KMS º½ÇÐȸ Æ÷Ç×°ø´ë 2000. 4. 22. (Åä)
On Linear Preservers of Several
Multivariate Majorization
Contents :
(0) Abstract
(1) Definitions
(2) History
(3) Previous Results
(4) Main Results
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KMS º½ÇÐȸ Æ÷Ç×°ø´ë 2000. 4. 22. (Åä)
(0) Abstract
In this paper, we characterize linear operators on real matrices that preserve multivariate majorization. We place no additional restrictions on the linear operator.
(1) Definitions
Majorization
is a topic of much
interest in various areas of mathematics and statistics. (1929³â Hardy, Littlewood.
Polya's : convex ft. g °¡ ÀÏ ÇÊ¿äÃæºÐÁ¶°Ç) (1923³â Schur's work on Hadamard ºÎµî½Ä)(1905³â °æÁ¦Çп¡¼
Lorenz curve)- ´ë¼ö, ÇØ¼®, ±âÇÏ, ¼öÄ¡ÇØ¼®, Åë°è, °æÁ¦µî
If and
are nonincreasing
-vectors of nonnegative real numbers such that
for
with equality at
, then we say that
is (vector)
majorized
by
and write
. Equivalently, if two row vectors have the relationship
then there is a doubly stochastic matrix
such that
. (ÀÌ ¿Ü¿¡
¿¬¼ÓÇÔ¼ö version, ¹«ÇÑ ¼ö¿ version µîµµ ÀÖÀ½)
Our interest is in the subject of majorization for matrices. The MATRIX VERSION
of majorization is that an real matrix
is multivariate majorized by
if there is a DOUBLY STOCHASTIC matrix
such that
.
G. Dahl's Definition in Matrix majorization, Linear Algebra Appl. 288:53-73(1999)--- "Row Stochastic Matrix"
A linear operator is said to preserve
a relation R on
if
R
implies R.
* The topic of linear preservers (ºÎ·Ï)
(2) History
In
"Majorization
and inequalities in matrix theory", Linear Algebra Appl., V.199:17-67 (1994), T. Ando characterized the linear
operators which preserve vector majorization (equivalently, that preserve multivariate majorization
on . We
shall characterize all linear operators which preserve multivariate majorization
with no conditions on m, n, or T.
*. "Linear Operators Strongly Preserving Multivariate Majorization " (with Y.H. Lee) Proc. Workshops in Pure Math. V. 17, part I (1997) pp.113-118.
**. Linear operators strongly preserving multivariate majorization with $T(I)=I$. Kyungpook Math. J. 39 (1999), no. 1, 191--194. (with L. Beasley and Y.-H. Lee) (Reviewer: Chi-Kwong Li) 15A04 (15A21 15A30)
***. A proof of conjecture on strong preservers of multivariate majorization" (with L. Beasley), preprint.
C.-K. Li, B.-S. Tam. N.-K. Tsing, Linear maps preserving the set of doubly stochastic matrices, Preprint(1999)'s Main Result : TFAE
(a) T(DS(n)) = DS(n)
(b) T(P(n)) = P(n)
(c) TÀÇ ¸ð¾çÀº for some P, Q in P(n)
µû¶ó¼
then So let
·Î ³õÀ¸¸é Á¶°Ç T(I) =I¸¦ ¾ø¾Ù ¼ö ÀÖ´Ù°í »ý°¢ÇßÀ½.
**** Linear Operators Preserving Multivariate Majorization " (with L. Beasley), Linear Algebra and its Applications 304 141-159 (2000) ( TODAY!! )
Linear Operators Strongly Preserving Matrix Majorization " (with Y.-H. Lee and L. Beasley), Preprint
(3) Previous Results
NOTE: ¾Æ·¡¿¡¼ ?? Àº ½Ç¼ö R À» ÀÇ¹Ì ÇÑ ´ä´Ï´Ù.
Áï, Àº
ÀÔ´Ï´Ù.
(editor ÀÇ error)
(´ë¿ì¼ø¼ö¼öÇÐ 1997) Theorem 2.11 Let for
. Then
is a multivariate majorization strong preserver on
if one of the following or a composition of the following holds :
(1) for any nonzero scalar
, an invertible matrix
and a permutation matrix
;
(2) for a linear functional
.
(°æºÏ¼öÇÐÀú³Î 1999) Theorem 3.1 If strongly preserves multivariate majorization and
(i.e.,
preserves nonnegative matrices), then
a permutation matrix
.
(4) Main Results
By Birkhoff's Theorem , DS(n) is the convex hull of the set P(n) of n by n permutation matrices.
We now define two linear mappings, which are fixed throughout the paper.
Definition 2.1
Define
by
where
. That is, is the column vector whose
th component is the
th row sum of
, equivalently
. Define
by
where
Thus,
is the diagonal matrix whose main diagonal is the vector
.
Lemma 2.2
If is any element of
and
is any element of
, then
and
D¿Í rÀÌ doubly stochastic Çà·Ä °öÇÑ °Í¿¡ ºÒº¯
Proof.
Let and
. Let
. Then the
entry of
is
That is, . Similarly
.
Lemma 2.4
Let and the linear operator
be defined by
, then
preserves multivariate majorization.
MAIN THEOREM 2.5
Let be a linear operator on
. Then TFAE:
(i) preserves multivariate majorization.
(ii) Either
(a) There exist matrices and
such that
for all
or
(b) There exist matrices and a permutation matrix
such that
for all
.
The remaining part of this article is devoted to the proof of the Main Theorem.
We state here the row version of Ando's characterization.
Lemma 2.6 (Ando, Corollary 2.7 ) Let preserve (vector) majorization, then either
(i) for some
or
(ii) for some
and
.
Lemma 2.7
Let the linear operator on
preserve multivariate majorization and
. Then
preserves multivariate majorization.
Áõ¸í : T´Â M.M.P. Àε¥ S°¡ ¾Æ´Ï¶ó¸é ¸ð¼øÀÓ.
¿©±â¼ ¿ì¼± T(X)ÀÇ j-th row¸¦ »ý°¢ÇÑ´Ù.
Lemma 2.8
If
preserves multivariate majorization, then
defined by
the th row of T [ 0 ... 0 x 0 ... 0 ]^t
i^th row
preserves (vector) majorization.
¿©±â¼ º¸ÀÌ´Â °ÍÀº
°¡ m.m.p.À̹ǷÎ
´Â °¢°¢ÀÇ row vector maj.À» º¸Á¸ÇÑ´Ù´Â °Í. ±×·¯¸é ÀÌ¾î¼ T°¡ linear À̹ǷÎ
´ÙÀ½À» °®´Â´Ù.
Lemma 2.9
If preserves multivariate majorization, then for
and
there exist
vectors
, permutation matrices
, and scalars
and
with or
,
and
, such that
ÀÌÁ¦ ÀÌ imageÀÇ ¸ð¾çÀ» ´Ü¼øÈ÷ Çϱâ À§ÇØ °è¼öÀÇ ¼ºÁúµéÀÇ °¡´É¼ºÀ» ÁÙ¿©°£´Ù.
Lemma 2.10
Suppose for some is not a multiple of
, we have
If preserves multivariate majorization then necessarily
for all
.
Lemma 2.12 If preserves multivariate majorization and
has at least two nonzero rows, one of which, say the th, is
for some nonzero vector
which is not a multiple of
, and the other, say the
th, is
for some
and
, then
.
ÀÌÁ¦ µÎ °³ÀÇ ¸ð¾çÀÌ µ¿½Ã¿¡ ³ªÅ¸³ª¸é ¸ð¼øÀÓÀ» º¸ÀδÙ.
Lemma 2.13
If
for some which is not a multiple of
, then
does not preserve multivariate majorization.
´ÙÀ½ÀÇ
µÎ Lemma´Â and
ÀÓÀ» º¸¿©ÁØ´Ù.
Lemma 2.15
Let be defined by
where . If
preserves multivariate majorization, then
.
Lemma 2.16
Let be defined by
where . If
preserves multivariate majorization, then
.
Now we can prove Main Theorem.
MAIN THEOREM 2.5
Let be a linear operator on
. Then TFAE:
(i) preserves multivariate majorization.
(ii) Either
(a) There exist matrices and
such that
for all
or
(b) There exist matrices and a permutation matrix
such that
for all
.
PROOF
From the Corollary (2.14), T(X) must have one of the forms:
Either
(i) There exist matrices and
such that
for all
or
(ii) T(X) =[] +
for some
,
in
, and
for all
in
.
In the second case, from the previous Lemmas 2.15, 2.16 and 2.7 we have
T(X) =[] +
=
for some matrix
and permutation matrix
. QED.
(2) Linear Preserver Problems
Let K be an algebraic structure and let M(K) denote the vector space of all m*n matrices over K.
Over the last century, a great deal of effort has been devoted to the following problem. Characterize those linear operators T : M --> M which leave a function or set invariant. We call this a linear preserver problem.
The most typical and oldest type of linear preserver problem is as follows:
(1)ÀÏ ¶§ ¾Æ·¡
´Â?
F ´Â scalar valued, matrix valued or set-valued function on M.
It is clear that the set of all such matrix-valued linear operators T is a multiplicative semigroup with an identity.
The study of these operators began in 1897 when Frobenius characterized the linear operators that preserve the determinant over two different sets of matrices :
Frobenius proved that the semigroup of linear operators that preserve the determinant consists of linear transformations of the form
(1.1)
(i) C °¡ complex field ÀÎ °æ¿ì, det (UV) = 1
(ii) M ÀÌ real symmetric matrices ÀÎ °æ¿ì,
U = kQ, V = Q^T and det(Q).
In 1925, Schur extended and improved the result for Case (i) as follows. Let ?(A) be the (nCk)^2 - tuple of the k-th order (i.e., kxk) minors of A in some order where k ? 3 is fixed.
Schur proved that if ?(T(A)) = S(?(A)), for a fixed nonsingular matrix S, then T has one of the two forms in (1.1) (without the restriction det (UV) = 1).
In 1949, Dieudonné showed that if F is any field and if T is a semilinear operator mapping M(F) onto itself, which holds the cone det (A) = 0 invariant, then T is of the form
where ? is an automorphism of the field and a_ij is the (i,j) entry of A.
We will call those operators T in (1.1)
(U,V)-operators.
Other interesting results of this type include:
(a) [59] If M is is the set of all nxn Hermitian matrices,
and F(A) = Inertia (A), then T is a (U,V)-operator
where U = V*, the conjugate transpose of U, for
some nonsingular matrix V ? M(C).
(b) [43] If M = M (C) and F(A) = { x*Ax| x ? C , x*x = 1},
then T is a (U,V)-operator where U = V* for some
unitary matrix U.
Consequences and recent work of this type can be found in [3, 17, 22, 23, 24, 28, 48, 53, 54] for preservers of generalized matrix functions, in [33, 39, 40, 50, 55] for inertia preservers, and in [44, 45, 46, 47] for numerical range and radius preservers.
We note that many linear preserver problems can be reduced to the problem of characterizing linear operators on M(K) which map the set of rank 1 matrices into itself.
A semiring (Gregory and Pullman [32] or Kim [41]) is a binary system (S, +, ?) such that (S, +) is an Abelian monoid (identity 0), (S, ?) is a monoid (identity 1), ? distributes over +, 0 ? s = s ? 0 = 0 for all s in S, and 1 $ 0. If 0 is the only element to have an additive inverse, then S is antinegative.
The Second type of linear preserver problem is:
(2) Let ÀÏ ¶§
´Â s.t
Some examples of this type of problem with
appropriate characterizations.
(a) [51] If M = M(C), B is the set of unitary
matrices in M(C) and T(B) ¡ø B, then T is a
(U,V)-operator for some unitary matrices U and V.
(b) [4, 11, 13, 53] Suppose M = M(C) and B is the
set of all rank-k matrices. If T(B)¡øB, then T is
a (U,V)-operator for some nonsingular matrices
U and V.
(c) [19] Suppose M = M(S) where S is an
antinegative semiring with no zero divisors, and B
is the set of all idempotent matrices in M(S). If
T(B) = B, then T is a (U,V)-operator where
U = V for some invertible matrix V in M(S).
We may note that, in the first example, we were simply characterizing the structure of all linear operators T that map the unitary group into itself.
There is an extensive literature concerning the characterization of linear operators of type [II]. Further results may be found in [1, 2, 6, 7, 8, 9, 30, 49] for sets defined by rank, in [15, 16, 18, 21, 29] for sets defined by graph theoretic properties, i.e., irreducibility or strong connectivity, term rank, etc., and in [10, 20, 25, 35, 56, 57] for characterization of preservers of other sets.
The last and 3rd type of linear preserver problem
is: (3) ÀÎ
´Â?
Some of the major results are:
(a) [5, 61] Suppose M = M (C) and A ~ D if A
and D commute. If T is a nonsingular linear
operator on M satisfying T(A) ~ T(D) whenever
A ~ D, then T is of the form
or
for some nonsingular matrix X ? M (C) ; l ? C
and linear functional f on M.
(b) [62] Suppose M = M (C) and A ~ D if A and
D are similar.
If T is a linear operator on M satisfying
T(A)~T(D) whenever A~D, then T is of the form
or
for some nonsingular matrix X ? M (C), l ? C and
linear functional f on M.
Further studies of the above type are found in [36, 61].
In [26] and [27], Chan, Lim and Tan gave the following characterization for those linear operators that preserve idempotent and tripotent matrices.
THE END
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Âü°í ÀÚ·á:
A. W. Marshall and I. Olkin, Inequalities: Theory of Majorization and Its Applications, Academic Press, 1979
T. Ando, Majorization, doubly stochastic matrices and comparison of eigenvalues, Linear Algebra Appl. V.118:163-248 (1989).
T. Ando, Majorization and inequalities in matrix theory, Linear Algebra Appl., V.199:17-67 (1994)
J. V. Bondar, Comments and complements to: Inequalities: Theory of Majorization and Its Appl. by Albert W. Marshall and Ingram Olkin, Linear
Algebra Appl. V.199:115-130(1994)
G. Dahl, Matrix majorization, Linear Algebra Appl. 288:53-73(1999)
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