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Abstract
We prove new inequalities and equalities for the generalized and the joint spectral radius (and their essential versions) of Hadamard (Schur) geometric means of bounded sets of positive kernel operators on Banach function spaces. In the case of non-negative matrices that define operators on Banach sequences, we obtain additional results. Our results extend the results of several authors that appeared relatively recently.
1. Introduction
In [Citation1], X. Zhan conjectured that, for non-negative matrices A and B, the spectral radius
of the Hadamard product satisfies
(1)
(1) where AB denotes the usual matrix product of A and B. This conjecture was confirmed by K.M.R. Audenaert in [Citation2] by proving
(2)
(2) These inequalities were established via a trace description of the spectral radius. Soon after, inequality (Equation1
(1)
(1) ) was reproved, generalized and refined in different ways by several authors ([Citation3–12]). Using the fact that the Hadamard product is a principal submatrix of the Kronecker product, R.A. Horn and F. Zhang proved in [Citation6], the inequalities
(3)
(3) Applying the techniques of [Citation6], Z. Huang proved that
(4)
(4) for
non-negative matrices
(see [Citation7]). A.R. Schep was the first one to observe that the results from [Citation13,Citation14] are applicable in this context (see [Citation11,Citation12]). He extended inequalities (Equation2
(2)
(2) ) and (Equation3
(3)
(3) ) to non-negative matrices that define bounded operators on sequence spaces (in particular on
spaces,
) and proved in [Citation11, Theorem 2.7] that
(5)
(5) (note that there was an error in the statement of [Citation11, Theorem 2.7], which was corrected in [Citation8,Citation12]). In [Citation8], the second author of the current paper extended the inequality (Equation4
(4)
(4) ) to non-negative matrices that define bounded operators on Banach sequence spaces (see below for the exact definitions) and proved that the inequalities
(6)
(6) and
(7)
(7) hold, where
. Moreover, he generalized these inequalities to the setting of the generalized and the joint spectral radius of bounded sets of such non-negative matrices.
In [Citation11, Theorem 2.8], A.R. Schep proved that the inequality
(8)
(8) holds for positive kernel operators on
spaces. Here
denotes the Hadamard geometric mean of operators A and B. In [Citation5, Theorem 3.1], R. Drnovšek and the second author, generalized this inequality and proved that the inequality
(9)
(9) holds for positive kernel operators
on an arbitrary Banach function space L. In [Citation10], the second author refined (Equation9
(9)
(9) ) and showed that the inequalities
(10)
(10) hold, where
for
. In [Citation15, Theorem 3.2], the second author showed that (Equation10
(10)
(10) ) holds also for the essential radius
under the additional condition that L and its Banach dual
have to order continuous norms. Formally, here and throughout the article
for j = 1 (eventhough I might not be a well-defined kernel operator). In particular, the following kernel version of (Equation3
(3)
(3) ) holds:
(11)
(11) Several additional closely related results, generalizations and refinements of the above results were obtained in [Citation3,Citation15–17].
In [Citation9, Theorem 3.4] and [Citation15, Theorem 3.5], the second author generalized inequalities (Equation9(9)
(9) ) and (Equation11
(11)
(11) ) and their essential version to the setting of the generalized and the joint spectral radius (and their essential versions) of bounded sets of positive kernel operators on a Banach function space (see also Theorems 2.3 and 2.4).
The rest of the article is organized in the following way. In Section 2, we recall definitions and results that we will use in our proofs. In Section 3, we extend the main results of [Citation15] by proving new inequalities and equalities for the generalized and the joint spectral radius (and their essential versions) of Hadamard (Schur) geometric means of bounded sets of positive kernel operators on Banach function spaces (Theorems 3.1(i), 3.2(i), 3.3, 3.4 and 3.6(i)). In the case of non-negative matrices that define operators on Banach sequences we prove further new inequalities that extend the main results of [Citation8] (Theorems 3.2(ii), 3.5 and 3.6(ii)). All the inequalities mentioned above are very special instances of our results. In Section 4, we prove new results on geometric symmetrization of bounded sets of positive kernel operators on and on weighted geometric symmetrization of bounded sets of non-negative matrices that define operators on
, which extend some results from [Citation3,Citation16,Citation18].
2. Preliminaries
Let µ be a σ-finite positive measure on a σ-algebra of subsets of a non-void set X. Let
be the vector space of all equivalence classes of (almost everywhere equal) complex measurable functions on X. A Banach space
is called a Banach function space if
,
, and
imply that
and
. Throughout the article, it is assumed that X is the carrier of L, that is, there is no subset Y of X of strictly positive measure with the property that
a.e. on Y for all
(see [Citation19]).
Let R denote the set for some
or the set
of all natural numbers. Let
be the vector lattice of all complex sequences
. A Banach space
is called a Banach sequence space if
,
and
imply that
and
. Observe that a Banach sequence space is a Banach function space over a measure space
, where µ denotes the counting measure on R. Denote by
the collection of all Banach sequence spaces L satisfying the property that
and
for all
. For
the set R is the carrier of L.
Standard examples of Banach sequence spaces are Euclidean spaces, spaces for
, the space
of all null convergent sequences (equipped with the usual norms and the counting measure), while standard examples of Banach function spaces are the well-known spaces
(
) and other less known examples such as Orlicz, Lorentz, Marcinkiewicz and more general rearrangement-invariant spaces (see e.g. [Citation20–22] and the references cited there), which are important, e.g. in interpolation theory and in the theory of partial differential equations. Recall that the cartesian product
of Banach function spaces is again a Banach function space, equipped with the norm
.
If is a decreasing sequence and
, then we write
. A Banach function space L has an order continuous norm, if
implies
as
. It is well known that spaces
,
, have order continuous norm. Moreover, the norm of any reflexive Banach function space is order continuous. In particular, we will be interested in Banach function spaces L such that L and its Banach dual space
have order continuous norms. Examples of such spaces are
,
, while the space
is an example of a non-reflexive Banach sequence space, such that L and
have order continuous norms.
By an operator on a Banach function space L, we always mean a linear operator on L. An operator A on L is said to be positive if it maps non-negative functions to non-negative ones, i.e. , where
denotes the positive cone
. Given operators A and B on L, we write
if the operator A−B is positive.
Recall that a positive operator A is always bounded, i.e. its operator norm
(12)
(12) is finite. Also, its spectral radius
is always contained in the spectrum.
An operator A on a Banach function space L is called a kernel operator if there exists a -measurable function
on
such that, for all
and for almost all
,
One can check that a kernel operator A is positive iff its kernel a is non-negative almost everywhere.
Let L be a Banach function space such that L and have order continuous norms and let A and B be positive kernel operators on L. By
we denote the Hausdorff measure of non-compactness of A, i.e.
where
. Then
,
,
and
for
. Also
implies
(see e.g. [Citation23, Corollary 4.3.7 and Corollary 3.7.3]). Let
denote the essential spectral radius of A, i.e. the spectral radius of the Calkin image of A in the Calkin algebra. Then
(13)
(13) and
. Recall that if
, then
and
, where
denotes the adjoint of A. Note that equalities (Equation13
(13)
(13) ) and
are valid for any bounded operator A on a given complex Banach space L (see e.g. [Citation23, Theorem 4.3.13 and Proposition 4.3.11]).
Observe that (finite or infinite) non-negative matrices, that define operators on Banach sequence spaces, are a special case of positive kernel operators (see e.g. [Citation3,Citation5,Citation8,Citation24,Citation25], and the references cited there).
It is well known that kernel operators play a very important, often even central, role in a variety of applications from differential and integro-differential equations, problems from physics (in particular from thermodynamics), engineering, statistical and economic models, etc (see e.g. [Citation26–29] and the references cited there). For the theory of Banach function spaces and more general Banach lattices we refer the reader to the books [Citation19,Citation20,Citation23,Citation30,Citation31].
Let A and B be positive kernel operators on a Banach function space L with kernels a and b respectively, and . The Hadamard (or Schur) product
of A and B is the kernel operator with kernel equal to
at point
which can be defined (in general) only on some order ideal of L. Similarly, the Hadamard (or Schur) power
of A is the kernel operator with kernel equal to
at point
which can be defined only on some order ideal of L.
Let be positive kernel operators on a Banach function space L, and
positive numbers such that
. Then the Hadamard weighted geometric mean
of the operators
is a positive kernel operator defined on the whole space L, since
by the inequality between the weighted arithmetic and geometric means.
A matrix is called non-negative if
for all
. For notational convenience, we sometimes write
instead of
.
We say that a non-negative matrix A defines an operator on L if for all
, where
. Then
for all
and so A defines a positive kernel operator on L.
Let us recall the following result which was proved in [Citation13, Theorem 2.2] and [Citation14, Theorem 5.1 and Example 3.7] (see also e.g. [Citation9, Theorem 2.1]).
Theorem 2.1
Let be positive kernel operators on a Banach function space L and let
,
,…,
are positive numbers.
If
, then the positive kernel operator
(14)
(14) satisfies the following inequalities
(15)
(15)
(16)
(16)
(17)
(17) If, in addition, L and
have order continuous norms, then
(18)
(18)
(19)
(19)
If
,
and
are non-negative matrices that define positive operators on L, then A from (Equation14
(14)
(14) ) defines a positive operator on L and the inequalities (Equation15
(15)
(15) ), (Equation16
(16)
(16) ) and (Equation17
(17)
(17) ) hold.
The following result is a special case of Theorem 2.1.
Theorem 2.2
Let be positive kernel operators on a Banach function space L and
positive numbers.
If
, then
(20)
(20) and
(21)
(21) If, in addition, L and
have order continuous norms, then
(22)
(22) and
(23)
(23)
If
,
and if
are non-negative matrices that define positive operators on L, then
defines a positive operator on L and (Equation20
(20)
(20) ) and (Equation21
(21)
(21) ) hold.
If
,
and if
are non-negative matrices that define operators on L, then
defines an operator on L and the following inequalities hold
(24)
(24)
(25)
(25)
(26)
(26)
Let Σ be a bounded set of bounded operators on a complex Banach space L. For , let
The generalized spectral radius of Σ is defined by
(27)
(27) and is equal to
The joint spectral radius of Σ is defined by
(28)
(28) Similarly, the generalized essential spectral radius of Σ is defined by
(29)
(29) and is equal to
The joint essential spectral radius of Σ is defined by
(30)
(30) It is well known that
for a precompact nonempty set Σ of compact operators on L (see e.g. [Citation32–34]), in particular for a bounded set of complex
matrices (see e.g. [Citation35–39,Citation40]). This equality is called the Berger–Wang formula or also the generalized spectral radius theorem (for an elegant proof in the finite-dimensional case see [Citation36]). It is known that also the generalized Berger-Wang formula holds, i.e, that for any precompact nonempty set Σ of bounded operators on L we have
(see e.g. [Citation32–34]). Observe also that it was proved in [Citation32] that in the definition of
one may replace the Haussdorf measure of non-compactness by several other seminorms, for instance, it may be replaced by the essential norm.
In general, and
may differ even in the case of a bounded set Σ of compact positive operators on L (see [Citation39] or also [Citation9]). Also, in [Citation41] the reader can find an example of two positive non-compact weighted shifts A and B on
such that
. As already noted in [Citation33] also
and
may in general be different.
The theory of the generalized and the joint spectral radius has many important applications for instance to discrete and differential inclusions, wavelets, invariant subspace theory (see e.g. [Citation33–36,Citation42] and the references cited there). In particular, plays a central role in determining stability in convergence properties of discrete and differential inclusions. In this theory, the quantity
is known as the maximal Lyapunov exponent (see e.g. [Citation42]).
We will use the following well-known facts that hold for all :
(31)
(31) where
and
.
Let be bounded sets of positive kernel operators on a Banach function space L and let
be positive numbers such that
. Then the bounded set of positive kernel operators on L, defined by
is called the weighted Hadamard (Schur) geometric mean of sets
. The set
is called the Hadamard (Schur) geometric mean of sets
.
The following result that follows from Theorem 2.1(i) was established in ([Citation9, Theorem 3.3] and [Citation15, Theorems 3.1 and 3.8].
Theorem 2.3
Let be bounded sets of positive kernel operators on a Banach function space L and let
be positive numbers such that
. If
and
, then
(32)
(32) and
(33)
(33) If, in addition, L and
have order continuous norms, then (Equation32
(32)
(32) ) and (Equation33
(33)
(33) ) hold also for each
.
The following theorem [Citation15, Theorem 3.5] was one of the main results in [Citation15].
Theorem 2.4
Let Ψ and Σ be bounded sets of positive kernel operators on a Banach function space L. If and
, then we have
(34)
(34)
(35)
(35) If, in addition, L and
have order continuous norms, then (Equation34
(34)
(34) ) and (Equation35
(35)
(35) ) hold also for each
.
Given , let
be bounded sets of non-negative matrices that define operators on L and let
be positive numbers such that
. Then the set
is a bounded set of non-negative matrices that define operators on L by Theorem 2.2(ii). By applying Theorem 2.1(ii), one can also prove the following result in a similar way as [Citation15, Theorem 3.8]. We omit the details of the proof.
Theorem 2.5
Given , let
be bounded sets of non-negative matrices that define operators on L. Let
be positive numbers such that
,
and
. Then Inequalities (Equation32
(32)
(32) ) hold.
In particular, if , then
(36)
(36)
3. Further inequalities and equalities
In [Citation15] and later it remained unnoticed that several inequalities in Theorem 2.4 are in fact equalities, which are established in the following result.
Theorem 3.1
Let Ψ and Σ be bounded sets of positive kernel operators on a Banach function space L and let be positive numbers such that
.
If
and
, then
(37)
(37) and
(38)
(38) If, in addition, L and
have order continuous norms, then (Equation37
(37)
(37) ) and (Equation38
(38)
(38) ) hold also for each
.
If
,
,
,
and if Ψ is a bounded set of non-negative matrices that define operators on L, then
(39)
(39) where in (Equation39
(39)
(39) ) the Hadamard products in
and in
are taken m times, and
(40)
(40)
Proof.
(i) To prove (Equation37(37)
(37) ) first observe that
, since
for all
. It follows that
by Theorem 2.3 and so
.
Similary, to prove (Equation38(38)
(38) ) observe that
, since
for all
and
. It follows that
by (Equation35
(35)
(35) ), which proves (Equation38
(38)
(38) ). It is proved similarly that (Equation37
(37)
(37) ) and (Equation38
(38)
(38) ) hold also for each
in the case when L and
have order continuous norms.
(ii) For the proof of (Equation39(39)
(39) ) observe that
, since
for all
. By Theorem 2.5, Inequalities (Equation39
(39)
(39) ) follow. Inequalities (Equation40
(40)
(40) ) are proved in a similar way.
Remark 1
Equalities (Equation38(38)
(38) ) show that the third inequality in (Equation34
(34)
(34) ) and the second and third inequality in (Equation35
(35)
(35) ) are in fact equalities.
This also implies that (only) [Citation15, Remark 3.6] is false. Indeed, [Citation8, Example 3.11] is not an example that would support the claim stated in [Citation15, Remark 3.6]. The second author of this article regrets for stating this false remark in [Citation15].
The following result extends Inequalities (Equation17(17)
(17) ) and (Equation32
(32)
(32) ) and Theorem 2.5.
Theorem 3.2
Let be bounded sets of positive kernel operators on a Banach function space L and let
be positive numbers.
If
,
and
, then
(41)
(41) If, in addition, L and
have order continuous norms, then Inequalities (Equation41
(41)
(41) ) hold also for each
.
If
,
,
and
are bounded sets of non-negative matrices that define positive operators on L, then Inequalities (Equation41
(41)
(41) ) hold.
In particular, if
are bounded sets of non-negative matrices that define positive operators on L and
, then
(42)
(42)
Proof.
(i) Let ,
and
. To prove the first inequality in (Equation41
(41)
(41) ), let
and
Then
, where for each
, we have
where
Then by (Equation15
(15)
(15) ) for each
, we have
where
Therefore
and
, which implies the first inequality in (Equation41
(41)
(41) ). The second and third inequality in (Equation41
(41)
(41) ) follow from (Equation32
(32)
(32) ).
If, in addition, L and have order continuous norms and
, then Inequalities (Equation41
(41)
(41) ) are proved similarly. Under the assumptions of (ii) Inequalities (Equation41
(41)
(41) ) are proved in a similar way by applying Theorems 2.1(ii) and 2.5.
Next, we extend Theorem 2.4 by refining (Equation33(33)
(33) ).
Theorem 3.3
Let be bounded sets of positive kernel operators on a Banach function space L and let
for
. If
, then
(43)
(43) If, in addition, L and
have order continuous norms, then Inequalities (Equation43
(43)
(43) ) are valid also for all
.
Proof.
Let . Denote
Then by (Equation31
(31)
(31) ), (Equation41
(41)
(41) ) and commutativity of Hadamard product, we have
which proves the first inequality in (Equation43
(43)
(43) ). The second and the third inequality in (Equation43
(43)
(43) ) follow from (Equation32
(32)
(32) ) (or from (Equation41
(41)
(41) )), since
by (Equation31
(31)
(31) ). If, in addition, L and
have order continuous norms, then (Equation43
(43)
(43) ) for
is proved in a similar way.
The following result extends (Equation38(38)
(38) ).
Theorem 3.4
Let be bounded sets of positive kernel operators on a Banach function space L and let
be non-negative numbers such that
. If
for
,
, then for all
we have
(44)
(44) If, in addition, L and
have order continuous norms, then Equalities (Equation44
(44)
(44) ) are valid for
.
Proof.
Let . To prove Equalities (Equation44
(44)
(44) ) we use the first inequality in (Equation41
(41)
(41) ) and (Equation31
(31)
(31) ) to obtain that
(45)
(45) for all
. Indeed, by (Equation31
(31)
(31) ) and the first inequality in (Equation41
(41)
(41) ) we have
which proves (Equation45
(45)
(45) ). Since
, Inequality (Equation45
(45)
(45) ) implies
(46)
(46) The second inequality in (Equation46
(46)
(46) ) follows from (Equation32
(32)
(32) ) and the fact that
. Since
for all
and
, we obtain
which together with (Equation46
(46)
(46) ) proves Equalities (Equation44
(44)
(44) ). If, in addition, L and
have order continuous norms, then Equalities (Equation44
(44)
(44) ) are proved in a similar way for
.
The following result, that extends the main results from [Citation8], is proved in a similar way as Theorem 3.3 by applying Theorems 2.5 and 3.2(ii) instead of Theorems 2.3 and 3.2(i) in the proofs above.
Theorem 3.5
Given , let
be bounded sets of non-negative matrices that define operators on L and
for
. Assume that
,
,
,
and
. If
and
for
, then we have
(47)
(47)
(48)
(48) If, in addition,
then
(49)
(49)
(50)
(50)
Proof.
Inequalities (Equation47(47)
(47) ) are proved in a similar way as Theorem 3.3 by applying Theorems 2.5 and 3.2(ii) instead of Theorems 2.3 and 3.2(i). For the proof of (Equation48
(48)
(48) ) observe that
for
. Now the first inequality in (Equation48
(48)
(48) ) follows from (Equation33
(33)
(33) ) (or from (Equation49
(49)
(49) )):
Other inequalities in (Equation48
(48)
(48) ) follow from Theorem 3.2(ii).
Assume . The first and second inequality in (Equation49
(49)
(49) ) follow from (Equation47
(47)
(47) ). To prove the third inequality in (Equation49
(49)
(49) ) notice that
,
and apply Theorem 2.5. The last inequality in (Equation49
(49)
(49) ) follows again from Theorem 2.5 and the fact that
.
To prove the first three inequalities in (Equation50(50)
(50) ), observe that
,
and apply Theorem 3.3. The remaining three inequalities in (Equation50
(50)
(50) ) follow from (Equation48
(48)
(48) ), which completes the proof.
We will need the following well-known inequalities (see e.g. [Citation43]). For non-negative measurable functions and for non-negative numbers α and β such that , we have
(51)
(51) More generally, for non-negative measurable functions
and for non-negative numbers
,
, such that
we have
(52)
(52) The sum of bounded sets Ψ and Σ is a bounded set defined by
.
Theorem 3.6
Let be bounded sets of positive kernel operators on a Banach function space L and let
be positive numbers.
If
,
and
, then
(53)
(53) If, in addition, L and
have order continuous norms, then Inequalities (Equation53
(53)
(53) ) hold also for each
.
If
,
,
and
are bounded sets of non-negative matrices that define positive operators on L, then Inequalities (Equation53
(53)
(53) ) hold.
Proof.
(i) Let ,
and
. To prove the first inequality in (Equation53
(53)
(53) ) let
and
Then
, where for each
we have
where
Then by (Equation52
(52)
(52) ) for each
we have
where
Therefore
and
, which implies the first inequality in (Equation53
(53)
(53) ). The second and third inequality in (Equation53
(53)
(53) ) follow from (Equation32
(32)
(32) ).
If, in addition, L and have order continuous norms and
, then Inequalities (Equation53
(53)
(53) ) are proved similarly. Under the assumptions of (ii) Inequalities (Equation53
(53)
(53) ) are proved in a similar way by applying Theorems 2.1(ii) and 2.5.
4. Weighted geometric symmetrizations
Let Ψ and Σ be bounded sets of positive kernel operators on and
. Denote by
and
bounded sets of positive kernel operators on
defined by
and
We denote simply
, the geometric symmetrization of Ψ. Observe that
and
for all
. By (Equation32
(32)
(32) ) it follows that
(54)
(54) for all
and
, since
. In particular, for all
and
we have
(55)
(55) Consequently,
(56)
(56) holds for all
.
The following result that follows from (Equation55(55)
(55) ) extends [Citation18, Theorem 2.2], [Citation16, Theorem 3.5] and [Citation3, Theorem 3.5(i)].
Theorem 4.1
Let Ψ be a bounded set of positive kernel operators on ,
and let
for
and
. Then for each n
Proof.
By (Equation55(55)
(55) ) we have
. Since
for all
by the first inequality in (Equation56
(56)
(56) ), the proof is completed.
The following result extends [Citation3, Proposition 3.2].
Proposition 4.2
Let be bounded sets of positive kernel operators on
,
,
and
. Then we have
(57)
(57)
(58)
(58) In particular, we have
(59)
(59)
Proof.
By Theorem 3.2(i) we have
where the last equality follows from the fact that
. The inequalities in (Equation58
(58)
(58) ) are proved in a similar way by applying Theorem 3.6 and (Equation55
(55)
(55) ). The first and second inequalities in (Equation59
(59)
(59) ) are special cases of (Equation57
(57)
(57) ), while the third inequality follows from (Equation57
(57)
(57) ) and the fact that
.
Let Ψ be a bounded set of non-negative matrices that define operators on and let α and β be non-negative numbers such that
. The set
is a bounded set of non-negative matrices that define operators on
by Theorem 2.1(ii).
For , the following result extends Theorem 4.1 in the case of bounded set of non-negative matrices that define operators on
. It also extends a part of [Citation3, Theorem 3.5(ii)].
Theorem 4.3
Let Ψ be a bounded set of non-negative matrices that define operators on and
. Assume α and β are non-negative numbers such that
and denote
for
. Then we have
(60)
(60)
Proof.
By Theorem 2.5, we have
(61)
(61) In particular, for n = 1, we have
(62)
(62) Since
for all
by the first inequality in (Equation62
(62)
(62) ), the proof of (Equation60
(60)
(60) ) is completed.
The following result is proved in similar way as Proposition 4.2 using Theorem 3.2(ii) instead of Theorem 3.2(i).
Proposition 4.4
Let Ψ, be bounded sets of non-negative matrices that define operators on
,
and let α and β be non-negative numbers such that
. Then we have
(63)
(63)
(64)
(64)
(65)
(65)
(66)
(66) for
.
Proof.
Inequalities (Equation63(63)
(63) ) and (Equation65
(65)
(65) ) are proved in a similar way as inequalities (Equation57
(57)
(57) ) and (Equation58
(58)
(58) ) by using Theorems 3.2(ii) and 3.6(ii). Inequalities (Equation64
(64)
(64) ) and (Equation66
(66)
(66) ) are special cases of (Equation63
(63)
(63) ).
Acknowledgments
The first author thanks the colleagues and staff at the Faculty of Mechanical Engineering and Institute of Mathematics, Physics and Mechanics for their hospitality during the research stay in Slovenia.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
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