1. Introduction
Throughout this study, we discuss only undirected, connected, finite, and simple graphs. A graph G is represented by the pair , whereas and represent the node and the edge sets of G, respectively. The size and order of G are, respectively, the cardinalities of and . The degree of is indicated by (or simply by ) and is equal to the number of edges incident on w. The neighborhood of is the collection of nodes of G connected to w, so is the same as . If each node is of same degree, then G is said to be regular.
Consider the diagonal matrix
of node degrees
of
G, when
. The
adjacency matrix
is a real symmetric matrix, where
-th entry is 1, if
is connected to
and 0 otherwise. The matrices
and
are, respectively, the
signless Laplacian as well as the
Laplacian matrices of
G. Their multiset of eigenvalues is the
signless Laplacian and the
Laplacian spectrums of
G, respectively. The Laplacian and the signless Laplacian are positive real semi-definite matrices, so their spectrum is real, and they are ordered as
and
, respectively. Further details about these matrices can be seen in [
1,
2].
Nikiforov [
3] suggested to investigate the symmetrical configurations
of
and
, and it is specified as
, whereas
. Certainly,
,
and
. Thus,
is a generalization of
as well as
of
G. Due to the fact that
is symmetric and real, so its eigenvalues are ordered as
whenever
is referred to as the
generalized adjacency spectral radius of
G. Moreover,
(
) is irreducible and non-negative for connected graph
G. As a result,
is a simple eigenvalue (Perron–Frobenius theorem), and its associated eigenvector
Y with positive entries is the generalized adjacency Perron vector of
G. The spectral properties of
are described in [
3,
4,
5,
6,
7] and the references listed therein.
Consider a commutative ring
R, with multiplicative identity
. If there exists
(
) such that
, then
(
) is referred to as a zero divisor of
The collection of zero divisors is symbolized by
, while
is the collection of non-zero zero divisors of
R. The
zero divisor graph of
R is a graph, where
is its node set and two different nodes
are connected whenever
. Beck [
8] established such graphs over commutative rings; in his concept, he incorporated the identity and was primarily concerned with the coloring of commutative rings. Following that, the authors of [
9] updated the concept of
by omitting the identity of
R. The finite field of order
n is represented by
and a ring of integers modulo
n by
. The order of
is
, whereas
is Euler’s phi function. The graph theoretic characteristics of
are widely investigated [
10,
11].
In [
12], the authors showed that
is a Laplacian integral, where
n is some prime power. According to [
13], whenever a connected graph is bipartite, its lowest signless Laplacian eigenvalue equals 0, and the multiplicity of the eigenvalue 0 equals the number of bipartite components. Afkhami et al. [
14] defined the normalized Laplacian as well as the signless Laplacian spectrums of
and evaluated such spectra over a range of n values. In addition, they have identified certain bounds for various eigenvalues of the normalized and signless Laplacian matrices of
. In [
15], the authors examined the adjacency spectrum of
. Furthermore, the normalized (signless) Laplacian eigenvalues were discussed in [
14,
16,
17,
18,
19,
20,
21,
22,
23,
24] carried out the Laplacian and the adjacency spectral analysis. We apply the standard, symbol
for the complete graph,
as its complement, and
for the complete bipartite graph. Additional unexplained terminologies and notations may be found in [
25].
We have investigated many articles for the spectral graph theory to learn in depth the applications and use of chemical substances. From the applications point of view, the use of the eigenvalues and especially in the Laplacian matrix plays a vital role in the computer algorithms, where they play a foundational role in machine learning. In addition, it can also be used for load balancing in in these algorithms. In computers, nowadays, the image processing is very important for the security point as well as other archaeological points of view. In these processes, the adjacency matrix plays a key role in the visualization and other zooming purposes. In addition, there is a build up of a strong inter-network connection for certain topologies that the algebraic graph theory can play in such a circumstances. The connections inside the super computers are based on certain topologies, and its working rule is based on famous Cayley graphs that use the concept of symmetry.
There are still significant gaps in the existing work about the identification of certain eigenvalues of zero divisor graphs for commutative and von Neumann rings. The apparent reason for this is that neither the construction of zero divisor graphs over rings is well specified nor it is feasible to derive convenient formulas of graph characteristics for wide classes of rings. We make an attempt in this article to examine one of these problems.
The remaining article is organized as follows:
Section 2 begins with some fundamental findings that will be employed to compute the
eigenvalues of
.
Section 3 discusses the
eigenvalues of zero divisor graphs over von Neumann regular rings.
Section 4 contains the paper’s conclusion and future work.
2. Eigenvalues of the Zero Divisor Graph
We begin this section with a couple of definitions and well-known outcomes, which we use to demonstrate our main results.
Definition 1. (Joined Union) Let us assume that a connected graph G with , and where are order disjoint graphs. The joined union of G denoted by is obtained from G by substituting every by and connecting every node of with each node of , when and are adjacent in
Consider the
matrix
such that the columns of
M and rows
M are partitioned as per the partition
of the
set. The matrix
is an
matrix with entries equal to the mean column or rows sum of the
blocks of
M; such matrix is known as the quotient matrix, see [
1,
26]. If every
has a fixed column (row) sum, the
P is known as regular, and
is said to be the
regular quotient matrix. For generality, the eigenvalues of
and
M are the same.
Let
be regular graphs, the subsequent result from [
27] indicates the
spectrum of the joined union of
in relation with the adjacency spectrum of
, for
, together with the eigenvalues of
.
Theorem 1 ([
27])
. Consider graph G of order . Suppose are -regular graphs having order and , where are their adjacency eigenvalues. The spectrum of the joined union comprises eigenvalues, for , , where is the sum of the orders of that correspond to the neighbors of . The other n eigenvalues of correspond to the eigenvalues of the matrix specified below:where , , and , , when and are connected, and 0 otherwise. Assume that is the simple connected graph, where of n is a set of proper divisors with two distinct nodes being adjacent whenever n divides
For
, consider
where
represents the G.C.D of
z and
n. Notice that
, when
; this implies that
are disjoint and partitions
as:
According to the
definition, a node of
is edge connected to the node of
in
when
n divides
, where
. In addition, the order of
is
, where
(see [
22]).
The succeeding lemma presents important properties about the subgraphs that are either null graphs or cliques.
Lemma 1 ([
12])
. Assume that is its proper divisor and . Then, the subsequent holds.- (i)
For any , the subgraph induced by of is either or Furthermore, is if .
- (ii)
For (), a node of is connected to either none or all of the nodes in of .
The sequel results give the structure of .
Lemma 2 ([
12])
. For , suppose is the subgraph induced by of . Then Lemma 3 ([
21])
. The following properties hold for .- (i)
If , whenever q is prime and , we have - (ii)
If , where q is prime and , we have
Furthermore, we examine the eigenvalues of of .
Theorem 2. The spectrum of contains the eigenvalues having multiplicity , also the eigenvalues of M presented in Equation (1). Proof. The proof directly follows from Theorem 1. □
Corollary 1. If , where and are distinct prime numbers, then the spectrum of contains the eigenvalues, where with multiplicity together with the eigenvalues of M presented in Equation (1). Next, we discuss the spectrum for some special classes of zero divisor graph. As a reminder, has an adjacency spectrum and that of is .
Lemma 4. If , then spectrum of is given as:where q is prime. Proof. For prime the zero divisor graph and its spectrum is already known. □
Lemma 5. For primes , the spectrum of is specified below: Proof. Suppose
, whereas
are prime numbers. Then, by Lemma 3,
and by Theorem 1,
and
The
spectrum of
contains the eigenvalue
whose multiplicity is
. Similarly,
is another
eigenvalue of
whose multiplicity is
. The remaining two
eigenvalues of
are the eigenvalues of the matrix presented below:
and its characteristic polynomial is
□
Lemma 6. For prime q, the spectrum of iswhere Proof. By Lemma 3, then the graph
of
is specified as:
that is, the complete split graph with the clique number
as well as the independence number is
. Using Theorem 1, the
spectrum of
contains the eigenvalue
with multiplicity
, the eigenvalue
whose multiplicity is
. The other two
eigenvalues of
correspond to the eigenvalues of the sequel matrix:
□
Theorem 3. Suppose , where and q is any prime. Then, the spectrum of comprises the eigenvalue whose multiplicity is , whenever , the eigenvalues with multiplicity , whenever and the eigenvalues of the matrix in Equation (2). Proof. Applying Lemma 3, the structure of
is given as:
Now, we need to know the structure of
. For that, note that
divides
n properly. Thus, by definition of
, the node
is connected to
if
and
where
. In addition,
and
where
. Then,
,
In general, using the fact that
, we have
for
Next, we find the remaining
’s
More generally, for
add and subtract
, so
values take the simple form
Applying Theorem 1, the
spectrum of
are the eigenvalues:
where
. Likewise, as
and using the values of
,
, and
, the other
eigenvalues are:
with
multiplicities. The remaining
eigenvalues of
are actually the subsequent matrix eigenvalues:
where
,
and
where
□
Following the steps as in Theorem 3, we can prove the odd case.
Theorem 4. If where , then the spectrum of contains eigenvalues whose multiplicity is , for , the eigenvalues with multiplicity , where , and the eigenvalues of the matrix below:where ,and where The next result gives the eigenvalues of , where n is the multiplication of prime numbers.
Proposition 1. The spectrum of contains the eigenvalues , , , , , and whose multiplicities are , , , , , and , respectively. The leftover eigenvalues of are actually the eigenvalues of the matrix presented in Equation (3). Proof. Figure 1 illustrates the proper divisor graph
. By expanding the divisor sequence while using Lemma 2 to the nodes, we obtain the following zero divisor graph:
By Theorem 1, the values of
are presented as:
As every component of
is an empty graph, therefore, the
spectrum of
comprises the eigenvalue
with multiplicity
. Likewise, the other
eigenvalues of
can be calculated as given in the statement. The remaining six
eigenvalues of
correspond to the matrix as specified below:
□
By putting
and
in Theorem 2 and its consequences, we obtain the adjacency spectrum while the signless Laplacian spectrum of
is obtained in [
14,
17,
20]. Similarly, using the fact
and Theorem 2 along with its consequences, we obtain the Laplacian eigenvalues, which were earlier obtained in [
12,
21].
3. Eigenvalues of Zero Divisor Graphs of Von Nuemann Regular Rings
A ring
R is known as
von Neumann regular if there exists
so that
for each
. The collection of idempotents of
R is represented by
and its zero divisor graph is represented by
. In [
28,
29,
30,
31,
32], researchers examined the zero divisor graphs of von Neumann regular rings and the adjacency spectrum was recently given in [
33].
If
, then the annihilator of
is denoted by
and is defined as
. Define a relation
on
if
and ∼ is clearly an equivalence relation. In [
29], the authors show the graph isomorphism, and the equivalence class has a particular idempotent if
R is a von Neumann regular. Patil and Shinde [
33] proved that for every non-trivial idempotent, the equivalence class of
e has an independent subgraph and two nodes
are edge connected whenever
and
are edge connected in
. They also showed that for a non-trivial idempotent
in
, the cardinality of
is
where × is the usual product of rings (fields).
The structure of of the von Neumann regular rings R is obtained by the following result.
Lemma 7 ([
33])
. Assume that are the non-trivial idempotents in Then, Now, we discuss the eigenvalues of
Theorem 5. Suppose R is a finite von Neumann regular ring whose non-trivial idempotents are . Then the spectrum of consists of eigenvalues with multiplicity , for , together with the eigenvalues of M given in (1). Proof. This proof directly follows by Theorem 1 and Lemma 7. □
If , for every and are distinct primes, the spectrum of is presented by Corollary 1. Thus, by Theorem 5, we may determine the spectrum of more general classes of zero divisors graphs of rings.
Next, we discuss some consequence of Theorem 5. First, we will find the spectrum of , whereas and are finite fields. If and , whereas are primes, then eigenvalues are as in Lemma 5; otherwise, the spectrum is presented by the sequel result.
Corollary 2. Suppose . Then, the spectrum of contains the eigenvalues and with multiplicities and , respectively, and the two zeros of the following polynomial: Proof. For
, the non-trivial idempotent set is
and
and
, with
,
. Thus, by the definition of
also by Lemma 7,
. Therefore, from Theorem 5, the
eigenvalues of
are the eigenvalue
with multiplicity
and the eigenvalues
with multiplicity
. The other
eigenvalues are actually the eigenvalues of the subsequent matrix:
□
If
, when
are distinct primes, as a result, Proposition
3 yields the
eigenvalues of
. For
. As a consequence, we obtain the following.
Corollary 3. Suppose . We have that the spectrum of contains the eigenvalues , , , , , with multiplicities , , , , , , respectively, and the other eigenvalues of are of Equation (4). Proof. For
, the non-trivial idempotent set is
and
,
is shown in
Figure 2. Likewise, the graph
is expressed on the right side of
Figure 2, where
and
and by Theorem 5, the
values are:
As a result, Theorem 5 states that the
eigenvalues of
consist of the eigenvalues
with multiplicity
, and the other
eigenvalues are as stated. The remaining six
eigenvalues correspond to the eigenvalues of the matrix given below:
□
We note that for
in Theorem 5, we obtain the adjacency eigenvalues of the von Neumann regular rings obtained by Patil and Shinde [
33]. Furthermore, from
, applying Theorem 5, we derive the Laplacian spectrum originally determined in [
33]. For
, we obtain the signless Laplacian eigenvalues of
, where
R is the von Neumann regular rings and they are given below.
Proposition 2. Assume . The signless Laplacian spectrum of comprises the eigenvalues , whose multiplicities are , and , respectively. The leftover two eigenvalues of are the eigenvalues given below: For , we obtain the following result.
Proposition 3. Suppose . The signless Laplacian spectrum of contains the eigenvalues , , , , , and with multiplicities , , , , , and , respectively. The leftover six eigenvalues of are the eigenvalues given below: 4. Conclusions
The present articles studied the eigenvalues of zero divisor graphs of various commutative rings. Therefore, we derived the adjacency, Laplacian, and the signless Laplacian eigenvalues of such graphs. The field of theoretical chemistry is significant. We study a large number of articles on spectral graph theory in order to investigate chemical substances. Another useful application for the adjacency matrix is the spectral embedding of graphs in the plane. In machine learning, the eigenvalues of the Laplacian matrix provide the foundation for spectral clustering algorithms. In addition, computer scientists incorporate it into load-balancing algorithms. Algebraic graph theory can be used to build and study the topologies of interconnection networks. The topologies used to integrate processors in a supercomputer are typically Cayley graphs with a high degree of symmetry.
However, some eigenvalues of these graphs remain unknown in terms of the eigenvalues of the quotient matrix, which are hard to find. At large, the eigenvalues of zero divisors graphs of other commutative rings are yet to be discussed, and extremal characterizations in terms of various spectral invariants are open and may be discussed in future.