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Research Article

Inequalities and equalities on the joint and generalized spectral and essential spectral radius of the Hadamard geometric mean of bounded sets of positive kernel operators

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Pages 2839-2857 | Received 07 Feb 2022, Accepted 31 Jul 2022, Published online: 22 Sep 2022

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.

MATH. SUBJ. CLASSIFICATION (2020)::

1. Introduction

In [Citation1], X. Zhan conjectured that, for non-negative N×N matrices A and B, the spectral radius ρ(AB) of the Hadamard product satisfies (1) ρ(AB)ρ(AB),(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) ρ(AB)ρ((AA)(BB))12ρ(AB).(2) These inequalities were established via a trace description of the spectral radius. Soon after, inequality (Equation1) 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) ρ(AB)ρ(ABBA)12ρ(AB).(3) Applying the techniques of [Citation6], Z. Huang proved that (4) ρ(A1A2Am)ρ(A1A2Am)(4) for n×n non-negative matrices A1,A2,,Am (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) and (Equation3) to non-negative matrices that define bounded operators on sequence spaces (in particular on lp spaces, 1p<) and proved in [Citation11, Theorem 2.7] that (5) ρ(AB)ρ((AA)(BB))12ρ(ABAB)12ρ(AB)(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) to non-negative matrices that define bounded operators on Banach sequence spaces (see below for the exact definitions) and proved that the inequalities (6) ρ(AB)ρ((AA)(BB))12ρ(ABAB)β2ρ(BABA)1β2ρ(AB)(6) and (7) ρ(AB)ρ(ABBA)12ρ(ABAB)14ρ(BABA)14ρ(AB).(7) hold, where β[0,1]. 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) ρ(A(12)B(12))ρ(AB)12(8) holds for positive kernel operators on Lp spaces. Here A(12)B(12) 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) ρ(A1(1m)A2(1m)Am(1m))ρ(A1A2Am)1m(9) holds for positive kernel operators A1,,Am on an arbitrary Banach function space L. In [Citation10], the second author refined (Equation9) and showed that the inequalities (10) ρ(A1(1m)A2(1m)Am(1m))ρ(P1(1m)P2(1m)Pm(1m))1mρ(A1A2Am)1m.(10) hold, where Pj=AjAmA1Aj1 for j=1,,m. In [Citation15, Theorem 3.2], the second author showed that (Equation10) holds also for the essential radius ρess under the additional condition that L and its Banach dual L have to order continuous norms. Formally, here and throughout the article Aj1=I for j = 1 (eventhough I might not be a well-defined kernel operator). In particular, the following kernel version of (Equation3) holds: (11) ρ(A(12)B(12))ρ((AB)(12)(BA)(12))12ρ(AB)12.(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) and (Equation11) 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 L2(X,μ) and on weighted geometric symmetrization of bounded sets of non-negative matrices that define operators on l2(R), which extend some results from [Citation3,Citation16,Citation18].

2. Preliminaries

Let µ be a σ-finite positive measure on a σ-algebra M of subsets of a non-void set X. Let M(X,μ) be the vector space of all equivalence classes of (almost everywhere equal) complex measurable functions on X. A Banach space LM(X,μ) is called a Banach function space if fL, gM(X,μ), and |g||f| imply that gL and gf. 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 f=0 a.e. on Y for all fL (see [Citation19]).

Let R denote the set {1,,N} for some NN or the set N of all natural numbers. Let S(R) be the vector lattice of all complex sequences (xn)nR. A Banach space LS(R) is called a Banach sequence space if xS(R), yL and |x||y| imply that xL and xLyL. Observe that a Banach sequence space is a Banach function space over a measure space (R,μ), where µ denotes the counting measure on R. Denote by L the collection of all Banach sequence spaces L satisfying the property that en=χ{n}L and enL=1 for all nR. For LL the set R is the carrier of L.

Standard examples of Banach sequence spaces are Euclidean spaces, lp spaces for 1p, the space c0L 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 Lp(X,μ) (1p) 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 L=E×F of Banach function spaces is again a Banach function space, equipped with the norm (f,g)L=max{fE,gF}.

If {fn}nNM(X,μ) is a decreasing sequence and f=inf{fnM(X,μ):nN}, then we write fnf. A Banach function space L has an order continuous norm, if 0fn0 implies fnL0 as n. It is well known that spaces Lp(X,μ), 1p<, 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 L have order continuous norms. Examples of such spaces are Lp(X,μ), 1<p<, while the space L=c0 is an example of a non-reflexive Banach sequence space, such that L and L=l1 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. AL+L+, where L+ denotes the positive cone L+={fL:f0a.e.}. Given operators A and B on L, we write AB if the operator AB is positive.

Recall that a positive operator A is always bounded, i.e. its operator norm (12) A=sup{AxL:xL,xL1}=sup{AxL:xL+,xL1}(12) is finite. Also, its spectral radius ρ(A) is always contained in the spectrum.

An operator A on a Banach function space L is called a kernel operator if there exists a μ×μ-measurable function a(x,y) on X×X such that, for all fL and for almost all xX, X|a(x,y)f(y)|dμ(y)<and(Af)(x)=Xa(x,y)f(y)dμ(y).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 L have order continuous norms and let A and B be positive kernel operators on L. By γ(A) we denote the Hausdorff measure of non-compactness of A, i.e. γ(A)=inf{δ>0:thereisafiniteMLsuchthatA(DL)M+δDL},where DL={fL:fL1}. Then γ(A)A, γ(A+B)γ(A)+γ(B), γ(AB)γ(A)γ(B) and γ(αA)=αγ(A) for α0. Also 0AB implies γ(A)γ(B) (see e.g. [Citation23, Corollary 4.3.7 and Corollary 3.7.3]). Let ρess(A) denote the essential spectral radius of A, i.e. the spectral radius of the Calkin image of A in the Calkin algebra. Then (13) ρess(A)=limjγ(Aj)1/j=infjNγ(Aj)1/j(13) and ρess(A)γ(A). Recall that if L=L2(X,μ), then γ(A)=γ(A) and ρess(A)=ρess(A), where A denotes the adjoint of A. Note that equalities (Equation13) and ρess(A)=ρess(A) 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 α0. The Hadamard (or Schur) product AB of A and B is the kernel operator with kernel equal to a(x,y)b(x,y) at point (x,y)X×X which can be defined (in general) only on some order ideal of L. Similarly, the Hadamard (or Schur) power A(α) of A is the kernel operator with kernel equal to (a(x,y))α at point (x,y)X×X which can be defined only on some order ideal of L.

Let A1,,Am be positive kernel operators on a Banach function space L, and α1,,αm positive numbers such that j=1mαj=1. Then the Hadamard weighted geometric mean A=A1(α1)A2(α2)Am(αm) of the operators A1,,Am is a positive kernel operator defined on the whole space L, since Aα1A1+α2A2++αmAm by the inequality between the weighted arithmetic and geometric means.

A matrix A=[aij]i,jR is called non-negative if aij0 for all i,jR. For notational convenience, we sometimes write a(i,j) instead of aij.

We say that a non-negative matrix A defines an operator on L if AxL for all xL, where (Ax)i=jRaijxj. Then AxL+ for all xL+ 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 {Aij}i=1,j=1k,m be positive kernel operators on a Banach function space L and let α1, α2,…, αm are positive numbers.

  1. If j=1mαj=1, then the positive kernel operator (14) A:=(A11(α1)A1m(αm))(Ak1(α1)Akm(αm))(14) satisfies the following inequalities (15) A(A11Ak1)(α1)(A1mAkm)(αm),(15) (16) A(A11Ak1)(α1)(A1mAkm)(αm)A11Ak1α1A1mAkmαm(16) (17) ρ(A)ρ((A11Ak1)(α1)(A1mAkm)(αm))ρ(A11Ak1)α1ρ(A1mAkm)αm.(17) If, in addition, L and L have order continuous norms, then (18) γ(A)γ((A11Ak1)(α1)(A1mAkm)(αm))γ(A11Ak1)α1γ(A1mAkm)αm,(18) (19) ρess(A)ρess((A11Ak1)(α1)(A1mAkm)(αm))ρess(A11Ak1)α1ρess(A1mAkm)αm.(19)

  2. If LL, j=1mαj1 and {Aij}i=1,j=1k,m are non-negative matrices that define positive operators on L, then A from (Equation14) defines a positive operator on L and the inequalities (Equation15), (Equation16) and (Equation17) hold.

The following result is a special case of Theorem 2.1.

Theorem 2.2

Let A1,,Am be positive kernel operators on a Banach function space L and α1,,αm positive numbers.

  1. If j=1mαj=1, then (20) A1(α1)A2(α2)Am(αm)A1α1A2α2Amαm(20) and (21) ρ(A1(α1)A2(α2)Am(αm))ρ(A1)α1ρ(A2)α2ρ(Am)αm.(21) If, in addition, L and L have order continuous norms, then (22) γ(A1(α1)A2(α2)Am(αm))γ(A1)α1γ(A2)α2γ(Am)αm(22) and (23) ρess(A1(α1)A2(α2)Am(αm))ρess(A1)α1ρess(A2)α2ρess(Am)αm.(23)

  2. If LL, j=1mαj1 and if A1,,Am are non-negative matrices that define positive operators on L, then A1(α1)A2(α2)Am(αm) defines a positive operator on L and (Equation20) and (Equation21) hold.

  3. If LL, t1 and if A,A1,,Am are non-negative matrices that define operators on L, then A(t) defines an operator on L and the following inequalities hold (24) A1(t)Am(t)(A1Am)(t),(24) (25) ρ(A1(t)Am(t))ρ(A1Am)t,(25) (26) A1(t)Am(t)A1Amt.(26)

Let Σ be a bounded set of bounded operators on a complex Banach space L. For m1, let Σm={A1A2Am:AiΣ}.The generalized spectral radius of Σ is defined by (27) ρ(Σ)=lim supm[supAΣmρ(A)]1/m(27) and is equal to ρ(Σ)=supmN[supAΣmρ(A)]1/m.The joint spectral radius of Σ is defined by (28) ρ^(Σ)=limm[supAΣmA]1/m.(28) Similarly, the generalized essential spectral radius of Σ is defined by (29) ρess(Σ)=lim supm[supAΣmρess(A)]1/m(29) and is equal to ρess(Σ)=supmN[supAΣmρess(A)]1/m.The joint essential spectral radius of Σ is defined by (30) ρ^ess(Σ)=limm[supAΣmγ(A)]1/m.(30) It is well known that ρ(Σ)=ρ^(Σ) for a precompact nonempty set Σ of compact operators on L (see e.g. [Citation32–34]), in particular for a bounded set of complex n×n 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 ρ^(Σ)=max{ρ(Σ),ρ^ess(Σ)}(see e.g. [Citation32–34]). Observe also that it was proved in [Citation32] that in the definition of ρ^ess(Σ) 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, ρ(Σ) and ρ^(Σ) 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 L=l2 such that ρ({A,B})=0<ρ^({A,B}). As already noted in [Citation33] also ρess(Σ) and ρ^ess(Σ) 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, ρ^(Σ) plays a central role in determining stability in convergence properties of discrete and differential inclusions. In this theory, the quantity logρ^(Σ) is known as the maximal Lyapunov exponent (see e.g. [Citation42]).

We will use the following well-known facts that hold for all r{ρ,ρ^,ρess,ρ^ess}: (31) r(Σm)=r(Σ)mandr(ΨΣ)=r(ΣΨ)(31) where ΨΣ={AB:AΨ,BΣ} and mN.

Let Ψ1,,Ψm be bounded sets of positive kernel operators on a Banach function space L and let α1,αm be positive numbers such that i=1mαi=1. Then the bounded set of positive kernel operators on L, defined by Ψ1(α1)Ψm(αm)={A1(α1)Am(αm):A1Ψ1,,AmΨm},is called the weighted Hadamard (Schur) geometric mean of sets Ψ1,,Ψm. The set Ψ1(1m)Ψm(1m) is called the Hadamard (Schur) geometric mean of sets Ψ1,,Ψm.

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 Ψ1,,Ψm be bounded sets of positive kernel operators on a Banach function space L and let α1,,αm be positive numbers such that

i=1mαi=1. If r{ρ,ρ^} and nN, then (32) r(Ψ1(α1)Ψm(αm))r((Ψ1n)(α1)(Ψmn)(αm))1nr(Ψ1)α1r(Ψm)αm(32) and (33) r(Ψ1(1m)Ψm(1m))r(Ψ1Ψ2Ψm)1m.(33) If, in addition, L and L have order continuous norms, then (Equation32) and (Equation33) hold also for each r{ρess,ρ^ess}.

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 r{ρ,ρ^} and β[0,1], then we have (34) r(Ψ(12)Σ(12))r((ΨΣ)(12)(ΣΨ)(12))12r((ΨΣ)(12)(ΨΣ)(12))14r((ΣΨ)(12)(ΣΨ)(12))14r(ΨΣ)12,(34) (35) r(Ψ(12)Σ(12))r((Ψ(12)Ψ(12))(Σ(12)Σ(12)))12r((ΨΣ)(12)(ΨΣ)(12))β2r((ΣΨ)(12)(ΣΨ)(12))1β2r(ΨΣ)12.(35) If, in addition, L and L have order continuous norms, then (Equation34) and (Equation35) hold also for each r{ρess,ρ^ess}.

Given LL, let Ψ1,,Ψm be bounded sets of non-negative matrices that define operators on L and let α1,,αm be positive numbers such that i=1mαi1. Then the set Ψ1(α1)Ψm(αm)={A1(α1)Am(αm):A1Ψ1,,AmΨm}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 LL, let Ψ,Ψ1,,Ψm be bounded sets of non-negative matrices that define operators on L. Let α1,,αm be positive numbers such that j=1mαj1, nN and r{ρ,ρ^}. Then Inequalities (Equation32) hold.

In particular, if t1, then (36) r(Ψ(t))r((Ψn)(t))1nr(Ψ)t.(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 α1,,αm be positive numbers such that j=1mαj=1.

  1. If r{ρ,ρ^} and β[0,1], then (37) r(Ψ)=r(Ψ(α1)Ψ(αm))(37) and (38) r(ΨΣ)=r((Ψ(12)Ψ(12))(Σ(12)Σ(12)))=r((ΨΣ)(12)(ΨΣ)(12))βr((ΣΨ)(12)(ΣΨ)(12))1β.(38) If, in addition, L and L have order continuous norms, then (Equation37) and (Equation38) hold also for each r{ρess,ρ^ess}.

  2. If LL, r{ρ,ρ^}, m,nN, α1 and if Ψ is a bounded set of non-negative matrices that define operators on L, then (39) r(Ψ(m))r(ΨΨ)r(ΨnΨn)1nr(Ψ)m,(39) where in (Equation39) the Hadamard products in ΨΨ and in ΨnΨn are taken m times, and (40) r(Ψ(α))r(Ψ(α1)Ψ)r((Ψn)(α1)Ψn)1nr(Ψ)α.(40)

Proof.

(i) To prove (Equation37) first observe that ΨΨ(α1)Ψ(αm), since A=A(α1)A(αm) for all AΨ. It follows that r(Ψ)r(Ψ(α1)Ψ(αm))r(Ψ)α1r(Ψ)αm=r(Ψ)by Theorem 2.3 and so r(Ψ)=r(Ψ(α1)Ψ(αm)).

Similary, to prove (Equation38) observe that ΨΣ(Ψ(12)Ψ(12))(Σ(12)Σ(12)), since AB=(A(12)A(12))(B(12)B(12)) for all AΨ and BΣ. It follows that r(ΨΣ)r((Ψ(12)Ψ(12))(Σ(12)Σ(12)))r((ΨΣ)(12)(ΨΣ)(12))βr((ΣΨ)(12)(ΣΨ)(12))1βr(ΨΣ)by (Equation35), which proves (Equation38). It is proved similarly that (Equation37) and (Equation38) hold also for each r{ρess,ρ^ess} in the case when L and L have order continuous norms.

(ii) For the proof of (Equation39) observe that Ψ(m)ΨΨ, since A(m)=AA for all AΨ. By Theorem 2.5, Inequalities (Equation39) follow. Inequalities (Equation40) are proved in a similar way.

Remark 1

Equalities (Equation38) show that the third inequality in (Equation34) and the second and third inequality in (Equation35) 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) and (Equation32) and Theorem 2.5.

Theorem 3.2

Let {Ψij}i=1,j=1k,m be bounded sets of positive kernel operators on a Banach function space L and let α1,,αm be positive numbers.

  1. If r{ρ,ρ^}, i=1mαi=1 and nN, then (41) r((Ψ11(α1)Ψ1m(αm))(Ψk1(α1)Ψkm(αm)))r((Ψ11Ψk1)(α1)(Ψ1mΨkm)(αm))r(((Ψ11Ψk1)n)(α1)((Ψ1mΨkm)n)(αm))1nr(Ψ11Ψk1)α1r(Ψ1mΨkm)αm.(41) If, in addition, L and L have order continuous norms, then Inequalities (Equation41) hold also for each r{ρess,ρ^ess}.

  2. If LL, r{ρ,ρ^}, j=1mαj1 and {Ψij}i=1,j=1k,m are bounded sets of non-negative matrices that define positive operators on L, then Inequalities (Equation41) hold.

    In particular, if Ψ1,,Ψk are bounded sets of non-negative matrices that define positive operators on L and t1, then (42) r(Ψ1(t)Ψk(t))r((Ψ1Ψk)(t))r(((Ψ1Ψk)n)(t))1nr(Ψ1Ψk)t.(42)

Proof.

(i) Let r{ρ,ρ^}, i=1mαi=1 and nN. To prove the first inequality in (Equation41), let lN and A((Ψ11(α1)Ψ1m(αm))(Ψk1(α1)Ψkm(αm)))l.Then A=A1Al, where for each i=1,,l, we have Ai=(Ai11(α1)Ai1m(αm))(Aik1(α1)Aikm(αm)),where Ai11Ψ11,,Ai1mΨ1m,,Aik1Ψk1,,AikmΨkm. Then by (Equation15) for each i=1,,l, we have AiCi:=(Ai11Ai21Aik1)(α1)(Ai1mAi2mAikm)(αm),where Ci(Ψ11Ψk1)(α1)(Ψ1mΨkm)(αm). Therefore AC:=C1Cl((Ψ11Ψk1)(α1)(Ψ1mΨkm)(αm))l,ρ(A)1/lρ(C)1/l and A1/lC1/l, which implies the first inequality in (Equation41). The second and third inequality in (Equation41) follow from (Equation32).

If, in addition, L and L have order continuous norms and r{ρess,ρ^ess}, then Inequalities (Equation41) are proved similarly. Under the assumptions of (ii) Inequalities (Equation41) are proved in a similar way by applying Theorems 2.1(ii) and 2.5.

Next, we extend Theorem 2.4 by refining (Equation33).

Theorem 3.3

Let Ψ1,,Ψm be bounded sets of positive kernel operators on a Banach function space L and let Φj=ΨjΨmΨ1Ψj1 for j=1,,m. If r{ρ,ρ^}, then (43) r(Ψ1(1m)Ψ2(1m)Ψm(1m))r(Φ1(1m)Φ2(1m)Φm(1m))1mr((Φ1n)(1m)(Φ2n)(1m)(Φmn)(1m))1nmr(Ψ1Ψ2Ψm)1m.(43) If, in addition, L and L have order continuous norms, then Inequalities (Equation43) are valid also for all r{ρess,ρ^ess}.

Proof.

Let r{ρ,ρ^}. Denote Σ1=Ψ1(1m)Ψm(1m),Σ2=Ψ2(1m)Ψm(1m)Ψ1(1m),,Σm=Ψm(1m)Ψ1(1m)Ψm1(1m).Then by (Equation31), (Equation41) and commutativity of Hadamard product, we have r(Ψ1(1m)Ψ2(1m)Ψm(1m))m=r((Ψ1(1m)Ψ2(1m)Ψm(1m))m)=r(Σ1Σ2Σm)r(Φ1(1m)Φ2(1m)Φm(1m)),which proves the first inequality in (Equation43). The second and the third inequality in (Equation43) follow from (Equation32) (or from (Equation41)), since r(Φ1)=r(Φ2)=r(Φm)=r(Ψ1Ψ2Ψm) by (Equation31). If, in addition, L and L have order continuous norms, then (Equation43) for r{ρess,ρ^ess} is proved in a similar way.

The following result extends (Equation38).

Theorem 3.4

Let Ψ1,,Ψm be bounded sets of positive kernel operators on a Banach function space L and let α1,,αm be non-negative numbers such that j=1mαj=1. If Φj=ΨjΨmΨ1Ψj1 for j=1,,m, β[0,1], then for all r{ρ,ρ^} we have (44) r(Ψ1Ψ2Ψm)=r((Ψ1(β)Ψ1(1β))(Ψm(β)Ψm(1β)))=r(Φ1(β)Φ1(1β))α1r(Φm(β)Φm(1β))αm.(44) If, in addition, L and L have order continuous norms, then Equalities (Equation44) are valid for r{ρess,ρ^ess}.

Proof.

Let r{ρ,ρ^}. To prove Equalities (Equation44) we use the first inequality in (Equation41) and (Equation31) to obtain that (45) r((Ψ1(β)Ψ1(1β))(Ψm(β)Ψm(1β)))r(Φi(β)Φi(1β))(45) for all i=1,,m. Indeed, by (Equation31) and the first inequality in (Equation41) we have r((Ψ1(β)Ψ1(1β))(Ψm(β)Ψm(1β)))=r((Ψi(β)Ψi(1β))(Ψm(β)Ψm(1β))(Ψ1(β)Ψ1(1β))(Ψi1(β)Ψi1(1β)))r(Φi(β)Φi(1β)),which proves (Equation45). Since j=1mαj=1, Inequality (Equation45) implies (46) r((Ψ1(β)Ψ1(1β))(Ψm(β)Ψm(1β)))r(Φ1(β)Φ1(1β))α1r(Φm(β)Φm(1β))αmr(Ψ1Ψm).(46) The second inequality in (Equation46) follows from (Equation32) and the fact that r(Φ1)==r(Φm)=r(Ψ1Ψm). Since ΨiΨi(β)Ψi(1β) for all i=1,,m and β[0,1], we obtain r(Ψ1Ψm)r((Ψ1(β)Ψ1(1β))(Ψm(β)Ψm(1β))),which together with (Equation46) proves Equalities (Equation44). If, in addition, L and L have order continuous norms, then Equalities (Equation44) are proved in a similar way for r{ρess,ρ^ess}.

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 LL, let Ψ1,,Ψm be bounded sets of non-negative matrices that define operators on L and Φj=ΨjΨmΨ1Ψj1 for j=1,,m. Assume that α1m, αj0, j=1,,m, j=1mαj1 and nN. If r{ρ,ρ^} and Σj=Ψj(αm)Ψm(αm)Ψ1(αm)Ψj1(αm) for j=1,,m, then we have (47) r(Ψ1(α)Ψm(α))r(Φ1(α)Φm(α))1mr((Φ1n)(α)(Φmn)(α))1mnr(Ψ1Ψm)α,(47) (48) r(Ψ1(α)Ψm(α))r(Ψ1(αm)Ψm(αm))1mr((Ψ1Ψm)(αm))1mr(((Ψ1Ψm)n)(αm))1nmr(Ψ1Ψm)α.(48) If, in addition, α1 then (49) r(Ψ1(α)Ψm(α))r(Φ1(α)Φm(α))1mr((Φ1n)(α)(Φmn)(α))1mn(r((Φ1n)(m))r((Φmn)(m)))αm2nr(Ψ1Ψm)α,(49) (50) r(Ψ1(α)Ψm(α))r(Σ1(1m)Σm(1m))1mr((Σ1n)(1m)(Σmn)(1m))1mnr(Ψ1(αm)Ψm(αm))1mr((Ψ1Ψm)(αm))1mr(((Ψ1Ψm)n)(αm))1nmr(Ψ1Ψm)α.(50)

Proof.

Inequalities (Equation47) 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) observe that Ψ1(α)Ψm(α)=(Ψ1(αm))(1m)(Ψm(αm))(1m)for i=1,,m. Now the first inequality in (Equation48) follows from (Equation33) (or from (Equation49)): r(Ψ1(α)Ψm(α))=r((Ψ1(αm))(1m)(Ψm(αm))(1m))r(Ψ1(αm)Ψm(αm))1m.Other inequalities in (Equation48) follow from Theorem 3.2(ii).

Assume α1. The first and second inequality in (Equation49) follow from (Equation47). To prove the third inequality in (Equation49) notice that (Φin)(α)=((Φin)(m))(αm), αm1m and apply Theorem 2.5. The last inequality in (Equation49) follows again from Theorem 2.5 and the fact that r(Φ1)==r(Φm)=r(Ψ1Ψm).

To prove the first three inequalities in (Equation50), observe that Ψi(α)=(Ψi(mα))(1m), αm1m and apply Theorem 3.3. The remaining three inequalities in (Equation50) follow from (Equation48), 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 α+β1, we have (51) f1αg1β++fmαgmβ(f1++fm)α(g1++gm)β(51) More generally, for non-negative measurable functions {fij}i=1,j=1k,m and for non-negative numbers αj, j=1,,m, such that j=1mαj1 we have (52) (f11α1f1mαm)++(fk1α1fkmαm)(f11++fk1)α1(f1m++fkm)αm(52) The sum of bounded sets Ψ and Σ is a bounded set defined by Ψ+Σ={A+B:AΨ,BΣ}.

Theorem 3.6

Let {Ψij}i=1,j=1k,m be bounded sets of positive kernel operators on a Banach function space L and let α1,,αm be positive numbers.

  1. If r{ρ,ρ^}, j=1mαj=1 and nN, then (53) r((Ψ11(α1)Ψ1m(αm))++(Ψk1(α1)Ψkm(αm)))r((Ψ11++Ψk1)(α1)(Ψ1m++Ψkm)(αm))r(((Ψ11++Ψk1)n)(α1)((Ψ1m++Ψkm)n)(αm))1nr(Ψ11++Ψk1)α1r(Ψ1m++Ψkm)αm.(53) If, in addition, L and L have order continuous norms, then Inequalities (Equation53) hold also for each r{ρess,ρ^ess}.

  2. If LL, r{ρ,ρ^}, j=1mαj1 and {Ψij}i=1,j=1k,m are bounded sets of non-negative matrices that define positive operators on L, then Inequalities (Equation53) hold.

Proof.

(i) Let r{ρ,ρ^}, i=1mαi=1 and nN. To prove the first inequality in (Equation53) let lN and A((Ψ11(α1)Ψ1m(αm))++(Ψk1(α1)Ψkm(αm)))l.Then A=A1Al, where for each i=1,,l we have Ai=(Ai11(α1)Ai1m(αm))++(Aik1(α1)Aikm(αm)),where Ai11Ψ11,,Ai1mΨ1m,,Aik1Ψk1,,AikmΨkm. Then by (Equation52) for each i=1,,l we have AiCi:=(Ai11+Ai21++Aik1)(α1)(Ai1m+Ai2m++Aikm)(αm),where Ci(Ψ11++Ψk1)(α1)(Ψ1m++Ψkm)(αm). Therefore AC:=C1Cl((Ψ11++Ψk1)(α1)(Ψ1m++Ψkm)(αm))l,r(A)1/lr(C)1/l and A1/lC1/l, which implies the first inequality in (Equation53). The second and third inequality in (Equation53) follow from (Equation32).

If, in addition, L and L have order continuous norms and r{ρess,ρ^ess}, then Inequalities (Equation53) are proved similarly. Under the assumptions of (ii) Inequalities (Equation53) 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 L2(X,μ) and α[0,1]. Denote by Ψ and Sα(Ψ) bounded sets of positive kernel operators on L2(X,μ) defined by Ψ={A:AΨ} and Sα(Ψ)=Ψ(α)(Ψ)(1α)={A(α)(B)(1α):A,BΨ}.We denote simply S(Ψ)=S12(Ψ), the geometric symmetrization of Ψ. Observe that (ΨΣ)=ΣΨ and (Ψm)=(Ψ)m for all mN. By (Equation32) it follows that (54) r(Sα(Ψ))r(Sα(Ψm))1mr(Ψ)(54) for all mN and r{ρ,ρ^,ρess,ρ^ess}, since r(Ψ)=r(Ψ). In particular, for all r{ρ,ρ^,ρess,ρ^ess} and nN{0} we have (55) r(Sα(Ψ))r(Sα(Ψ2n))2nr(Ψ).(55) Consequently, (56) r(Sα(Ψ))2r(Sα(Ψ2))r(Ψ)2(56) holds for all r{ρ,ρ^,ρess,ρ^ess}.

The following result that follows from (Equation55) 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 L2(X,μ), α[0,1] and let rn=r(Sα(Ψ2n))2n for nN{0} and r{ρ,ρ^,ρess,ρ^ess}. Then for each n r(Sα(Ψ))=r0r1rnr(Ψ).

Proof.

By (Equation55) we have rnr(Ψ). Since rn1rn for all nN by the first inequality in (Equation56), the proof is completed.

The following result extends [Citation3, Proposition 3.2].

Proposition 4.2

Let Ψ1,,Ψm be bounded sets of positive kernel operators on L2(X,μ), α[0,1], nN and r{ρ,ρ^,ρess,ρ^ess}. Then we have (57) r(Sα(Ψ1)Sα(Ψm))r((Ψ1Ψm)(α)((ΨmΨ1))(1α))r(((Ψ1Ψm)n)(α)(((ΨmΨ1))n)(1α))1nr(Ψ1Ψm)αr(ΨmΨ1)1α,(57) (58) r(Sα(Ψ1)++Sα(Ψm))r(Sα(Ψ1++Ψm))r(Sα((Ψ1++Ψm)n))1nr(Ψ1++Ψm).(58) In particular, we have (59) r(Sα(Ψ1)Sα(Ψ2))r((Ψ1Ψ2)(α)((Ψ2Ψ1))(1α))r(((Ψ1Ψ2)n)(α)(((Ψ2Ψ1))n)(1α))1nr(Ψ1Ψ2).(59)

Proof.

By Theorem 3.2(i) we have r(Sα(Ψ1)Sα(Ψm))=r((Ψ1(α)(Ψ1)(1α))(Ψm(α)(Ψm)(1α)))r((Ψ1Ψm)(α)((ΨmΨ1))(1α))r(((Ψ1Ψm)n)(α)(((ΨmΨ1))n)(1α))1nr(Ψ1Ψm)αr((ΨmΨ1))1α=r(Ψ1Ψm)αr(ΨmΨ1)1α,where the last equality follows from the fact that r(Ψ)=r(Ψ). The inequalities in (Equation58) are proved in a similar way by applying Theorem 3.6 and (Equation55). The first and second inequalities in (Equation59) are special cases of (Equation57), while the third inequality follows from (Equation57) and the fact that r(Ψ1Ψ2)=r(Ψ2Ψ1).

Let Ψ be a bounded set of non-negative matrices that define operators on l2(R) and let α and β be non-negative numbers such that α+β1. The set Sα,β(Ψ)=Ψ(α)(Ψ)(β)={A(α)(B)(β):A,BΨ} is a bounded set of non-negative matrices that define operators on l2(R) by Theorem 2.1(ii).

For r{ρ,ρ^}, the following result extends Theorem 4.1 in the case of bounded set of non-negative matrices that define operators on l2(R). 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 l2(R) and r{ρ,ρ^}. Assume α and β are non-negative numbers such that α+β1 and denote rn=r(Sα,β(Ψ2n))2n for nN{0}. Then we have (60) r(Sα,β(Ψ))=r0r1rnr(Ψ)α+β.(60)

Proof.

By Theorem 2.5, we have (61) r(Sα,β(Ψ))=r(Ψ(α)(Ψ)(β))r((Ψ2n)(α)((Ψ)2n)(β))2n=rnr(Ψ)α+β.(61) In particular, for n = 1, we have (62) r(Sα,β(Ψ))2r(Sα,β(Ψ2))r(Ψ)2(α+β).(62) Since rn1rn for all nN{0} by the first inequality in (Equation62), the proof of (Equation60) 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, Ψ1,,Ψm be bounded sets of non-negative matrices that define operators on l2(R), nN and let α and β be non-negative numbers such that α+β1. Then we have (63) r(Sα,β(Ψ1)Sα,β(Ψm))r((Ψ1Ψm)(α)((ΨmΨ1))(β))r(((Ψ1Ψm)n)(α)(((ΨmΨ1))n)(β))1nr(Ψ1Ψm)αr(ΨmΨ1)β,(63) (64) r(Sα,β(Ψ))r(Sα,β(Ψn))1nr(Ψ)α+β,(64) (65) r(Sα,β(Ψ1)++Sα,β(Ψm))r(Sα,β(Ψ1++Ψm))r(Sα,β((Ψ1++Ψm)n))1nr(Ψ1++Ψm)α+β,(65) (66) r(Sα,β(Ψ1)Sα,β(Ψ2))r((Ψ1Ψ2)(α)((Ψ2Ψ1))(β))r(((Ψ1Ψ2)n)(α)(((Ψ2Ψ1))n)(β))1nr(Ψ1Ψ2)α+β(66) for r{ρ,ρ^}.

Proof.

Inequalities (Equation63) and (Equation65) are proved in a similar way as inequalities (Equation57) and (Equation58) by using Theorems 3.2(ii) and 3.6(ii). Inequalities (Equation64) and (Equation66) are special cases of (Equation63).

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

The first author acknowledges a partial support of Erasmus+ European Mobility program [grant number KA103], COST Short Term Scientific Mission program (action CA18232) and the Slovenian Research Agency [grant number P1-0222] and [grant number P1-0288]. The second author acknowledges a partial support of the Slovenian Research Agency [grant number P1-0222], [grant number J1-8133], [grant number J2-2512].

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