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Research Article

Secondary range symmetric matrices

[version 1; peer review: 2 approved, 1 approved with reservations]
PUBLISHED 19 Feb 2024
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This article is included in the Manipal Academy of Higher Education gateway.

Abstract

The concept of secondary range symmetric matrices are introduced here. Some characterizations as well as the equivalent conditions for a range symmetric matrix to be secondary range symmetric matrix is given. The idea of range symmetric matrices, range symmetric matrices over Minkowski space and secondary range symmetric matrices are different, and is depicted with the help of suitable examples. Finally, a necessary and sufficient condition for a secondary range symmetric matrix to have a secondary generalized inverse has been obtained.

Keywords

Generalized inverses, Secondary generalized inverses, Secondary transpose, EP matrices

Introduction

The theory of symmetric matrices as well as range symmetric matrices are well known in literature. A matrix is said to be EP (or range symmetric), whenver the range space of the matrix is equal to the range space of its conjugate transpose. In other words, matrix is EP whenever its null space is same as that of the null space of its conjugate transpose. Ballantine1 has studied about the product of two EP matrices of specific rank to be again an EP matrix. In2 new characterizations of EP matrices are given. Also, weighted EP matrix is defined and characterized. Meenakshi3 extended the concept of range symmetric matrices over Minkowski space. In 2014, the same author defined range symmetric matrices in indefinite inner product space.4

For an n×n matrix A, the secondary transpose is related to transpose of the matrix by the relation AS=VATV. Here, the matrix V has non zero unitary entries only on the secondary diagonal. For a matrix A with complex entries, the secondary transpose will be renamed as secondary conjugate transpose Aθ and is given by Aθ=VAV.

Definition 1

(Ref. 5) Let An×n. Then the secondary transpose (or secondary conjugate transpose Aθ in the case of complex matrices) of A denoted by AS and is defined as AS=bij, where bij=anj+1,ni+1, i,j=1,2,n.

Throughout this article we assume V to be a permutation matrix with units in the secondary diagonal. Also, NA represents the null space of the matrix A. The column space and rank of A are denoted by CA,ρA respectively. The set of matrices of order n×n over the field of real numbers is denoted by n×n.

The concept of secondary conjugate transpose is gaining importance in recent years. Shenoy6 has defined Outer Theta inverse by combining the outer inverse and secondary transpose of a matrix A. Drazin-Theta matix AD,θ7 is a new class of generalized inverse introduced for a square matrix of index m. One can refer8 for the extension of these inverses over rectangular matrices. R. Vijayakumar9 introduced the concept of secondary generalized inverse with the help of secondary transpose of a matrix. This concept is similar to Moore Penrose inverse. But unlike Moore penrose inverse, existence of s-g inverse is not assured in general. In Ref. 10, a necessary and sufficient conditions of existence of s-g invese is given. In the same article, a few characterizations and a determinantal formula for s-g inverse also has been discussed. In 2009, Krishnamoorthy and Vijayakumar11 has defined the concept of s-normal matrices with the help of secondary transopse for a class of complex square matrices. Jayashree12 has defined secondary k-range symmetric fuzzy matrices. Its relation with s-range symmetric fuzzy matrices, k-range fuzzy symmetric matrices and EP matrices are defined.

In this article, we define secondary range symmetric matrices. Several equivalent conditions for a matrix to be secondary range symmetric, is obtained here. Also, the existence of secondary generalized inverse of a secondary range symmetric matrix is discussed.

Below are some useful deifnitions and results related to secondary conjugate transpose.

Definition 2

(Ref. 13) Let An×n. Then the conjugate secondary transpose of A denoted by Aθ and is defined as Aθ=A¯s=cij where cij=a¯nj+1,ni+1.

Definition 3

(Ref. 13) A matrix is said to be secondary normal (s-normal) if AAS=ASA.

Definition 4

(Ref. 10) AS is said to be secondary generalized inverse of A if

AASA=AASAAS=AS
and AAS and ASA are S-symmetric.

Theorem 0.1

(Ref. 10) Given an m×n matrix A. The following statements are equivalent.

  • (i) A has s-cancellation property (i.e., AsAX=0AX=0 and YAAs=0YA=0).

  • (ii) ρAsA=ρAAs=ρA

  • (iii) As exists.

Definition 5

(Ref. 14) A matrix An×n is said to be EP (or range symmetric) if NA=NA.

Meenakshi3 has defined EP in Minkowski space and has given equivalent conditions for a matrix to be range symmetric.

Definition 6

(Ref. 3) A matrix An×n is said to be range symmetric in Minkowski space if and only if NA=NA+.

Here A+ represents the Minkowski adjoint given by A+=GAG where G is the Minkowski metric tensor.

Results

In this section, we define secondary range symmetric matrices which is analogous to that of range symmetric matrices. Some equivalent conditions for a matrix to be range symmetric is also given here.

Definition 7

X is secondary right (left) normalized g inverse of A if AXA=A, XAX=X and AX is S-symmetric. (XA is S-symmetric).

Definition 8

Consider Am×n. The s-transpose of A is defined as As=bij where bij=amj+1,ni+1, 1in,1jm.

Definition 9

A matrix An×n secondary range symmetric if and only if NA=NAS

Theorem 0.2

Let An×n. Then the following conditions are equivalent.

  • (i) A is secondary range symmetric

  • (ii) VA is EP

  • (iii) AV is EP

  • (iv) NA=NAV

  • (v) CA=CAS

  • (vi) AS=BA=AC where B and C are some nonsingular matrices

  • (vii) CA=CVA

  • (viii) CANA=n

  • (ix) CANA=n

Proof 1

A is secondary range symmetricNA=NASNVA=NASVVA is EPVVAVSis EPAV is EP.

Hence 123 holds true.

14

A is secondary range symmetricNA=NASNA=NVAVNA=NAVAV=AVA1AA=AVA1AVA=AAV1AVNA=NAV

This proves the equivalence of 1 and 4.

35

AV is range symmetricCAV=CAVCA=CVACA=CVAVCA=CAS

Hence 3 and 5 are equivalent.

26

VAis range symmetricVA=VAPfor some nonsingularn×nmatrixPAV=VAPVAV=APAS=APA=APS=PSASAS=PS1AAS=KAwhereK=PS1.

Hence 26.

57

CA=CASCA=CVASVCA=CVASVA=AA1VAA=VAA1VAA=VAVA1ACA=CVA

Thus equivalence of 5 and 7 are proved.

2 8.

VA is range symmetricn=CVANGA=CVANA=CAVNA=CANA

Thus equivalence of 2 and 8 are proved.

39

AV is range symmetricn=CAVNAV=n=CAVNAV=CANA

Thus the equivalence of 3 and 9 is proved.

From the following example, it is clear that EP matrices in Minkowski space defined by Meenakshi3 and secondary range symmetric matrices are two different concepts.

Consider a matrix A=1111 where AS=1111. Here, A is secondary normal as well as ρA=ρAAS. The matrix A is secondary range symmetric. However, the matrix is not range symmetric in Minkowski’s space since A+=GAG=1111. It is clear that NANA+.

Let B=1111 and BS=1111. Clearly B is not secondary range symmetric.

Observe that B is range symmetric in Minkowski space. Since, B+=GBG=1111 so that NB=NB+.

Note that AS=VAV=VGA+GV.

A necessary condition for a matrix to be a s-EP (secondary range symmetric) is proved here.

Theorem 0.3

Let An×n. If A is secondary normal and ρA=ρAAS, then A is secondary range symmetric.

Proof 2

Since A is secondary normal, AAS=ASA. Hence ρA=ρAAS=ρASA=ρAS which implies NA=NAAS=NASA=NAS. Thus A is secondary range symmetric.

A relation connecting range symmetric and secondary range symmetric matrices is given below:

Theorem 0.4

Let An×n. Then any two of the following conditions imply the third one.

  • (1) A is EP.

  • (2) A is secondary EP.

  • (3) CA=CVA.

Proof 3

1,23

Since A is EP, CA=CA. By Theorem 0.2, CA=CVA as A is secondary range symmetric. Hence A is secondary EP CA=CVA.

2,31

Since A is s-EP, by Theorem 0.2, VA is range symmetric. Hence CVA=CVA=CAV=CA. Also, By (3), CA=CVA from which it follows that CA=CA. Hence A is range symmetric. Thus (1) holds.

For any square complex matrix A, there exists unique S- symmetric matrices such that A=M+iN where M=12A+AS and N=12iAAS. In the following theorem, an equivalent condition for a matrix A to be secondary range symmetric is obtained interms of M, the S-symmetric part of A.

Theorem 0.5

For An×n, A is secondary range symmetric if and only if NANM where M is the S-symmetric part of A.

Proof 4

If A is secondary range symmetric, then NA=NAS. For xNA, Ax=0 and ASx=0. Hence Mx=0. Thus, NANM, then Ax=0Mx=0 and hence Nx=0. Therefore NANN. Thus NANMNN. Since, both M and N are S-symmetric, they are secondary range symmetric.

NM=NMS=NVMV=NMV
and
NN=NNS=NVNV=NNV

Now, NANMNN=NMVNNVNM+iNV=NAV and ρA=ρA=ρAV. Therefore, NA=NAV=NVAV=NAS. Thus A is secondary range symmetric.

We shall discuss the existence of secondary generalized inverse inverse of a secondary range symmetric matrix. First, we shall prove certain lemmas, to simplify the proof of the main result.

Lemma 1

For an m×n matrix A, if AS exists, then CAS=CAS.

Proof 5

If AS exists, then ASA=ASAS=ASAASSASS and

AS=ASAAS=ASASSASCASCAS.

Further, ρAS=ρA=ρAS. Thus, CAS=CAS.

Lemma 2

For an m×n matrix A, if AS exists, then CAAS is the projection on CAS and ASA is the projection on CAS.

Proof 6

xCA if and only if x=Ay=AASAy=AASx. By definition 2, AAS being S-symmetric, idempotent is the projection on CA. Similarly, xCAS if and only if x=ASAASy=ASAx and ASA is S-symmetric and idempotent. Hence ASA is the projection on CAS.

Theorem 0.6

For an n×n matrix A, the following are equivalent:

  • (1) A is secondary range symmetric and ρA=ρA2.

  • (2) AS exists and AS is secondary range symmetric.

  • (3) There exists a symmetric idempotent matrix E such that AE=EA and CA=CE.

Proof 7

12. Since ρA=ρA2 and A is secondary symmetric, by using Theorem 0.2 we have, ρASA=ρBA2=ρA2=ρA and ρAAS=ρA2C=ρA2=ρA. Thus ρA=ρAAS=ρASA. Hence by Thoerem 0.1, it follows that AS exists, By Lemma 1 and Theorem 0.2, CAS=CAS=CA=CASS=CASS. Hence AS is range symmetric. Thus (2) holds.

23. Since AS exists, by Lemma 1, CAS=CAS, by Theorem 0.2, AS is secondary range symmetric which implies that CAS=CASS. Hence CAS=CASS. By Lemma 2, it follows that ASASS=ASSAS, hence ASAS=AASS. By definition 2, ASA=AAS=E, is S-symmetric, idempotent and AE=EA=A; hence CACE and ρE=ρAAS=ρA, which implies CA=CE. Thus 3 holds.

31. Since, E is S-symmetric and idempotent, ES=E=E2, by lemma 1.1, ES exists and ES=E implies E is the projection on CA. For all reflexive g-inverses Ar of A, AAr=EES=E. Since E is S-symmetric and idempotent, AAr is S-symmetric. Hence by definition 7, An exists and AAn=EES=E which implies EA=A. By hypothesis AE=EA=A. Therefore AAn=AnA=E. Thus both AAn and AnA are S-symmetric. By definition 2, AS exists and E=AAS=ASA. By taking secondary transpose on AE=EA=A, we get EAS=ASE=AS. CASCE=CA and ρAS=ρA. Therefore CA=CAS. By theorem 0.2, A is secondary ramge symmetric. ρAASρAASASS=ρAASS, ρAE=ρAρAAS. Thus ρA=ρAAS=ρA2C=ρA2. Thus (1) holds. Hence the theorem.

Corollary 1

Consider an n×n secondary range symmetric matrix A. Then AS exists if and only if ρA=ρA2.

Proof 8

Since A is secondary range symmetric and ρA=ρA2, the existence of AS follows from Thereom 0.6. Conversly, if A is secondary range symmetric, and AS exists, then by Theorem 0.1 ρA=ρAAS=ρASA and by Theorem 0.2, AS=AC. Hence ρA=ρAAC=ρA2.

Conclusion

As an extension of this work, one can think of defining weighted secondary EP matrices and its characteriations. Also, extending secodary range symmetric matrix to indefinite inner prodcut spaces will open up a new area of research.

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Shenoy D. Secondary range symmetric matrices [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2024, 13:112 (https://doi.org/10.12688/f1000research.144171.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 1
VERSION 1
PUBLISHED 19 Feb 2024
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Reviewer Report 08 Jun 2024
Mehsin Jabel Atteya, Department of Mathematics, Al- Mustansiriyah University, Falastin St, Baghdad, Iraq 
Approved
VIEWS 13
Dear Sir.,
My Report:
1. The Definitions 7, 8 and 9 need to provide examples.
2. In the proof of Theorem 0.4, where the prove of the case (1) and (3) implies to (2).
3. in ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Atteya MJ. Reviewer Report For: Secondary range symmetric matrices [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2024, 13:112 (https://doi.org/10.5256/f1000research.157925.r261048)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 11 Sep 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    11 Sep 2024
    Author Response
    Comments and Responses:

    Comment 1: The Definitions 7, 8 and 9 need to provide examples.
    Response:  Definitions 7,8 and 9 are illustrated with examples- 1, 2 and 3 respectively.
    ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 11 Sep 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    11 Sep 2024
    Author Response
    Comments and Responses:

    Comment 1: The Definitions 7, 8 and 9 need to provide examples.
    Response:  Definitions 7,8 and 9 are illustrated with examples- 1, 2 and 3 respectively.
    ... Continue reading
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12
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Reviewer Report 08 Jun 2024
Pankaj Kumar Manjhi, Department of Mathematics,, Vinoba Bhave University,, Hazaribag,, Jharkhand,, India 
Approved with Reservations
VIEWS 12
I am very delighted to see the scholarly interest in the study of range symmetric matrices. Here are my suggestions for improving the article:
  1. Some definitions (such as definition 1) are not clearly written and
... Continue reading
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CITE
HOW TO CITE THIS REPORT
Manjhi PK. Reviewer Report For: Secondary range symmetric matrices [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2024, 13:112 (https://doi.org/10.5256/f1000research.157925.r274406)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 11 Sep 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    11 Sep 2024
    Author Response
    Comments and Responses:

    Comment 1: Some definitions (such as definition 1) are not clearly written and need to be clarified for better understanding.
    Response: Definition 1 (of the secondary ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 11 Sep 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    11 Sep 2024
    Author Response
    Comments and Responses:

    Comment 1: Some definitions (such as definition 1) are not clearly written and need to be clarified for better understanding.
    Response: Definition 1 (of the secondary ... Continue reading
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27
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Reviewer Report 28 Mar 2024
P Sam Johnson, National Institute of Technology Karnataka, Surathkal, Surathkal, Karnataka,, India 
Approved
VIEWS 27
The paper is well written.  It discusses secondary range symmetric matrices.  It should incorporate the following suggestions / corrections :
Minor points :
(i) First line of abstract should be "is" introduced.
(ii) No uniformity of symbol ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Johnson PS. Reviewer Report For: Secondary range symmetric matrices [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2024, 13:112 (https://doi.org/10.5256/f1000research.157925.r252908)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 04 Apr 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    04 Apr 2024
    Author Response
    I thank reviewer 1 for the critical comments.

    The suggested corrections (typo errors) and the inclusion of latest references in the manuscript and their corresponding information in the body ... Continue reading
  • Author Response 11 Sep 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    11 Sep 2024
    Author Response
    Comments and Responses

    A. Response to Minor points :


    Comment (i): First line of abstract should be "is" introduced.
    Response: The correction has been incorporated.

    Comment (ii): No ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 04 Apr 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    04 Apr 2024
    Author Response
    I thank reviewer 1 for the critical comments.

    The suggested corrections (typo errors) and the inclusion of latest references in the manuscript and their corresponding information in the body ... Continue reading
  • Author Response 11 Sep 2024
    Divya Shenoy, Department of Mathematics, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Udupi, 576104, India
    11 Sep 2024
    Author Response
    Comments and Responses

    A. Response to Minor points :


    Comment (i): First line of abstract should be "is" introduced.
    Response: The correction has been incorporated.

    Comment (ii): No ... Continue reading

Comments on this article Comments (0)

Version 2
VERSION 2 PUBLISHED 19 Feb 2024
Comment
Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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