Nest algebras in an arbitrary vector space
Don Hadwin and K.J.
Harrison
University of New Hampshire, NH., USA Murdoch University, WA., Australia
Abstract
We examine the properties of algebras of linear transformations that leave
invariant all subspaces in a totally ordered lattice of subspaces of an
arbitrary vector space. We compare our results with those that apply for the
corresponding algebras of bounded operators that act on a Hilbert space.
1 Introduction
The study of triangular forms for operators has long been an important part of
the theory of non-self-adjoint operators and operator algebras. See [1]
for a detailed account. In [5] Ringrose introduced the terms ‘nest’
and ‘nest algebra’. For Ringrose a nest N is a complete, totally
ordered sublattice of the lattice of all closed subspaces of a Hilbert space
H that contains the trivial subspaces {0} and H.
The corresponding nest algebra AlgN is algebra
of all operators on H that leave invariant each of the subspaces
in N.
In this paper we examine totally ordered lattices of subspaces of an arbitrary
vector space and the associated operator algebras. Here a nest N
in a vector space X is a complete, totally ordered sublattice of
the lattice of all subspaces of X that contains the trivial
subspaces {0} and X. The corresponding nest algebra
AlgN is algebra of all operators on
X that leave invariant each of the subspaces in N.
We obtain results concerning the finite rank operators in AlgN that mirror those that apply in the Hilbert space case. We also
examine the Jacobson radical of AlgN and obtain
a simple characterization when the nest satisfies a descending chain
condition. We also show that the same characterization of the Jacobson radical
holds for other types of nest algebras.
1.1 Complete distributivity
The lattice operations ∧ and ∨in S(X), the
lattice of all subspaces of the vector space X, are
intersection and linear span. In particular, if M and N are subspaces of X, M∨N=span{M,N}={x+y:x∈M,y∈N}. However in a totally ordered sublattice the lattice
operations are simply the set operations ∩ and ∪. So any nest
N is completely distributive (see [1]).
Suppose that N is a nest in X. For each x∈X we define
[TABLE]
It follows easily from (1) that
[TABLE]
Lemma 1
The join-irreducible elements of the completely distributive lattice
N are the subspaces of the form N(x) where x is
any non-zero vector in X.
Proof. Suppose that x=0, and that N(x)⊆⋃{N:N∈N#} where N#⊆N. Then
x∈⋃{N:N∈N#} by (2). So x∈N
for some N∈N#, and it follows from (2) that
N(x)⊆N. So N(x) is join-irreducible.
Suppose now that N is a join-irreducible subspace in N.
Clearly N=⋃{N(x):x∈N}, and
so N⊆N(x) for some x∈N.
So N=N(x).
Remark 2
Complete distributivity distinguishes the vector space case from the Hilbert
space case. Some of the most interesting nests of closed subspaces of a
Hilbert space are ‘continuous’, have no join-irreducible elements, and are not
completely distributuve.
2 Finite rank operators
The rank of an operator in L(X) is the dimension
of its range. In this section we examine the properties of operators in a
nest algebra A=AlgN whose ranks are
finite. Let R denote the set of finite-rank operators
in L(X). Various authors have investigated the
properties of R∩A in the Hilbert space context. For
example, Erdos proved [2] that if N is a nest of closed
subspaces of a Hilbert space then the strong closure of R∩A is A.
Rank-one operators also have an important role in the Hilbert space context.
Suppose that T∈R1, where R1 denotes the set
of all rank-one operators in L(X). Then there exists
y∈X such that for all x∈X, Tx=φ(x)y
where φ(x)∈F. Since T is linear the map x→φ(x) is a linear functional of X. Let
X′ denote the algebraic dual of X, i.e. the
set of all linear maps from X into F. Each rank-one
operator on X has the form x⊗φ, where x∈X, φ∈X′, and (x⊗φ)(y)=φ(y)x for all y∈X.
The following lemma characterizes the rank-one operators in A.
Lemma 3
Suppose that x∈X and φ∈X′. Then x⊗φ∈R1∩A if and
only if N−(x)⊆kerφ.
Proof.* First suppose that x⊗φ∈R1∩A, and
that y∈N−(x). Since N−(x)∈A, (x⊗φ)(y)=φ(y)x∈N−(x). Since x\notin$$\mathfrak{N}_{-}(x) it follows that φ(y)=0.
So N−(x)⊆kerφ.*
*Now suppose that N−(x)⊆kerφ and that N∈N. If N⊂N(x) then N⊆N−(x) and (x⊗φ)N={0}⊆N. If N(x)⊆N then (x⊗φ)N=spanx⊆N(x)⊆N. So x⊗φ∈R1∩A.
*
2.1 Reflexivity of N
For any subset of A of L(X) let
\operatorname*{Lat}$$\mathfrak{A} denote the sublattice of S(X) consisting of all subspaces of X that are
invariant under each of the operators in A. We shall show that
[TABLE]
from which it follows that N is reflexive, i.e. N=LatAlgN.
Longstaff shows in ([4]) that (3) holds in the Hilbert
space context.
The following lemma will be used to establish the reflexivity of
N.
Lemma 4
If x and y are non-zero vectors in X and y∈N(x), then there exists R∈R1∩A
such that Rx=y.
Proof.* Since y∈N(x), N(y)−⊂N(y)⊆N(x). So x∈/N(y)−, and hence there
exists φ∈X′ such that φ(x)=1 and N(y)_⊆kerφ. Then R=y⊗φ∈R1∩A and Rx=φ(x)y.
* **
Theorem 5
N* is reflexive.*
Proof.* We shall show that \mathfrak{N}=$$\operatorname*{Lat}(\mathcal{R}_{1}\cap\mathcal{A}). Clearly N⊆Lat(R1∩A). Suppose that N∈Lat(R1∩A). It is enough to show that N∈N.*
Suppose that x and y are non-zero vectors in N and N(x)
respectively. So by Lemma 4 there exists R∈R1∩A such that Rx=y. Since N∈Lat(R1∩A), it follows that y∈N, and
hence N(x)⊆N.
Clearly N⊆⋃{N(x):x∈N}, and so
[TABLE]
*So N=⋃{N(x):x∈N}∈N, as required.
*
2.2 Finite rank idempotents
A simple calculation shows that (x1⊗φ1)(x2⊗φ2)=φ1(x2)(x1⊗φ2). So x⊗φ is idempotent if and only if φ(x)=1.
The following lemma concerning rank-one idempotents in A will be useful.
Lemma 6
Suppose that M is a finite-dimensional subspace
of X. Then M=ranP for some idempotent P∈A. Furthermore, P is the sum of n rank-one idempotents in
A, where n=dimM.
Proof.* The proof is by induction on dimM. First suppose that dimM=1, and
choose a non-zero vector x∈M. Now choose φ∈X′ such that N(x)−⊆kerφ and φ(x)=1. Such a φ exists because x∈/N(x)−.Then x⊗φ is the required idempotent.*
Now suppose that n=dimM>1 and that the result is true for all subspaces
of X with dimension less than n. Choose a non-zero vector y∈M and a subspace M# of M such that M# and
spany are complementary subspaces of M, i.e. M=M#+spany=M and M#∩spany={0}.
By the induction hypothesis there exists an idempotent P#∈A
such that ranP#=M#, and rank-one
idempotents P1,P2,⋯,Pn−1 in A such
that P#=P1+P2+⋯+Pn−1. Let x=y−P#y. Then 0=x∈M and P#x=0. Suppose that x=u+v, where u∈N(x)− and v∈M#. Then P#x=P#u+P#v, i.e. 0=P#u+v, since M#=ranP#
and P# is idempotent. So x=u−P#u. Since P#∈A
it follows that u−P#u∈N(x)−. Since x∈/N(x)− we have a contradiction. So x∈/N(x)−+M#=N(x)−+ranP#, and hence there
exists φ∈X′ such that
[TABLE]
Let Pn=x⊗φ. Then Pn is idempotent since φ(x)=1, and Pn∈A since N(x)−⊆kerφ. Furthermore, P#Pn=P#x⊗φ=0, and
PnP#=x⊗φP#=0 since ranP#⊆kerφ. Now let P=P#+Pn. Then
[TABLE]
*and ranP=ranP#+ranPn=M#+spanx=M, as required.
*
2.3 Rank decomposition
Lemma 6 provides an easy proof of a rank-decomposition property
of finite rank operators in the nest algebra A.
Theorem 7
Suppose that T is a finite rank operator in A.
Then T is the sum of n rank-one operators in A, where n=rankT.
Proof.* By Lemma 6, ranT=ranP for
some idempotent P in A. Furthermore P=P1+P2+⋯+Pn where each Pk is a rank-one idempotent in A.
Let Tk=PkT for 1≤k≤n. Then Tk∈A and
rankTk≤1 for each k. Furthermore,*
[TABLE]
This is the required decomposition. The Hilbert version of this result was
proved by Ringrose (**[2*]**).
* **
Remark 8
The proof of Theorem 7 is easily modified to show that if T is
a finite rank operator in I, where I is a left ideal
in A, then T is the sum of n rank-one operators in
I, where n=rankT.
2.4 Density
Lemma 6 also provides an easy proof of a density property of
the linear span of rank-one operators in A. First we introduce a
special topology on L(X).
Definition 9
The set of all subsets of L(X) of the form
[TABLE]
where x∈X and T∈L(X), is a set of
subbasic neighbourhoods of T for the strict topology on L(X)
Theorem 10
The span of the rank-one operators in A is strictly
dense in A.
Proof.* Suppose that T\in$$\mathcal{A} and that F is a finite
subset of X. Let R1#∩A denote
the span of R1∩A. We need to show that there
exists S∈R1#∩A such that Sx=Tx for all
x∈F.*
By Lemma 6 spanF=ranP for some idempotent P∈A.
Furthermore, P is the sum of n rank-one idempotents in A,
where n=dimspanF. Let Tk=TPk for 1≤k≤n. Then Tk∈A and rankTk≤1 for each k. So S=∑k=1nTk∈R1#∩A. Furthermore, for each x∈spanF,
[TABLE]
*as required.
*
Remark 11
The proof of Theorem 10 is easily modified to show that if T is a
finite rank operator in I, where I is a right ideal in
A, then T is the sum of n rank-one operators in I,
where n=rankT.
3 Dual nests
For any subset M of X, let M⊥ denote the annihilator
of M, i.e.
[TABLE]
Suppose that N is a nest of subspaces of X, and
that N⊥={M⊥:M∈N}. We
call N⊥ the dual of the nest N. Since the
map M↦M⊥ is order reversing, i.e. M1⊆M2⟺M1⊥⊇M2⊥, N⊥ is a linearly ordered family of subspaces of X′
that is anti-order isomorphic to N.
We are interested in the issue of completeness of N⊥.
Lemma 12
For any family {Mα:α∈Ψ} of
subspaces in N,
[TABLE]
Proof.* Suppose that φ∈X′. It is easy to see that*
[TABLE]
*Similarly, if φ∈⋃α∈ΨMα⊥
then Mα#⊆kerφ for some α#∈Ψ. It
follows that ⋂α∈ΨMα⊆kerφ,
i.e. φ∈(⋂α∈ΨMα)⊥.
*
Corollary 13
N⊥* is complete if and only if ⋃α∈ΨMα⊥=(⋂α∈ΨMα)⊥
for each family {Mα:α∈Ψ} of subspaces in N.*
Proof.* In the light of Lemma 12 it is sufficient to show that
if N⊥ is complete and {Mα:α∈Ψ} is a
family of subspaces in N, then (⋂α∈ΨMα)⊥⊆⋃α∈ΨMα⊥.*
*If N⊥ is complete, ⋃α∈ΨMα⊥=M#⊥ for some M#∈N. Suppose
that α0∈Ψ. Then Mα0⊥⊆⋃α∈ΨMα⊥=M#⊥, and so M#⊆Mα0. Therefore M#⊆⋂α∈ΨMα, and so (⋂α∈ΨMα)⊥⊆M#⊥=⋃α∈ΨMα⊥,
as required.
*
Example 14
Suppose that X=c00(N), the vector
space of all finitely non-zero F-valued sequences. Then
X′ can be regarded as the vector space of all
F-valued sequences. If f=(f(k))k=1∞∈X
and φ=(φ(k))k=1∞∈X′, then
φ(f)=∑k=1∞φ(k)f(k).
For each n∈N, let Mn={f∈X:suppf⊆{1,2,3,⋯,n}}, where
supp(f(k))k=1∞={k:f(k)=0} , and let
[TABLE]
Then N is a complete, totally ordered family of subspaces of
X, i.e. N is a nest.
Note that Mn⊥={φ∈X′ :suppφ⊆{n+1,n+2,n+3,⋯}. It is
easy to see that N⊥={X′,M1⊥,M2⊥,M3⊥,⋯,{0}} is a complete,
totally ordered family of subspaces of X′,
i.e. N⊥ is a nest.
Example 15
Suppose that X=c00(N) as in Example
14, and let
[TABLE]
where Mn#={f∈X:suppf⊆{n+1,n+2,n+3,⋯} for each n∈N. Then N#
is a complete, totally ordered family of subspaces of X, i.e.
N# is a nest.
Note that (M_{n}^{\#})^{\bot}=M_{n}=$$\{\varphi\in\mathfrak{X}^{\prime}:\operatorname*{supp}\varphi\subseteq\{1,2,3,\cdots,n\}\} as in Example
14. So (M1#)⊥,(M2#)⊥,(M3#)⊥,⋯ is a strictly increasing sequence in (N#)⊥, and \bigcup_{n=1}^{\infty}(M_{n}^{\#})^{\bot}$$=\mathfrak{X}\notin\left(\mathfrak{N}^{\#}\right)^{\bot}. So (N#)⊥ is not complete.
The nest N# in Example 15 has a strictly
decreasing, infinite sequence of subspaces, i.e., it is not well-ordered. The
following lemma shows that this is the key to the incompleteness of
(N#)⊥.
Lemma 16
Suppose that N is a complete nest of subspaces
of a vector space X. Then N⊥ is complete if
and only if N is well-ordered.
Proof.* First suppose that N is well-ordered, and that {Mα:α∈Ψ} is a family of subspaces in N. In the light of
Corollary LABEL:dualcorr it is sufficient to show that (⋂α∈ΨMα)⊥ ⊆⋃α∈ΨMα⊥.*
Since N is well-ordered, ∩α∈ΨMα=Mα# for some α#∈Ψ. So
[TABLE]
Now suppose that N is not well-ordered, and that M1,M2,M3,⋯ is a strictly decreasing infinite sequence of subspaces
in N. For each n∈N choose xn such that xn=Mn∖Mn+1. Then {x1,x2,x3,⋯} is a
linearly independent set and span{x1,x2,x3,⋯}∩M∞={0}, where M∞=∩n=1∞Mn. So there exists φ∈X′ such that
[TABLE]
It follows easily from (4) that φ∈M∞⊥∖(⋃n=1∞Mn⊥). So
[TABLE]
*Suppose that ⋃n=1∞Mn⊥∈N⊥,
i.e. ⋃n=1∞Mn⊥=M⊥ for some M∈N. Then Mn⊥⊆M⊥ and M⊆Mn for each n∈N. So M⊆M∞, and
hence M∞⊥⊆M⊥. But this contradicts
(5), and so there is no such subspace M in N. So
N⊥ is not complete.
*
4 The Jacobson radical
Suppose that R is a ring with identity 1. The Jacobson radical
RadR is the intersection of all maximal left
ideals of R. It is also the intersection of all maximal right
ideals of R. See ([3]). A more useful characterisation
of RadR is the following:
Proposition 17
Suppose that T∈R. The following are equivalent:
1. T∈RadR
2. 1−AT is invertible in R for each A∈A
3. 1−TA is invertible in R for each A∈A
Definition 18
Suppose that N is a nest on X and that
A=AlgN. The strictly triangular ideal
A− is defined by
[TABLE]
Lemma 19
Suppose that N is a nest on X and that
A=AlgN. Then
[TABLE]
Proof.* Suppose that T∈A∖A−. Then Tx∈/N(x)− for some x∈X. Choose φ∈X′ such that φ(Tx)=1 and N(x)−⊆kerφ. It follows from (3) that x⊗φ∈A.*
*Now (1−(x⊗φ)T)x=x−φ(Tx)x=0. So 1−(x⊗φ)T is not invertible and so T∈/RadA
by Proposition 17.
*
We now seek conditions which are either necessary or sufficient for the
equality of the radical RadA and the strictly
triangular ideal A− The notion of local nilpotence will be useful.
Definition 20
We say that T∈L(X) is nilpotent at x∈X if Tnx=0 for sufficiently large n. We say that T
is locally nilpotent if it is nilpotent at each x∈X.
Lemma 21
If each T∈A− is locally nilpotent,
then RadA=A−.
Proof.* Suppose that T∈A− and that A∈A. Then AT∈A− and hence is locally nilpotent by assumption.*
*Let S= 1+∑n=1∞(AT)n. The sum S is well-defined as
an operator in L(X), because the local nilpotence of
AT ensures that for each x∈X the series ∑n=1∞(AT)nx has only finitely many non-zero terms. If x∈M for
some M∈N, it is clear that Sx∈M. So S∈A.
Furthermore, it is easy to see that S(1−AT)=(1−AT)S=1. So S is the
inverse of 1−AT in A, and hence T∈RadA.
*
Lemma 22
If N is well-ordered then each T∈A− is locally nilpotent.
Proof.* Suppose that T∈A− is not locally nilpotent. Then there
exists x∈X such that Tnx=0 for all n∈N. Since T∈A−, for each *n∈N,
[TABLE]
*So N(Tnx):n=1,2,3,⋯ is a strictly decreasing,
infinite sequence of subspaces in N, and hence N is
not well-ordered.
* **
Corollary 23
If N is well-ordered then RadA=A−.
The following result shows that for dual nests, well-ordering is not essential
for the equality of the radical and the strictly triangular ideal.
Theorem 24
Suppose that N is a nest of subspaces of a
vector space X whose order type is ω, the first infinite
ordinal. Then N⊥ is a nest of subspaces of X′, whose order type is anti-isomorphic to ω, and
(AlgN⊥)−=Rad(AlgN⊥).
Proof.* In view of Lemma 16 it is sufficient to show that
A−=RadA, where A=AlgN⊥.*
Let M0={0}, and for each n>0 let Mn denote the immediate
successor of Mn−1 in N. Since the order type of
N is ω, ⋃n=1∞Mn=X.
Suppose that T∈A− and that φ∈Mn⊥. Then Tφ∈N⊥(φ)−⊂N⊥(φ)⊆Mn⊥. Since
Mn+1⊥ is the immediate predecessor of Mn⊥in N⊥, it follows that Tφ∈Mn+1, and so T(Mn⊥)⊆Mn+1⊥.
Suppose that A∈A. Then AT∈A− and so
AT(Mn⊥)⊆Mn+1⊥ for each n≥0 and so
(AT)n(X′)=(AT)n(M0⊥)⊆Mn⊥ for each n≥0.
*Let S= 1+∑n=1∞(AT)n. The sum S is well-defined as
an operator in L(X′) because, for each x∈X and each φ∈X′, the
series ∑n=1∞(AT)n)(φ)(x) has only finitely many
non-zero terms. (To see this note that x∈Mn# for some n#≥0, and ((AT)nφ)(x)=0 if n≥n#.)
Furthermore S(1−AT)φ(x)=(1−AT)Sφ(x)=φ(x), and so S=(1−AT)−1. Finally, it is easy to check that S(Mn⊥)⊆Mn⊥ for each n≥0 and so S∈A. So T∈RadA, and hence A−⊆RadA. It follows from Lemma 19
that A−=RadA.
*
4.1 An example
The nest N defined in Example 14 satisfies the
conditions of Theorem 24, and so (AlgN⊥)−=Rad(AlgN⊥). Note that N⊥ is not well-ordered.
It does, however, satisfy the ascending chain condition, i.e. each subset of
N⊥ contains a maximal element.
Definition 25
Suppose that X1 and X2 are vector spaces over
the same field F, and that Nk is a nest of
subspaces of Xk for k∈{1,2}. The ordinal sum
N1∔N2 is a nest of subspaces of
X=X1⊕X2 defined by
[TABLE]
Let A=Alg(N1∔N2) and let Ak=AlgNk for k∈{1,2}. Every T in L(X) has an operator matrix,
[TABLE]
relative to the decomposition X=X1⊕X2. It is easy to check that
[TABLE]
[TABLE]
Lemma 26
With the above notation and C=0,
[TABLE]
[TABLE]
Proof.* A simple matrix computation shows that if \left(\begin{array}[c]{cc}D&E\\
0&F\end{array}\right)=\left(\begin{array}[c]{cc}A_{1}&B\\
0&A_{2}\end{array}\right)^{-1} if and only if D=A1−1, F=A2−1 and E=−A1−1BA2−1. So \left(\begin{array}[c]{cc}A_{1}&B\\
0&A_{2}\end{array}\right)^{-1}\in\mathcal{A} if and only if A_{1}^{-1}\in\mathcal{A}_{1}\ and A2−1 ∈A2. Statement (8) is
now obvious. Statement (9) follows from (7)and
(8).
* **
Example 27
Let X=Y⊕Y, where Y is
the vector space of all F-valued sequences. Let
[TABLE]
where Mn⊥={φ∈Y: suppφ⊆{n+1,n+2,n+3,⋯},as in Example 14,
and let
[TABLE]
where (Mn#)⊥={φ∈Y: suppφ⊆{1,2,⋯,n}}, as in Example 15.
Note that N1=N⊥, where N is as
defined in Example 14. Since N1 is well-ordered with
order type ω, it follows from Theorem LABEL:dualrad that
RadA1=(A1)−. Note also that
N2 is well-ordered, i.e. it satisfies the descending chain
condition. So by Corollary 23 RadA2=(A2)−. So by Lemma 26
Rad(N1∔N2)=(N1∔N2)−.
But N1∔N2) satisfies neither the
ascending chain condition nor the ascending chain condition. Its order type
is 1+ω∗+ω+1, i.e. the order type of {−∞}∪Z∪{∞}, where Z denote the set of integers,
and it contains both strictly decreasing and strictly increasing infinite
sequences of subspaces.