1. Introduction
The inequalities of operators on Hilbert space are interesting and useful for applying operator theory to any field of natural science. Numerical radius inequalities play an important role in various fields of operator theory and matrix analysis [1,2], and there have been many generalizations of the numerical radius. The numerical radius is not only a powerful tool for characterizing the numerical range but also provides a key tool for stability, convergence and error estimation in practical applications [3]. The close relationship between the numerical radius, norm, and spectral radius makes it an indispensable tool in functional analysis and numerical calculations. In research on numerical radius inequalities, researchers mainly focus on improving and generalizing the existing inequalities. The purpose of this paper is to study one of the generalizations of the numerical radius, that is, the Davis–Wielandt radius. By using the Moore–Penrose inverse of bounded linear operators with closed ranges, we will establish some new Davis–Wielandt radius inequalities. Furthermore, by providing numerical examples, we will show that these inequalities are better than the existing inequalities. Let us recall the following necessary definitions and related symbols.
Let be a complex Hilbert space and let be the -algebra of all bounded linear operators on H. For , the Moore–Penrose inverse of A is the operator that satisfies the following Penrose equations [4]:
where denotes the adjoint operator. Note that the Moore–Penrose inverse of A exists if and only if the range of A is closed and that it is unique and denoted by in this case. Throughout the paper, denotes the subset of of all operators with closed ranges. Obviously, when H is a finite dimensional space, all operators in have closed ranges. Therefore, each matrix has a unique Moore–Penrose inverse. It is easy to see that, for , and where and . Recently, Sababheh et al. [5] and Bhunia et al. [6] studied the numerical radius of bounded linear operators by using the Moore–Penrose inverse. For further discussion of the Moore–Penrose inverse of bounded linear operators, we direct readers to [7,8].For , the numerical range of A is defined as [9]
The numerical radius and the operator norm of A, denoted as and , respectively, are defined as
andIt is well known that defines a norm on , which is equivalent to the operator norm . Namely, for every , the following inequalities hold:
The concept of numerical radius is useful in studying the bounded linear operators, and there have many generalizations of the numerical radius, such as in, e.g., [10,11,12,13,14,15,16] and the references therein. One of the most interesting generalizations is the Davis–Wielandt radius, which is defined as [17,18]
for . It is clear that the Davis–Wielandt radius satisfies the following inequality:(1)
The second inequality in (1) becomes equality if and only if A is normaloid, i.e., (see [19], Corollary 3.2). In recent years, the Davis–Wielandt radius inequalities have been studied by many researchers. For instance, in [20,21], the authors proved that if , then
(2)
In [22], Zamani and Shebrawi proved that
(3)
(4)
(5)
(6)
whereIn [23], Bhunia et al. proved that
(7)
(8)
(9)
(10)
For more results on the Davis–Wielandt radius inequalities, the reader may be referred to [24,25,26,27,28].
In this paper, using the Moore–Penrose inverse of bounded linear operators, we obtain some new upper bounds for the Davis–Wielandt radius of bounded linear operators with closed ranges and show that these upper bounds are better than the existing ones mentioned above by numerical examples.
2. Main Results
In order to prove our results, we need the following lemmas:
([29]). Let A be a non-negative bounded linear operator in Hilbert space H, and let be any unit vector. Then, for , we have
([30]). Let with and . Then,
In particular, if , then the above inequality becomes the Buzano inequality ([31])
([32]). Let with . Then,
for every and .([5]). Let . Then,
for any .We know that is closed if and only if is closed, while . So, when , then . Now applying Lemma 4, we obtain the following inequality:
for , . Indeed,Now, we are in a position to state our main results.
Let . Then, for , we have
(11)
(12)
(13)
and(14)
Let be a unit vector. Then,
Taking the supremum over all unit vectors in H, we obtain
Similarly, we can show that
From ([33], Theorem 3.3), we have , and so we obtain the inequalities (13) and (14). □
In particular, by considering in Theorem 1, we obtain the following corollary:
Let . Then
(15)
where
and
The inequality in Corollary 1 is better than inequalities (1), (2), (3), (4), (8), (9), and (10); the inequalities in [22], which are Theorems 2.2, 2.5, 2.16, and 2.17; and that in [21], which is Theorem 2.10. The inequalities in [22], namely Theorems 2.2, 2.5, 2.16, and 2.17 and that in [21], namely Theorem 2.10, are shown, respectively, as follows:
If we take . Then, by calculations, we obtain and , and so Corollary 1 gives , whereas inequalities (1), (2), (3), (4), (8), (9), and (10), and Theorems 2.2, 2.5, 2.16, 2.17 in [22], and Theorem 2.10 in [21] give , , , , , , , , , , and , respectively. Therefore, for this example, the upper bound of in Corollary 1 is better than the existing bounds mentioned above.
Let . Then, for , we have
(16)
and(17)
Let be a unit vector. Then,
Taking the supremum over all unit vectors in H, we obtain
Similarly, we can show that
Since , we have
□
Let , . Then, for , we have
(18)
and(19)
where
Let be a unit vector. Then,
Taking the supremum over all unit vectors in H, we obtain inequality (18). Similarly, we can show that
Since , and so we obtain the inequality (19). □
In particular, if we take in inequality (18), then we obtain the inequality (16). If we take in inequality (19), we obtain inequality (17).
Now, we observe the following inequality:
(20)
By employing the inequality (20), we prove the following theorem:
Let . Then,
(21)
and(22)
Let be a unit vector. Then,
Taking the supremum over all unit vectors in H, we obtain inequality (21). Similar to the proof of inequality (21), and using , we obtain inequality (22). □
In [34], for Equation (4), the authors show that if are self-adjointed, then
(23)
By using the inequality (23), we obtain the following remark, which shows that Theorem 4 improves Theorem 2 for the case :
Since and are self-adjointed, we have
Let . Then, for , we have
(24)
and(25)
Let be a unit vector. Then,
Taking the supremum over all unit vectors in H, we obtain
(26)
Similar to the proof of inequality (26), and using , we obtain inequality (25). □
In particular, if we take in Theorem 5, then we obtain following inequalities:
(27)
and(28)
Next, we consider an example to show that inequalities (27) and (28) are better than existing inequalities (3), (4), and (23). If we consider , then from (27) and (28), we obtain , whereas the inequalities in (3), (4), and (23) give , , and , respectively. Thus, for this example, the upper bound of in inequalities (27) and (28) are better than the existing bounds.
Next, based on Lemmas 2 and 4, we obtain the following result:
Let , . Then, for , we have
(29)
and(30)
where
Let be a unit vector. Then,
Therefore,
Taking the supremum over all unit vectors in H, we obtain the inequality (29). Similar to the proof of inequality (29), and using , we obtain inequality (30). □
As a special case for and in Theorem 6, we have the following corollary:
Let . Then,
(31)
and(32)
We note that, if the inequalities
(33)
and(34)
hold, then inequalities (31) and (32) are the improvements of inequalities (24) and (25) for the case in Theorem 5, respectively. Next, we give an example to show that there is such that inequalities (33) and (34) hold. Consider . Then, andNext, using Lemma 3, we obtain the following Davis–Wielandt radius of the bounded linear operators:
Let , . Then, for , we have
(35)
and(36)
Let be a unit vector. Then, from the Lemma 3, we obtain
Therefore,
Taking the supremum over all unit vectors in H, we obtain the inequality (35). Similar to the proof of inequality (35), and using , we obtain inequality (36). □
If we take in inequality (35), then we have
(37)
It is obvious that inequality (37) improves the inequality in [20], i.e., Theorem 3.1.
In particular, if we consider in Theorem 7, then we have the following corollary:
Let . Then
where
and
Let , . Then, for , we have
(38)
and(39)
Let be a unit vector. Then, from the Lemmas 3 and 4, we obtain
Therefore,
Taking the supremum over all unit vectors in H, we obtain inequality (38). Similar to the proof of inequality (38), and using , we obtain inequality (39). □
In particular, if we take in Theorem 8, then we obtain the following corollary:
Let . Then,
where
and
Since . Then,
(40)
Inequality (40) refines the inequalities in (4), (5), and (6) for some operators. Let , then (40) gives , whereas the inequalities in (4), (5), and (6) give , , and , respectively. Thus, for this example, the inequalities in Theorem 8 for are better than the existing inequalities.
Let , . Then, for , we have
(41)
and(42)
Let be a unit vector. Then, from the Lemma 3, we have
Therefore,
Taking the supremum over all unit vectors in H, we obtain inequality (41). Similar to the proof of inequality (41), and using , we obtain inequality (42). □
If we take and in Theorem 9, then Theorem 9 reduces to Corollary 2.
Finally, we compare some upper bounds of the Davis–Wieldant radius obtained by us. In the following remark, we first show that the upper bounds of the Davis–Wieldant radius in Theorem 1 are smaller than those in Theorem 2.
Let , , with . Then,
By taking the supremum over all with , we obtain
Similarly, we obtain
and
Thus, the upper bounds of the Davis–Wieldant radius in Theorem 1 are smaller than those in Theorem 2.
If the inequalities
(43)
and(44)
hold, then the upper bounds of the Davis–Wieldant radius in Corollary 2 are smaller than those in Theorem 4. Indeed, let be a unit vector. Then,
Therefore, if , we obtain
Similarly, if , we obtain
Now, we give an example to show that there is such that inequalities (43) and (44) hold. Consider . Then,
andNext, we provide numerical examples to illustrate that the upper bounds of the Davis–Wieldant radius obtained by Corollary 1, Corollary 3 and Corollary 4 are generally not comparable.
Let , , and . Then, the upper bounds of the Davis–Wieldant radii in Corollary 1, Corollary 3, and Corollary 4 are as shown in Table 1.
X.D. wrote the main manuscript; Y.G. and D.W. were primarily responsible for proposing concepts and revising manuscripts; X.D. and D.W. were responsible for securing funding. All authors have read and agreed to the published version of this manuscript.
The original contributions presented in this study are included in this article. Further inquiries can be directed to the corresponding author.
The authors are very grateful to the anonymous referees for their valuable suggestions and comments which have greatly improved this paper.
The authors declare no conflicts of interest.
Footnotes
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The upper bounds of the Davis–Wieldant radii.
| | | |
---|---|---|---|
Corollary 1 | 1.414 | 16.492 | 5.843 |
Corollary 3 | 1.25 | 17 | 5.457 |
Corollary 4 | 1.25 | 20 | 5.744 |
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Abstract
In this paper, we obtain some new upper bounds involving powers of the Davis–Wielandt radius of bounded linear operators with closed ranges by using the Moore–Penrose inverse. Moreover, by providing some examples, we show that the upper bounds obtained here are better than the existing ones in some situations.
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1 College of Sciences, Inner Mongolia University of Technology, Hohhot 010051, China; [email protected]
2 School of Mathematical Sciences, Inner Mongolia University, Hohhot 010021, China; [email protected]