We find that a bounded linear operator T on a complex Hilbert space H satisfies the norm relation |||T| na|| =2q, for any vector a in H such that q≤(||Ta||-4 -1||Ta|| 2)≤1.A partial converse to Theorem 1 by Haagerup and Harpe in [1] is suggested. We establish an upper bound for the numerical radius of nilpotent operators.
The motivation for this note is provided by the results obtained in [1-4]. Let T be a bounded linear operator on a complex Hilbert space H. The numerical range of T, denoted by W(T), is the subset of the complex plane and
The numerical radius of T is defined as,
The following lemma is known and is an easy consequence of the definitions involved.
Lemma 1.1., where T* is the adjoint operator of T and is the complex conjugate of.
Berger and Stampfli in [
Theorem 2.1 also generalizes the result in [
Our next main result in Theorem 2.3 gives an alternative and shorter proof of Theorem 1 in [
Applying Lemma 2 and Proposition 2 of [
Finally, two examples are discussed. Example 3.1 deals with the operator, where 1 is not the eigenvalue of if. Example 3.3 justifies why fails to increase until and unless.
Theorem 2.1. The following statements are true for a bounded linear operator T on a Hilbert space H with.
1) such that
,.
2) If for some integer n, then
and.
3) The set forms a nontrivial subspace of T so that its orthogonal complement is invariant.
Proof. 1) For each real number and a postive integer, n, let. Then the inner product relation implies that
That is,
Hence,
Since
it follows that
Dividing the above inequality by, we have
Let be the following block-diagonal matix of order n and
If γn denotes the determinant of such that then the value of γn is positive because all principal minors of are nonnegative. Suppose that
We consider the following cases:
Case 1. Iffor the leastthen
and converges to zero.
Case 2. Let for all. Then
and by induction
Further, the inequality
implies that converges to q as n goes to infinity for some q ≥ 0. Therefore from Equation (2.1), as. Thus. Obviously, q = 1 only if.
2) By the assumption, for some positive integer n. Now fom Equation (2.1), we obtain:
and so that. The equality,
now follows from (a) and thus. Also, which gives since.
3) To prove this case, we assume that if the vector is orthogonal to the spanning set then. Let
, for. Then
Hence, for and the spanning set is a non-trivial invariant subspace on T.
In [2, p. 1052], an example of an operator T on and an element x in H with, is given where
. Theorem 2.1 above establishes that is the best constant in this case.
Remark 2.2. An operator A on H is hyponormal if
. Let thenif A is a hyponormal operator. Hence, , and the set of vectors forms a reducing subspace of A.
A natural connection between Feijer’s inequality and the numerical radius of a nilpotent operator was estaplished by Haagerup and Harpe in [
with. Such a polynomial is positive if for all. Here, we present a simplified proof of Theorem 1 in [
Theorem 2.3. For an operator N on H with and, we have.
Proof. We will follow the notations of Theorem 1 in [
and for
The matrix for S gives a dialation for T. Let A be the matrix for S and
If is a unitary operator on with diagonal then. By Lemma 1, we have:
This helps to define the characteristic function of a contraction.
For the operator N on H, let then
is a positive operator and depends on N. Let the range of be denoted by. Then the tensor product, , is a Hilbert space. We define the map so that F is an isometry.
For λ, let where I is the identity operator, and is an operator on.
Therefore and.
Now, we claim that, for we hope that By Lemma 1.1
That is,.
Since, we have:
and
where is the spectral radius of. By the definition of the spectral radius, we have the characteristic polynomial f such that by [5, p. 179, Example 9], the roots of are given by
, and and
.
Karaev in [
Using Theorem 2 and the assumption that
, , we have as a closed or an open disc centered at zero with radius equal to. In fact, we have the following theorem.
Theorem 2.4. For a nilpotent operator N on H with, and, the numerical range is a disc centered at zero with radius.
Proof. For any we must claim that, for and is a vector in.
From [1, p. 374, Proposition 2], we have. Also, for some,
. Now by [
and
Let. Then:
and the theorem follows from above since is arbitrarily chosen.
An operator A is a unilateral weghted shift if there is an orthonormal basis and a sequence of scalers such that for all. It is easy to see that where S is the unilateral shift and D is the diagonal operator with, for all n.
Thus, and for all n. So is the basis of eigenvectors for. Also, note that A is bounded if is bounded.
If A is a unilateral shift then and for. Consequently, for a hyponormal operator A, and for. A wighted shift is hyponormal if and only if its weight sequence is increasing.
Example 3.1. Let be an operator on such that and for and. Here, we show that is not an eigenvalue of if
. We prove our claim by contradiction Let be an eigenvalue of. Then, there exists with and, n = 2, 3, ···. It is not hard to see that:
For, we have and thus, which shows that, contrary to our assumption. Thus, is not an eigenvalue of if
.
Remark 3.2. Following [
Therefore, the numerical radius, is equal to 1.
The example below shows that there exists an operator such that for.
Example 3.3. Let be a unilateral shift. If is the orthogonal projection of onto the spanning set of vectors then and has the usual matrix representation. Let
Then the characteristic polynomial of is given by a Chebyshev polynomial of the first kind. Let where. Then:
(easily proven by trigonometric identities) and for is a linear combination of powers of xk. Also, det. If then the roots are given by the Chebyshev polynomial of the first kind. The roots can be found by finding the eigenvalues of matrix B. By [2, p. 179, Example 9], the eigenvalues of B are given by
, for.
Suppose that
then. Hence, if.