to the number of vertices for which . The Wiener index of a graph equals the sum of distances between all unordered pairs of vertices, i.e.
The mean distance of the graph equals Some general form of mean distance can be derived from the notion of power means.
Definition 1.1
The power mean of positive real numbers is
When , .
Furthermore .
Other graphical indices used in this paper, are the hyper-Wiener index, the external Wiener index, terminal Wiener index, Szeged index and weighted Szeged index. They are defined respectively as
In Section 2 we give an alternative proof for a theorem of Dankelmann Dankelmann (1994) on the maximum Wiener index of a connected graph with given order and matching number. We prove this for a notion of generalized Wiener index , implying the result for e.g. the hyper-Wienerindex. Due to a relation between order, matching number and independence number, we also observe a power mean version of a result of Chung Chung (1988). We present alternative, short proofs for the main results of Dimitrov et al. (2019) and Jiang and Li (2019) based on results known before in Sections 3 and 4 respectively. Also we give a proof for Conjecture in Darabi et al. (2021) in Section 5 and for Conjecture in Bok et al. (2019) in Section 6.
2 Maximum generalized Wiener index given or
Theorems , and in the survey of Xu et al. (2014) give the extremal graphs attaining the minimum hyper-Wiener index among all graphs with given order and matching number, for the family of graphs being the connected graphs, the trees and the unicyclic graphs respectively. Some general version was proven in Chen et al. (2017) as the result holds for a more general class of indices represented by In this section we will prove the analog for the maximum. The general statement works for a different class of distance-based indices.
Definition 2.1
The generalized Wiener indices are of the form
where is a convex function satisfying which is strictly increasing on .
Note that when we take or , we get the Wiener index or the hyper-Wiener index, respectively. The condition that is just a handy convention, as is just shifted with if one shifts with a constant The additional constraint that is convex (when comparing with the result in Chen et al. (2017)) is added to have the same extremal graph for the whole class of indices.
Let be a path with vertices, with one leaf of the path connected to different vertices and the other leaf with pendent vertices, i.e. it is a balanced double broom with leaves when and if , it is a path.
For any generalized Wiener index , we will prove that is the unique extremal graph attaining the maximum value of among all graphs having order and matching number . This was known already for the Wiener index by Dankelmann Dankelmann (1994).
We will use a kind of tree rearrangements, which we call subtree pruning and regrafting (SPR). It was defined in Cambie (2019), but for completeness we give the definition here again.
Definition 2.2 (SPR)
Let be a graph. Given a rooted subtree of , such that the root Pruning from is removing the whole structure excluding the root . Regrafting at a vertex , means that we are taking a copy of which we insert at , letting its root coincide with . No additional edges are drawn in this process.
We know that extremal graphs are trees, since deleting an edge which is not part of a maximum matching will increase the generalized Wiener index as at least one distance strictly increases.
We will use the notation . For , the extremal graphs are stars. So from now onwards, we assume , which implies that the diameter of the extremal graph (being a tree) is at least .
The first proposition we need for the proof is the following.
Proposition 2.3
For fixed , when and the sets and are both nonempty, then .
Proof 2.1.
Assume this proposition is not true. In that case there exist some and such that and are both nonempty and For some fixed , we take the least integer for which holds and take an extremal graph with .
Since is a tree which is not a path (as a path reaches the largest possible matching number), we can choose a leaf and a vertex of degree at least such that is the smallest among all such choices. Considering as a rooted tree in , there are at least three branches, the path from to being one of them. Let be a branch different from and be the union of the remaining branches different from and . Here we do not consider as a vertex of nor of . We can prune the subtree (with root ) and regraft it at . After this operation, the set of distances between and or is the same as before, while the distance between any vertex of and any vertex of has increased with . Since is a strictly increasing function, this implies that has strictly increased by performing the SPR operation, while the matching number has not increased with more than one. This implies that for every was not true. This contradiction implies that the proposition is true.
Let be an extremal graph and and be two vertices such that the distance between them equals the diameter and the path between them equals . If is the path , we are in a trivial case since itself is of the form . In the other case, there are some subtrees attached to the path . The following proposition gives more information about them.
Proposition 1.
There are no vertices of different from and having degree at least .
Proof 2.2.
If the proposition is not true, there is an extremal graph with a subtree connected to some with Let and be the graphs by pruning and regrafting at resp. . Let be the graph i.e. the graph when is pruned Note that every neighbour of a leaf will be in a maximum matching. In particular, without loss of generality, we can assume and are edges in a maximum matching of or . This implies that the matching number of both and is exactly equal to while the matching number of , , is at least equal to (and plausible one larger). So the matching number of both and is not larger than the matching number of Let be the copy of which is connected to and be the copy of which is connected to We will prove that
(1) |
For every (here we take in as the vertex corresponding to the original and similarly in ) we have since Since is convex and strictly increasing, From this and the fact that it is strict for , Equation (1) follows. Hence at least one of the two graphs or has a larger generalized Wiener index than and so taking into account Proposition 2.3 we conclude was not extremal.
Theorem 2.4
Let be a graph of order with matching number When is a strictly increasing, convex function, then with equality if and only if .
Proof 2.3.
As a consequence of Proposition 1, the extremal graph is a path with pendent vertices to and pendent vertices to , where . The maximum of the generalized Wiener index for such a graph with matching number equals clearly needs a diameter being equal to if and is the path if Since
with strictly increasing, i.e. , the maximum occurs when as we are considering the nontrivial case with (as ) and being fixed.
As an immediate corollary, we determine the extremal graphs attaining the maximum generalized Wiener index among all graphs having order and independence number for some regime.
Theorem 2.5
If is a connected graph with independence number , then , with equality if and only if
Proof 2.4.
Note that for any graph, the sum , since given an independent set and a matching , any edge of contains at least one vertex which is not in This implies that Applying Proposition 2.3 (recall extremal graphs with respect to are trees) and Theorem 2.4, we have that . Since the graph has independence number , it is the unique extremal graph.
In the case , the proof of Dankelmann Dankelmann (1994) can be extended to , as well. In that case the extremal graph being the balanced dumbbell graph of diameter This is the graph obtained when connecting two vertices from two cliques of almost equal order and by a path of length .
Theorem 2.6
If is a connected graph with independence number , then , with equality if and only if
As corollaries, we get power mean versions of the result of Chung Chung (1988), which states that the average distance is bounded by the independence number.
Theorem 2.7
Let be the power mean of the distances . Then for and any connected graph , one has
Proof 2.5.
The function is a convex function on when . Note that for this , we have So from the previous two theorems, we know the maximum is attained when equals or Note that for every , there are more pairs of vertices with then pairs with in the extremal graph. Combining with (true by the inequality of Jensen), we conclude.
By the observation that when , we also have the following corollary. Note that for , it is exactly the original result of Chung.
Corollary 2.
For every and graph , we have Equality holds if and only if .
3 Maximum external Wiener index of graphs
In this section, we give a short alternative proof for the main result in Dimitrov et al. (2019), which proves Conjecture in Gutman et al. (2016). We show that the conjecture is basically a corollary of a theorem in Gutman et al. (2009).
Remark that if is a spanning tree of a graph , then since and .
Note that for any two vertices and in a tree, there are two leaves such that the path between them goes through and . This implies that adding an edge between two non-neighbours of any tree will strictly decrease the external Wiener index as at least one term got smaller (or even vanishes). As a consequence, any extremal graph is a tree.
Hence the result will follow from the following lemma, as we know the extremal graphs are trees.
Lemma 3.
Let be a tree of order with leaves. Then
Proof 3.1.
Let be the sets of nonleafs, which has size Note that for every leaf , is a connected graph and hence
Equality holds if and only if is a path and is connected to an endvertex of . The second part is Theorem 4 of Gutman et al. (2009), with the addition that it is also true for
Theorem 3.1
The graphs on vertices with the maximum external Wiener index are balanced double brooms.
Proof 3.2.
Assume is the extremal graph and it has leaves. Note that
is bounded by
due to Lemma 3. Equality in the first part holds if and only if is a double broom. A double broom for which equality holds in the second equality need to be balanced and balanced double brooms attain equality. The maximum among all graphs is now attained by the double brooms having leaves, where is an integer maximizing the expression.
4 Maximum Wiener index of unicyclic graphs with given bipartition
In this section, we show that the answer to Problem in Knor et al. (2016) is mainly a corollary of the proof of Problem in the same survey, which was adressed in Cambie (2019). The problem, being the unsolved part in Du , was recently solved in Jiang and Li (2019) and Bok et al. (2019). Nevertheless, one can observe that the proof by deducing it from earlier work is much shorter.
We start with proving a lemma dealing with the case that the cycle is not minimal.
Lemma 4.
Among all unicyclic graphs of order containing an even cycle , the Wiener index is maximized by the graph formed by attaching a path of order to a vertex of a .
Proof 4.1.
We can prove this by induction, the case being the trivial base case as is the only unicyclic graph on vertices containing a Assume the lemma is true for . Any unicyclic graph of order containing a has at least one leaf . Let . Note that the distance from to the is at most and the diameter of is at most . At least consecutive distances between and vertices of appear twice, these are at most up to . Thus and together with the induction hypothesis on , we get the result.
Using the notation as has been done in Cambie (2019) (Figure ), the theorem is stated below.
Theorem 4.1
The maximum Wiener index among all -vertex unicyclic graphs with bipartition sizes () is attained by exactly one graph,
Proof 4.2.
Note that a graph having bipartition of sizes has a matching number which is at most . If , the result is a consequence of Theorem 7.1 and Proposition 2.1 from Cambie (2019) applied on and . If , we have to take the maximum over all possible graphs containing an even cycle.
The maximum for the graphs in Lemma 4 is attained when . There are multiple ways to see this. Let be with a path attached to it. Let be a neighbour of the vertex with degree , or a random vertex of if Then
Equality holds if and only if
If , we know the extremal graph containing a with and is by Section in Cambie (2019). Furthermore if .
The graph has a larger Wiener index than the extremal graphs in Lemma 4 for , from which we conclude again. For this it is enough to note that for all , we have
as adding the path of order to both structures only makes the difference larger.
5 Maximum difference of Wiener Index and Eccentricity
In this section, we prove Conjecture in Darabi et al. (2021).
Theorem 5.1
For , among all graphs with order , is maximized by Moreover, is the unique extremal graph.
To start with, we prove that we can focus on trees as deleting an edge does not decrease the quantity , where denotes .
Lemma 5.
Let be a graph with order and radius at least . Let be an edge such that is connected. Then
Proof 5.1.
Let and assume Suppose the shortest cycle in containing is . Note that distances do not decrease when deleting edges, so we have to focus on the eccentricities that increase. Let be a vertex not belonging to for which the eccentricity increases when deleting . Without loss of generality we can assume . Let for a vertex (where possible ). Then we know that , so the shortest path from to in uses the edge and so This also implies that Combining these observations with the definition of eccentricity and the triangle inequality, we get that
As the difference in eccentricity for is cancelled by the difference of distance between and , while was taken arbitrary, implies that
(2) |
which is only the case if and then the difference is exactly equal to .
Case: To have a contradiction, both and need to increase when deleting . This implies there is a vertex such that . Let be the neighbour of on a shortest path in from to Then So if , we have an additional difference that (in the expansion of ) is at least , leading to a contradiction. If , there is an other vertex not belonging to the such that and we conclude again.
Case: In this case, let be the neighbour from in the different from . When doing the check in the reduced case that , we take into account that the eccentricity of goes up by in . So is only possible if But since , there is a vertex not belonging to the for which As we did not take this difference into account before when looking to , we conclude that again.
Having proven this lemma, it is essentially enough to prove it for trees, once checking the result for graphs with radius at least For this a bit of work is needed (as one can expect due to the behaviour of the extremal graphs for ).
Proof 5.2 (Proof of Theorem 5.1).
First, one can check that is smaller than when in case has radius at most . For , a brute force check confirms. For , if the diameter is at most , then and and we are done. If the diameter is , we have and , so The cases work similarly. For , note that the diameter of is bounded by and so
So from now on, we only have to consider graphs with radius at least and hence by Lemma 5 we can first focus on trees. A bruteforce check by computer over all trees of order verifies the theorem for these values. For , we first observe that the diameter of an extremal graph is at least , since otherwise Now we can prove the statement by induction. If the diameter equals , we have the path . If the diameter is smaller, , one can remove a leaf which is not part of the diameter. Now the eccentricities of all vertices different from are the same in and . By the induction hypothesis, we have Furthermore we have
from which we conclude. This implies that is the unique tree maximizing By Lemma 5 no graph with a spanning tree which is not a path can be extremal (note that the radius does not decrease when removing edges). Since the cycle (and the path itself) is the only graph which has only a spanning graph, but for , as concluded from the computation in Equation 2, the path is the unique extremal graph.
Additionally, we add two remarks on the work in Darabi et al. (2021) about the minimum for In their Theorem , the authors prove that the minimum for among trees is attained by caterpillars. More precisely, the extremal tree is when and if , the extremal tree is attained for the star with one edge subdivided. This is mainly a corollary of the following lemma, as it implies that we only have to compare a few possible trees.
Lemma 6.
Among all trees with fixed diameter and order , the minimum of occurs if and only if we have a path of diameter with the remaining vertices connected to the same vertex on the path, which is a central vertex if is odd, or a central vertex or neighbour of it, if is even.
Proof 5.3.
Let be the set of vertices different from the ones on the diameter . Then with equality if and only if they are all connected to the same vertex on the diameter. We note that for every , is minimal if is connected to a central vertex and equality is also possible if it is connected to a neighbouring vertex of a central vertex when is odd as then there is only one central vertex. Here we use that where is the neighbour of and .
We now also determine this minimum among all graphs.
Proposition 7.
For every graph of order , we have
Proof 5.4.
For every vertex , one has , since all distances are at least equal to one, there is a vertex with and an other one with . Summing over all vertices , we conclude that Dividing by and observing that is always an integer, we conclude.
The minimum of is attained by the complement of
For , this is the exact characterization of the extremal graphs. The graph for and the one sketched in Figure 4 for are also extremal.
6 Maximum weighted Szeged index
In this section, we prove the following open conjecture, posed in Bok et al. (2019).
Conjecture 8 (Conjecture 1 in Bok et al. (2019)).
For any -vertex graph , the weighted Szeged index of , , is upper-bounded by and equality is only attained by the balanced complete bipartite graph , or if
First, we make the following crucial observation.
Lemma 9.
For any edge , we have
Proof 6.1.
Since , this is trivial when . If , then and have at least neighbours in common, which satisfy and hence do not belong to nor Hence which is equivalent with
Let the degrees of the vertices of the graph be . For an edge whose end vertices have degree and , let be the average degree of the two endvertices.
Then by double counting, we find the following two equalities (the first one being the hand shaking lemma)
Lemma 10.
We have
Next, we prove two propositions which are the main ingredients for the proof.
Proposition 11.
For every edge , we have
Proof 6.2.
Combining (by AM-GM) and Lemma 9, we have
Now we have if is even or when is odd and (as is integral).
When , then Lemma 9 gives and hence and the conclusion holds again.
Proposition 12.
For any graph , we have
Proof 6.3.
Using Lemma 10, we get
Proof 6.4 (Proof of Conjecture 8).
Combining Proposition 11 and Proposition 12, we find that the weighted Szeged index of the graph satisfies
If is even, equality holds if and only there is equality in every step. In particular for all and thus for every edge , which also implies that the graph should be triangle-free as well since for every edge But then and are connected with disjoint independent sets of order and since the degree of every vertex is exactly , we conclude .
If , we see that and these two graphs are the only extremal ones.
If is odd, equality holds if and only if . Note that all need to be equal to or to have equality in Proposition 12. Note that we also need equality in Lemma 9 for every edge to have equality in Proposition 11. So it is impossible that and if , we have a triangle with three vertices which all need to have degree and do not create other triangles, which is impossible. Hence the conclusion follows as for every edge, i.e. the end vertices of any edge have degree and
Acknowledgements.
The author is very grateful to the anonymous referees for the time they dedicated to this article and for the comments they made which improved this manuscript.References
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