1. Introduction
Let
be a simple connected graph. For a vertex
, its neighborhood is defined by
, and the degree of
u is
. The distance between two vertices
u and
v is denoted by
, and the diameter of
G is defined as
The path on
n vertices and the complete bipartite graph are denoted by
and
, respectively. All notations and terminology used in this paper follow the conventions in [
1].
Topological indices are numerical descriptors of graphs and are frequently used to model molecular properties in chemical structures. These indices play a significant role in determining structure–property and structure–activity relationships. Recently, new approaches that aim to limit the influence of high-degree vertices and provide more results have attracted considerable attention [
2]. The Sombor index, a prominent topological index in graph theory, was introduced in [
3] and is defined as
It has attracted considerable attention for its applications in quantitative structure–property and structure–activity relationship (QSPR/QSAR) studies. Liu et al. [
4] reviewed existing bounds and extremal results for the Sombor index and its variants. Movahedi and Akhbari [
5] computed exact formulas for several Sombor-type topological indices of hyaluronic acid–methotrexate conjugates used in cancer treatment. Zhou et al. [
6] characterized trees and unicyclic graphs with minimum Sombor index among graphs with given maximum degree. Movahedi and Akhbari [
7] introduced the entire Sombor index and established various bounds for it. Liu et al. [
8] determined extremal (reduced) Sombor index values for chemical trees and showed that boiling points of benzenoid hydrocarbons are highly correlated with these indices. Movahedi et al. [
9] applied topological indices and data analysis techniques to model physicochemical properties of tetracycline antibiotics. Samiei and Movahedi [
10] investigated graph invariants for predicting properties of chemical structures of antiviral drugs. More recently, a variant known as the diminished Sombor index was first proposed in [
11] and referred to by this name in [
12]. This index is defined as follows
In their study, Movahedi et al. [
12] established various bounds for the diminished Sombor (DSO) index, characterized extremal graphs, and formulated inequalities analogous to those of the Nordhaus–Gaddum type. They also conducted numerical investigations to explore how the DSO index varies with structural features, highlighting its possible applications in chemistry. Furthermore, in [
13], the tricyclic graph of a given order that achieves the maximum DSO value was identified, along with an analysis of its unique structural properties. Subsequently, the conjecture concerning tricyclic graphs minimizing the DSO index was resolved in [
14], where the extremal structures attaining the minimum value were completely characterized. In addition, the work presented in [
15] investigated the relationship between the DSO index and several classical degree-based topological indices, establishing sharp bounds including
, where
is the Albertson index and
, as well as bounds in terms of the maximum degree
, minimum degree
, and the size
m of the graph.
In recent years, significant progress has been made in the study of Sombor-type indices, particularly in determining extremal values for various graph classes. Cruz and Rada [
16] determined extremal values of the Sombor index in unicyclic and bicyclic graphs. Cruz, Gutman and Rada [
17] characterized the extremal graphs with respect to the Sombor index over chemical graphs, chemical trees, and hexagonal systems. Das and Gutman [
18] investigated the Sombor index of trees. Liu [
19] determined extremal values of the Sombor index for unicyclic graphs with a given diameter. Sun and Du [
20] determined the Sombor index of trees with fixed domination number. For trees, extremal results have been extensively developed under structural constraints such as fixed order, diameter, and matching number. In the case of unicyclic and bicyclic graphs, the presence of cycles introduces additional structural complexity, and extremal configurations are typically obtained through degree-based transformations and edge-redistribution techniques. Khanra and Das [
21] determined extremal values of the Euler Sombor index for trees and unicyclic and chemical graphs, and proposed several open problems. Kizilirmak [
22] derived the minimum Euler Sombor index for unicyclic graphs with fixed diameter. Ali et al. [
23] established the best possible bounds for graphical edge-weight-function indices of trees under constraints on matching number, number of pendent vertices and maximum degree, with applications to the Euler Sombor index. Tache et al. [
24] determined extremal unicyclic graphs for the Euler Sombor index.
These approaches have been further extended to more complex graph families. Hu et al. [
25] obtained bounds on the Euler Sombor index of maximal outerplanar graphs. Kizilirmak [
26] determined the extremal values of the Euler Sombor index of tricyclic graphs. Ren et al. [
27] investigated the Euler Sombor index of trees. In addition to the classical Sombor index, several variants have been investigated. Zhang et al. [
28] obtained bounds for the Euler Sombor index of molecular trees and its applications. Albalahi et al. [
29] characterized graphs attaining optimal values of the Euler Sombor index among all molecular tricyclic graphs. Su and Tang [
30] determined maximal and minimal values of the Euler Sombor index for unicyclic and bicyclic graphs. Das and Bera [
31] resolved two open problems on the Euler Sombor index concerning extremal graphs with fixed girth and given number of pendant vertices. Das, Mondal and Pal [
32] determined extremal trees for the Euler Sombor index with given parameters.
Motivated by the growing body of work on extremal Sombor-type indices under structural constraints, it is natural to investigate how global metric parameters, such as the diameter, influence the behavior of these indices. While many existing studies focus on local properties, including degree sequences, matching number, and connectivity, comparatively less attention has been given to the role of distance-based parameters in shaping extremal configurations. Since the diameter imposes a layered structure on the graph and significantly affects vertex interactions, it provides a meaningful framework for analyzing the diminished Sombor index from a different perspective.
Recently, the two-scale fractal dimension has emerged as a powerful tool for characterizing the spatial geometric complexity of molecular and network structures. Unlike classical fractal dimensions, it effectively captures both self-similar and non-self-similar structures, making it widely applicable in structural description [
33,
34].
In chemical applications, the two-scale fractal dimension mainly captures the spatial geometric complexity of molecules. The key difference between the two-scale fractal dimension and the degree-based DSO index is that the former focuses on spatial geometry, while the latter emphasizes vertex degree distribution and local edge contributions. Thus, they are complementary rather than substitutable. To illustrate this distinction, consider the path graph
on four vertices
with edges
. The degrees are
and
, and the DSO index is computed edge by edge as follows:
This value reflects the degree imbalance at terminal versus internal vertices. In contrast, the two-scale fractal dimension of the same linear chain characterizes its self-similar spatial extension along one dimension. Changing the chain length affects the fractal dimension continuously, while the DSO index changes discretely as new edges and degrees are introduced. The two descriptors thus provide complementary structural information, and neither can substitute for the other. The main contributions of this paper are as follows. First, we establish a sharp upper bound for the DSO index over the class
of connected bipartite graphs with fixed order and diameter, and completely characterize all extremal graphs attaining this bound. Second, we prove that the maximum DSO index over
is strictly decreasing as the diameter increases. Third, as a consequence, we determine the connected bipartite graphs of fixed order achieving the three largest DSO values. While extremal problems for degree-based indices under degree-sequence constraints are well studied, the role of diameter as a structural parameter in shaping extremal configurations for normalized Sombor-type indices has not been previously investigated.
2. Characterization of Graphs with Maximal Diminished Sombor Index
For each
, there exists a partition of the vertex set
into subsets
, where
for some fixed vertex
v, and for each
, we define
Each
is called a partition set, and we denote
for
. The vertex partition
induces a layered structure on the graph, where each set
consists of vertices at distance
i from a fixed root vertex. By construction, no edges exist within the same layer, and edges may occur only between consecutive layers. In the extremal case, this structure becomes highly organized: most layers contain a single vertex, while at most two adjacent layers may contain multiple vertices, forming a complete bipartite subgraph. This layered configuration plays a central role in the analysis of the diminished Sombor index. This structure is illustrated in
Figure 1.
Lemma 1 ([
12])
. Let where . Then for , the function is strictly increasing with respect to x and strictly decreasing with respect to y. Moreover, for one has . Lemma 2. Let , where , . Then is strictly increasing with respect to x, and strictly decreasing with respect to y.
Proof. By definition, we have
and from Lemma 1, it follows that
for
,
. Hence,
.
By direct calculation, one may obtain
which shows that
is strictly increasing in
x.
so
is strictly decreasing in
y.
This completes the proof. □
Lemma 3 ([
35])
. For any graph with the above partition of , the induced subgraph is an empty graph (i.e., contains no edge) for each . Lemma 4. Let be a graph with the maximal value. Then induces a complete bipartite subgraph for each , and whenever .
Proof. The first part follows directly from the definition of the diminished Sombor index. Thus, we only need to establish the second part.
Let
, and choose
and
. If
, then
, and the collection
forms a partition of
. It is straightforward to verify that
which is a contradiction.
Therefore, when . This completes the proof of Lemma 4. □
Lemma 5. Let have the maximal value. Then there exist at most two partition sets and such that , and .
Proof. The case is trivial. Now let . If there exists only one partition set, say , in G such that , then there is nothing to prove. To complete the proof, it suffices to show the following: if there exist at least two partition sets of cardinality at least 2, then for each such pair, say and with and , one must have .
Choose
such that it attains the maximal value of the diminished Sombor index. Assume there exist two partition sets
and
such that
,
and
. Choose a vertex
and let
be the graph obtained by deleting all edges incident to
u and joining
u to each vertex in
. Clearly
. To simplify the expression, we set
According to Lemma 1 we get
and
. We suppose
. Since
and
, we obtain
Hence we get
. This contradicts the maximality of
G. This completes the proof of the Lemma. □
Lemma 6. Let where . Then we have
- (i)
,
- (ii)
,
- (iii)
.
Proof. Let
We start from the identity
where
A direct computation gives
Moreover, we have
Hence,
Dividing both sides by
, we obtain
In particular, since
, we have
.
Thus, the desired result is achieved. □
Theorem 1. Let be the graph with the maximal value of the diminished Sombor index, then .
Proof. We analyze the proof by considering the following four cases.
According to Lemma 1,
and
Let
Then
Thus,
implies
. For
, the proof is done.
According to Lemmas 4 and 5,
for
. Suppose on the contrary
and
so that
. Since
and
, we have:
Let
and define
Obviously
.
Step 1: Expansion of . For
we have
, and
Step 2: Bounding the -terms. According to Lemma 6, we now apply this bound to the terms and .
(i) For
, we set
and
. Then
and therefore
(ii) For
, we take
and
. Then
which yields
(iii) For
, we take
and
. Then
and hence
Step 3: Obtaining the lower bound for . Substituting the above estimates into
, we obtain the following lower bound:
Let
. Then inequality (
1) can be rewritten as
Step 4: Verifying . On the other hand, since
the right-hand side of (
2) yields
From inequalities (
1) and (
2), we define the following lower bound:
To combine the terms, we take the common denominator
After a straightforward simplification, we obtain
It remains to verify that . Since it follows that if and only if
Hence, it suffices to show that
for all
and
. We next differentiate
with respect to
bFor
, in particular at
, we obtain
Hence
holds for all
, and therefore
is decreasing with respect to
b on this interval. Thus
, and consequently
. Since (
2) implies that
, we obtain
This yields a contradiction, as
Hence, Case 2 is completed.
Claim 1. For and , we have .
Since
, we have
Moreover, for
and
,
hence
Therefore,
For , we have or . We only consider , as the other case is symmetric.
Assume and let be defined as in the previous cases (with ).
Step 1: Expansion of . By a direct edge-counting argument, we obtain
Using
and
we rewrite
where
Step 2: Bounding , and . Since
with
, we obtain
According to Lemma 6,
and hence
Moreover, from the estimate
we obtain
Step 3: Verifying . Combining the above bounds, we obtain
, where
To eliminate the square root, we further use
which yields
Taking the common denominator
, a straightforward computation gives
where
Since all coefficients of are positive, we have for all . Therefore , and consequently This implies , contradicting the maximality of G.
Step 1: Expansion of . By a direct edge-by-edge comparison, we obtain
Step 2: Bounding the negative terms. According to Lemma 6,
Moreover, applying the mean value theorem to
,
and since
we obtain
Step 3: Obtaining the lower bound . Substituting these bounds into (
3), we obtain
Step 4: Monotonicity of and conclusion. We now show that
is increasing in
b for
. Taking the common denominator
, a straightforward simplification yields
where
is a polynomial in
a and
b whose partial derivative with respect to
b has all positive coefficients. Hence
for
, and therefore
is increasing in
b.
Thus its minimum is attained at
, and we obtain
Now set
. Then
,
, and
. Since
for all
, we have
Therefore
Since
, we obtain
Taking the common denominator
and simplifying, we get
Since all coefficients in the numerator and denominator are positive, the right-hand side is positive for all integers . Consequently , and therefore . This implies , contradicting the maximality of G.
For , we consider the following three subcases:
- (i)
;
- (ii)
;
- (iii)
.
Subcases (i) and (ii) can be treated similarly to Case 3, and we omit the details.
Now we consider subcase (iii). Assume and . Then . Let and let be obtained from G by the same edge transfer operation as before.
Step 1: Expansion of . By an edge-by-edge comparison, we obtain
Step 2: Bounding each term. According to Lemma 6,
and
Moreover, according to Lemma 2,
is increasing in
x and decreasing in
y. Since
and
, we obtain
Also, since
, we have
, and by the mean value theorem,
Finally, using
, we have
Step 3: Obtaining the lower bound . Combining the above estimates, we obtain
where
Since
, we have
, and thus
Step 4: Monotonicity of and conclusion. To complete the proof, it suffices to show that
for all
and
. We claim that
is increasing in
b for
. Indeed, after clearing denominators,
can be written as a rational function whose numerator is a polynomial with positive coefficients on the region
; hence
there. Consequently, for
the minimum of
is attained at
, and thus
Step 5: Verifying . Substituting
gives
Moreover, since
we obtain the convenient lower bound
A direct differentiation yields
so
is increasing on
. Since
it follows that
for all
, and hence
. Consequently
, i.e.,
, contradicting the maximality of
G. Therefore
also holds for
. □
To further illustrate the structural implication of Theorem 1, we present a numerical comparison of the function for different distributions of adjacent partition sizes.
Table 1 presents the values of the function
for different distributions of
a and
b with fixed sums. It can be observed that
increases as the difference
increases. However, this local behavior does not directly determine the extremal structure of the graph.
The diminished Sombor index is obtained as a sum of contributions over all edges, and therefore depends on both the magnitude of and the number of edges between layers. In extremal graphs, balanced partitions maximize the total number of edges between consecutive layers, which compensates for the smaller individual values. As a result, the overall DSO value is maximized when , in agreement with Theorem 1.
Theorem 2. Let be a graph with the maximal diminished Sombor index. Then G is uniquely determined as follows:
- (i)
Case :
, the balanced complete bipartite graph.
- (ii)
Case : , the graph of the form where , that is, the two middle partition sets differ in size by at most one.
- (iii)
Case : , the graph whose distance partition has exactly two consecutive nontrivial layers with sizes as balanced as possible, while all remaining layers consist of a single vertex.
Proof. (i) The case follows from the fact that consists of complete bipartite graphs and the maximum is attained at . For , the extremal graph has the form and, by Theorem 1, , hence .
(ii) For , the statement can be verified by calculations. Now assume .
Case 1. with
. Then
,
and
Since
and according Lemma 2, we obtain
Thus attains the maximum when is even and .
Then . If , then and the statement is trivial. Assume .
Moreover,
and
according to Lemma 2 and
. □
Remark 1. The extremal graphs described in Theorem 2 exhibit a layered structure in which only two adjacent partition sets contain multiple vertices, while all other layers consist of a single vertex. This configuration reflects the balance condition established in Theorem 1 and highlights the role of diameter in shaping the global structure of graphs maximizing the diminished Sombor index.
3. Ordering the Extremal Maximum Graphs in with Respect to Their Diameters
Let
By Theorem 2,
is the maximal diminished Sombor index among all graphs in
.
Theorem 3. Let . For fixed n, the function is strictly decreasing in d.
Proof. We divide the proof into two claims.
Proof (Proof of Claim 2). We distinguish two cases according to the parity of .
Then
and
Hence
Since
with equality if and only if
, we have
,
and
Therefore,
and
.
Then
and
Thus
Since
, we obtain
Also, for
(with
and
),
and
. Writing
and using
for
, we get
Hence
Since
for
, it follows that
Consequently,
and thus
also in this case.
This completes the proof of Claim 2. □
Proof (Proof of Claim 3). Assume first that
is even, where
. Using the extremal structures for
, we obtain
Hence we have
Thus holds when n is even. The case when n is odd can be treated analogously. This completes the proof of Claim 3. □
According to Claims 2 and 3, is strictly decreasing in d for fixed n. This completes the proof of the theorem. □
Corollary 1. Among all connected bipartite graphs with fixed order n, the maximum diminished Sombor index is attained by the complete bipartite graph .
Theorem 4. Let be the set of all connected bipartite graphs with vertices. For , denote by and the largest, the second-largest, the third-largest and the smallest diminished Sombor index, respectively. Then:
- (i)
;
- (ii)
;
- (iii)
and for .
Proof. Parts (i) and (ii) follow from Theorem 3. For fixed n, the function is strictly decreasing in d. Hence the maximal value is attained at and the minimal value at . By Theorem 2, these values are attained by and , respectively.
We now prove (iii).
Let
. Since
G is bipartite and
, every pair of vertices in different bipartition classes must be adjacent (otherwise their distance would be an odd number at least 3). Hence
G is a complete bipartite graph
. For such graphs,
Define
A direct differentiation yields
since
. Hence
is strictly increasing on
. Therefore
has the second-largest diminished Sombor index in
.
By Theorem 2, attains the maximal diminished Sombor index in .
Since
is strictly decreasing in
d, we have
Hence the second-largest value in
must come from either
or
. Thus it suffices to compare
Odd . Write
with
. Then
Moreover,
and from the structure of
we obtain
Since
,
Hence, we obtain
Each term is strictly positive:
and
since
with equality only at
. Hence
for all odd
.
where
Moreover, for
, and from the structure of
we obtain
where
Hence,
Therefore for all even .
Combining the odd and even cases yields
and hence
The third-largest value in
is attained at
It remains to show that
Even , . Then
has
edges, hence
On the other hand,
has
edges and
, so
Since
for
, we obtain
for even
.
Odd , . Then has edges, hence
Also
has
edges, so
Since
for
, we get
for odd
. The remaining small cases
can be verified by direct computation. Therefore,
This completes the proof. □
Example 1. To illustrate the conclusions of Theorems 2 and 4 concretely, we compute the explicit DSO values and identify the corresponding extremal structures for small values of n.
The results obtained above provide a coherent structural understanding of the diminished Sombor index in bipartite graphs. Theorem 1 establishes a fundamental balance condition, showing that extremal configurations require adjacent partition sizes to differ by at most one. This result highlights the importance of degree balance in maximizing the total contribution of the index.
Building on this, Theorem 2 characterizes the precise structure of extremal graphs, revealing that they possess a layered configuration in which only two consecutive partition sets may contain multiple vertices, while all other layers consist of a single vertex. This provides a complete description of the graphs attaining the maximal DSO value.
Theorem 3 further clarifies the role of global graph structure by proving that the maximal diminished Sombor index is strictly decreasing with respect to the diameter. This demonstrates that more compact graphs yield higher index values, whereas increasing distances between vertices reduce the overall contribution.
Finally, Theorem 4 complements these results by establishing a complete ordering of bipartite graphs with respect to their DSO values, identifying the graphs that attain the largest, second-largest, and third-largest indices.
Taken together, these results show that the diminished Sombor index is governed by a delicate interplay between local degree balance and global distance constraints, providing a unified perspective on its extremal behavior.
4. Discussion
In this paper, we studied the diminished Sombor index of connected bipartite graphs of fixed order and diameter. The main contribution of the paper is the complete determination of the sharp upper bound of the diminished Sombor index in the class , together with the characterization of all extremal graphs attaining this bound. Our results show that, despite the normalized form of the diminished Sombor index, the extremal structures exhibit a strong rigidity phenomenon. More precisely, once the distance partition is considered, the maximizing graph must have at most two consecutive nontrivial partition sets, and these two layers must be as balanced as possible. This balancing property plays a central role in the proof and eventually leads to the complete identification of the extremal graphs in .
Another important outcome of the paper is the strict monotonicity of the extremal value with respect to the diameter. This shows that, for fixed order n, the maximal diminished Sombor index decreases as the diameter increases. Consequently, the extremal graphs can also be ordered according to their diameters, which makes it possible to determine the connected bipartite graphs with the largest, second-largest, third-largest, and smallest diminished Sombor indices.
The methods used here rely essentially on edge transfer arguments, distance–partition analysis, and careful comparisons of the local contributions of the function . These techniques may be useful in the study of other normalized Sombor-type indices or related degree-based graph invariants.
The present work focuses on classical combinatorial graphs; however, it is both natural and meaningful to ask whether the results can be extended to two-scale fractal spaces. The two-scale fractal dimension provides a geometric framework that captures the self-similar and non-self-similar structure of complex networks at different scales [
33,
34]. In fractal graph theory, the underlying metric structure is richer than in classical graphs: vertices may be organized according to fractal hierarchies rather than simple diameter-based layers, and the notion of distance is replaced by a more nuanced fractal distance.
Extending the extremal theory of the diminished Sombor index to such fractal graph structures represents a promising and important direction for future research. In particular, one could investigate whether the balance conditions and monotonicity properties established here have natural fractal analogues, and whether the layered extremal structures characterized in Theorem 2 correspond to self-similar configurations in fractal networks. Such an extension would bridge discrete graph theory and fractal geometry, potentially offering new tools for the structural analysis of complex molecular and biological networks.
There are several directions for further research. A natural open problem is to determine the minimum diminished Sombor index among bipartite graphs with fixed order n and diameter d, since in the present paper only the maximal case is completely resolved.
It would also be interesting to investigate extremal values of the diminished Sombor index for bipartite graphs under other graph parameters, such as matching number, connectivity, domination number, or girth.
Beyond classical graph families, extending the analysis to fractal graph models, including Sierpiński-type graphs and hierarchical networks arising in chemistry and biology, represents a particularly promising direction. The interplay between fractal dimension and degree-based indices in such settings is largely unexplored [
33,
34].
Moreover, the results of this paper provide a foundation for applying the diminished Sombor index in quantitative structure–property relationship (QSPR) modeling, particularly for bipartite molecular graphs such as those arising in coordination chemistry and polymer science. Correlating the extremal DSO values with physicochemical properties of molecules would be a natural applied counterpart to the theoretical results established here.
Finally, another natural direction is to investigate the relationship between the DSO index and the cyclomatic number for bipartite graphs, which may provide additional structural insight beyond the diameter-based approach adopted in this work.