Abstract
The results obtained by the authors in the present article refer to quantum calculus applications regarding the theories of strong differential subordination and superordination. The q-analogue of the multiplier transformation is extended, in order to be applied on the specific classes of functions involved in strong differential subordination and superordination theories. Using this extended q-analogue of the multiplier transformation, a new class of analytic normalized functions is introduced and investigated. The convexity of the set of functions belonging to this class is proven and the symmetry properties derive from this characteristic of the class. Additionally, due to the convexity of the functions contained in this class, interesting strong differential subordination results are proven using the extended q-analogue of the multiplier transformation. Furthermore, strong differential superordination theory is applied to the extended q-analogue of the multiplier transformation for obtaining strong differential superordinations for which the best subordinants are provided.
Keywords:
convex function; differential operator; extended q-analogue operator; strong differential subordination; strong differential superordination; best dominant; best subordinant MSC:
30C45; 30A20; 34A40; 33D05
1. Introduction
Jackson initiated the use of the q-calculus by defining the q-derivative [1] and q-integral [2]. Ismail et al. provided the first examples of q-calculus applications in geometric function theory in a paper published in 1990 [3], where an extension of the set of starlike functions was introduced and studied related to q-calculus aspects. Many applications of quantum calculus in geometric function theory have appeared in recent years, following Srivastava’s establishment of the broad background for such study in a book chapter released in 1989 [4]. In addition to the numerous q-operators generated by utilizing well-known differential and integral operators specific to geometric function theory, some aspects of the application of quantum calculus in geometric function theory are highlighted in recent papers [5,6], respectively.
Several studies focused on the q-analogues of the Ruscheweyh differential operator described in paper [7] and the q-analogues of the Sălăgean differential operator established in [8]. In [9], for instance, differential subordinations were investigated using a specific q-Ruscheweyh-type derivative operator; in [10], a new class of analytic functions was defined, and its coefficient estimates were analyzed; and in [11], classes of analytic univalent functions were introduced and investigated using both Ruscheweyh and Sălăgean q-analogue operators. In [12,13], a generalization of the Sălăgean q-differential operator was used to investigate certain differential subordinations. Subordination outcomes using the q-analogue of the Sălăgean differential operator were achieved in [12,13]. The q-Bernardi integral operator was introduced in [14], and the multiplier transformation and Srivastava–Attiya operator was studied, involving the quantum calculus in [15].
The concept of strong differential subordination was first used by Antonino and Romaguera [16] for the investigation of Briot–Bouquet’s strong differential subordination. It was intended to be an extension of the classical notion of differential subordination, due to Miller and Mocanu [17,18]. The concept was developed, setting the basis for the theory of strong differential subordination in 2009 [19], where the authors extended the concepts familiar to the established theory of differential subordination [20]. The introduction of the dual notion of strong differential superordination followed in 2009 [21], based on the pattern set for classical differential superordination theory [22]. Both theories developed nicely during the next years. Means for obtaining the best subordinant of a strong differential superordination were provided in [23], and special cases of strong differential subordinations and superordinations were considered for the studies [24]. Strong differential subordinations began to be obtained by associating different operators to the studies, such as the Sălăgean differential operator [25], Liu–Srivastava operator [26], Ruscheweyh operator [27], combinations of Sălăgean and Ruscheweyh operators [28], multiplier transformation [29,30], Komatu integral operator [31,32], Mittag-Leffler-confluent hypergeometric functions [33,34,35], or general differential operators [36,37]. The topic remains of interest at the present, as it was proved by citing recently published works [38,39,40,41].
Using q-analogue of the multiplier transformation, we have defined and studied new subclasses of harmonic univalent functions in [42] and have obtained fuzzy differential subordinations in [43].
We first remind of the notions and results used in this study.
Denote by the class of analytic functions in where and .
In [44], the authors introduced some special subclasses of that were used only in relation to the theories of strong differential subordination and its dual strong differential superordination:
with and holomorphic functions in , , and
with holomorphic functions in , and
The next definitions concern the concept of strong differential subordination, as it was used in [16] and further developed in [19,44].
Definition 1
([19]). The analytic function is strongly subordinate to the analytic function if there exists an analytic function w in U, such that and for all . It is denoted
Remark 1
([19]). (i) In the particular case when the function is univalent in for all the conditions from Definition 1 can be written as and for all
(ii) In the particular case when and , the strong differential subordination is reduced to differential subordination.
The next definitions are connected to strong differential superordination theory.
Definition 2
([21]). The analytic function is strongly superordinate to the analytic function if there exists an analytic function w in U, such that and for all . It is denoted
Remark 2
([21]). (i) In the particular case when the function is univalent in for all , the conditions from Definition 2 can be written as and for all
(ii) In the particular case when and , the strong differential superordination is reduced to the differential superordination.
Definition 3
([45]). represents the set of analytic and injective functions on , with property for , where represents the subclass of with .
The following lemmas are useful to prove the new results exposed in the next sections.
Lemma 1
([46]). Consider a complex number such that and a convex function with the property for every . If and
then
where is convex and it represents the best dominant.
Lemma 2
([46]). Consider a convex function in and let
with . If
is holomorphic in and
then
this result is sharp.
Lemma 3
([47]). Consider , such that and a convex function with the property . If is univalent in and
then
where The convex function q represents the best subordinant.
Lemma 4
([47]). (Consider a convex function in and let with .
If , is univalent in and
then
where , represents the best subordinant.
The notations and notions from q-calculus theory are presented below.
For and , we denote
and
The q-derivative operator applied to a function is defined by [2]
When f is a differentiable function, we can see that
For the special case when we have
In Section 2 of the paper, the q-analogue of the multiplier transformation is extended and defined on the class Next, a new class of analytic normalized functions is introduced using the extended q-analogue of the multiplier transformation. The convexity of the class is shown, and strong differential subordination theorems are proved involving the extended q-analogue of the multiplier transformation and the convex functions from class . In Section 3, the dual theory of strong differential superordinations is employed in connection to the extended q-analogue of the multiplier transformation, in order to establish strong differential superordination results, for which the best subordinants are also obtained.
2. Strong Differential Subordination Results
We extend the q-analogue of the multiplier transformation to the new class of analytic functions
Definition 4.
The extended q-analogue of multiplier transformation has the the following form
with , , m a real number and .
Applying the properties of q-calculus, we obtain
We define a new class of normalized analytic functions using the extended q-analogue of the multiplier transformation introduced in Definition 4.
Definition 5.
The class consists of the functions with the property
for .
The convexity of the class is established by the first result.
Theorem 1.
is a convex set.
Proof.
Taking the functions
from the class it is enough to prove that the function
belongs to the class when and are positive real numbers with the property
The function f can be written by the following relation
and
Differentiating relation (2), with respect to z, we obtain
Hence
Taking account that the functions , we can write
We next expose a series of strong differential subordinations using the convex functions from the class and the extended q-analogue of the multiplier transformation .
Theorem 2.
Taking a convex function, we consider the function
For set
then the strong differential subordination
implies the sharp strong differential subordination
with the function g as best dominant.
Proof.
Relation (6) can take the following form
and after differentiating it, with respect to z, we obtain
and
Differentiating again the last relation with respect to z, we obtain
and the strong differential subordination (7) can be written in the form
Denoting
strong differential subordination (12) can be written as
Applying Lemma 2, we obtain
equivalent with
and the sharpness of this result is given by the best dominant g. □
Theorem 3.
Let . Denoting
then
where
Proof.
Following the steps used in the proof of Theorem 2, taking account the hypothesis of Theorem 3 and taking the convex function , we obtain the strong differential subordination
where p is given by relation (13).
Applying Lemma 1, we obtain the strong differential subordinations
written in the following form
where
Taking account that g is a convex function with symmetric to the real axis, we obtain
□
Theorem 4.
Taking the convex function with the property we consider the function
If satisfies the strong differential subordination
then the sharp strong differential subordination
holds, with the function g as best dominant.
Proof.
Considering
, so we can write
and differentiating it, with respect to z, we obtain
The strong differential subordination (17) takes the form
and applying Lemma 2, we have
that means
and the sharpness of this result is given by the best dominant g. □
Theorem 5.
Taking the convex function with the property for , such that the strong subordination
holds, we obtain the strong differential subordination
for the convex function considered as the best dominant.
Proof.
Let
Differentiating, with respect to z this relation, we obtain
and strong differential subordination (18) can be written as
After applying Lemma 1, we have
equivalent with
with g being the best dominant. □
Theorem 6.
Taking a convex function with the property we consider the function ,. If and the strong subordination
holds, then we obtain the sharp strong differential subordination
with the function g as best dominant.
Proof.
Let
Differentiating this relation, with respect to we obtain , written as
.
Strong differential subordination (19) can be written for as
and applying Lemma 2, we have the strong differential subordination, for
equivalent with
and the sharpness of this result is given by the best dominant g. □
3. Strong Differential Superordination Results
In this section, strong differential superordinations are studied, regarding the extended q-analogue of the multiplier transformation . The best subordinant is established for each of the studied strong differential superordinations.
Theorem 7.
Taking and a convex function in with the property consider , , , and suppose that is a univalent function in , . If the strong differential superordination
states, then we obtain the strong differential superordination
with the convex function the best subordinant.
Proof.
Using the relation from Theorem 2 and differentiating it, with respect to z, we can write in the following form which, after differentiating it again, with respect to z, has the form
Theorem 8.
Taking a convex function , we consider the function with , For set , , and suppose that is univalent in and . When the strong differential superordination
states, then we obtain the strong differential superordination
for the best subordinant.
Proof.
Considering , following the proof of Theorem 7, we can write the strong differential superordination (23) in the following form
Applying Lemma 4 for and we obtain the strong differential superordination having the best subordinant. □
Theorem 9.
For , set , and where , Assume that is univalent in , and the strong differential superordination
is satisfied, then the strong differential superordination
is satisfied for the convex function as the best subordinant.
Proof.
Let , and following the proof of Theorem 7, the strong superordination (24) can be written as
Applying Lemma 3, we obtain the strong differential superordination , where and g is the best subordinant and it is convex. □
Theorem 10.
Consider and a convex function with the property . Assume that is univalent and . When the strong superordination
states, then the following strong differential superordination
is satisfied, for the convex function the best subordinant.
Proof.
Let With this notation we can write and differentiating it, with respect to z, we obtain
Using this notation, the strong differential superordination (25) becomes and applying Lemma 3, we obtain for is the best subordinant and convex. □
Theorem 11.
Taking a convex function in , we consider the function Suppose is univalent, for and the strong superordination
is satisfied, then the strong differential superordination
is satisfied for the best subordinant.
Proof.
Taking account the proof of Theorem 10 for , the strong superordination (26), can be written in the following form
Applying Lemma 4, we obtain the strong differential superordination equivalently with , for g the best subordinant. □
Theorem 12.
Let with , For , assume that is univalent and . If the strong differential superordination
holds, then we have the following strong differential superordination
and the best subordinant is the convex function .
Proof.
Following the proof of Theorem 10 for , the strong superordination (27) takes the form
Applying Lemma 3, we obtain the following strong differential superordination , equivalent with The convex function g is the best subordinant. □
Theorem 13.
Taking a convex function with the property , for , assume that is univalent and . If the strong differential superordination
holds, then we obtain the following strong differential superordination
and the best subordinant is the convex function .
Proof.
Let after differentiating this relation, with respect to z, we obtain , written in the following form .
Strong differential superordination (28) for , becomes
Applying Lemma 3, we obtain the following strong differential superordination for the best subordinant convex. □
Theorem 14.
Taking a convex function , we consider For , assume that is univalent and . If the strong differential superordination
states, then we obtain the strong differential superordination
and the best subordinant is .
Proof.
Following the proof of Theorem 13 for , the strong superordination (29) has the form
Applying Lemma 4, it yields equivalently with and the best subordinant is g. □
Theorem 15.
Consider , with . For assume that is univalent and . If the strong differential superordination
holds, then the strong differential superordination
states, and the best subordinant is the convex function .
Proof.
Considering the notation , the strong differential superordination (30) can be written
Applying Lemma 3, we have the strong differential superordination , equivalently with
The best subordinant is the convex function g. □
4. Conclusions
The significant findings in this paper are connected to a new class of mathematically normalized analytic functions in , , defined in Definition 5, using the multiplier transformation shown in Definition 4 as an expanded version of the q-analogue of the expression. The class is presented, and its convexity property is established in Section 2 of the article. Sharp strong differential subordinations are next studied in five theorems using the property of the functions belonging to the class . The best dominant for the strong differential subordination is similarly given in Theorem 2, and in Theorem 3, a specific inclusion relation for the class is established. Strong differential superordinations are established in the nine theorems involving the extended q-analogue of the multiplier transformation , its first derivative with regard to z, , second derivative , and the representation and its derivative, with respect to z, in Section 3 of the article.
Strong subordination and superordination outcomes such as those shown here may serve as an inspiration for future research that substitutes various extended q-operators for the multiplier transformation . An additional set of conditions for the univalence of the operator under investigation might be derived because the best dominant of the strong differential subordinations in Theorem 2, and the best subordinants for the strong differential superordinations discussed in Section 3 are both presented. Using the extended q-analogue of the multiplier transformation, , and other strong subordination relations, further classes of univalent functions might be created. It will also be possible to look for coefficient estimates for the class . With the previously established convexity of this class, more research might be performed to demonstrate other symmetry features of this class.
Author Contributions
Conceptualization, A.A.L. and F.G.; methodology, F.G.; software, A.A.L.; validation, A.A.L. and F.G.; formal analysis, A.A.L. and F.G.; investigation, A.A.L.; resources, F.G.; data curation, F.G.; writing—original draft preparation, A.A.L.; writing—review and editing, A.A.L. and F.G.; visualization, A.A.L.; supervision, F.G.; project administration, A.A.L.; funding acquisition, A.A.L. All authors have read and agreed to the published version of the manuscript.
Funding
The publication of this research was partially supported by University of Oradea.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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