This paper considers rank of a rhotrix and characterizes its properties, as an extension of ideas to the rhotrix theory rhomboidal arrays, introduced in 2003 as a new paradigm of matrix theory of rectangular arrays. Furthermore, we present the necessary and sufficient condition under which a linear map can be represented over rhotrix.
By a rhotrix A of dimension three, we mean a rhomboidal array defined as
where,. The entry in rhotrix is called the heart of and it is often denoted by. The concept of rhotrix was introduced by [
where, and belong to set of all three dimensional rhotrices,.
The definition of rhotrix was later generalized by [
The element and are called the major and minor entries of R respectively. A generalization of row-column multiplication method for n-dimensional rhotrices was given by [
The method of converting a rhotrix to a special matrix called “coupled matrix” was suggested by [
The following definitions will help in our discussion of a useful result in this section and other subsequent ones.
Let be an n-dimensional rhotrix. Then,
is the -entries called the major entries of
and is the -entries called the minor entries of.
A rhotrix of n-dimension is a coupled of two matrices and consisting of its major and minor matrices respectively. Therefore, and are the major and minor matrices of.
Let be an n-dimensional rhotrix. Then, rows and columns of () will be called the major (minor) rows and columns of respectively.
For any odd integer n, an matrix is called a filled coupled matrix if for all whose sum is odd. We shall refer to these entries as the null entries of the filled coupled matrix.
There is one-one correspondence between the set of all n-dimensional rhotrices over and the set of all filled coupled matrices over.
Let, the entries and
in the main diagonal of the major and minor matrices of respectively, formed the main diagonal of R. If all the entries to the left (right) of the main diagonal in are zeros, is called a right (left) triangular rhotrix. The following lemma follows trivially.
Let is a left (right) triangular rhotrix if and only if and are lower (upper) triangular matrices.
This follows when the rhotrix is being rotated through 45˚ in anticlockwise direction.
In the light of this lemma, any n-dimensional rhotrix can be reduce to a right triangular rhotrix by reducing its major and minor matrix to echelon form using elementary row operations. Recall that, the rank of a matrix denoted by is the number of non-zero row(s) in its reduced row echelon form. If, we define rank of denoted by as:
It follows from equation (3) that many properties of rank of matrix can be extended to the rank of rhotrix. In particular, we have the following:
Let and, be any two n-dimensional rhotrices, where Then 1);
2);
3);
4).
The first two statements follow directly from the definition. To prove the third statement, we apply the corresponding inequality for matrices, that is, , where is and is. Thus,
For the last statement, consider
Let
.
Then, the filled coupled matrix of is given by
.
Now reducing to reduce row echelon form , we obtain
which is a coupled of and matrices, i.e.
and respectively.
Notice that,
Hence, .
One of the most important concepts in linear algebra is the concept of representation of linear mappings as matrices. If and are vector spaces of dimension and respectively, then any linear mapping from to can be represented by a matrix. The matrix representation of is called the matrix of denoted by. Recall that, if is a field, then any vector space of finite dimension over is isomorphic to . Therefore, any matrix over can be considered as a linear operator on the vector space in the fixed standard basis. Following this ideas, we study in this section, a rhotrix as a linear operator on the vector space. Since the dimension of a rhotrix is always odd, it follow that, in representing a linear map on a vector space by a rhotrix, the dimension of is necessarily odd. Therefore, throughout what follows, we shall consider only odd dimensional vector spaces. For any and be an arbitrary field, we find the coupledof
and
by
It is clear that coincides with and so, if, any n-dimensional vector spaces
and is of dimensions and respectively. Less obviously, it can be seen that not every linear map of can be represented by a rhotrix in the standard basis. For instance, the map
defined by
is a linear mapping on which cannot be represented by a rhotrix in the standard basis. The following theorem characterizes when a linear map on can be represented by a rhotrix.
Let and be a field. Then, a linear map can be represented by a rhotrix with respect to the standard basis if and only if is defined as
where and are any linear map on and respectively.
Suppose is defined by
where, and are any linear map on and respectively, and consider the standard basis
. Note that, for
and. Since are linear maps,. Thus,
Let for
and
for. Then from (5), we have the matrix of is
This is a filled coupled matrix from which we obtain the rhotrix representation of as.
Suppose has a rhotrix representation in the standard basis. Then, the corresponding matrix representation of is the filled coupled given in (6) above. Thus, we obtain the system
From this system, it follows that for each we have the linear transformation defined by
where, and are any linear map on with for and for
.
Consider the linear mappings define by To find the rhotrix of relative to the standard basis. We proceed by finding the matrices of. Thus,
Therefore, by definition of matrix of with respect to the standard basis, we have
which is a filled coupled matrix from which we obtain the rhotrix of in,.
Now starting with the rhotrix the filled coupled matrix of is.
And so, defining
Thus, if
Therefore,
We have considered the rank of a rhotrix and characterize its properties as an extension of ideas to the rhotrix theory rhomboidal arrays. Furthermore, a necessary and sufficient condition under which a linear map can be represented over rhotrix had been presented.
The Authors wish to thank Ahmadu Bello University, Zaria, Nigeria for financial support towards publication of this article.