In this paper, we introduce a graph structure, called component intersection graph, on a finite dimensional vector space . The connectivity, diameter, maximal independent sets, clique number, chromatic number of component intersection graph have been studied.
Apart from its combinatorial motivation, graph theory can also
identify various algebraic structures. The investigation of graphs
associated to algebraic structures is very important and main task of
studying graphs associated to algebraic structures is to characterize
the algebraic structures with graph and vice versa. Many fundamental
papers devoted to graphs assigned to a ring had been studied. Till date,
a lot of researches, viz.[1, 2, 3, 4, 5, 6] have been
performed on simple graph structures to commutative rings. Recently,
some algebraic graphs associated to groups, modules and vector spaces
have been studied by different mathematicians (see [2, 6, 7, 8, 9]).
For the last few decades several mathematicians studied such graphs on
various algebraic structures. These interdisciplinary studies allow us
to obtain characterizations and representations of special classes of
algebraic structures in terms of graphs and vice versa. The first step
in this direction was initiated by Bosak [10] in 1964. After that Cskny and Pollk [11] studied the graphs of subgroups of a finite
group. Zelinka [12]
continued the work on intersection graphs of the nontrivial subgroups of
finite abelian groups.
In[5], Chakrabarty et.
al introduced the intersection graph of a family of nontrivial left
ideals of a ring . Let denotes the set of all nontrivial
(nonzero proper) left ideals of
The intersection graph of is
the undirected simple graph (without loops and multiple edges) whose
vertices are in a one-to-one correspondence with all nontrivial left
ideals of and two distinct
vertices are joined by an edge if and only if the corresponding left
ideals of have a nontrivial
(nonzero)intersection.
Most properties of a vector space are connected to the behavior of
its basis. Also, basis plays a crucial roles in the study of vector
space constructions. Let
be a basis of a -dimensional
vector space over a
field Then any vector
can be
expressed as a linear combination of the form
We define skeleton of
with respect to as
and
Das [13] introduced and
studied the nonzero component graph on a
finite dimensional vector space which is a simple undirected
graph with vertex set as nonzero vectors of and any two distinct vertices
are adjacent if and only if
there exists at least one along which both and have nonzero components. Later, on in
[8] Das investigated
another interesting graph known as non-zero component union graph which
is a simple undirected graph with vertex set as non-zero vectors of
and any two distinct
vertices are adjacent if and
only if
Motivated by the above work, we introduce a new graph structure
known as component intersection graph associated with the basis of a finite dimensional
vector space .
is a graph with the set of vertices and any two
distinct vertices and
of
are adjacent if and only if
In Section 3, we investigate some basic properties of
component intersection graph
and show that
is connected and
Also, we investigate the graph theoretic properties of
and algebraic properties of Furthermore, we establish the
equivalence between vector space isomorphism and graph isomorphism.
Apart from this, we also study some basic properties of
i.e., maximal clique, chromatic number of
In Section 4, we evaluate the order of
and the degree of a vertex of
when the order of the base field is finite i.e., . Moreover, we
show that
is Eulerian. Finally in Section 5, we discuss the area of further research for
,
for example, the structure of automorphism group, domination number and
independent sets of
when the base field is
finite.
2. Definition and Preliminaries
Throughout this paper, denotes a finite dimensional
vector space over a field and is a finite field of order
Let be a Graph, where is the set of vertices and is the set of edges of We say that is connected if there exists a path
between any two distinct vertices of . For vertices and of , denotes the length of the shortest
path from to . In particular, and
The diameter of , denoted by A
cycle in a graph is a path that
begins and ends at the same vertex. A cycle of length is denoted by A graph is said to be Eulerian if
it contains a cycle containing all the edges in exactly once. The girth of , denoted by , is the length of a shortest cycle
in Two graphs and are said to be
isomorphic if there exists a bijection such that if and only if A complete
graph is a graph where all
distinct vertices are adjacent. The complete graph with is denoted by A graph is said to be a subgraph of
if and Moreover, is said to be induced subgraph of if and and
is denoted by Also is called a null graph if For a graph a complete subgraph of is called a clique. The clique number,
is the greatest integer
such that and for all The chromatic number of a graph is the minimum number of colours needed
to colour all the vertices of
such that every two adjacent vertices get different colours. For a
connected graph
and A subset of is said to be dominating set if each
vertex in is adjacent to at least one vertex in The dominating number are the minimum size of a
dominating set in
Graph-theoretic terms are presented as they appeared in Diestel [14].
3. Component Intersection Graph on Vector Spaces and Its Basic
Properties
In this section, we study some basic properties, like connectedness,
diameter, completeness, clique number and chromatic number of
Example 1. Let and
be the vector spaces over and
be the bases of and
respectively. Clearly,
and
respectively. The components intersection graphs
and
are given by the following Figures 1 and 2.
Figure 1: Figure 2:
Remark 1. In view of above example, it may be
noticed that the vertex set of our proposed graph
is different from the vertex set of
and
introduced by Das [8, 13]. Also the vertex set of
is different from the vertex set of
and
The vertices and are not adjacent in but are
adjacent in
Moreover, and are not adjacent in
and ,
but are adjacent in
Remark 2. Let
be the basis of a vector space such that The vertex set of is
different from the vertex set of and
Also
and are not adjacent in and but are
adjacent in
Theorem 1. Let be a -dimensional vector space over a field
Then
is a complete bipartite graph if and only if .
Proof. Suppose that and is a basis of Then
can be partitioned into two sets and such that
and
If and
then
in
and any two vertices of are not adjacent in
Similarly, any two vertices of are not adjacent in
Hence
is complete bipartite.
Conversely, assume that
is complete bipartite and let If then there exists a basis
of such that
for and Thus such that
for and and is a
cycle of length three. Hence
is not complete bipartite. If
then by direct part of this theorem,
is complete bipartite. This complete the proof.
If is a finite
dimensional vector space over then it is easy to show that
is empty graph if and only if Apart from this, the
following theorem holds trivially;
Theorem 2.
is complete if and only if and
Now we facilities our discussion with the following lemma;
Lemma 1. Let be a finite dimensional vector
space such that Then
is connected and
Proof. Let
be a basis of and be two distinct vertices of
We have the following cases;
(i) If
then is a path in
and
(ii) If
then we arrive at the following two subcases :
(a) If
or
then there exists
such that
Thus is a path in
and
(b) If
or
then there exists
such that and
Thus is
a path in
and Therefore in all the
cases, we find that
is connected and Hence proved.
The following theorem gives a characterization of the diameter of
;
Theorem 3. Let be a -dimensional vector spaces over Then
Proof. Suppose that
is a basis of We have
the following cases;
(ii) If and then by
Theorem 1,
is complete bipartite and
(iii) If then
and
such that . Note
that
and . If then there exists such that
and is
a path in
This gives
a contradiction. Thus and and are two distinct vertices of
such that
Therefore is a path in
and By Lemma 1, we
know that
and hence
The following theorem gives a characterization of the diameter of
;
Theorem 4. Let be a -dimensional vector space over Then
Proof. Suppose that
is a basis of a -dimensional
vector space over a
field Now we have the
following three cases;
(ii) If and then by
Theorem 1,
is complete bipartite and
contain a cycle of length four and
(iii) If then such that forms
a triangle in
Hence
Theorem 5. Let be a vector space over a field
with Then
is triangulated.
Proof. Let
be a basis of and We have the
following two cases;
(i) If then
there exist
such that
(ii) If then
there exist
such that
Thus forms a triangle in
Thus in all the cases, is a
vertex of some triangle and hence
is triangulated.
Theorem 6. Let be a finite dimensional vector
space. Then if
and only if
Proof. Suppose that
is a basis of Note that
is a clique in
If possible, suppose is a clique of
where Then
for all and
a contradiction. Finally, we prove that there does not exist any clique
of size If is a
clique of size then
for all and
a contradiction. Therefore the clique number
of
is
Conversely, assume that
and dimension of is
Then by direct part of this
theorem,
Therefore
Corollary 1. Let and be two finite dimensional
vector spaces over the field . Then and are isomorphic (as vector
spaces) if and only if
and
are isomorphic (as graphs).
Proof. It is obvious that if and are isomorphic (as vector
spaces), then
and
are isomorphic (as graphs).
Conversely, assume that
and
are isomorphic (as graphs) and are
respectively. Then by Theorem 6, the clique
number
and
are and respectively. However, as the two
graphs are isomorphic, Thus
and are finite dimensional
over the field with
and hence both are isomorphic
(as vector spaces).
Corollary 2. Let be a vector space over a field
and
be the graphs associated with with respect to the bases
and
of respectively. Then
and
are graph isomorphic.
Remark 3. The above corollary shows that the
graph theoretic properties of
does not depend on the choice of the basis
Theorem 7. Let be a -dimensional vector space. Then the
following statements hold;
(i) There exists a graph homomorphism from
to
(ii) If i.e., is odd, then is a maximal
independent set in
(iii) If i.e., is even, then
is a maximal independent set in
Proof. Suppose that
is a basis of
(i) Note that by Theorem 6,
is a clique, i.e., a complete graph and every vertex of
such that contains
at least one ( possible more than one ) member of Therefore there exists a
map given by
where and such that
By the axioms of
choice the existence of such type of map is guaranteed. If in
i.e.,
then
Thus and
since
is a complete graph,
Therefore is an
adjacency preserving map and a graph homomorphism.
(ii) Note that if
then Therefore is an independent set.
For maximality, if
with then there exists
such that
Hence is a
maximal independent set in
(iii) Note that if
then
Therefore,
is an independent set. For maximality, let If
then there exists
such that
Hence
is a maximal independent set in
Theorem 8. If be a -dimensional vector space, then .
Proof. Let
be a basis of Since the
clique number
of
is , . By Theorem 7,
Moreover, since is a
maximal clique,
Since we have the
following inequality.
and hence the theorem follows.
Lemma 2. If is a -dimensional vector space, then
Proof. Suppose that
is a basis of a -dimensional
vector space Clearly,
for are distinct
member of Hence proved.
Lemma 3. If is a -dimensional vector space and is a dominating set in
then
Proof. Suppose that is a dominating set of
We know that by Lemma 2, If
then and we
are done. Otherwise, there exist
and
such that
Clearly,
Without loss of generality, we assume that
Therefore are distinct member of and
If for
all then and we are done.
Otherwise, there exists
Without loss of generality we assume that
Since
and
there exists
such that
Clearly,
and
Therefore are distinct member of and If for
all then and we are done.
Otherwise, there exists
Without loss of generality we assume that
Since
and there exists
such that
Clearly,
and Therefore are distinct member of and
If for
all then and we are done.
Otherwise, there exists
Without loss of generality we assume that
Since
and
there exists
such that
Clearly,
and
Continuing in the similar way, there exist at least distinct members
in and the lemma
follows.
Theorem 9. If is a -dimensional vector space over a field
then
Proof. Suppose that
is a basis of Let be an arbitrary vertex of
Now we show that either or for some
Assume that and for all
Then
for all and
i.e.,
which is a contradiction. Thus either or for some
and is a domination set for
For
minimal dominating set
and
for all
i.e., for
all and
Thus is a minimum
dominating set of
and by Lemma 3, we get the required result.
4. Component Intersection Graph When the Base Field of a Finite
Dimensional Vector Space is Finite
In this section, we study some basic properties of
when the order of the base field is finite i.e., . Moreover, we
find order of
and degree of vertex of
Theorem 10. Let be a -dimensional vector space over a field
Then order of
is
Proof. Suppose that is a basis of -dimensional vector space over a field Note that and the number
of ways choosing
such that is
Therefore the order of
is
Theorem 11. Let be a -dimensional vector space over a field
If is a vertex in
such that then
Proof. Let
be a basis of -dimensional vector
space over a field and such that For
we find the total number of
vertices of
such that
For this without loss of generality, we may assume that
If such that
and then
i.e., for all Thus the set of all such that
and for and for some has elements.
Therefore the
Corollary 3. Let be a -dimensional vector space over a field
Then the following
statements hold:
(i) and
(ii)
is Eulerian if and only if is
even.
5. Conclusion
In this paper, we have introduced a component intersection graph
of a finite dimensional vector space and investigated various
inter-relationships between
(as a graph) and (as a
vector space). The main aim of this analysis is to study the basic
properties of connectedness, diameter, clique, and chromatic number of
.
As an area of further research, one can look into the structure of
automorphism group, independent number and genus of
in case of finite field.
Acknowledgements
The authors are indebted to the referee for his/her useful
suggestions critical comments.
Conflict of
Interest
The author declares no conflict of interests.
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