1. Introduction
Throughout this article, the symbol
denotes the collection of all
matrices over the field of complex numbers,
denotes the conjugate transpose of
,
denotes the rank of
, i.e., the maximum order of the invertible submatrix of
A, and
denotes the range (column space) of a matrix
. A matrix
is said to be Hermitian if and only if
; to be skew-Hermitian if and only if
; to be normal if and only if
; to be EP if and only if
. The Moore–Penrose generalized inverse of
, denoted by
, is the unique matrix
satisfying the four Penrose equations:
A square matrix
is said to be group invertible if and only if there exists an
satisfying the following three matrix equations:
The matrix
X satisfying the three equations, called the group inverse of
A, is unique and is denoted by
. As we know, the theory of generalized inverses of matrices, as ubiquitous tool to deal with singular matrices, has been widely utilized to approach various complicated theoretical and computational problems in mathematics and applications. The most important fact is that we can use generalized inverses of matrices in the case when ordinary inverses of matrices do not exist in order to deal with general matrix equations. As shown above, generalized inverses can be defined to be common solutions to one or more algebraic equations as certain extensions of the ordinary inverses of matrices. In comparison, the Moore–Penrose inverse and the group inverse of a matrix are two highly recognized generalized inverses, which are known to have many remarkable algebraic and computational properties, and thus they have been widely studied in mathematics and other applications. For more detailed information regarding generalized inverses of matrices, we refer the reader to [
1,
2,
3].
Let us start with the introduction of the problem considered in this article. Given two matrices
and
of the same size, the matrix equality
is directly defined by the fact that
holds for all elements in
A and
B. In matrix theory and applications, we may encounter various problems with solving a simple or general matrix equation
, where
and
are certain algebraic operations of two given matrices
A and
B of appropriate size. One of the specified cases related to this type of problem can be formulated as:
namely,
is the unique solution to the matrix equation on the left-hand side. Due to the arbitrariness of the matrix expression
, there does not exist a general and significant method to construct matrix equations such as (
3) or to find their solutions, except in some special cases (cf. [
4,
5]).
Increasingly complex research on algebraic expressions and equalities has created a need for sophisticated methods that go beyond conventional operations of elements in a given algebraic framework. The aim of this article is to review some well-known matrix rank equalities in the theory of generalized inverses and to establish a diversity of new expansion formulas for calculating ranks of many specified block matrices. We also provide some novel and insightful methods for constructing and characterizing matrix equalities and use them in the study of problems such as (
3).
The article is organized as follows. In
Section 2, we introduce some established useful formulas, results, and facts regarding ranks, ranges, and generalized inverses of matrices in linear algebra and matrix theory. In
Section 3 and
Section 4, we give a series of well-known or novel concrete block matrices, calculate their ranks, and derive various consequences and applications from the rank formulas, including the characterization of the Hermitian/skew-Hermitian matrix, normal matrix, etc. Conclusions are given in
Section 5.
3. How to Establish Equalities for Ranks of Block Matrices
As described at the beginning of
Section 2, the usefulness of matrix rank formulas in the characterization of matrix equalities has been noted by some earlier mathematicians. In particular, in an earlier paper [
6], a wide variety of fundamental matrix rank equalities were systematically established, and various remarkable applications of the matrix rank methodology were proposed and established in the characterizations of matrix equalities composed of generalized inverses. In the past several decades, the original work developed in the seminal paper [
6] has been viewed as one of the essential contributions to the current development of matrix theory and applications, and indeed, some important and valuable studies have been done in this domain. As a fruitful investigation in this respect, we intend to establish in this section a wide range of simple and useful formulas for calculating the ranks of certain specified partitioned matrices and present their essential consequences in characterizing a series of basic matrix equalities.
Theorem 1. Let Then, the following rank equalities hold:If and thenIf and thenIn particular, for the following rank equality holds:Hence, Proof. The first equality in (
12) directly follows from (
11). Consequently, simplifying it leads to the second equality in (
12). Equation (
13) directly follows from (
9). Note that
and
are equivalent to
,
, and
by (
6). Thus, (
14) and (15) follow from (
13). Equation (16) follows from (
9). Equation (17) follows from (
12) and from the simple fact
. □
Theorem 2. Let and Then, the following facts hold:
- (a)
, and
- (b)
- (c)
If , then
Proof. It is easily seen that the first range equalities in Result (a) imply:
where (19) implies
by (7). Combining (
18) and (19) leads to:
which further implies that:
by noticing that
,
,
, and
. Therefore, the last two range equalities in Result (a) hold. Conversely, by (7), the three range equalities on the right-hand side of Result (a) imply that:
Correspondingly,
These rank equalities imply that the first two range equalities in Result (a) hold by (
6).
The first four rank equalities in Result (b) imply:
by (
6), and further imply
,
,
, and
. In this case, the first four rank equalities are reduced to the rank equalities on the right-hand side of Result (b). Conversely, combining the following simple rank inequalities:
with the rank equalities on the right-hand side of Result (b) yields the first four rank equalities on the left-hand side of Result (b). Result (c) is a direct consequence of Result (b). □
As we know, constructive methodology in the field of mathematics is an effective strategy when solving certain specified mathematical proof problems. This method is particularly suitable for approaching the given topics that are difficult to deal with by means of conventional analysis methods. The methodology usually requires observing, analyzing, and understanding research objects from new perspectives and viewpoints based on the characteristics and properties of the problem conditions and conclusions. By firmly grasping the intrinsic connection between the conditions and conclusions that reflect the given problem, utilizing the characteristics of the problem and known mathematical relationships and theories as tools, a mathematical object that satisfies the conditions or conclusions is then constructed properly. In this way, the implicit relationships and properties in the original problem are clearly presented in the newly constructed mathematical object, making it convenient and efficient to solve mathematical problems.
In what follows, we construct a selection of block matrices, calculate their ranks, and derive various consequences from the rank formulas.
Theorem 3. Let Then, the following rank equalities hold:where Proof. Equation (
20) follows from the following block matrix decomposition equality:
and the fact that the block matrices
and
are obviously nonsingular. Replacing
B in (
20) with
and noting that
leads to (21). Replacing
A and
B in (
20) and (21) with
and
and simplifying leads to (22) and (23), respectively. □
Observe that the construction of matrix equality in (
24) is simple and explicit so that the reader can properly understand the occurrence of the two basic rank expansion formulas in (
20)–(23) and their consequences. Obviously, (
20)–(23) reveal certain essential links between the two specified block matrices and the operations of their sub-matrices so that we are able to derive from them a series of possible new matrix rank equalities by choosing
A and
B as certain specified forms. As some illustrative examples, we give below diverse expansion formulas for calculating the ranks of several concrete block matrices.
Corollary 1. Let and let integer Then, the following rank equalities hold: Proof. Follows from expanding the left-hand sides of the matrices in (
25)–(
28) and applying (
20)–(23). □
Theorem 4. Let , and Then, the following rank equalities hold: Proof. Follows from expanding the left-hand sides of the matrices in (
29) and (30) and applying (
20) and (21). □
Theorem 5. Let and Then, the following rank equalities hold: Proof. Follows from replacing the two matrices in (
20) and (21) with the given
sub-block matrices on the left-hand sides of (37)–(
51). □
Theorem 6. Let Then, the following rank equalities hold:For , and the following rank equalities hold: Proof. Follows from replacing the two matrices in (
20) and (21) with the given
sub-block matrices on the left-hand sides of (55)–(57). □
Theorem 7. Let Then, the following rank equalities hold: Proof. Follows from replacing the two matrices in (
20) and (21) with the given
sub-block matrices on the left-hand sides of (59) and (61). □
The rank expansion formulas in the following lemma are well-known in elementary linear algebra, which can be viewed as entry-level examples for illustrating the constructive matrix methodology.
Lemma 6. Let and let be scalars. Then, the following rank equalities hold:If then the following rank equalities hold: Theorem 8. Let and Then, the following rank equalities hold:In particular, if then holds. Hence, the two equalities and are equivalent under Proof. Applying (
9) to the block matrix
and simplifying, we first obtain
Combining the two rank equalities yields (
62). □
As immediate applications of (
62), we are able to obtain the following concrete matrix rank formulas and their consequences.
Theorem 9. Let and Then, the following rank equalities hold:In consequence, the following facts hold: All the rank expansion formulas in the following theorems can directly be established by (
9) and elementary block matrix operations and, therefore, their derivations are omitted.
Theorem 10. Let Then, the following rank equalities hold:and the following facts hold (cf. [9]): Theorem 11. Let and let λ be a nonzero scalar. Then, the following rank equalities hold:In consequence, the following facts hold:and Theorem 12. Let and let λ be a nonzero scalar. Then, the following rank equalities hold:and the following facts hold:and Theorem 13. Let and let λ be a nonzero scalar. Then, the following rank equalities hold:and the following facts hold:and Moreover, we have the following expansion formulas for calculating the ranks of block matrices composed of multiple products of matrices.
Theorem 14. Let and let λ be a nonzero scalar. Then, the following rank equalities hold: Remark 1. The versatile and engaging findings in the above theorems actually reveal the remarkable fact that we are able to establish certain nontrivial links between different algebraic matrix equalities composed of general matrices through certain constructions of block matrices and the calculations of the ranks of the block matrices. Undoubtedly, numerous expressions of block matrices and the corresponding rank expansion formulas can be reasonably established for two or more given matrices and their algebraic operations, and consequently, many kinds of essential equivalent facts concerning matrix equalities can be obtained from the rank formulas as more and deeper approaches are devoted to this research topic.
4. Characterizations of Matrix Equalities by the Matrix Rank Methodology
In this section, we continue to construct some block matrices, calculate their ranks, and use them to characterize various matrix equalities related to the Hermitian matrix, the skew-Hermitian matrix, the normal matrix, etc.
Theorem 15. Let and Then, the following five conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
and
Proof. Applying (5) to the block matrix
, we first obtain
In this case, the matrix rank equality in Condition (a) is equivalent to the following facts:
by (8). Obviously, the first two matrix equalities in (
63) are equivalent to
by (
6). Next, post-multiplying the second equality with
and simplifying by the first pair of equalities leads to
, thus establishing the equivalence of Conditions (a) and (e).
Also, by (
4), we are able to obtain the following two rank equalities
Consequently, Condition (b) is equivalent to
and
by (8), where
is well-known to be equivalent to
(cf. [
1]). Thus, Conditions (b) and (e) are equivalent.
Note that the two rank equalities in Conditions (a) and (b) can also be written as
In such cases, applying (
6) to the two pairs of equalities leads to the equivalences of Conditions (a)–(d). □
For different choices of
B and
C in Theorem 15, we are able to derive various concrete equivalent facts concerning matrix equalities that involve a matrix and its conjugate transpose. We next present five corollaries that display how rank and range equalities of block matrices are involved in the characterizations of some well-known matrix equalities composed of matrix products of a matrix and its conjugate transpose (cf. [
2,
10,
11,
12,
13,
14,
15,
16,
17]).
As we know, Hermitian matrices possess many elegant and pleasing formulas and facts, have many significant applications in the research areas of both theoretical and applied mathematics, and have already been recognized as one of the basic conceptual objects and building materials in matrix theory and its applications.
Corollary 2. Let Then, the following five conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
Proof. Replacing in Theorem 15 leads to the equivalences of Conditions (a)–(e), where obviously implies and thus is removed from Condition (e) of Theorem 15. □
Given the above preparations, we are able to derive our main results as follows.
Theorem 16. Let Then, the following five conditions are equivalent:
- (a)
.
- (b)
and
- (c)
and
- (d)
and
- (e)
and
Proof. The equivalences of Conditions (a)–(e) follow from (
14) and (15). □
Theorem 17. Let be two Hermitian matrices. Then, the following three conditions are equivalent:
- (a)
- (b)
and
- (c)
and
Specifically, for two invertible Hermitian matrices A and B of the same size, the following three conditions are equivalent:
- (d)
- (e)
and
- (f)
and
Proof. Condition (a) obviously implies Conditions (b) and (c) under the Hermitian matrix assumption. Under Condition (b), we apply the well-known Frobenius rank inequality
for the product of any three matrices of appropriate sizes to the two products
and
to obtain:
Combining the facts with the two regular rank inequalities
and
leads to:
which further implies that the following range equalities
hold as well, since
and
always hold. In this case, we obtain, by
, Lemma 3, and elementary block matrix operations, that
which implies that
holds for matrix
X by Lemma 4. Finally, pre-multiplying
by
X and simplifying yields
, thus establishing Condition (a).
Under Condition (c), we apply the Frobenius rank inequality to the two products
and
to obtain
which further imply
and thus,
hold. In this case, we obtain, by
, Lemma 3, and elementary block matrix operations, that
which implies that the following equalities
hold for matrix
X by Lemma 4. Finally, pre-multiplying
with
X and simplifying yields
, thus establishing (a).
If A and B are invertible, then hold naturally. Thus, Conditions (a), (b), and (c) are reduced to Conditions (d), (e), and (f), respectively. □
As direct consequences, we replace A with and B with in Theorem 17, where A and B are any two matrices, to obtain the following facts.
Corollary 3. Let Then, the following three statements are equivalent:
- (a)
- (b)
and
- (c)
and
Similar to the preceding results and facts, the equivalent facts in Theorems 16 and 17 and their derivations also reveal some essential links between the matrix equality
and some other weaker conditions composed of different matrix rank equalities and algebraic matrix equalities for
A and
B, where
is known as the Yang–Baxter matrix equation in the literature (cf. [
18,
19,
20,
21]).
Theorem 18. Let Then, the following 12 conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
and
- (f)
A is Hermitian.
- (g)
is Hermitian.
- (h)
is Hermitian.
- (i)
and are Hermitian.
- (j)
and are Hermitian.
- (k)
and are Hermitian.
- (l)
and are Hermitian.
Proof. Replacing and in Theorem 15 leads to the equivalences of Conditions (a)–(d) and (g), where implies and thus is removed in Condition (g).
The equivalences of Conditions (f), (g) and (h) follow from [
4], Theorem 7.
The first equality in (e) implies . So that holds by noting . Hence, and hold by Lemma 5 (II) and (III). Now substituting the first equality into the second in (e) leads to . Pre-multiplying the equality with and simplifying with the above two equalities, we obtain . Thus, Condition (e) implies Condition (f). Conversely, Condition (f) implies Condition (e) as well.
From and in Condition (i), we first obtain . Hence, and hold by Lemma 5 (II) and (III). In this case, pre-multiplying with and simplifying yields , thus Condition (i) implies Condition (f). The equivalences of Conditions (f), (j), (k), and (l) can be established by a similar approach. □
Theorem 19. Let Then, the following 12 conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
and
- (f)
A is skew-Hermitian.
- (g)
is skew-Hermitian.
- (h)
is skew-Hermitian.
- (i)
is Hermitian, and is skew-Hermitian.
- (j)
is Hermitian, and is skew-Hermitian.
- (k)
is skew-Hermitian, and is Hermitian.
- (l)
and and are skew-Hermitian.
Recently, the present author showed in [
22] the following equivalent facts:
Combining this result with (17) and Theorems 1 and 16, we are able to obtain the following consequences.
Theorem 20. Let Then, the following 21 conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
- (f)
and
- (g)
and
- (h)
and
- (i)
and
- (j)
and
- (k)
and
- (l)
and
- (m)
and
- (n)
and
- (o)
and
- (p)
and
- (q)
and
- (r)
and
- (s)
and
- (t)
and
- (u)
and
Theorem 21. Let Then, the following 21 conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
- (f)
and
- (g)
and
- (h)
and
- (i)
and
- (j)
and
- (k)
and
- (l)
and
- (m)
and
- (n)
and
- (o)
and
- (p)
and
- (q)
and
- (r)
and
- (s)
and
- (t)
and
- (u)
and
As applications of the above results, we present below a group of characterizations of normal matrix.
Theorem 22. Let Then, the following 13 conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
and
- (f)
and
- (g)
and
- (h)
namely, A is normal.
- (i)
and and are normal.
- (j)
and and are normal.
- (k)
and and are normal.
- (l)
and and are normal.
- (m)
and and are normal.
Proof. Replacing and in Theorem 15 leads to the equivalences of Conditions (a)–(d) and (h), where also implies and thus is removed from Condition (h). The equivalences of Conditions (e), (f), and (h) follow from replacing A and B with and in Theorem 17 (a), (b), and (c).
Note that is obviously equivalent to the fact that hold for certain matrices X and Y. In this case, substituting the second given equality in Condition (g) into both sides of the third given equality in Condition (g), respectively, yields and . Consequently, pre-and post-multiplying the two equalities with the above two matrices Y and X respectively yields and . Next pre-and post-multiplying these two equalities with respectively yields . In this case, which further implies , i.e., (h) holds. Conversely, pre-multiplying with A and and applying the given condition yield and , as required for the second and third equalities on the right-hand side. Pre-and post-multiplying with A and yields , which implies that , since and are positive semi-definite. Thus, Condition (h) implies Condition (g).
Note from Condition (i) that the two normal matrices
and
commute. Then, we first obtain from Lemma 5 (I) that there exists an unitary matrix
P such that
and
hold, where
B and
C are two diagonal matrices. In this case,
by the definition of the Moore–Penrose inverse, where
is diagonal as well. Further, we obtain from
and
that
. Hence,
and
hold by Lemma 5 (II) and (III). Consequently, we obtain from the above facts the following result:
where the product
of the two diagonal matrices is also diagonal. This fact means that
holds. Thus, Condition (i) implies Condition (h). The equivalences of Conditions (h), (j), (k), (l), and (m) can be established by a similar approach. □
Corollary 4. Let and denote Then, holds, and the following 36 conditions are equivalent:
- (a)
namely, is Hermitian.
- (b)
is Hermitian.
- (c)
and are Hermitian.
- (d)
and are Hermitian.
- (e)
and are Hermitian.
- (f)
and are Hermitian.
- (g)
and
- (h)
and
- (i)
- (j)
- (k)
- (l)
- (m)
- (n)
- (o)
- (p)
- (q)
- (r)
- (s)
- (t)
- (u)
- (v)
- (w)
- (x)
- (y)
- (z)
- (a1)
- (b1)
- (c1)
- (d1)
- (e1)
- (f1)
- (g1)
- (h1)
- (i1)
- (j1)
Proof. Replacing A with in Theorems 2, 18, and 20 leads to the equivalences of Conditions (a)–(j1). □
Corollary 5. Let Then, the following five conditions are equivalent:
- (a)
- (b)
- (c)
- (d)
- (e)
and
Proof. Replacing and in Theorem 15 leads to the equivalences of Conditions (a)–(e). □
Corollary 6. Let Then, the following five conditions are equivalent:
- (a)
for any integer
- (b)
for any integer
- (c)
for any integer
- (d)
for any integer
- (e)
for any integer
Proof. Replacing and in Theorem 15 leads to the equivalences of Conditions (a)–(e). □
Finally, we present a group of identifying conditions for the commutativity of two Hermitian matrices and leave their proofs for the reader.
Corollary 7. Let be two Hermitian matrices, and denote Then, holds, and the following 41 statements are equivalent:
- (a)
namely, is Hermitian.
- (b)
- (c)
- (d)
- (e)
and
- (f)
and
- (g)
and are Hermitian.
- (h)
and are Hermitian.
- (i)
and are Hermitian.
- (j)
and are Hermitian.
- (k)
- (l)
and
- (m)
and
- (n)
- (o)
- (p)
- (q)
- (r)
- (s)
- (t)
- (u)
- (v)
- (w)
- (x)
- (y)
- (z)
- (a1)
- (b1)
- (c1)
- (d1)
- (e1)
- (f1)
- (g1)
- (h1)
- (i1)
- (j1)
- (k1)
- (l1)
- (m1)
- (n1)
- (o1)