Abstract
There are many characterizations of linear operators from various matrix spaces into themselves which preserve term rank. In this research, we characterize the linear maps which preserve any two term ranks between different matrix spaces over anti-negative semirings, which extends the previous results on characterizations of linear operators from some matrix spaces into themselves. That is, a linear map T from matrix spaces into matrix spaces preserves any two term ranks if and only if T preserves all term ranks if and only if T is a ()-block map.
MSC:
15A03; 15A04; 15A86
1. Introduction
There are many characterizations of linear operators from various matrix spaces into themselves which preserve term rank. Beasley and Pullman ([1]) determined the linear operators on the Boolean matrices, which preserve Boolean term rank. Their results are the following: For a linear operator on the Boolean matrices,
Beasley et al. ([2]) characterized linear operators on the matrices over a commutative anti-negative semiring which preserve term rank. The results are the following: For a linear operator on the commutative anti-negative semiring matrices,
Song and Beasley ([3]) characterized the linear maps that preserve term rank between different Boolean matrix spaces.
For the case of symmetric matrices, we have some results on the term rank preservers in [4,5].
In this paper, we investigate the characterizations of linear maps which preserve term rank between different matrix spaces over anti-negative commutative semirings, which extends the previous results on characterizations of linear operators between different matrix spaces.
2. Preliminaries
In this section, we give some definitions and basic results for our main results.
A semiring [1] is a set with addition(+) and multiplication (·) such that is a commutative semigroup with identity 0 and is a semigroup with identity 1. Moreover, the operation · is distributive over +. A semiring is called anti-negative if only 0 has an additive inverse. A semiring is called commutative if for all .
The following are interesting examples of some anti-negative commutative semirings.
For a fixed positive integer h, let be the Boolean algebra [6] of subsets of an h-element set and denote the singleton subsets of . Union is denoted by + (addition) and intersection by juxtaposition (multiplication); 0 denotes the empty set and 1 the whole set . Under these two operations, is a commutative anti-negative semiring, which is called generalized Boolean algebra. Then all of its elements, except 0 and 1, are zero-divisors because each proper subset of has empty intersection with its complement. In particular, if , is called the binary Boolean algebra [6].
Let be any set with at least two elements. If is totally ordered by < (i.e., or for any two distinct elements in ), then define as and as for all . If has a universal upper bound and a universal lower bound, then is a semiring, which is called a chain semiring [6].
Let be the field of real numbers, let 01} be a subset of . Define and for any . Thus is a chain semiring, which is called a fuzzy semiring [7]. In particular, if we take , a singleton set and we denote ∅ by 0 and by 1, then this chain semiring is the binary Boolean algebra , which is a subsemiring of any chain semiring. Since a Boolean algebra () is not totally ordered under inclusion, it does not become a chain semiring.
In the following, will denote an arbitrary commutative anti-negative semiring. For all a, b , we supress the dot of a · b, and simply write ab. Let () be the set of all ( respectively) matrices with entries in . The addition and multiplication on are defined as usual.
In the following, we assume that integers p, q, m and n are positive integers with and .
Let be the (0,1)-matrix whose only th entry is 1, and be called a cell. O is the zero matrix, is the identity matrix and J is the matrix all of whose entries are 1.
A matrix is the hth full row matrix and is the kth full column matrix. A matrix L is called a full line matrix if or for some or for some .
A line of matrix is a column or a row of U.
A matrix has TR t (or term rank t) if the minimum number of lines needed to cover all nonzero entries of U is equal to t. We denote if U has TR t.
For matrices U, V , it is said that dominates (denoted or ) if implies for all h and k.
Lemma 1.
For matrices U, V , we have
(1) ;
(2) ;
(3) implies that .
Proof.
(1) It is trivial from the definition.
(2) If , then we can find t lines that cover all nonzero entries of U. If these lines cover all nonzero entries of V, then . However, If these lines cannot cover all nonzero entries of V, then . Thus, .
(3) If , then we can find t lines that cover all nonzero entries of V. Since , these lines can cover all nonzero entries of U. Thus . □
For a matrix U and lists and of column and row indices, respectively, denotes the submatrix constructed by deleting the columns and rows from U and denotes the submatrix constructed by taking the columns and rows from U.
For matrices , the matrix denotes the Schur or Hadamard product of U and V. That is, the entry of is .
A map is said to be linear if for all and .
If is a map, then T is called a -block map if there is a permutation matrix P and a permutation matrix Q, and with nonzero , such that
- and , and for any or
- and , and for any .
It is obvious that -block map is a linear map.
3. Linear Maps that Preserve TR of Matrices over Anti-Negative Commutative Semirings
In this section, we characterize the linear maps that preserve TR of matrices over anti-negative commutative semirings, which are contained in Theorem 2.
For a linear map , we say that T
- (i)
- preserves TR t if whenever for all ;
- (ii)
- doubly (or strongly) preserves TR t if if and only if for all ;
- (iii)
- preserves TR if it preserves any TR t with .
Throughout this section, T denotes a linear map .
Lemma 2.
Let T be a -block map. Then T doubly preserves any TR t for .
Suppose that T is a -block map, and U with with . Then or .
Consider the first case: . Since all entries of B are not zero, , and . Since the permuting columns and rows does not change the TR, we have
.
Thus T preserves TR t.
Conversely if , then
.
Thus . That is, T doubly preserves TR t.
Consider the second case: . As in the first case, a similar argument shows the same results. That is, T doubly preserves TR t.
Theorem 1.
Let T doubly preserve TR 1. Then T is a -block map, and vice versa. (Here, we have either and , or and .)
Suppose that T doubly preserves TR 1. Then, the image of each line under T in is a line in since T preserves TR 1. Thus we assume that either or .
Consider the first case: . Assume that . Then, since is in both and and since and lies in the first row , h must be 1. However, then, for . Hence, has TR 1. However, , a contradiction. Thus we conclude that the image of any full column matrix is contained in a column matrix. By a similar argument, the image of any full row matrix is contained in a row matrix. And, since two columns have TR 2, the image of distinct full columns must be contained in distinct columns. Let be defined by if and define by if . Then, and are injective maps, and hence, and . Let and be a bijective maps such that and . Let and be the permutation matrices of order p and q, respectively, that correspond to the bijective maps and .
Thus we obtain that and , and there is some nonzero such that , for every cell . Therefore,
for every . Thus T is a -block map.
Consider the second case: . As in the first case, a similar argument implies that and . We obtain for all . Hence
for every . This implies that T is a -block map.
Conversely, if T is a -block map, then T doubly preserves TR 1 by Lemma 2.
Lemma 3.
Suppose that T preserves TR 1 and TR . Then we have
(1) T doubly preserves TR 1;
(2) T is a -block map.
(1) Consider the first case that : If has TR 1, then also has TR 1.
Conversely, if is the matrix with , and , then . However, since implies by assumption that . Thus . Let such that and with . Then . Thus by Lemma 1, which inequality is impossible. That is, T doubly preserves TR 1.
Consider the second case that : Assume that a TR 2 matrix is mapped to a TR 1 matrix. Then we may consider without loss of generality. Then, since T preserves TR 1 and TR t,
,
which is impossible. Hence, T doubly preserves TR 1.
(2) By (1), T doubly preserves TR 1. Hence T is a -block map by Theorem 1.
Lemma 4.
Suppose that T preserves TR t.
(1) If and T does not preserve TR 1, then there is a matrix U such that and .
(2) If for some , then .
(1) Assume that T does not preserve TR 1 and for all U with . Then, there is a cell with . We may assume that without loss of generality. Since and T preserves TR t, we get . If we make , then we can take some cells such that for all , and . Since , there is a cell in whose image dominates two cells in , which contradicts for all U with in the assumption. This contradiction implies that there is a matrix U such that and .
(2) If , then since T preserves TR t. Assume that , and . Then there exists a matrix V such that and hence . However, by Lemma 1,
,
which is impossible. Therefore it follows that
Lemma 5.
If T preserves any TR , but does not preserve TR 1, then , where J is the matrix with all entries 1.
By Lemma 4, if T does not preserve TR 1, then there is some matrix U such that and . So without loss of generality we may assume that .
Assume that . Then, . So we may assume that without loss of generality. Thus, there are cells, such that . Then, . However, and , which contradicts Lemma 4 (2). Thus, .
Lemma 6.
Let . If and , then there is some , such that .
Assume that and . Then there are cells such that and . If then some cell must be a cell where , which is in contradiction with the assumption . Thus does not hold. That is, there is some h, , such that
.
Lemma 7.
For , if T preserves consecutive TR t and TR , then it preserves TR 1.
If , we have finished. Assume that , and that T does not preserve TR 1. Then we have by Lemma 5. Since T preserves TR , .
Thus, for or . Now, we may assume that for some with , . This implies that
Now, without loss of generality, we may assume that there are cells such that for . Assume that the image of one cell in dominates more than one cell in . Without loss of generality, we may assume that . Then, , which is a contradiction since , and hence by Lemma 4 (2), but Therefore, for each , dominates only one . So, by permuting we may assume that . Consider . This matrix Z must have TR and dominates . Applying Equation (1) to Lemma 6, we can choose a cell in such that . However, , which is a contradiction.
This contradiction implies that T preserve TR 1.
Lemma 8.
If T preserves TR t and TR s with , then it preserves TR 1.
Assume that T does not preserve TR 1. Then by Lemma 5. For any , we have by Lemma 1 and assumption. However, if we take , then must have TR s by assumption, while , a contradiction. That is, for arbitrary TR 1 matrix U. Therefore T preserves TR 1.
Lemma 9.
If T preserves TR t and TR , then it preserves TR .
Let .
First, consider the case that and . Let be matrices of TR 1 such that . Since for some , we may assume that , for every . However, then while , a contradiction. Thus if , .
Second, consider the cases and . We may assume without loss of generality that and . Then there are r elements in whose sum dominates . Say, without loss of generality, that . Now, so that . However, since , it follows that and there are r elements of whose sum with has TR , say . Since , and . By the above case, we have a contradiction.
Thus T preserves TR .
Lemma 10.
If T doubly preserves any one TR , then T preserves TR and hence T preserves TR 1.
Consider the first case : Assume that has TR 1. Then we may choose a matrix such that and . Since since T doubly preserves TR 2. Since , it follows that . Thus the Lemma holds in the case .
Consider the second case : Let and . Assume that . Say we may assume that . Since , it follows that . So we may assume without loss of generality, that and that for some . Thus, there are s cells in such that . Then . Thus . However,
which contradicts the assumption that T doubly preserves TR t. Hence . Further, by Lemma 4 (2), since T doubly preserves TR t. Therefore , which implies that T preserves TR .
Moreover, T preserves TR 1 by Lemma 7.
Lemma 11.
(1) If T preserves any two TR t and TR , then T is a -block map. (2) If T doubly preserves any one TR t, then we have that T is also a -block map.
(1) First case : Then T preserves TR 1 by Lemma 7.
Second case : Lemma 9 implies that T preserves TR . Hence T preserves TR 1 by Lemma 7.
Third case : Then by Lemma 8, T preserves TR 1.
Consequently, T preserves TR 1 by the above three cases. Hence, T doubly preserves TR 1 by Lemma 3. By Theorem 1, T is a -block map.
(2) By Lemma 10, T preserves TR 1. By Lemma 3, T doubly preserves TR 1. Thus T becomes a -block map by Theorem 1.
Now we have the main theorem:
Theorem 2.
The following are equivalent for
- T preserves any two TR t and TR s, with and
- T doubly preserves any one TR t, with
- T preserves TR;
- T is the -block map.
It holds trivally that 3 implies 1 and 3 implies 2. Moreover, by Lemma 2, we have that 4 implies the other items 1, 2 and 3.
To show that 1 implies 4, suppose that T preserves TR t and TR s, with Then, by Lemma 11 (1), T is the -block map.
To show that 2 implies 4, suppose that T doubly preserves TR t. Then T is the -block map Lemma 11 (2).
Thus we obtained characterizations of the linear maps that preserve any two term rank between different matrix spaces.
4. Conclusions
There are many research articles on the linear operators which preserve term rank over some matrix spaces. However, there are few articles for the characterizations of the linear maps that preserve term rank between different matrix spaces over semirings. In this paper, we have characterized the linear maps which preserve term rank between different matrix spaces over anti-negative commutative semirings, which extend the previous results on characterizations of linear operators between the same matrix spaces. That is, a linear map T from matrix spaces into matrix spaces preserves any two term ranks if and only if T preserves all term ranks if and only if T is a ()-block map. In the future, we may apply these results and this proof method to investigate the linear preserver problems over various semirings. We hope to apply these results to characterize the linear maps that preserve the semiring rank between different matrix spaces, which extends the previous results on characterizations of linear operators that preserve the semiring rank between the same matrix spaces.
Author Contributions
Create and conceptualize ideas, K.T.K. and S.-Z.S.; writing—original draft preparation, K.T.K. and S.-Z.S.; writing—review and editing, Y.B.J.; funding acquisition, S.-Z.S. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by Basic Science Research Program to RIBS of Jeju National University through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2019R1A6A1A10072987).
Conflicts of Interest
The authors declare no conflict of interest.
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