Abstract
Let and be a weighted sequence that is recursively generated by five weights . In this paper, we give sufficient conditions for the positive quadratic hyponormalities of and , with and
Keywords:
positively quadratically hyponormal; quadratically hyponormal; unilateral weighted shift; recursively generated MSC:
47B37; 47B20
1. Introduction
Let be a separable, infinite dimensional, complex Hilbert space, and let be the algebra of all bounded linear operators on . An operator T in is said to be normal if hyponormal if and subnormal if where N is normal on some Hilbert space For , let . We say that an n-tuple of operators in is hyponormal if the operator matrix is positive on the direct sum of n copies of . For arbitrary positive integer k, is (strongly) k-hyponormal if is hyponormal. It is well known that T is subnormal if and only if T is ∞-hyponormal. An operator T in is said to be weaklyn-hyponormal if is hyponormal for any polynomial p with degree less than or equal to An operator T is polynomially hyponormal if is hyponormal for every polynomial . In particular, the weak two-hyponormality (or weak three-hyponormality) is referred to as quadratical hyponormality (or cubical hyponormality, resp.) and has been considered in detail in [,,,,,,,,].
Let be the canonical orthonormal basis for Hilbert space , and let be a bounded sequence of positive numbers. Let be a unilateral weighted shift defined by It is well known that is hyponormal if and only if The moments of are usually defined by It is well known that is subnormal if and only if there exists a Borel probability measure supported in with supp such that [] d It follows from [] (Theorem 4) that is subnormal if and only if for every and every the Hankel matrix:
A weighted shift is said to be recursively generated if there exists and such that:
where is the moment of i.e., equivalently,
Given an initial segment of weights there is a canonical procedure to generate a sequence (denoted ) in such a way that is a recursively-generated shift having as an initial segment of weight. In particular, given an initial segment of weights with we obtain and
In [,], Curto-Putinar proved that there exists an operator that is polynomially hyponormal, but not two-hyponormal. Although the existence of a weighted shift, which is polynomially hyponormal, but not subnormal, was established in [,], a concrete example of such weighted shifts has not been found yet. Recently, the authors in [] proved that the subnormality is equivalent to the polynomial hyponormality for recursively-weighted shift with Based on this, in this paper, we have to consider the weighted shift operator with five generated elements.
The organization of this paper is as follows. In Section 2, we recall some terminology and notations concerning the quadratic hyponormality and positive quadratic hyponormality of unilateral weighted shifts . In Section 3, we give some results on the unilateral weighted shifts with recursively generated by five weights . In Section 4, we consider positive quadratic hyponormalities of with weights and In Section 5, we give more results on the positive quadratic hyponormality for any unilateral weighted shift . In Section 6, we present the conclusions.
2. Preliminaries and Notations
Recall that a weighted shift is quadratically hyponormal if is hyponormal for any [], i.e., for any Let be an orthonormal basis for , and let be the orthogonal projection on For , we let:
where:
and Hence, is quadratically hyponormal if and only if for every and every Hence, we consider , which is a polynomial in of degree with Maclaurin expansion It is easy to find the following recursive relations []:
Furthermore, we can obtain the following:
and:
In particular, for any we have:
Furthermore, we can obtain the following results.
Lemma 1.
Let Then, for any we have:
Lemma 2.
Let Then, for any we have:
Lemma 3.
For any and we have:
To detect the positivity of we need the following concept.
Definition 1.
Let be a positive weight sequence. We say that is positively quadratically hyponormal if for all with and for all [].
Positive quadratic hyponormality implies quadratic hyponormality, but the converse is false []. In addition, the authors in [] showed that the positive quadratic hyponormality is equivalent to the quadratic hyponormality for recursively-generated weighted shift with (here, ).
3. Recursive Relation of
Given the initial segment of weights with we obtain the moments:
Let:
and we assume that are linearly independent, i.e.,
Then, there exist three nonzero numbers , such that:
A straightforward calculation shows that:
Thus:
i.e.,
By (1), we can obtain a recursively-generated weighted shift, and we set it as . In this case, we call the weighted shift operator with rank three.
Proposition 1.
with rank three is subnormal if and only if:
(1)
(2)
(3)
Proof.
See [], Example 3.6. □
Proposition 2.
If with rank three is subnormal, then and
Proof.
By Proposition 1, we know that:
Thus, Since:
and:
we have and The proof is complete. □
Proposition 3.
Let Then:
Proof.
Since:
so:
Thus, we have:
Thus, we have our conclusion. □
Since , we let and by (2), we have hence:
4. Main Results
First, we give the following result (cf. [], Corollary 5).
Proposition 4.
Let be any unilateral weighted shift. Then, is two-hyponormal if and only if
It is well-known that if is two-hyponormal or positively quadratically hyponormal, then is quadratically hyponormal. By Proposition 4 and Lemma 1∼3, we have the following result.
Theorem 1.
Let be any unilateral weighted shift. If is 2-hyponormal, then is positively quadratically hyponormal.
4.1. The Positive Quadratic Hyponormality of
Let with and we consider the following matrix:
Let Then:
Lemma 4.
and .
Proof.
In fact, and:
Thus, we have our conclusion. □
Lemma 5.
Assume that for Then, for we have:
Proof.
For
By the inductive hypothesis, we have our result. □
Thus, if for then by Lemma 1∼3 and Lemma 5, for we have:
where Therefore, when we have:
To complete our analysis of the coefficients it suffices to determine the values of x for which
Lemma 6.
(for any if and
Proof.
For by Lemma 2, we have:
and since we get:
If we can factor to get:
Hence, we have our result. □
Let:
By direct computations, we have:
For a calculation using the specific form of and shows that:
it follows that:
Let . Then, for
Lemma 7.
where as in (3).
Proof.
Since:
from which it follows that:
Thus:
Thus, we have (for ):
Since we have:
Thus, we have our conclusion. □
Let:
By Lemma 7 and the fact in [] (p. 399), if is increasing, then we know that in (5) is decreasing and Thus, we have the following result.
Theorem 2.
Assume that with rank three is subnormal. Let and let:
If is increasing, then:
where:
Remark 1.
By (6), we know that if is increasing, then so is Hence, our problems are as follows.
Problem 1.
Let be any unilateral weighted sequence. If is subnormal, is increasing or not? In particular, what is the answer for subnormal with rank three?
Example 1.
Let Then, and We obtain That is, if then is positively quadratically hyponormal. Numerically, we know that and are all increasing. See the following Table 1.
Table 1.
Numerical data for and in Example 1.
4.2. The Positive Quadratic Hyponormality of
Let We also consider the matrix as in (4), and let Then:
and:
Since:
we can similarly show that for all , if and where . Thus, we have the following result.
Theorem 3.
Let If is increasing, and:
(1)
(2) where:
then is positively quadratically hyponormal.
Example 2.
Let If with then is positively quadratically hyponormal. See the following Figure 1.
Figure 1.
A subset of the region of positive quadratic hyponormality of in Example 2.
5. More Results
From the above discussions, we obtain the following criteria for any unilateral weighted shifts.
Proposition 5.
Let and be subnormal weighted shifts. Let:
If is increasing and (as ), then:
where:
By Proposition 5, we can have the following results, but we omit the concrete computations.
Example 3.
(1) Let Then, (cf. [], Proposition 7).
(2) Let Then, (cf. [], Theorem 3.7).
(3) Let Then,
(4) Let Then, (cf. [], Example 3.4).
6. Conclusions
In this work, we study a weighed shift operator for which the weights are recursively generated by five weights. We give sufficient conditions of the positive quadratic hyponormalities. Next, it is worth studying the cubic hyponormality, semi-weak k-hyponormalities, and so on.
Author Contributions
All authors contributed equally in writing this article. All authors read and approved the final manuscript.
Funding
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2017R1A2B4006092).
Conflicts of Interest
The authors declare no conflict of interest.
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