Invertible Matrices over Idempotent Semirings

Similar documents
On Regularity of Incline Matrices

Determinants - Uniqueness and Properties

1 Multiply Eq. E i by λ 0: (λe i ) (E i ) 2 Multiply Eq. E j by λ and add to Eq. E i : (E i + λe j ) (E i )

Linear Systems and Matrices

Linear Algebra Solutions 1

Boolean Inner-Product Spaces and Boolean Matrices

Apprentice Program: Linear Algebra

Elementary maths for GMT

Matrix Arithmetic. j=1

Linear Algebra review Powers of a diagonalizable matrix Spectral decomposition

COLUMN RANKS AND THEIR PRESERVERS OF GENERAL BOOLEAN MATRICES

RANK AND PERIMETER PRESERVER OF RANK-1 MATRICES OVER MAX ALGEBRA

CS 246 Review of Linear Algebra 01/17/19

New method for finding the determinant of a matrix

0 Sets and Induction. Sets

Diameter of the Zero Divisor Graph of Semiring of Matrices over Boolean Semiring

This operation is - associative A + (B + C) = (A + B) + C; - commutative A + B = B + A; - has a neutral element O + A = A, here O is the null matrix

MATH 433 Applied Algebra Lecture 22: Semigroups. Rings.

MATH 323 Linear Algebra Lecture 6: Matrix algebra (continued). Determinants.

Linear Algebra review Powers of a diagonalizable matrix Spectral decomposition

Matrix Algebra. Matrix Algebra. Chapter 8 - S&B

A Note on Linearly Independence over the Symmetrized Max-Plus Algebra

MULTI-RESTRAINED STIRLING NUMBERS

CHAPTER I. Rings. Definition A ring R is a set with two binary operations, addition + and

THREE LECTURES ON QUASIDETERMINANTS

Tropical Optimization Framework for Analytical Hierarchy Process

Math 320, spring 2011 before the first midterm

PHYS 705: Classical Mechanics. Rigid Body Motion Introduction + Math Review

det(ka) = k n det A.

Matrices. Chapter Definitions and Notations

CHAPTER 2 BOOLEAN ALGEBRA

Elementary Row Operations on Matrices

Math Camp II. Basic Linear Algebra. Yiqing Xu. Aug 26, 2014 MIT

Matrix Algebra & Elementary Matrices

Math Camp Lecture 4: Linear Algebra. Xiao Yu Wang. Aug 2010 MIT. Xiao Yu Wang (MIT) Math Camp /10 1 / 88

1 Linear Algebra Problems

Chapter 1 Matrices and Systems of Equations

Determinants Chapter 3 of Lay

Chapter 1: Systems of linear equations and matrices. Section 1.1: Introduction to systems of linear equations

The variety of commutative additively and multiplicatively idempotent semirings

1182 L. B. Beasley, S. Z. Song, ands. G. Lee matrix all of whose entries are 1 and =fe ij j1 i m 1 j ng denote the set of cells. The zero-term rank [5

Review of linear algebra

Materials engineering Collage \\ Ceramic & construction materials department Numerical Analysis \\Third stage by \\ Dalya Hekmat

CHAPTER 6. Direct Methods for Solving Linear Systems

Fundamentals of Engineering Analysis (650163)

MATH 315 Linear Algebra Homework #1 Assigned: August 20, 2018

= 1 and 2 1. T =, and so det A b d

Matrix Multiplication

DETERMINANTS. , x 2 = a 11b 2 a 21 b 1

Assignment 11 (C + C ) = (C + C ) = (C + C) i(c C ) ] = i(c C) (AB) = (AB) = B A = BA 0 = [A, B] = [A, B] = (AB BA) = (AB) AB

Moore Penrose inverses and commuting elements of C -algebras

Chapter 4 - MATRIX ALGEBRA. ... a 2j... a 2n. a i1 a i2... a ij... a in

Matrices: 2.1 Operations with Matrices

SYMMETRIC DETERMINANTAL REPRESENTATIONS IN CHARACTERISTIC 2

Course 2BA1: Hilary Term 2007 Section 8: Quaternions and Rotations

Week 15-16: Combinatorial Design

Matrices. 1 a a2 1 b b 2 1 c c π

Chapter 1: Systems of Linear Equations and Matrices

Ronalda Benjamin. Definition A normed space X is complete if every Cauchy sequence in X converges in X.

II. Determinant Functions

A Characterization of (3+1)-Free Posets

UMA Putnam Talk LINEAR ALGEBRA TRICKS FOR THE PUTNAM

MATH 422, CSUSM. SPRING AITKEN

. =. a i1 x 1 + a i2 x 2 + a in x n = b i. a 11 a 12 a 1n a 21 a 22 a 1n. i1 a i2 a in

MATH 56A: STOCHASTIC PROCESSES CHAPTER 1

Linear Algebra: Lecture notes from Kolman and Hill 9th edition.

1 Determinants. 1.1 Determinant

On the adjacency matrix of a block graph

Block Diagonal Majorization on C 0

Section 9.2: Matrices.. a m1 a m2 a mn

Lecture Notes in Linear Algebra

Linear Equations and Matrix

William Stallings Copyright 2010

The following two problems were posed by de Caen [4] (see also [6]):

Section Summary. Sequences. Recurrence Relations. Summations Special Integer Sequences (optional)

Chapter 3. Differentiable Mappings. 1. Differentiable Mappings

Intrinsic products and factorizations of matrices

Eigenvalues and Eigenvectors

Matrices and Vectors

Lectures on Linear Algebra for IT

Cheng Soon Ong & Christian Walder. Canberra February June 2017

CS100: DISCRETE STRUCTURES. Lecture 3 Matrices Ch 3 Pages:

Linear Algebra and Matrix Inversion

The Cayley Hamilton Theorem

Linear Algebra Review. Vectors

Appendix A: Matrices

Equality: Two matrices A and B are equal, i.e., A = B if A and B have the same order and the entries of A and B are the same.

arxiv:math/ v2 [math.ac] 1 Dec 2007

A matrix over a field F is a rectangular array of elements from F. The symbol

Solutions to Assignment 3

ICS 6N Computational Linear Algebra Matrix Algebra

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 1 x 2. x n 8 (4) 3 4 2

A note on an Abel-Grassmann's 3-band. 1. Introduction

MATH2210 Notebook 2 Spring 2018

GAUSSIAN ELIMINATION AND LU DECOMPOSITION (SUPPLEMENT FOR MA511)

SOLUTION OF GENERALIZED LINEAR VECTOR EQUATIONS IN IDEMPOTENT ALGEBRA

Chapter 2 - Basics Structures MATH 213. Chapter 2: Basic Structures. Dr. Eric Bancroft. Fall Dr. Eric Bancroft MATH 213 Fall / 60

MATH 106 LINEAR ALGEBRA LECTURE NOTES

ACI-matrices all of whose completions have the same rank

PROBLEMS ON LINEAR ALGEBRA

Transcription:

Chamchuri Journal of Mathematics Volume 1(2009) Number 2, 55 61 http://www.math.sc.chula.ac.th/cjm Invertible Matrices over Idempotent Semirings W. Mora, A. Wasanawichit and Y. Kemprasit Received 28 Sep 2009 Accepted 1 Dec 2009 Abstract: By an idempotent semiring we mean a commutative semiring (S, +, ) with zero 0 and identity 1 such that x + x = x = x 2 for all x S. In 1963, D.E. Rutherford showed that a square matrix A over an idempotent semiring S of 2 elements is invertible over S if and only if A is a permutation matrix. By making use of C. Reutenauer and H. Straubing s theorems, we extend this result to an idempotent semiring as follows: A square matrix A over an idempotent semiring S is invertible over S if and only if the product of any two elements in the same column [row] is 0 and the sum of all elements in each row [column] is 1. Keywords: Idempotent semiring, invertible matrix 2000 Mathematics Subject Classification: 16Y60, 15A09 1 Introduction A semiring is a system (S, +, ) such that (S, +) and (S, ) are semigroups and x (y+z) = x y+x z and (y+z) x = y x+z x for all x, y, z S. A semiring (S, +, ) is called additively [multiplicatively] commutative if x + y = y + x [x y = y x] for all x, y S and it is called commutative if it is both additively and multiplicatively commutative. An element 0 S is called a zero of (S, +, ) if x + 0 = 0 + x = x Corresponding author

56 Chamchuri J. Math. 1(2009), no. 2: W. Mora, A. Wasanawichit and Y. Kemprasit and x 0 = 0 x = 0 for all x S. By an identity of a semiring (S, +, ) we mean an element 1 S such that x 1 = 1 x = x for all x S. Notice that a zero and an identity of a semiring are unique. By an idempotent semiring we mean a commutative semiring with zero 0 and identity 1 such that x + x = x = x 2 for all x S. Example 1.1. Let S [0, 1] be such that 0, 1 S. Define the operations and on S by x y = max{x, y} and x y = min{x, y} for all x, y S. Then (S,, ) is an idempotent semiring having 0 and 1 as its zero and identity, respectively and it may be written as (S, max, min). Example 1.2. Let X be a nonempty set and P(X) the power set of X. Define A B = A B and A B = A B for all A, B P(X). Then (P(X),, ) is an idempotent semiring having and X as its zero and identity, respectively and it may be written as (P(X),, ). Let S be a commutative semiring with zero 0 and identity 1, n a positive integer and M n (S) the set of all n n matrices over S. Then under usual addition and multiplication, M n (S) is an additively commutative semiring. The n n zero matrix 0 n and the n n identity matrix I n over S are the zero and the identity of the semiring M n (S), respectively. If S contains more than one element and n > 1, then M n (S) is not multiplicatively commutative. For A M n (S) and i, j {1,..., n}, let A ij be the element (entry) of A in the i th row and j th column. The transpose of A M n (S) will be denoted by A t, that is, A t ij = A ji for all i, j {1,..., n}. Then for A, B M n (S), (A t ) t = A, (A + B) t = A t + B t and (AB) t = B t A t. A matrix A M n (S) is said to be invertible over S if AB = BA = I n for some B M n (S). Notice that such B is unique and B is called the inverse of A. Also, A is invertible over S if and only if A t is invertible over S. A matrix A M n (S) is called a permutation matrix if every element (entry) of A is either 0 or 1 and each row and each column contains exactly one 1. A permutation matrix A over S is clearly invertible over S and A t is the inverse of A. In 1963, D.E. Rutherford characterized the invertible matrices in M n (S) where S is an idempotent semiring of 2 elements as follows:

Invertible Matrices over Idempotent Semirings 57 Theorem 1.3. [2] Let S be an idempotent semiring of 2 elements. Then a square matrix A over S is invertible over S if and only if A is a permutation matrix. Let S n be the symmetric group of degree n 2, A n the alternating group of degree n and B n = S n A n, that is, A n = { σ S n σ is an even permutation }, B n = { σ S n σ is an odd permutation }. If S is a commutative semiring with zero and identity and n is a positive integer greater than 1, then the positive determinant and the negative determinant of A M n (S) are defined respectively by det + A = ( n ) A iσ(i), σ A n det A = σ B n i=1 ( n ) A iσ(i). Notice that det + I n = 1 and det I n = 0. In 1984, C. Reutenauer and H. Straubing [1] gave the following significant results. i=1 Theorem 1.4. ([1]) Let S be a commutative semiring with zero and identity and n a positive integer 2. If A, B M n (S), then there is an element r S such that det + (AB) = (det + A)(det + B) + (det A)(det B) + r, det (AB) = (det + A)(det B) + (det A)(det + B) + r. Theorem 1.5. ([1]) Let S be a commutative semiring with zero and identity and n a positive integer. For A, B M n (S), if AB = I n, then BA = I n. The purpose of this paper is to extend Theorem 1.3 to an idempotent semiring by making use of Theorem 1.4 and Theorem 1.5. We show that an n n matrix over an idempotent semiring S with zero 0 and identity 1 is invertible over S if and only if (i) the product of any two elements in the same column [row] is 0 and (ii) the sum of all elements in each row [column] is 1.

58 Chamchuri J. Math. 1(2009), no. 2: W. Mora, A. Wasanawichit and Y. Kemprasit 2 Invertible Matrices over Idempotent Semirings The following series of lemmas is needed. The first one is evident. Lemma 2.1. Let S be an idempotent semiring with zero 0 and identity 1. Then the following statements hold. (i) For x, y S, x + y = 0 x = 0 = y. (ii) For x, y S, xy = 1 x = 1 = y. Lemma 2.2. Let S be an idempotent semiring and n a positive integer 2. If A M n (S) is invertible over S, then det + A + det A = 1. Proof. Let B M n (S) be such that AB = BA = I n. By Theorem 1.4, there exists an element r S such that det + (AB) = (det + A)(det + B) + (det A)(det B) + r, det (AB) = (det + A)(det B) + (det A)(det + B) + r. But det + (AB) = det + I n = 1 and det (AB) = det I n = 0, so we have that 1 = (det + A)(det + B) + (det A)(det B) + r, 0 = (det + A)(det B) + (det A)(det + B) + r. The last equality and Lemma 2.1(i) yield the result that Then (det + A)(det B) = (det A)(det + B) = r = 0. 1 = (det + A)(det + B) + (det A)(det B) = (det + A)(det + B) + (det A)(det B) + (det + A)(det B) + (det A)(det + B) = (det + A + det A)(det + B + det B). By Lemma 2.1(ii), we have that det + A + det A = 1, as desired. Theorem 2.3. Let S be an idempotent semiring with zero 0 and identity 1, n a positive integer and A M n (S). Then A is invertible over S if and only if (i) the product of any two elements in the same column is 0 and (ii) the sum of all elements in each row is 1.

Invertible Matrices over Idempotent Semirings 59 Proof. By Lemma 2.1(ii), the theorem is obviously true for n = 1. Let n > 1 and assume that A is invertible over S. Let B M n (S) be such that AB = BA = I n. Let i, j {1,..., n} be distinct. Then 0 = (I n ) ij = (AB) ij = A ik B kj. It follows from Lemma 2.1(i) that A ik B kj = 0 for all k {1,..., n}. This proves that A lk B kt = 0 for all l, t, k {1,..., n} such that l t. (1) Then for k {1,..., n}, A ik A jk = (A ik A jk )1 = (A ik A jk )(BA) kk ( n ) = A ik A jk B kt A tk = A ik A jk B kt A tk = A ik A jk B kj A jk + = (A ik B kj )A jk + A ik A jk B kt A tk t j A ik (A jk B kt )A tk t j = 0 + 0 = 0 from (1). Hence (i) is proved. From Lemma 2.2, we have that det + A + det A = 1. By (i), we have that A 1k1 A 2k2... A nkn = 0 if k 1,..., k n {1,..., n} are not all distinct. (2) Then ( n A 1k )( n A 2k )... ( n ) A nk = A 1k1 A 2k2... A nkn k 1,...,k n {1,...,n} = A 1σ(1) A 2σ(2)... A nσ(n) from (2) σ S n = det + A + det A = 1.

60 Chamchuri J. Math. 1(2009), no. 2: W. Mora, A. Wasanawichit and Y. Kemprasit Hence by Lemma 2.1(ii), A 1k = A 2k = = A nk = 1. Therefore (ii) is proved. Conversely, assume that (i) and (ii) hold. Claim that AA t = I n. If i {1,..., n}, then from (ii), (AA t ) ii = A ik A t ki = A ik A ik = A ik = 1. Also, for distinct i, j {1,..., n}, from (i) (AA t ) ij = A ik A t kj = A ik A jk = 0. This shows that AA t = I n. Therefore by Theorem 1.5, A t A = I n. Hence A is invertible over S. Since A is invertible over S if and only if A t is invertible over S, the following result is obtained directly from Theorem 2.3. Corollary 2.4. Let S be an idempotent semiring with zero 0 and identity 1, n a positive integer and A M n (S). Then A is invertible over S if and only if (i) the product of any two elements in the same row is 0 and (ii) the sum of all elements in each column is 1. Corollary 2.5. Let (S, max, min) be the idempotent semiring defined as in Example 1.1, n a positive integer and A M n (S). Then A is invertible over S if and only if A is a permutation matrix. Proof. Assume that A is invertible over S. Let i {1,..., n}. If there are distinct l, t {1,..., n} such that A il 0 and A it 0, then A il A it = min{a il, A it } = 0 which is contrary to Corollary 2.4. By Theorem 2.3, A i1 A in = 1. Then 1 = max{a i1,..., A in }, so A ik = 1 for some k {1,..., n}. This shows that every row of A contains only one nonzero element which is 1. We can show similarly by Theorem 2.3 and Corollary 2.4 that every column of A contains only one nonzero element which is 1. Hence A is a permutation matrix. As mentioned previously, a permutation matrix is invertible.

Invertible Matrices over Idempotent Semirings 61 Remark 2.6. From the proof of Theorem 2.3, we have that if A M n (S) is invertible over S, then the inverse of A is A t. It can be seen that Theorem 1.3 is a special case of Corollary 2.5. Example 2.7. Let (P(X),, ) be the idempotent semiring defined in Example 1.2. Let X 1, X 2,..., X n be subsets of X such that X = X 1 X 2... X n and X 1,..., X n are pairwise disjoint. By Theorem 2.3, X 1 X 2 X n 1 X n X n X 1 X n 2 X n 1 A = M n ((P(X),, )) X 3 X 4 X 1 X 2 X 2 X 3 X n X 1 is invertible over (P(X),, ). By Remark 2.6, the inverse of A is X 1 X n X 3 X 2 X 2 X 1 X 4 X 3. X n 1 X n 2 X 1 X n X n X n 1 X 2 X 1 References [1] C. Reutenauer and H. Straubing, Inversion of matrices over a commutative semiring, J. Algebra, 88(1984), 350 360. [2] D.E. Rutherford, Inverses of Boolean matrices, Proc. Glasgow Math. Assoc., 6(1963), 49 53. W. Mora A. Wasanawichit 1 and Y. Kemprasit 2 Department of Mathematics, Department of Mathematics, Faculty of Science, Faculty of Science, Prince of Songkla University, Chulalongkorn University, Songkhla 90110, Thailand Bangkok 10330, Thailand Email: k winita@hotmail.com Email: 1 amorn.wa@chula.ac.th and 2 yupaporn.k@chula.ac.th