This paper extends the spectral order concept to multidimensional settings for commuting selfadjoint operators, showing its preservation under spectral integral transformations and characterizing the order via operator inequalities.
Contribution
It introduces a multidimensional spectral order for families of commuting selfadjoint operators and explores its properties and characterizations.
Findings
01
Multidimensional spectral order is preserved by spectral integral transformations.
02
The spectral order for positive tuples is characterized by operator inequalities.
03
The multidimensional spectral order generalizes the product of one-dimensional spectral orders.
Abstract
The aim of this paper is to extend the notion of the spectral order for finite families of pairwise commuting bounded and unbounded selfadjoint operators in Hilbert space. It is shown that the multidimensional spectral order ≼ is preserved by transformations represented by spectral integrals of separately increasing Borel functions on Rκ. In particular, the κ-dimensional spectral order is the restriction of product of κ spectral orders for selfadjoint operators. If A and B are positive κ-tuples of pairwise commuting selfadjoint operators, then relation A≼B holds if and only if Aα⩽Bα for every α∈Z+κ.
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Full text
Multidimensional spectral order for selfadjoint operators
Artur Płaneta
Katedra Zastosowań Matematyki, Uniwersytet Rolniczy w Krakowie,
ul. Balicka 253 c, PL-30198 Kraków
The aim of this paper is to extend the notion of the spectral order for finite families of pairwise commuting bounded and unbounded selfadjoint operators in Hilbert space. It is shown that the multidimensional spectral order ≼ is preserved by transformations represented by spectral integrals of separately increasing Borel functions on Rκ. In particular, the κ-dimensional spectral order is the restriction of product of κ spectral orders for selfadjoint operators. In the context of positive families of pairwise commuting selfadjoint operator, the relation A≼B holds if and only if Aα⩽Bα for every α∈Z+κ.
Key words and phrases:
spectral order, joint spectral measure, joint bounded vectors, integral inequalities, separately increasing function
The author was supported by the Ministry of Science and Higher Education of the Republic
of Poland.
1. Introduction
Let H be a complex Hilbert space. Denote by Bs(H) the set of all bounded selfadjoint operators on H. If A,B∈Bs(H), then we write A⩽B whenever ⟨Ah,h⟩⩽⟨Bh,h⟩ for every h∈H.
In [28] Sherman proved that As the set
of all selfadjoint elements of a C∗-algebra A of bounded linear operators on H is a lattice with respect to ⩽ if and only if A is
commutative. In fact, the more noncommutative A is the less lattice structure As has. The result of
Kadison [18] shows that partially ordered set (Bs(H),⩽) is an anti-lattice. This means that for any A,B∈Bs(H), the greatest lower bound of the set {A,B} exists if and only if A⩽B or B⩽A.
These results motivated Olson to introduce spectral order ≼ for bounded selfadjoint operators [23]. One of the main result in [23] says that (Bs(H),≼) is a conditionally complete lattice. It should also be mentioned that in contrast to the classical order ⩽, the spectral order is not a vector order. Spectral order was considered in the context of matrix theory and von Neumann algebras (see [19, 2, 3, 1]). The spectral order also enabled to solve Dirichlet problem for operator-valued harmonic function in [14].
The spectral order has natural interpretation in the mathematical description of quantum mechanics (see [16]). This fact has led to increased interest in automorphisms of the spectral order. For instance, automorphisms of partially ordered set (E(H),≼), where E(H) denote the set of all positive bounded operators in the closed unit ball of B(H), were described in [22, 21]. In turn, automorphisms of subsets of positive selfadjoint operators were investigated in [30, 17]. Spectral order is also an important ingredient of the topos formulation of quantum theory (see for example [9, 10, 31, 12]).
In the previous paper [24] (see also [17, 30]) the spectral order was investigated in the context of unbounded selfadjoint operators. The aim of this paper is to extend the notion of the spectral order also for finite families of pairwise commuting bounded and unbounded selfadjoint operators. We start with the definition of the spectral order for selfadjoint operators. Let A and B be selfadjoint operators in H. If EA and EB are spectral measures of A and B defined on Borel subsets of R, then
A≼B if and only if EB((−∞,x])⩽EA((−∞,x]) for every x∈R. As we see, the definition of spectral order depends on the fact that for every selfadjoint operator A, there exists a unique spectral measure E on the σ-algebra of all Borel subsets of real line satisfying the condition
[TABLE]
If A=(A1,…,Aκ) is a κ-tuple of selfadjoint operators, κ∈N, then similar representation
[TABLE]
holds for some Borel spectral measure E on Rκ if and only if A1,…,Aκ pairwise commute. The set of all κ-tuples of pairwise commuting selfadjoint operators in H will be denoted by Sc(H,κ). By definition, A=(A1,…,Aκ)∈Sc(H,κ) if spectral measures EA1,…,EAκ commute, i.e.
[TABLE]
for every Borel sets Δ1,Δ2⊂R and k,j∈{1,…,κ}.
In fact, condition (1.1) determine the unique measure E=EA, which allow us to consider the multivariable spectral resolution FA(x1,…,xκ)=EA((−∞,x1]×…×(−∞,xκ]) for x1,…,xκ∈R.
In particular, if A,B∈Sc(H,κ), then they can be ordered by A≼B if FB(x)⩽FA(x) for every x∈Rκ.
This is the first argument for the choice of Sc(H,κ).
The second argument comes from quantum theory. Let o1,…,oκ and p1,…,pκ be two systems of commensurable observables represented by A,B∈Sc(H,κ), respectively. Consider unit vector h in H, which is interpreted as the state of the system. Then the pairs (h,A) and (h,B) determine random vectors X=(X1,…,Xκ) and Y=(Y1,…,Yκ), respectively. In particular, the distribution functions of X and Y are given by FX(x)=⟨FA(x)h,h⟩ and FY(x)=⟨FB(x)h,h⟩, x∈Rκ. Concluding, the relation A≼B means that the corresponding distribution functions FX and FY are pointwise ordered. For more details on quantum theory, we refer reader to [7].
In Section 5 we investigate fundamental properties of multidimensional spectral order. The main results state that the multidimensional spectral order is preserved by transformation represented by spectral integrals of separately increasing Borel functions on Rκ (see Theorem 5.6 and Theorem 5.7), which extends the known results for spectral order (confer [24, Proposition 6.2.],[22]). In particular, we obtain equivalent definition of multidimensional spectral order in Corollary 5.8, which is a counterpart of [13, Theorem 1.]. As the consequence of Theorem 5.6 we derive some information when the spectral order behaves like a vector order in Corollaries 5.12 and 5.13. According to Theorem 5.7 it is also possible to extend the multidimensional spectral order to S(H,κ) the set of all κ-tuples of selfadjoint operators in H as a product order. It means that A≼B if and only if Aj≼Bj for every j=1,…,κ whenever A,B∈S(H,κ). Note that (S(H,κ),≼) is a conditionally complete lattice since (S(H,1),≼) is a conditionally complete lattice by [24, Corollary 5.4.]. In contrast to (S(H,κ),≼), partially ordered set (Sc(H,κ),≼) is not even a lattice (see Example 5.11). It should also be pointed out that in the case κ=2 the multidimensional spectral order on Sc(H,2) can be identified with the spectral order for normal operators (see Example 5.14 and Proposition 5.15). This order was considered by Brenna and Flori in [8] in the context of the daseinisation of normal operators.
In Section 7 we discuss the relation between domains of monomials Aα and Bα for α∈Z+κ provided that A,B∈Sc(H,κ) and A≼B. The role of operators Aα and Bα becomes more important if we consider positive A,B∈Sc(H,κ). This question is studied in Section 8. One of the main result of this Section states that A≼B if and only if Aα⩽Bα for every α∈Z+κ. This generalize [23, Theorem 3.], which says that A≼B if and only if An⩽Bn for every n=1,2,…, where A and B are bounded positive selfadjoint operators on H.
2. Prerequisites
Denote by Z+, N, Q, R+, R, and C the
sets of nonnegative integers, positive integers, rational numbers,
nonnegative real numbers, real numbers, and complex numbers,
respectively. Set R=R∪{−∞}∪{∞}. As usual, χσ
stands for the characteristic function of a set
σ (it is clear from the context which set is
the domain of definition of χσ).
In what follows, H denotes a complex Hilbert
space. By an operator in H we understand a
linear mapping A:H⊇D(A)→H defined on a linear subspace D(A)
of H, called the domain of A. Let A be
an operator in H. We write N(A), R(A), A∗
and Aˉ for the kernel, the range, the adjoint
and the closure of A, respectively (in case they
exist). Set D∞(A)=⋂n=1∞D(An)
and
[TABLE]
Call a member of B(A):=⋃a∈R+Ba(A) a bounded vector of A (cf. [11]). We say that an operator A in H is
positive if ⟨Ah,h⟩⩾0 for every h∈D(A). A densely defined operator A is said to be
selfadjoint if A=A∗. If A is a positive
selfadjoint operator in H, then its square root is
denoted by A1/2.
Denote by B(H) the C∗-algebra of all bounded
operators A in H such that D(A)=H. We write
I=IH for the identity operator on H. It is well-known that the set
P(H) of all orthogonal projections on H
equipped with the above-defined partial order
“⩽” is a complete lattice. If
A⊆P(H), then ⋁A (respectively, ⋀A)
stands for the supremum (respectively, the infimum) of
A. Denote by PM the orthogonal
projection of H onto a closed linear subspace M
of H. If {Mj}j∈J is a family of subsets
of H, then ⋁j∈JMj stands for the
smallest closed linear subspace of H containing
⋃j∈JMj. Note that if each Mj is a
closed linear subspaces of H, then
[TABLE]
We shall use the symbol “\textscsot−lim” to
represent the limit in the strong operator topology on
B(H).
Let E:B(X)→B(H) be a spectral measure defined on the σ-algebra B(X)
of all Borel subsets of a topological space X.
A set Y⊆X
is called a support of E, if Y is the least (with
respect to set inclusion) closed subset of X such
that E(X\Y)=0. The support of E is
denoted by suppE. It is known that every
spectral measure E on B(X), where X is a
separable complete metric space, has closed support
(cf. [5, page 129]). We say
that E is regular if
[TABLE]
For the sake of completeness, we prove the following Proposition (see also [20, Exercise 6.8.]).
Proposition 2.1**.**
If X is a separable complete metric space and E
is a spectral measure on B(X), then E is
regular.
Proof.
Let σ∈B(X). It is evident that
[TABLE]
To establish the opposite inequality, take
h∈H such that h⊥E(τ)H for every
compact set τ⊆σ. Applying
[5, Subsection 1.3.22] we get that
μh(⋅):=⟨E(⋅)h,h⟩ is an inner regular Borel
measure (cf. [25]). Choose g∈H. Then
[TABLE]
Thus h⊥E(σ)H, since g was chosen arbitrarily. This completes the proof.
∎
Let us recall that
suppEA=σ(A) for every selfadjoint operator
A in H, where σ(A) denotes the spectrum
of A and EA is the spectral measure of A. In particular, a selfadjoint operator A is
positive if and only if suppEA⊆[0,∞)
(cf. [5]).
If φ:R→R is a Borel function,
then we set
[TABLE]
The operator φ(A) is selfadjoint. Moreover, if
φ⩾0 a.e. [E], then φ(A) is
positive. For more information concerning Stone-von
Neumann operator calculus φ↦φ(A), we refer the reader to [5, 27].
Given a positive selfadjoint operator A in H and
s∈R+, we define As=ψs(A), where
ψs(x)=∣x∣sχ[0,∞)(x) for x∈R (with the convention that 00=1). This
definition agrees with the usual one for nonnegative
integer exponents. If A1 and A2 are positive
selfadjoint operators in H such that
D(A21/2)⊆D(A11/2) and
∥A11/2h∥⩽∥A21/2h∥ for every h∈D(A21/2), then we write A1⩽A2 (cf. [27]). The last definition is easily seen to be
consistent with that for bounded operators.
Finally, let (X,A,μ) be a measure space and φ:X→R be an A-measurable function. We denote by Mφ the multiplication operator by φ in L2(X,μ), which is defined as follows:
[TABLE]
It is known that Mφ is selfadjoint and
[TABLE]
for every σ∈B(R) and h∈L2(X,μ) (see [27, Example 5.3.]).
3. Separately increasing functions
Here we collect some facts about separately increasing functions we need in this
paper.
Fix κ∈N. In what follows, Rκ
is regarded as the κ-dimensional Euclidean
space. Denote by {ej}j=1κ the standard
orthonormal basis of Rκ, i.e.
[TABLE]
Throughout this paper, we adhere to the usual
convention that if a∈Rκ,
then the jth coordinate of a is denoted by aj;
thus a=(a1,…,aκ). Let a∈Rκ and
b∈Rκ. We write a⩽b
(resp., a<b) if aj⩽bj (resp., aj<bj) for
all j=1,…,κ. Set
[TABLE]
Similarly, we define (−∞,x), [x,∞) and
(x,∞). Given ι∈{1,…,κ}, a∈Rκ and b∈Rκ, we write
a⩽ιb if aj⩽bj for j=1,…,ι
and aj=bj for j>ι. Note that
(Rκ,⩽) and
(Rκ,⩽ι) are partially ordered
sets.
Let (X,⪯) be a partially ordered set. A set
S⊆X is called a lower set in X if
[TABLE]
The collection of all lower sets in X is denoted by
L(X,⪯). Note that ⋂Γ∈L(X,⪯) for any collection Γ⊆L(X,⪯). Hence, if Ω⊆X, then
the following set
[TABLE]
is the smallest lower set in X containing
Ω. The following properties of lower sets
are easily seen to be true.
Proposition 3.1**.**
If (X,⪯) is a partially ordered set and
Ω,Ω1,Ω2⊆X, then
(i)
↓Ω=⋃x∈Ω{y∈X:y⪯x},
2. (ii)
if Ω1⊆Ω2, then
↓Ω1⊆↓Ω2.
In the case of the partially ordered set
(Rκ,⩽ι), we write ↓ιS in place of ↓S. The following fact is
of some importance in this paper.
Proposition 3.2**.**
If Ω⊆Rκ is compact, then
↓ιΩ is closed for every
ι∈{1,…,κ}.
Proof.
Fix x∈↓ιΩ. Then
there exists a sequence {xn}n=1∞⊆↓ιΩ such that
xn→x as n→∞. By Proposition
3.1(i), we can find a sequence
{yn}n=1∞⊆Ω such that
xn⩽ιyn for all n∈N. By the
compactness of Ω, there exists a subsequence
{ynk}k=1∞ of
{yn}n=1∞ which converges to some
y∈Ω. In particular, we have
[TABLE]
Applying Proposition 3.1(i) again, we see
that x∈↓ιΩ.
∎
Remark 3.3*.*
First, we note that if Ω=∅,
then the set ↓ιΩ is always
unbounded (see Proposition 3.1(i)). It is
also worth pointing out that the assumption about
compactness of Ω in the Proposition 3.2
is essential. Indeed, if κ=2 and
Ω={(−n1,n):n∈N}, then
by Proposition 3.1(i),
↓2Ω=(−∞,0)×R. This
means that ↓2Ω is not closed,
though Ω is.
The following terminology will be frequently used in
this paper.
Definition 3.4**.**
Let κ1,κ2∈N, ι∈{1,…,κ1} and
Ω⊆Rκ1. We say that a
function φ:Ω→Rκ2 is ι-increasing if
[TABLE]
The function φ is called increasing if
it is κ1-increasing.
As shown below, lower sets can be used to characterize
increasing functions.
Proposition 3.5**.**
Let κ1,κ2∈N and ι∈{1,…,κ1}. Then a function φ:Rκ1→Rκ2 is
ι-increasing if and only if
[TABLE]
where {φ⩽y}:={x∈Rκ1:φ(x)⩽y}.
Proof.
It is enough to prove the sufficiency.
Take x1,x2∈Rκ1 such that
x1⩽ιx2. Set Ω={φ⩽φ(x2)}. Since Ω∈L(Rκ1,⩽ι) and x2∈Ω,
we see that x1∈Ω. Thus φ(x1)⩽φ(x2).
∎
Now we prove that the distance function to a
ι-lower set is ι-increasing.
Proposition 3.6**.**
Let κ∈N and
ι∈{1,…,κ}. Suppose ∥⋅∥ is a norm on Rκ and
Ω∈L(Rκ,⩽ι). If
Ω=∅, then
(i)
the function dΩ:Rκ→R defined by
[TABLE]
is ι-increasing,
2. (ii)
Ω(ε):={dΩ⩽ε}∈L(Rκ,⩽ι)* for every ε∈(0,∞).*
Proof.
(i) Let x,y∈Rκ be
such that x⩽ιy. Fix ε∈(0,∞) and take yε∈Ω
such that ∥y−yε∥<dΩ(y)+ε.
Then xε:=yε+x−y⩽ιyε, which implies that
xε∈Ω (because Ω∈L(Rκ,⩽ι)). Since ∥x−xε∥=∥y−yε∥<dΩ(y)+ε,
we deduce that dΩ(x)<dΩ(y)+ε. This yields
dΩ(x)⩽dΩ(y).
We conclude this section with an example showing that
increasing function f:Rκ→R may
not be Borel (this is possible only for κ⩾2,
see [24, Lemma 6.1.]).
Example** 3.7****.**
Let V be a subset of R which is not Borel
measurable (cf. [25, Corollary, p. 53]). Set
S={(x,y)∈R2:x+y=0},
S1={(x,y)∈R2:x+y>0} and S2=S∩(V×R). It is easily seen that the function
f:=χS1∪S2 is increasing. If f were a
Borel function, then the set f−1({1})=S1∪S2 would be a Borel subset of R2. This and the
fact that S1 is an open set in R2 which is
disjoint from S2 would imply that
S2∈B(R2). Since the function
φ:R∋x→(x,−x)∈R2
is continuous and V=φ−1(S2), this would
give a contradiction.
4. Some integral inequalities on Rκ
In this section we provide integral inequalities for separately incresing function. These inequalities are related to the multidimensional spectral order. The main result of this section is Theorem 4.2, which is a generalization of [24, Theorem 4.1.]. In the proof of this theorem, we will need the following lemma which characterizes
regularity of lower sets.
Lemma 4.1**.**
Let μ be a finite Borel measure on Rκ
and let ι∈{1,…,κ}. If Ω∈L(Rκ,≤ι)∩B(Rκ), then
[TABLE]
Proof.
Let Ω∈L(Rκ,≤ι)∩B(Rκ).
Applying [25, Theorem 2.18.], Proposition
3.1, and Proposition 3.2, we get that
[TABLE]
This completes the proof.
∎
Theorem 4.2**.**
Let μ1 and μ2 be a finite Borel measure
on Rκ. We consider the following
conditions:
(i)
μ2(Ω)⩽μ1(Ω)* for every Ω∈L(Rκ,≤ι)∩B(Rκ),*
2. (ii)
∫Rκfdμ1⩽∫Rκfdμ2* for every ι-increasing Borel
function f:Rκ→[0,∞),*
3. (iii)
∫Rκfdμ1⩽∫Rκfdμ2* for every ι-increasing Borel
function f:Rκ→R such
that ∫Rκ∣f∣dμ2<∞
*(the integral ∫Rκfdμ1 may
be -\infty$$),
4. (iv)
∫Rκfdμ1⩽∫Rκfdμ2* for every ι-increasing bounded
continuous function*
f:Rκ→R,
5. (v)
∫Rκfdμ1⩽∫Rκfdμ2* for every nonnegative ι-increasing bounded
continuous function f:Rκ→[0,∞).*
Inequality
μ1(Rκ)⩽μ2(Rκ) and
(i) imply that μ1(Rκ)=μ2(Rκ).
3. (c)
If μ1(Rκ)=μ2(Rκ), then all conditions (i)-(v)
are equivalent.
Proof.
We only prove (c), since (a) and (b) are obvious. Assume that μ1(Rκ)=μ2(Rκ).
(i)⇒(iii) Let f be a real ι-increasing Borel
function
such that ∫Rκ∣f∣dμ2<∞. Define
νj(σ):=μj(f−1(σ)) for
σ∈B(R) and j=1,2. It is evident
that ν1 and ν2 are finite
Borel measure on R and
[TABLE]
Moreover,
[TABLE]
for every x∈R since f−1((−∞,x]) is a lower set in (Rκ,⩽ι) by Proposition
3.5.
Applying the measure transport theorem [15, p. 163, Theorem C.], we obtain
[TABLE]
Thus, by the measure transport theorem, (4.1), (4.2), and [24, Theorem 4.1.],
we have
[TABLE]
(iii)⇒(ii), (iii)⇒(iv), and
(iv)⇒(v) are obvious.
(ii)⇒(i) Let Ω∈B(Rκ)∩L(Rκ,≤ι).
Then
f=χRκ\Ω is a ι-increasing Borel function. By assumption we obtain
[TABLE]
Hence μ2(Ω)⩽μ1(Ω), since
μ1(Rκ)=μ2(Rκ).
(v)⇒(i) According to Lemma 4.1
it is sufficient to show that
[TABLE]
for every closed set D∈L(Rκ,≤ι).
Fix a closed set D∈L(Rκ,≤ι). For every n∈N, we
define function
fn:Rκ→R by
fn(x):=min{1,ndD(x)}, x∈Rκ.
It is easily seen that 0⩽fn(x)⩽1, fn(x)⩽fn+1(x) and
limn→∞fn(x)=χRκ\D(x) for every x∈Rκ. Note that fn’s
are continuous and ι-increasing, since dD
is ι-increasing by Proposition 3.6. It follows from Lebesgue’s monotone convergence theorem and assumption that
[TABLE]
This and equality μ1(Rκ)=μ2(Rκ) imply that
μ2(D)⩽μ1(D).
∎
Remark 4.3*.*
Let μ1 and μ2 be finite nonnegative
Borel measures on Rκ such that
μ1(Rκ)=μ2(Rκ). In this
settings the condition
[TABLE]
does not have to imply conditions (i)-(v) in
Theorem 4.2. Indeed, take two Borel measures
μ1 and μ2 on R2 defined by the
following formulas
[TABLE]
where δ(0,0), δ(0,1),
δ(1,0) and δ(1,1) are Dirac
measures on B(R2). It is evident, that
μ1(R2)=μ2(R2)=2 and
μ2((−∞,x])⩽μ1((−∞,x]) for every
x∈R2. At the same time μ1(S)<μ2(S),
where S={(x1,x2)∈R2:x1+x2⩽1}.
This means that measures μ1 and μ2 do not
satisfy the condition (i). Hence all of conditions
(i)-(v) in Theorem 4.2 do not hold.
5. Multidimensional spectral order
In this section we generalize the notion of spectral
order to the case of finite families of pairwise commuting selfadjoint
operators. First we give necessary background on
joint spectral measures and multivariable resolution of the identity.
Let Bcs(H,κ):=Sc(H,κ)∩B(H)κ. If A=(A1,…,Aκ)∈Sc(H,κ),
then there exists the
unique spectral measure EA:B(Rκ)→B(H), called the joint spectral measure of A, such that
[TABLE]
In fact, EA coincides with the product of the
spectral measures of the operators A1,…,Aκ (cf. [5]). This relationship can be made more explicit by the following two equivalent equations
[TABLE]
where
πj:Rκ∋(x1,…,xκ)→xj∈R, and
[TABLE]
The joint spectral
distributionFA of A is defined by
[TABLE]
As in the one-variable case (cf. [5]), one can
build the theory of multivariable resolutions of the identity independently of spectral measures. In Section A, for
the reader’s convenience, we recall the definition of
an abstract multivariable resolution of the identity and we
outline an idea how to construct
spectral measures on B(Rκ) by using multivariable resolution of the identity.
Let A∈Sc(H,κ).
Given a Borel function φ:Rκ→R we define
[TABLE]
The operator φ(A) is selfadjoint. Moreover, if φ⩾0, then φ(A) is positive.
After these preliminary remarks, we can state the definition of spectral order in multidimensional case.
Definition 5.1**.**
Let A,B∈Sc(H,κ). We write A≼B, if FB(x)⩽FA(x)
for every x∈Rκ.
It is easily seen that the relation ”≼” is a partial order in Sc(H,κ), since there is a one-to-one correspondence between the set of all resolutions of the identity on
Rκ and the set Sc(H,κ). This order will be called multidimensional spectral order. If κ=1, then we obtain the definition of spectral order for selfadjoint operators (cf. [23],[24]).
Now we are going to investigate the fundamental properties of multidimensional spectral order ”≼”. First we are going to answer the question which Borel functions φ:Rκ→R preserve the multidimensional spectral order, i.e. the map Φ:(Sc(H,κ),≼)∋A→φ(A)∈(Sc(H,1),≼) is a morphism in the category of partially ordered set. We begin by showing that a Borel function φ:Rκ→R preserving the multidimensional spectral order has to be increasing.
Proposition 5.2**.**
Let κ∈N and let H be a Hilbert space
such that dimH⩾1. If φ:Rκ→R is a Borel function
satisfying the following condition
[TABLE]
for every A,B∈Sc(H,κ), then φ is an increasing function.
Proof.
Fix a=(a1,…,aκ)∈Rκ and
b=(b1,…,bκ)∈Rκ such that
a⩽b. Define Ai=aiI and Bi=biI for
i=1,…,κ. It is easily seen that
EA(σ)=δa(σ)I and
EB(σ)=δb(σ)I for every
σ∈B(Rκ), where δc is a
Dirac measure defined on B(Rκ) at the
point c∈Rκ. Hence A≼B because
a⩽b. Then, by the condition (5.5),
φ(a)I=φ(A)≼φ(B)=φ(b)I. Thus φ(a)⩽φ(b),
since dimH⩾1. This completes the proof.
∎
In fact, as we will see, every increasing Borel function φ:Rκ→R preserves multidimensional spectral order. In order to prove this, we will need a few lemmata.
Lemma 5.3**.**
Let M be a σ-algebra on a set
X and let E be a spectral measure on
M. If
{Vn}n=1∞⊆M, then
[TABLE]
Proof.
Set V∞:=⋃n=1∞Vn and Mk:=E(Vk)H, for k∈N∪{∞}. It suffices to show that PM∞=E(V∞)⩽⋁n=1∞E(Vn),
since E(Vn)⩽E(V∞) for every n∈N. By equation (2.1), we have ⋁n=1∞E(Vn)=⋁n=1∞PMn=P⋁n=1∞Mn.
Thus we need to show that
M∞⊆⋁n=1∞Mn. Take
h∈M∞ and let
[TABLE]
It is obvious that
V∞=⋃n=1∞Wn and Wn∩Wm=∅ if m=n. Hence
[TABLE]
This completes the proof.
∎
Lemma 5.4**.**
Let E be a spectral measure on
B(Rκ),
Ω∈B(Rκ) and
ι∈{1,…,κ}. If Ω∈L(Rκ,⩽ι), then
[TABLE]
Proof.
Let E0(Ω):=⋁{E(D):D⊆Ω,D=D∈L(Rκ,⩽ι)}. It
is obvious that E0(Ω)⩽E(Ω). For
the opposite inequality, take any compact set
K⊆Ω. Applying Proposition 3.2 and Proposition
3.1 (ii) we get
that ↓ιK=↓ιK⊆↓ιΩ=Ω and
We need some additional notation.
Let ι∈N such that ι<κ. If C=(C1,…,Cκ)∈Sc(H,κ), then we define C′:=(C1,…,Cι)∈Sc(H,ι) and C′′:=(Cι+1,…,Cκ)∈Sc(H,κ−ι). Applying spectral theorem for finitely many commuting selfadjoint operators and measure transport theorem [5, Theorem 5.4.10.], we can deduce that EC′ and EC′′ commute and
[TABLE]
Lemma 5.5**.**
Let A=(A1,…,Aκ),B=(B1,…,Bκ)∈Sc(H,κ) and let ι∈{1,…,κ}. Assume that Aj=Bj for every j=ι+1,…,κ, whenever ι<κ. If A≼B, then
[TABLE]
for every Ω∈B(Rκ)∩L(Rκ,⩽ι).
Proof.
The proof of inequality (5.9) will be divided into several steps. We are going to deal only with the case ι<κ, since the proof in the case ι=κ is similar.
Step 1. Inequality
(5.9) holds for Ω=(−∞,x′]×Ω′′,
where x′∈Rι and
Ω′′∈B(Rκ−ι).
Equation (5.8), Lemma 5.3, and inequality A≼B imply that
[TABLE]
By assumption, EB′′=EA′′. Therefore,
[TABLE]
Step 2. Inequality (5.9)
holds, if
Ω=⋃n=1∞(−∞,xn]×Ωn′′, where xn∈Rι and
Ωn′′∈B(Rκ−ι) for all
n∈N.
Step 3. Assume that Ω is a lower set in
(Rκ,⩽ι). Let ∥⋅∥=∥⋅∥m, m∈N, be a norm on Rm given by ∥x∥m=∑j=1m∣xj∣ for every x∈Rm.
We are going to show that
[TABLE]
for every ε>0, where Bm(x,r) denote open ball {y∈Rm:∥y−x∥m<r} for x∈Rm and r>0.
Let x∈Ω. By the density of Qκ, we find
q∈Bκ(x,ε)∩Qκ such that x<q.
Hence q∈Ω(ε) and
x∈(−∞,q′]×Bκ−ι(q′′,ε). This proves the first
inclusion.
To prove the second inclusion fix q=(q′,q′′)∈(Qι×Qκ−ι)∩Ω(ε). Then
[TABLE]
since dΩ(q)⩽ε. Hence, by Proposition 3.1 and Proposition 3.6,
[TABLE]
This gives the second inclusion.
Step 4. Inequality
(5.9) holds whenever Ω is a closed lower set in (Rκ,⩽ι).
Let Qq,n:=(−∞,q′]×Bκ−ι(q′′,n1), where q=(q′,q′′)∈(Qι×Qκ−ι)∩Ω(n1) and n∈N. By (5.10) and Step 2., we obtain that
[TABLE]
Note that
{Ω(n1)}n=1∞ is a
decreasing family of sets (with respect to set
inclusion). What is more,
Ω=⋂ϵ∈(0,∞)Ω(ϵ),
since Ω is closed.
Hence
[TABLE]
Step 5. Application of Step 4. and Lemma 5.4 completes the proof of
the inequality (5.9) for an arbitrary Borel lower set
Ω in (Rκ,⩽ι).
∎
Theorem 5.6**.**
Let A=(A1,…,Aκ),B=(B1,…,Bκ)∈Sc(H,κ), and φ:Rκ→R be a Borel function. Assume that A≼B. If
(a)
the function φ is increasing,
or there exist ι∈N such that ι<κ, and Ω∈B(Rκ−ι) satisfying the following conditions
(a’)
Aj=Bj* for every j=ι+1,…,κ,*
2. (b’)
the function φ
is ι-increasing on Rι×Ω,
3. (c’)
EA′′(Rκ−ι∖Ω)=EB′′(Rκ−ι∖Ω)=0,
then φ(A)≼φ(B).
Proof.
We are going to prove only the second case (i.e. ι<κ), since similar
line of reasoning applies in the first case. First let us observe, that the set
[TABLE]
is a lower set in (Rκ,⩽ι) for every
x∈R by the assumption (b’). Using measure
transport theorem,
equality (5.8), and
(c’), we get that
(ii)⇒(iii) Apply equation (5.1) for the function πj, which is increasing and Borel for every j=1,…,κ.
(iii)⇒(i) Fix an arbitrary x=(x1,…,xκ)∈Rκ. By the definition of the multidimensional spectral order for selfadjoint operators and equality (5.3), we get that
[TABLE]
for every x1,…,xκ∈R. This completes the proof.
∎
The following corollary give us an alternative definition for the multidimensional spectral order (see [13, Theorem 1.] for bounded selfadjoint operators and [24, Theorem 6.5.] for unbounded selfadjoint operators) in terms of standard order ”⩽” for bounded selfadjoint operators and the spectral integrals of increasing Borel functions.
Corollary 5.8**.**
Let A,B∈Sc(H,κ). Then the following conditions are equivalent:
(i)
A≼B,
2. (ii)
φ(A)⩽φ(B)* for every bounded increasing continuous function φ:Rκ→R,*
3. (iii)
φ(A)⩽φ(B)* for every bounded increasing Borel function φ:Rκ→R.*
Proof.
(i)⇒(iii) Notice that φ(A),φ(B)∈B(H) for every bounded Borel function φ:Rκ→R and apply Theorem 5.7 and [24, Proposition 6.3.].
(iii)⇒(ii) It is obvious.
(ii)⇒(i) In view of Theorem 5.7, it is sufficient to show that Aj≼Bj for every j=1,…,κ. Fix j∈{1,…κ}. Let f:R→R be an arbitrary continuous and bounded increasing function. In this case φ:=f∘πj:Rκ→R
is a continuous and bounded increasing function. By [5, Lemma 6.5.2.] and condition (ii) we get that
[TABLE]
Since this inequality holds for every bounded continuous increasing function f:R→R, we deduce that Aj≼Bj by [24, Theorem 6.5.].
∎
Remark 5.9*.*
Note that there is another proof of the implication (ii)⇒(i). Indeed, similarly as in the proof of the implication (ii)⇒(i) in [24, Theorem 6.5.], we obtain that
[TABLE]
for every bounded increasing continuous function φ:Rκ→R. Thus, by Theorem 4.2, ⟨FB(x)h,h⟩⩽⟨FA(x)h,h⟩ for every x∈Rκ and h∈H. This means that A≼B.
Let A∈Sc(H,κ) and
φ=(φ1,…,φι):Rκ→Rι be a Borel function. Set
[TABLE]
It is evident that φ(A)∈Sc(H,ι).
Corollary 5.10**.**
Let κ,ι∈N.
Suppose that A,B∈Sc(H,κ) and A≼B. If φ:Rκ→Rι is an increasing Borel function, then φ(A)≼φ(B).
Proof.
First let us observe, that the functions φj:=πj∘φ, where j=1,…,ι, are increasing, since φ is increasing.
Applying Theorem 5.7 to φj we get that φj(A)≼φj(B) for j=1,…,ι. By Theorem 5.7, this is equivalent to the inequality φ(A)≼φ(B).
∎
Now let us turn our attention to two questions concerning the multidimensional spectral order. The first problem is whether the partially ordered sets (Sc(H,κ),≼) and (Bcs(H,κ),≼) are a conditionally complete lattice if κ>1.
The second question that we study is whether spectral order satisfies some kind of vector order properties.
The first question is answered in the negative by the following example. In fact, the sets (Sc(H,κ),≼) and (Bcs(H,κ),≼) are not even a lattice for κ>1.
Example** 5.11****.**
Let H=C3 be a Hilbert space with the standard orthonormal basis {(1,0,0),(0,1,0),(0,0,1)}. Then (S(H,2),≼) and (Bcs(H,2),≼) are not a lattice. Indeed, let M1, M2, N1, and N2 are defined to be the linear subspaces of C3 of the form
[TABLE]
Define A=(A1,A2) and B=(B1,B2) by
[TABLE]
It is obvious that A,B∈Bcs(H,2). Suppose that C=(C1,C2) is the infimum of {A,B} in (Bcs(H,2),≼). Then, by Theorem 5.7 and the definition of infimum, we obtain that
[TABLE]
On the other hand, (PM1∩N1,0),(0,PM2∩N2)∈Bcs(H,2). Moreover, the set {A,B} is bounded below by (PM1∩N1,0) and (0,PM2∩N2) with respect to the multidimensional spectral order. Hence, by the definition of infimum and Theorem 5.7, we deduce that
[TABLE]
Inequalities (5.12) and (5.13) imply that C=(PM1∩N1,PM2∩N2)∈/Bcs(H,2) since
[TABLE]
do not commute. Thus (Bcs(H,2),≼) is not a lattice. The same argument shows that (Sc(H,2),≼) is not a lattice too.
Now we are going to consider the second question. As shown by Olson (cf. [23]) the relation
0≼A−B may not imply A≼B for arbitrary bounded selfadjoint operators A,B unless A and B commute. Thus the spectral order is not a vector order. It is known also that A≼B imply λA≼λB whenever λ∈[0,∞). It appears that this properties can be strengthened, which is the consequence of Theorem 5.7 and Theorem 5.6.
Corollary 5.12**.**
Let A=(A1,A2),B=(B1,B2)∈Sc(H,2). Assume that A1≼B1 and A2≼B2. Then
[TABLE]
Proof.
Note that A≼B by assumptions and Theorem 5.7. Let φ:R2→R be a function defined by φ(x1,x2):=x1+x2 for x1,x2∈R. By [5, Theorem 5.4.7]
and Theorem 5.7 applied to the function φ, which is increasing, we get that
Suppose that A,B,C are selfadjoint operators in H. Assume also that C is positive and commutes with A and B. If A≼B, then
[TABLE]
Proof.
Let A=(A,C) and B=(B,C). By Theorem 5.7 (iii), A≼B. Take a function ψ:R2→R given by ψ(x1,x2):=x1⋅x2 for x1,x2∈R. It is easily seen that the function ψ is 1-increasing on R×[0,∞) and EC((−∞,0))=0. Thus, by Theorem 5.6 and [5, Theorem 5.4.7], we obtain that
[TABLE]
∎
We close this section with the example of an order for normal operators. In [8] Brenna and Flori defined spectral order for bounded normal operators. The definition of this order can be easily adopted also in the case of unbounded normal operators.
Example** 5.14****.**
Let T be a normal operator in H, i.e. densely defined operator such that D(T)=D(T∗) and ∥Th∥=∥T∗h∥ for every h∈D(T). The notation N(H) will mean the set of all normal operators in H and Bn(H):=N(H)∩B(H). Denote by ET the spectral measure of T on B(C), where C≃R2 via ρ(x,y)=x+iy, x,y∈R. Consider the real and imaginary part of T defined by
[TABLE]
Then
[TABLE]
Note that ReT and ImT are selfadjoint. Moreover, from the [5, Theorem 5.4.10.] we derive
[TABLE]
Therefore (ReT,ImT)∈Sc(H,2).
Now, let T1,T2∈N(H). Then we write
[TABLE]
Applying equations (5.3) and (5.4) we can rewrite this as
[TABLE]
The following propositions shows that the spectral order for pairs of commuting selfadjoint operators and the spectral order for normal operators are isomorphic in the category of partially ordered sets.
Proposition 5.15**.**
The mappings Ψ and Ψ0 are order isomorphisms, where Ψ:(N(H),≼)∋T→(ReT,ImT)∈(Sc(H,2),≼) and Ψ0:(Bn(H),≼)∋T→(ReT,ImT)∈(Bcs(H,2),≼).
Proof.
Let A=(A1,A2)∈Sc(H,2). Define the measure EA∘ρ−1 on B(C) by EA∘ρ−1(Δ)=EA(ρ−1(Δ)), Δ∈B(C). Then TA=∫CzEA∘ρ−1(dz) is a normal operator in H such that ReTA=A1 and ImTA=A2.
Indeed, we have
[TABLE]
and
[TABLE]
In partcular, Ψ is bijective. According to the definition of the multidimensional spectral order and (5.15), Ψ is order preserving. At the end, note that Ψ(Bn(H))=Bcs(H,2), which completes the proof.
∎
6. Joint bounded vectors
The aim of this section is to describe the joint resolution of the identity of A∈Sc(H,κ) in terms of joint bounded vectors. The main result
of this section Proposition 6.3 will be used in Section 8 to characterize multidimensional spectral order in the case of positive operators.
First we are going to recall the definition of joint bounded vectors. Let x=(x1,…,xκ)∈Rκ and α∈[0,∞)κ. Set xα:=x1α1⋅…⋅xκακ provided that xjαj are well-defined for every j=1,…,κ. Define functions φα:Rκ→R, α∈Z+κ, and ψβ:Rκ→R, β∈[0,∞)κ, by the following formulas
[TABLE]
The monomial Aα is defined by
[TABLE]
Similarly, the fractional power Aα is given by
[TABLE]
Note that ψα(A)=φα(A),
provided that α∈Z+κ and suppEA⊆[0,∞)κ.
Let A∈Sc(H,κ). We define the following sets
[TABLE]
We say that h∈H is a joint
bounded vector of A if
h∈B(A). More information on joint bounded vectors can be found in [26].
For the sake of completeness, Proposition 6.3 will be preceded by the following two Lemmata (see also [26, Theorem 1.13.]).
Lemma 6.1**.**
If A=(A1,…,Aκ)∈Sc(H,κ), then
[TABLE]
Proof.
Applying equalities (5.2) and (5.6) we obtain that
[TABLE]
what proves the claim.
∎
If suppEA⊆[0,∞)κ, then we say
that A is positive.
Lemma 6.2**.**
Let A=(A1,…,Aκ)∈Sc(H,κ). Then
[TABLE]
Moreover, if A is positive, then
[TABLE]
Proof.
Let
D:=j=1⋂κD∞(Aj). We have to show that D⊆D∞(A) since
inclusion D∞(A)⊆D is obvious.
Let h∈D and α∈Z+κ. Consider a
measure μh on B(Rκ) defined by
μh(σ):=⟨EA(σ)h,h⟩ for
σ∈B(Rκ). Using the definition of
D we derive that ∫Rκxj2καjdμh(x)<∞ for
j=1,…,κ. This and [6, Corollary
2.11.5] imply that
∫Rκx2αdμh(x)<∞. Thus h∈D(Aα) for every α∈Z+κ.
Consequently, h∈D∞(A).
For the ”moreover” part, consider only the inclusion ⊆ since the inclusion ⊇ is evident.
Let h∈D∞(A) and α∈[0,∞)κ. Without loss of generality we may assume that ∥h∥=1. Take β∈Nκ such that κα⩽β. By assumption, ∫[0,∞)κxj2βjdμh(x)<∞. Applying [6, Corollary 2.11.5] and Jensen inequality, we obtain that
[TABLE]
Hence h∈⋂α∈[0,∞)κD(Aα), which completes proof.
∎
In the sequel we will use the following notation
DΛ(A):=⋂α∈ΛD(Aα) for
Λ⊆[0,∞)κ and
∣α∣:=α1+…+ακ
for
α=(α1,…,ακ)∈[0,∞)κ.
Proposition 6.3**.**
Let A∈Sc(H,κ) be positive, h∈H, and a∈[0,∞)κ. Assume that Λ⊆[0,∞)κ satisfies the condition
[TABLE]
Then the following conditions are equivalent:
(i)
h∈Ba(A),
2. (ii)
h∈R(FA(a)),
3. (iii)
h∈D∞(A)* and there exists real number c>0 such that*
[TABLE]
Moreover, if h∈DΛ(A)∩(⋃j=1κN(Aj))⊥ and there exists real number c>0 such that
[TABLE]
then h∈R(FA(a)).
Proof.
Let μh(σ):=⟨EA(σ)h,h⟩
for every σ∈B(Rκ).
(i)⇒(ii) By Lemma 6.2,
h∈D∞(Aj) for every
j=1,…,κ. At the same time ∥Ajnh∥=∥Anejh∥⩽cajn for every n∈Z+. This
implies that h∈Baj(Aj). Hence, by [24, Proposition 5.1.],
h∈R(FAj(aj)) for every j=1,…,κ.
Thus h∈R(FA(a)), since
FA(a)=FA1(a1)…FAκ(aκ).
(ii)⇒(iii) Let
α∈[0,∞)κ. Then, by (ii) and positivity of
A, we obtain that suppμh⊆[0,a] and
[TABLE]
Thus h∈D(Aα) and
[TABLE]
(iii)⇒(i) It is obvious.
For the ”moreover” part, assume that
h∈DΛ(A)∩(⋃j=1κN(Aj))⊥ satisfies equation (6.4). Suppose that
h∈/R(FA(a)). In particular, μh(Rκ\(−∞,a])>0.
Applying [5, Theorem
6.1.3] and (5.2) we obtain that
[TABLE]
What is more
EA(Rκ\[0,∞)κ)=0,
since A is positive. Thus
[TABLE]
Put
[TABLE]
for j∈{1,…,κ} and n∈N. Then
[TABLE]
This together with (6.5) allow us to choose j∈{1,…,κ} and n∈N such that
By condition (6.3), we can find a
sequence
{α(m)}m=1∞⊆Λ such
that
[TABLE]
where
α(m)=(α1(m),…,ακ(m)). Then inequality (6.6) implies that
[TABLE]
which is a contradiction. Thus h∈R(FA(a)).
∎
Assume that A and Λ satisfy the assumptions of Proposition 6.3. The following example shows that without the condition (6.4)
it may happen that h∈DΛ(A)∩(⋃j=1κN(Aj))⊥ but h∈/D∞(A).
Example** 6.4****.**
Let Λ:=[0,∞)×(0,∞) and H=L2([1,∞),m), where m is Lebesgue measure on Borel subsets of [1,∞). Define A=(Mφ1,Mφ2), where the functions
φ1,φ2:[1,∞)→R
are given by φ1(x)=x and
φ2(x)=e−x for x∈R. Then, by Lemma
7.6, A∈Sc(H,2). A is also positive since φj(x)⩾0
for every x∈R and j=1,2. Let
h(x):=x1 for x∈[1,∞). It is
evident that h∈H and the set Λ satisfies
the condition (6.3).
We are going to show that h∈DΛ(A)\D∞(A). If
α∈Λ, then α2>0. Hence
[TABLE]
Thus, by Lemma 7.6 (iii),
h∈D(Mφ1α1φ2α2)=D(Aα). On the other hand,
[TABLE]
which means that h∈/D(A1)⊇D∞(A), which completes the proof.
7. Monomials and multidimensional spectral order
Let A,B∈Sc(H,κ). In this section we discuss the relations between inequality A≼B and the domains of Aα and Bα for α∈Zκ. In Theorem 7.3, the appropriate condition guaranteeing the inclusion D(Bα)⊆D(Aα) will be formulated.
We begin our consideration by some facts about
positive and negative parts of selfadjoint
operators. Let A be a selfadjoint operator in H. We denote the positive part and the negative part of A by A+ and A−, respectively. By the definition,
[TABLE]
where the functions f±:R→R are given by
[TABLE]
It is known that
A+ and A− are selfadjoint. Moreover, A+ is positive.
Since the functions f+ and f− are increasing, the following property holds.
Lemma 7.1**.**
If A and B are selfadjoint operators in H such that A≼B, then A+≼B+ and A−≼B−.
Let ε=(ε1,…,εκ)∈{−,+}κ. The function fε1×…×fεκ:Rκ→Rκ, where f± are given by formulas (7.1), will be dentoted by fε. In particular,
[TABLE]
In the sequel we will use the following multi-sign †=(†1,…,†κ)∈{−,+}κ, where
†j=+ for j=1,…,κ.
For C=(C1,…,Cκ)∈Sc(H,κ), we define Cε∈Sc(H,κ) by
[TABLE]
Then, by (5.11), (7.2), and [5, Lemma 6.5.2.], we derive that
[TABLE]
Moreover, by equality
fεj(Cj)=(πj∘fε)(C) and [5, Theorem 5.4.10], we get that
which gives (7.5), since h∈H was chosen arbitrarily.
∎
The following theorem answers question raised at the beginning of this section.
Theorem 7.3**.**
Let A,B∈Sc(H,κ) and
let α∈Z+κ. If A≼B and
[TABLE]
then
[TABLE]
Proof.
First observe that the function fε is increasing. Hence, by Corollary 5.10 and assumptions, we get that Aε=fε(A)≼fε(B)=Bε.
Now we will prove the inclusion (7.7). It follows from the condition (7.6) that D((Aε)α)=H for every ε=†. This and the equality (7.5) imply that
[TABLE]
Note that suppEA†∪suppEB†⊆[0,∞)κ
by Corollary 6.1 and the definition of A† and B†.
Hence, by Theorem 5.7, we have
(A†)α=ψα(A†)≼ψα(B†)=(B†)α, since the function
ψα is increasing.
Moreover, the operators (A†)α and
(B†)α are positive. Applying [24, Proposition
7.1.] we
infer that D((B†)α)⊆D((A†)α). Eventually, using equalities
(7.5) and (7.8), we deduce that
[TABLE]
which completes the proof.
∎
Remark 7.4*.*
If κ=1 and α=α1=1, then Theorem 7.3 implies the second part of [24, Proposition 6.3.]. Indeed, the condition A−∈B(H) holds if and only if A is bounded from below.
We are now going to discuss in more detail the condition (7.6). It may happen that the inclusion (7.7) may not hold, even if the condition (7.6) does not hold for only one ε∈{−,+}κ\{†}. This will be illustrated by Example 7.8. The example will be preceded by two propositions describing spectral order for multiplication operators.
Proposition 7.5**.**
Let (X,A,μ) be a measure space. Assume that μ is σ-finite.
If φ,ψ:X→R are A-measurable, then the following conditions are equivalent:
(i)
Mφ≼Mψ,
2. (ii)
⟨Mφh,h⟩⩽⟨Mψh,h⟩* for every h∈D(Mφ)∩D(Mψ),*
3. (iii)
(ii)⇒(iii) Suppose that for some N∈N there exists an A-measurable set Δ⊂{x∈X:−N<ψ(x)<φ(x)<N} such that 0<μ(Δ)<∞. Then
[TABLE]
On the other hand, h:=χΔ∈D(Mφ)∩D(Mψ). Thus, by assumption,
[TABLE]
which is a contradiction. Hence φ⩽ψ a.e. [μ], since μ is σ-finite.
(iii)⇒(i) Let t∈R. Note that
[TABLE]
By assumption, μ({x∈X:ψ(x)<φ(x)})=0. Thus, by [27, Example 4.3.] and (7.9), we obtain that
[TABLE]
for every h∈L2(X,μ). Hence FMψ(t)⩽FMφ(t) for every t∈R, which completes the proof.
∎
For the sake of completeness, we include the following lemma.
Lemma 7.6**.**
Let (X,A,μ) be a measure space. Assume that
φj:X→R is an A-measurable function for every j=1,…,κ. If φ=(φ1,…,φκ):X→Rκ and Mφ:=(Mφ1,…,Mφκ), then
(i)
Mφ∈Sc(L2(X,μ),κ),
2. (ii)
for every σ∈B(Rκ) and h∈L2(X,μ)
[TABLE]
3. (iii)
if f:Rκ→R is a Borel function, then
[TABLE]
Proof.
(i) Let σ,τ∈B(R) and h∈L2(X,μ).
Applying equation (2.2) we obtain that
[TABLE]
Hence Mφ∈Sc(L2(X,μ),κ).
(ii) Let us define E(σ)h:=χφ−1(σ)h for σ∈B(Rκ) and h∈L2(X,μ). Take σ=σ1×…×σκ, where σ1,…,σκ∈B(R). Then, by (2.2) and (5.3),
[TABLE]
Hence EMφ(σ)=E(σ) for every σ∈B(Rκ), since E is a spectral measure on B(Rκ) and (B(R))κ generates σ-algebra B(Rκ).
(iii) Using [5, Theorem 5.4.10.]transport theorem, (7.10), and (2.2), we obtain
[TABLE]
This implies (7.11), since there is a one to one correspondence between spectral measures and selfadjoint operators.
∎
Combining Proposition 7.5, Lemma 7.6, and Theorem 5.7, we obtain the following proposition.
Proposition 7.7**.**
Let (X,A,μ) be a σ-finite measure space. Assume that
φj,ψj:X→R are A-measurable functions for every j=1,…,κ. Consider φ=(φ1,…,φκ):X→Rκ and ψ=(ψ1,…,ψκ):X→Rκ. Then
[TABLE]
Example** 7.8****.**
Let H=L2(Rκ,mκ), where mκ denotes Lebesgue measure on B(Rκ), and let ε=(ε1,…,εκ)∈{−,+}κ\{†}.
Fix j0∈{1,…,κ} such that εj0=−. Define the functions φj,ψj:Rκ→R for j∈{1,…,κ} by
[TABLE]
[TABLE]
and
[TABLE]
It is evident that φj and ψj are Borel function for every j=1,…,κ.
Let A:=Mφ and B:=Mψ, where φ=(φ1,…,φκ) and ψ=(ψ1,…,ψκ). According to
Lemma 7.6, A,B∈Sc(H,κ).
We are going to show that A and B satisfy the following conditions:
(i)
A≼B,
2. (ii)
(Aδ)α∈B(H) for every δ∈{−,+}κ\{ε} and for all α∈Nκ,
3. (iii)
(Aε)α∈/B(H) for every α∈Nκ,
4. (iv)
D(Bα)⊆D(Aα) for every α∈Nκ.
(i) This is the consequence of Proposition 7.7, since φj(x)⩽ψj(x) for every x∈Rκ and j=1,…,κ.
(ii) We can find i∈{1,…,κ} such that δi=εi, since δ=(δ1,…,δκ)=ε. Then
[TABLE]
By definition (7.3), Lemma 7.6 (iii), and equality (7.14), we obtain
[TABLE]
(iii) Similarly to (ii), we show that
[TABLE]
since the function ∏j=1κ(fεj∘φj)αj(x)=(−1)αj0xα−αj0ej0(xj02+1)αj0χRεκ(x) is not essentially bounded with respect to Lebesgue measure.
where Δ=[−1,1]×…×[−1,1]×j0(−∞,0]×[−1,1]×…×[−1,1].
Note that h∈D(Bα)\D(Aα). Indeed, by the definition of h and Fubini theorem,
we get
[TABLE]
Thus h∈D(MΠj=1κ(ψj)αj). At the same time
[TABLE]
since αj0=0. This means that h∈/D(MΠj=1κ(φj)αj).
8. Positive κ-tuples
In this section we study the multidimensional spectral order in the case of positive κ-tuples of pairwise commuting selfadjoint operators. We begin by the following proposition, which generalizes [24, Proposition 7.1.].
Proposition 8.1**.**
Let A,B∈Sc(H,κ) and
let α∈[0,∞)κ. Suppose that A
and B are positive. If A≼B, then the
following conditions hold:
(i)
Aα≼Bα,
2. (ii)
D(Bα)⊆D(Aα),
3. (iii)
∥Aαh∥⩽∥Bαh∥* for every h∈D(Bα),*
4. (iv)
⟨Aαh,h⟩⩽⟨Bαh,h⟩* for every h∈D(Bα),*
5. (v)
Aα⩽Bα.
Moreover D∞(B)⊆D∞(A) and
B(B)⊆B(A).
Proof.
(i) Apply Theorem 5.7 for function ψα defined by equality (6.1), which is increasing.
(ii), (iii), (iv) and (v) follows from (i) and
[24, Proposition 7.1.] applied for s=1 and
positive operators Aα and Bα.
To prove the ”moreover” part let us note that
inclusion D∞(B)⊆D∞(A) follows from
(ii) and Lemma 6.2. If
h∈Ba(B) for some
a∈(0,∞)κ, then using (iii) and
Proposition 6.3 (b) we can find real number
c>0 such that
[TABLE]
Applying Proposition 6.3 once more we get that h∈Ba(A), which gives us the second inclusion.
∎
The following two theorems Theorem 8.2 and Theorem 8.3, which are counterparts of [24, Theorem 7.4.], characterize multidimensional spectral order for positive κ-tuples in terms of appropriate inequalities for C∞-vectors.
In Theorem 8.3 we assume additionally that one of the compared κ-tuples consists of injective operators.
Theorem 8.2**.**
Let A=(A1,…,Aκ),B=(B1,…,Bκ)∈Sc(H,κ) be positive.
Then the following conditions are equivalent:
(i)
A≼B,
2. (ii)
D∞(B)⊆D∞(A)* and LA/B(h)⩽1 for every h∈D∞(B),*
3. (iii)
B(B)⊆D∞(A)* and LA/B(h)⩽1 for every h∈B(B),*
4. (iv)
B(B)⊆D∞(A)* and LAj/Bj(h)⩽1 for every h∈B(B) and j=1,…,κ,*
5. (v)
B(B)⊆B(A)* and LA/B(h)⩽1 for every h∈B(B),*
where111We use the convention that 0/0=0 and a/0=∞ if a>0.
Implications (ii)⇒(iii), (iii)⇒(iv), and (v)⇒(iii) are obvious.
(iv)⇒(i) According to Theorem 5.7, it suffices to show that
[TABLE]
since A,B are positive. Fix j∈{1,…,κ} and x⩾0.
Let h∈R(FBj(x)). Define hk:=EB(Δk)h for k∈N, where
[TABLE]
By Proposition 6.3, hk∈B(B) for every k∈N. In particular, by the assumption, Lemma 6.2, and [24, Proposition A.1.], hk∈B(Bj)∩D∞(Aj) and limn→∞n∥Ajnhk∥/∥Bjnhk∥=LAj/Bj(hk)⩽1 for every k∈N. This implies that there is N∈N such that ∥Ajnhk∥=∥Bjnhk∥=0 or ∥Bjnhk∥=0 for n>N.
Then, by [29, Lemma 8.], we have
[TABLE]
Hence, by [29, Lemma 8.] and [24, Proposition 5.1.], hk∈Bx(Aj)=R(FAj(x)) for every k∈N. Note that hk→h as k→∞, since h∈R(FBj(x)) and \bigcup_{k\in\mathbb{N}}\Delta_{k}=[0,\infty)\times\ldots\times\underbrace{[0,x]}\limits_{j}\times\ldots\times[0,\infty). Thus h∈R(FAj(x)) as R(FAj(x)) is closed, which proves (8.1).
∎
Theorem 8.3**.**
Let A=(A1,…,Aκ),B∈Sc(H,κ) be positive.
Assume that N(Aj)={0} for j=1,…,κ.
If Λ⊆[0,∞)κ satisfies the
condition (6.3), then the following
conditions are equivalent:
(i)
A≼B,
2. (ii)
D∞(B)⊆D∞(A)* and LA/B(h)⩽1 for every h∈D∞(B),*
3. (iii)
B(B)⊆DΛ(A)* and LA/BΛ(h)⩽1 for every h∈B(B),*
4. (iv)
B(B)⊆B(A)* and LA/BΛ(h)⩽1 for every h∈B(B),*
where
[TABLE]
Proof.
(i)⇒(ii) This follows from
Proposition 8.1 and equality (6.2).
(ii)⇒(iii) It is obvious.
(iii)⇒(i) It suffices to
verify, that FB(a)⩽FA(a) for every
a∈[0,∞)κ, since A and B are
positive. Fix a∈[0,∞)κ and
h∈R(FB(a)). Applying Proposition
6.3 we get that
[TABLE]
for some real number c>0. By the assumptions
[TABLE]
Fix ε>0. Since LA/BΛ(h)⩽1, there exists a positive number M∈N such that
[TABLE]
In particular,
[TABLE]
for every α∈ΛM. Note that the set ΛM satifies the condition (6.3). Hence, by
(8.2) and Proposition
6.3, we obtain that h∈R(FA((1+ε)a)). Since ε>0 was chosen arbitrarily, we infer that h∈R(FA(a)).
Repeating the proof of Proposition 8.4 and applying Theorem 8.3 instead of Theorem 8.2, we have the following proposition.
Proposition 8.5**.**
Let A,B∈Sc(H,κ) be positive and let Λ⊆[0,∞)κ such that N(Aj)={0} for
j=1,…,κ,
Suppose that the set
Λ⊆[0,∞)κ satisfies condition (6.3),
and there exists a family
{rα}α∈Λ⊆[1,∞)
satisfying the following condition
[TABLE]
Then A≼B if and only if Aα⩽rαBα for every α∈Λ.
Let A,B∈Sc(H,κ) be positive. Let us consider the set
[TABLE]
Proposition 8.1 tells us, that Λ(A,B)=[0,∞)κ if A≼B. Taking into account [24, Corollary 7.6.], we are going to determine what are sufficient and necessary condition on the set Λ(A,B) for the relation A≼B to hold.
Proposition 8.6**.**
Let A=(A1,…,Aκ),B=(B1,…,Bκ)∈Sc(H,κ) be positive. Cosider the following conditions:
(i)
A≼B,
2. (ii)
the set Λ(A,B)∩{sej:s∈[0,∞)}
is unbounded for every j=1,…,κ.
3. (iii)
[TABLE]
Then conditions (i) and (ii) are equivalent.
Moreover, if N(Aj)={0} for j=1,…,κ, then all the conditions (i)-(iii) are equivalent.
Proof.
(i)⇒(ii) It is a consequence of the
Proposition 8.1.
(ii)⇒(i) Fix j∈{1,…,κ}. By
[5, Lemma 6.5.2] we get that
Cjs=Csej for every positive C∈Sc(H,κ)
and for every s∈[0,∞), since
ψsej(x)=ψs∘πj(x) for every
x∈[0,∞)κ. Thus the set {s∈[0,∞):Ajs⩽Bjs} is infinite for every j=1,…,κ. From [24, Corollary 7.6] we infer that
Aj≼Bj for every j=1,…,κ.
Hence A≼B by Theorem 5.7.
Now assume that N(Aj)={0} for j=1,…,κ. The equivalence (i)⇔(iii) follows from Proposition
8.5 applied for
Λ=Λ(A,B) and
{rα}α∈Λ, where rα=1
for every α∈Λ.
∎
Note that in the case κ=1 conditions (ii) and (iii) coincide.
In particular, injectivity of A1 can be omitted by [24, Corollary 7.6]. On the other hand, the condition (8.5) may be to weak to ensure inequality A≼B if κ>1. This can happen if some of the operators A1,…,Aκ are not injective.
Example** 8.7****.**
Let H=C2 be a Hilbert space with standard orthonormal basis {(1,0),(0,1)} and let θ∈[1,∞). Consider the 2×2 matrices A1, A2, Bθ,1, Bθ,2 given by
[TABLE]
Let us define A:=(A1,A2) and Bθ:=(Bθ,1,Bθ,2). It is evident that A,Bθ∈Bcs(H,2) are positive for θ∈[1,∞), N(A1)=H, and N(A2)={0}. We are going to show, that A and Bθ satisfy the following conditions:
(i)
for every k∈N there exixts θk∈(2,∞) such that
[TABLE]
2. (ii)
A≼Bθ if and only if θ=2.
In particular, if θ=2, then A≼Bθ
although A and Bθ satisfy
condition (8.5).
Proof.
(i) First, if
(s,t)∈(0,∞)×[0,∞), then
A1sA2t=0 and
Bθ,1sBθ,2t=Bθ,2t⩾0. In
particular
(s,t)∈Λ(A,Bθ).
On the other hand, by [24, Proposition 8.3.]
there exists θk∈(2,∞) such that
[TABLE]
This implies that
[TABLE]
By Löwner-Heinz inequality we get that
A2s=(A2k)ks⩽(Bθ,2k)ks=Bθ,2s for
every s∈[0,k]. Thus
[TABLE]
(ii) We deduce from Theorem 5.7 and Corollary
5.12 that the inequality A≼Bθ
holds if and only if A=A2−IH≼Bθ,2−IH=Bθ, since A1≼Bθ,1. The application of [24, Lemma 8.2.]
completes the proof.∎
Appendix A Resolutions of the identity on Rκ
In this section, we recall the definition of
an abstract multivariable resolution of the identity and we
outline an idea how to construct
spectral measures on Rκ by using multivariable resolutions of the identity (see [4] for the case of scalar
measures).
For c,d∈R and j∈{1,…,κ}, we
define the difference operator
△d,c(j) acting on operator-valued
functions F:Rκ→B(H) by
[TABLE]
for all x1,…,xκ∈R. If
F:Rκ→B(H), then we set
[TABLE]
We say that an operator-valued function
F:Rκ→P(H) is a resolution of the identity on Rκ if F satisfies the
following three conditions222Given a sequence
{an}n=1∞⊆Rκ and
a∈Rκ, we write an↘a (resp., an↗a) if
{an}n=1∞ is monotonically decreasing
(resp., increasing) with respect to the partial order
“⩽” in Rκ, and convergent to a.
If a=(−∞,…,−∞) (resp., a=(∞,…,∞)), we also write an↘−∞ (resp., an↗∞).:
(A)
\big{(}F(a,b]\big{)}(x)\in\mathbf{P}({\mathcal{H}}) for all
a,b,x∈Rκ such that a⩽b,
2. (B)
\textscsot−x→x0x0⩽xlimF(x)=F(x0) for every x0∈Rκ,
3. (C)
if {an}n=1∞,{bn}n=1∞⊆Rκ are such that an↘−∞ and bn↗∞, then
[TABLE]
If E is a spectral measure on
B(Rκ), then the function
F:Rκ→P(H) given by
[TABLE]
is a resolution of the identity.
In fact, the equation (A.1) defines a one-to-one correspondence between the set of all resolutions of the identity on
Rκ and the set of all spectral measures on B(Rκ), which can be deduced from the following theorem.
Theorem A.1**.**
Let F be a resolution of the identity on Rκ. Then there exists the unique spectral measure on
B(Rκ) such that
[TABLE]
The sketch of the proof.
The uniqueness. The uniqueness is a consequence of the fact that the family {(a,b]:a,b∈Rκ,a⩽b} generates the σ-algebra B(Rκ).
The existence. Denote by
F0(Rκ) the collection of all
finite disjoint sums of sets of the form (a,b]∩Rκ, where a,b∈Rκ. Clearly,
F0(Rκ) is the algebra generated
by the family I={(a,b]∩Rκ:a,b∈Rκ}.
Now we define the function E0:F0(Rκ)→P(H) in few steps:
Step 1. If a,b∈Rκ and a⩽b, then E0((a,b]):=F(a,b].
Step 2. If a,b∈Rκ and a⩽b, then
E0((a,b]):=\textscsot−limF(an,bn],
where an,bn∈Rκ for N,
an↘a and bn↗b. The limit exists since F(a,b]⩽F(c,d] whenever c⩽a⩽b⩽d.
Step 3. Now if J=⋃j=1nJj, where J1,…,Jn∈I are pairwise disjoint, then we set
E0(J):=∑j=1nE0(Jj). E0 is well-defined and additive. Moreover,
E0(Rκ)=I by (C).
By [5, Theorem 5.2.3.] it is sufficient to show that E0 is σ-additive. Fix h∈H. Let
μh0(J):=⟨E0(J)h,h⟩ for
J∈F0(Rκ) and
Fh(x):=⟨F(x)h,h⟩ for x∈Rκ.
By the conditions (A) and (B), Fh is a distribution function
on Rκ. Moreover,
μh0((a,b])=Fh(a,b] for
a,b∈Rκ,a⩽b. By
[4, Theorem 1.4.9.] there exists a Borel measure μh such that μh((a,b])=Fh(a,b] for a,b∈Rκ,a⩽b. In particular,
μh∣F0(Rκ)=μh0. Thus μh0 is σ-additive. Therefore
E0 is also σ-additive.
∎
Acknowledgements
I would like to thank Professor Jan Stochel for his helpful advice, which improved the paper.
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