1. Preliminaries
We begin by reviewing the basic terminology and notation used throughout this paper. Unless specified otherwise, all graphs are assumed to be undirected, finite, and simple. For more extensive discussions of particular operations and concepts, the reader is referred to the literature.
1.1. Power Graph and Directed Power Graph
A Power Graph has group elements as vertices, with edge joining elements when one is a power of the other. Directed Power Graph uses group elements as vertices and a directed edge whenever for some .
Definition 1.1 (Group)
. [
6,
7,
8] A
group is a pair
consisting of a nonempty set
G and a binary operation
satisfying the following axioms:
- 1.
Associativity: For all
,
- 2.
Identity: There exists a unique element
such that for all
,
- 3.
Inverse: For each
, there exists an element
such that
Definition 1.2 (Power Graph)
. [
9,
10,
11] Let
G be a group. The
power graph of
G is the (undirected) graph
whose edge set is
Equivalently,
is the underlying simple graph of
.
Example 1.3 (Power Graph of the Cyclic Group of Order 4)
. Let
. Its power graph
is given by
Definition 1.4 (Directed Power Graph)
. [
9,
11] Let
G be a group. The
directed power graph of
G is the digraph
where
Example 1.5 (Directed Power Graph of the Cyclic Group of Order 4)
. On the same group
G, the directed power graph
has
Here each arc
satisfies
for some
and
.
1.2. SuperHyperGraph
A
hypergraph generalizes a standard graph by allowing
hyperedges that can join any number of vertices simultaneously [
3,
12,
13,
14]. Extending this idea, a
SuperHyperGraph incorporates iterated powerset constructions to capture hierarchical relationships among hyperedges, a topic of growing interest in recent studies [
5,
15,
16,
17,
18,
19]. Practical applications of SuperHyperGraphs include molecular modeling, network analysis, and signal processing [
20,
21,
22,
23,
24,
25]. In what follows, the integer parameter
n in the
nth powerset and in an
n-SuperHyperGraph always denotes a nonnegative integer.
Definition 1.6 (Base Set)
. A
base set S is the underlying domain from which all further constructions are drawn. Formally,
Every element appearing in
or in iterated powersets
is an element of
S.
Definition 1.7 (Powerset)
. The
powerset of a set
S, written
, is the collection of all subsets of
S, including
∅ and
S itself:
Definition 1.8 (Hypergraph)
. [
3,
26] A
hypergraph consists of
A finite vertex set .
A finite collection of nonempty subsets of , called hyperedges.
Hypergraphs are well suited to model higher-order interactions among elements of .
Theorem 1.9.
Let G be a group and let
be its power graph (Definition 1.2). Then
is a 2-uniform hypergraph (Definition 1.8), and its 2-section (the simple graph obtained by replacing each hyperedge by an undirected edge) is exactly .
Proof. We verify that satisfies the hypergraph axioms:
is finite (since G is finite or else this construction still formally applies).
Each is a nonempty subset of G, and by construction .
Hence H is a 2-uniform hypergraph. Its 2-section is formed by interpreting each hyperedge as an undirected edge between x and y. But exactly those pairs appear in E for which or , so the resulting simple graph coincides with the power graph . □
Definition 1.10 (
n-th Powerset)
. [
27,
28,
29,
30,
31] The
n-th powerset of a set
X, denoted
, is defined by:
The corresponding nonempty powerset
is obtained by iterating
, where
.
Definition 1.11 (
n-SuperHyperGraph)
. [
32,
33,
34] Let
be a finite base set. Define iteratively
An
n-SuperHyperGraph is a pair
where each element of
V is called an
n-supervertex and each element of
E an
n-superedge.
Example 1.12 (3-SuperHyperGraph: Global Project Organization)
. We illustrate a 3-SuperHyperGraph by modeling the hierarchy of a multinational corporation’s project structure.
First–level (teams). Elements of
:
Second–level (departments). Elements of
. Select:
Third–level (global divisions). Elements of
. Choose two representative supervertices:
Here models the “Asia–Europe Division” (linking Department 1 and Department 2), while models the “Global Integration Division” (combining Department 1 with the cross-team set ).
Interpretation. The 3-supervertices represent high–level divisions composed of lower–level departments and teams. The single superedge indicates a strategic collaboration between these two global divisions on a company-wide initiative.
Hence
is a concrete instance of a 3-SuperHyperGraph reflecting a real-world organizational hierarchy.
1.3. Directed SuperHyperGraph
Directed SuperHyperGraphs are graph classes that extend SuperHyperGraphs, respectively, in a manner analogous to Directed Graphs. Below, we present their formal definitions and illustrative examples.
Definition 1.13 (Directed Hypergraph)
. A directed hypergraph is a pair where
Each hyperedge
is an ordered pair
where
and one typically requires
and
. This structure generalizes a directed graph by allowing each hyperedge to connect multiple source vertices
to multiple target vertices
simultaneously.
Theorem 1.14.
Let G be a group and let be its directed power graph (Definition 1.4), where
Define a directed hypergraph
Then H is a directed hypergraph, and its underlying digraph is exactly . Hence is realized as a directed hypergraph with all hyperedges of size one.
Proof. First,
is finite and nonempty. Each hyperedge in
is of the form
with
and both
and
are nonempty by construction. Therefore
H satisfies the requirements of the Definition.
Next, the underlying directed graph of H has an arc precisely when there exists a hyperedge . By definition of , this occurs if and only if , i.e. for some . This is exactly the arc-set of . Hence the two directed graphs coincide. □
Definition 1.15 (Directed
n-SuperHyperGraph)
. (cf.[
22,
34,
35]) Let
S be a nonempty
base set and let
be an integer. Define iterated powersets by
A
directed n-SuperHyperGraph is a pair
where
and each directed
n-superedge
is an ordered pair
typically both nonempty. Such an
e carries “flow” from the entire set
of
n-supervertices into
.
Example 1.16 (Directed 2-SuperHyperGraph: Corporate Workflow)
. We model a simplified approval process in a company with two teams and a central review committee.
Second–level (departments):
Directed superedges (approval flow):
Interpretation. Each directed superedge
represents the flow of deliverables (or approval requests) from department
into the central committee
. Thus
is a concrete directed 2-SuperHyperGraph illustrating this corporate workflow.
Theorem 1.17.
Every directed hypergraph can be realized as a directed 1-SuperHyperGraph. Concretely, if
and for each directed hyperedge defining
yields a directed 1-SuperHyperGraph with
Proof. We verify that satisfies Definition 1.15 for :
By construction, and is nonempty.
Each and is a nonempty subset of V, since .
Thus every is an element of .
Hence is a directed 1-SuperHyperGraph. Since directed hyperedges and directed 1-superedges correspond bijectively, H is represented exactly by . □
Corollary 1.18. Every directed hypergraph is a special case of a directed n-SuperHyperGraph for any , via the inclusion .
Proof. Embed each singleton into by iterated singletoning: . The same construction of tails and heads yields a directed n-SuperHyperGraph isomorphic to the directed 1-case. □
2. Main Results
As the main contributions of this paper, we show that:
2.1. n-th Power Graphs
Vertices are n-fold powersets of group G; two vertices are adjacent if one equals the m-th power-set image of the other.
Definition 2.1 (Iterated Exponentiation)
. Let
G be a group and
. Define maps
and recursively for
,
Definition 2.2 (Undirected
n-th Power Graph)
.
Then the
n-th power graph is the simple graph
Example 2.3 (Rotating Shift Patterns as an Undirected 2nd Power Graph)
. We model a weekly rotating shift system on a seven-day cycle as an undirected 2nd power graph.
Base group and daily blocks. Let
with addition modulo 7 representing days of the week. Define two daily shift blocks:
Weekly patterns (). Vertices are collections of these blocks in one week:
where
. Thus
Edge relation (). In the undirected 2nd power graph
, two patterns
are adjacent precisely if one is obtained by applying the same shift
m to the other:
since
Interpretation. Vertices represent entire weekly shift schedules; an (undirected) edge between two patterns indicates they differ by a uniform rotation of all daily blocks. Here form a triangle, reflecting that any pattern can be reached from any other by some two-day rotation.
Theorem 2.4.
For any group G and integer , the graph is a 2-uniform n-SuperHyperGraph on G. Concretely, if one sets
then satisfies the definition of an n-SuperHyperGraph, and its underlying simple graph is exactly .
Proof. By construction, with , and . Hence is an n-SuperHyperGraph. Moreover, since every hyperedge in E has size 2 and corresponds precisely to the exponentiation relation , the simple graph obtained by replacing each by an undirected edge is exactly . □
Theorem 2.5 (Functoriality)
.
If is a group isomorphism, then for each there is a graph isomorphism
Proof. Since
is bijective, so is
. Moreover, if
is an edge in
, then
or vice versa for some
m. Applying
yields
showing
is an edge of
. Thus
preserves adjacency and is a graph isomorphism. □
Theorem 2.6 (Vertex-Transitivity)
. For any finite group G and , the graph is vertex-transitive under the action of G by conjugation on each level of the iterated powerset.
Proof. Let
. Conjugation by
g induces a permutation
for each
. These maps are bijections and satisfy
Hence conjugation commutes with iterated exponentiation, and so
if and only if
. This shows the induced permutation on
is an automorphism of
. Since
G acts transitively on itself by conjugation (and hence on its iterated powersets),
is vertex-transitive. □
Theorem 2.7 (Diameter Bound)
. Let G be a finite group of exponent e (so for all ). Then for any , the diameter of is at most 2.
Proof. Given any two vertices
, if
we are done. Otherwise, consider the identity supervertex
. Because each element of
G has order dividing
e,
Thus and , so there is a path A––B of length 2. Hence . □
2.2. Directed n-th Power Graphs
Directed n-th power graphs: vertices are n-fold powersets, with if B equals the mth power of every element in A.
Definition 2.8 (Directed
n-th Power Graph)
. Under the same hypotheses, the
directed n-th power graph of
G is the digraph
where
Example 2.9 (Rotating Shift Schedules as a Directed 2-nd Power Graph)
. We model a rotating shift schedule over a seven-day cycle using the directed 2-nd power graph.
Base group and first-level sets. Let
with addition modulo 7 representing days of the week (e.g.
Mon,
Tue,…). A
daily shift block is any nonempty subset
. For example,
Second-level: weekly roster patterns. Elements of
are
weekly patterns, i.e. collections of daily blocks. For instance,
where
denotes shifting every block forward by two days:
Directed 2-nd power graph. Define
Then is the directed 2-nd power graph. In particular, we have an arc because Q is obtained by applying the same shift days to each daily block in P.
Interpretation. Vertices of represent entire weekly shift patterns, and a directed edge indicates that Q arises from P by uniformly advancing every daily block by m days. This captures the real-world operation of rotating shift schedules in a hierarchical (daily→weekly) framework.
Theorem 2.10. For any group G and integer :
- 1.
coincides with the classical power graph of Definition 1.2.
- 2.
coincides with the directed power graph of Definition 1.4.
- 3.
The vertex sets satisfy , so is a nested family reflecting the iterated powerset .
Proof.
- 1.
By the Definition, . Hence the adjacency rule in reduces exactly to “ or ” for , which is the condition defining .
- 2.
Likewise, has vertex set G and an arc precisely when for some m, matching Definition 1.4.
- 3.
From , every element of is also a (singleton) element of . Thus for all k, and the sequence of graphs grows strictly (or stabilizes) with n. This nesting mirrors the iterated powerset structure.
□
Theorem 2.11. For any group G and , the digraph is a directed 2-uniform n-SuperHyperGraph. In particular, its arc-set defines the directed superedges of an n-SuperHyperGraph structure on .
Proof. Since and each satisfies , it endows with the structure of a directed hypergraph whose hyperedges all have size two and carry a direction. By Definition (specialized to directed arcs), this coincides with a directed 2-uniform n-SuperHyperGraph. □
Theorem 2.12 (Transitivity)
. For any group G and , the directed n-th power graph is transitive: if and are arcs, then is also an arc.
Proof. Suppose
and
. By definition there exist
such that
But then
so
. Hence the adjacency relation is transitive. □
Theorem 2.13 (Reachability to the Identity Supervertex)
. Let G be a finite group of exponent e (i.e. for all ). In , every vertex has a directed path of length one to the singleton supervertex .
Proof. For any
, consider
Since
(unless
, in which case there is no self-loop), and
, the definition of arcs ensures
. Thus every supervertex reaches
by a single directed edge. □
3. Conclusion and Future Work
In this paper, we have shown that the Power Graph of a group can be realized as a hypergraph and that the Directed Power Graph is a directed hypergraph. Furthermore, we introduced the
nth Power Graph and the Directed
nth Power Graph, and demonstrated that they form subclasses of SuperHyperGraphs and Directed SuperHyperGraphs, respectively. In future work, we plan to extend the concepts developed here to various frameworks of uncertainty, including Fuzzy Sets [
36,
37], Intuitionistic Fuzzy Sets [
38], Hyperfuzzy Sets [
39,
40,
41,
42], SuperHyperFuzzy Sets [
43,
44], Neutrosophic Sets [
45,
46], and Plithogenic Sets [
47,
48,
49].
Funding
This study did not receive any financial or external support from organizations or individuals.
Data Availability Statement
This research is purely theoretical, involving no data collection or analysis. We encourage future researchers to pursue empirical investigations to further develop and validate the concepts introduced here.
Acknowledgments
We extend our sincere gratitude to everyone who provided insights, inspiration, and assistance throughout this research. We particularly thank our readers for their interest and acknowledge the authors of the cited works for laying the foundation that made our study possible. We also appreciate the support from individuals and institutions that provided the resources and infrastructure needed to produce and share this paper. Finally, we are grateful to all those who supported us in various ways during this project.
Conflicts of Interest
The authors confirm that there are no conflicts of interest related to the research or its publication.
Ethical Approval
As this research is entirely theoretical in nature and does not involve human participants or animal subjects, no ethical approval is required.
Disclaimer
This work presents theoretical concepts that have not yet undergone practical testing or validation. Future researchers are encouraged to apply and assess these ideas in empirical contexts. While every effort has been made to ensure accuracy and appropriate referencing, unintentional errors or omissions may still exist. Readers are advised to verify referenced materials on their own. The views and conclusions expressed here are the authors’ own and do not necessarily reflect those of their affiliated organizations.
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