Abstract
This paper introduces novel subfamilies of analytic and bi-univalent functions in , defined by applying a linear operator associated with the Mittag–Leffler function and requiring subordination to domains related to generalized bivariate Fibonacci polynomials. The proposed framework provides a unified treatment that generalizes numerous earlier studies by incorporating parameters controlling both the operator’s fractional calculus features and the domain’s combinatorial geometry. For these subfamilies, we establish initial coefficient bounds (, ) and solve the Fekete–Szegö problem (). The derived inequalities are interesting, and their proofs leverage the intricate interplay between the series expansions of the Mittag–Leffler function and the generating function of the Fibonacci polynomials. By specializing the parameters governing the operator and the polynomial domain, we show how our main theorems systematically recover and extend a wide range of known results from the literature, thereby demonstrating the generality and unifying power of our approach.
Keywords:
bi-univalent; analytic; subordination; Mittag–Leffler function; convolution; bivariate Fibonacci polynomials MSC:
Primary 30C45; Secondary 30C20
1. Introduction and Preliminaries
Let be an open unit disk, where is the complex plane. Denote by the family of all holomorphic functions in that have the next series:
and let , is univalent in . For , , is subordinate to , if there is a Schwarz function that is holomorphic in with and , such that ,. This subordination is symbalized as , . In case, if , then
The famous Koebe theorem ([1]) states that every univalent function of the series (1) has an inverse function , where
satisfying and ,. A function is said to be bi-univalent function if in . The family of bi-univalent functions was presented by Levin in his work [2]. The family is not a null set where , and are functions in the family but the Koebe function and are not elements of the family , although they are univalent functions in . For a shortened analysis and to discover some of the properties of the family , see [3,4,5,6].
In 2010, Srivastava et al. [7] derived bounds for the coefficients and of functions in two significant subfamilies of the family . Motivated by this article, numerous scholars have studied new subfamilies of to find new bounds for the coefficients and (see [8,9,10,11,12]). Also, for each univalent function defined by (1), the Fekete–Szegö functional , , is well renowned for its rich history in the field of Geometric Function Theory (GFT). Its origin was in the refutation by Fekete and Szegö [13]. Several researchers have found coefficient estimates and Fekete–Szegö problems for subfamilies of (involving different operators) that are subordinate to a known number sequence or special polynomials (refer to [14,15,16,17,18,19] for additional details). The problems of finding coefficient bounds and solving the Fekete–Szegö inequality are essentially optimization problems in mathematics. Interestingly, similar boundedness and optimization problems appear in other fields such as high-dimensional data analysis and system identification (see [20]). This shows a useful connection between geometric function theory and modern applied mathematics.
For , generalized bivariate Fibonacci polynomials (GBFP) are defined by the recurrence relation:
where and are polynomials in and y, with real coefficients, , and . The generating function of generalized bivariate Fibonacci polynomials is (see [21])
For the specific chosen of and , GBFP tends to various familiar polynomials (see [22]). Readers interested in GBFP can find a brief history and more extensive information in [23] and its references. For members of certain subclasses of involving GBFP, interesting properties regarding coefficient estimates and Fekete–Szegö problems have been found in [24,25].
For the sake of brevity, we write and . Therefore,
are evident from (3).
The Mittag–Leffler function plays a main role in a diversity of problems in mathematical analysis, fractional calculus, operator theory, fractional adaptive control systems [26], uncertainty modeling in power flow analysis [27] and other fields related to science and engineering. Furthermore, it has always been a source of inspiration for many researchers [28,29,30,31,32,33]. In 1903, Mittag–Leffler [34] introduced the function , , defined by the next form,
It is convergent in the whole complex plane. For , the one-parameter Mittag–Leffler function is an entire function of order and satisfies the recurrence relation
Special values of the Mittag–Leffler function for integer are
and
where is the Gauss error function given by
and , where denotes the complimentary error function. These functions are widely used in fractional dynamical systems, such as in structural control and digital signal integration (see [35]).
In [36], Srivastava and Tomovski defined the generalized Mittag–Leffler function as follows:
where and is the Pochhammer symbol defined by
If such that are given by
then the function is defined by
which is called the convolution of and or the Hadamard product of and
In 2016, Attiya [37] defined and studied a certain linear operator by using convolution as follows:
where
Hence, we get
Remark 1.
Setting the parameters as , , and reduces the operator to , which coincides with the operator introduced by Livingston [38]. Similarly, choosing , , and yields the integral form , known as the Alexander integral operator [39,40]. These concrete reductions demonstrate how the Mittag–Leffler framework systematically encapsulates both classical differential and integral operators within a unified analytic structure.
Remark 2.
For and , we have .
This paper introduces and investigates new subfamilies of analytic and bi-univalent functions by applying a linear operator based on the generalized Mittag–Leffler function and imposing subordination to domains associated with the generalized bivariate Fibonacci polynomials. The Mittag–Leffler function provides a flexible fractional calculus operator, while the Fibonacci polynomials define a diverse family of geometric shapes. By unifying these two parameterized frameworks, we establish bounds for the initial Taylor coefficients and and solve the corresponding Fekete–Szegö problem for the functional .
2. Main Results
Using the operator and the generalized bivariate Fibonacci polynomials , we define the following families.
Definition 1.
Let . If satisfies
and
then we say that , where and
Remark 3.
The subfamilies are derived for particular choices of λ in the family :
Definition 2.
Remark 4.
The subfamilies are derived for particular choices of λ in the family :
2. .
Throughout our following discussion, we will assume, unless otherwise stated, that , k and l are polynomials in and y, with real coefficients such that and all the powers are considered the principal ones. In the first theorem, for functions in the newly introduced subfamily , we establish the upper bounds for the initial Maclaurin coefficients and , and solve the Fekete–Szegö inequality .
Theorem 1.
Proof.
Let . Then, from conditions (6) and (7), we can find that
and
such that are Schwarz functions with the property (See [1])
Using simple mathematical techniques, we can find from (21) and (22) that
and
From the comparison of Equations (24) and (25), we conclude due to equality (21) that
and
Similarly, consequent to (22), we find by comparing the terms of the same degree in (26) and (27) that
and
Equating (28) and (30) gives us
Also, by squaring (28) and (30) and adding them together, we get
Addition of (29) and (31) yields
Replacing from (33) in (34), we get
Utilizing (5) for and , and applying (23) to , produces (17). Now, we subtract (31) from (29) to find the bound on :
If we replace from (33) in (36), we get
We derive (18) from (37) by using (5) and (23). Finally, we calculate the estimate on using the values of and from (35) and (36), respectively. Consequently, we have
where
Clearly, we have
We derive (19) from (38), where ℸ is the same as in (20). □
Next, we provide the initial upper bounds for functions in the subfamily .
Theorem 2.
Proof.
Let . Then, from (13) and (14), we get
and
where
and
are Schwarz functions with the following properties:
Utilizing the series expansions of and given by (1) and (44), respectively, we obtain
Moreover, by utilizing the series expansion of and given by (1) and (45), respectively, we obtain
Therefore, by comparing the corresponding coefficients in (47) and (48), it is possible to get
and
Now, the results (39)–(41) follow from (49)–(52), using the same method as used in Theorem 1 in relation to (28) to (31). □
Remark 5.
The coefficient bounds derived here are analogous to the stability bounds in interval power flow models and adaptive system identification [41].
3. Special Cases
In this section, we present some special cases for our results with specific parameters, such as .
When , Theorem 1 would yield the next corollary.
Corollary 1.
When , Theorem 1 would yield the following corollary.
Corollary 2.
Taking and in the above corollary, we obtain the next example.
Example 1.
If the functions satisfy the next conditions:
and
then
and, for , we have
When , Theorem 2 reduce to the next corollary.
Corollary 3.
Taking and in the above corollary, we obtain the following example.
Example 2.
If the functions satisfy the next conditions
and
then
and for , we have
4. Conclusions
Many mathematicians have recently conducted research on special functions due to their use in various mathematical and scientific fields. This study introduces new subfamilies of holomorphic functions defined using convolution operator based on the generalized Mittag–Leffler function and generalized bivariate Fibonacci polynomials. The key findings are given below:
- Two new subfamilies and of biunivalent functions are established and analyzed.
- The initial bounds of the Maclaurin coefficients inequality are derived.
- The Fekete–Szegö inequality is solved for a real parameter .
- Specializing the parameters yields new results for certain subfamilies of biunivalent functions that had not been explored before in geometric function theory.
Open Problems. The following list of the related open problems will presumably of interest to the readers:
- Determine the upper bounds for higher-order coefficients ().
- Extend the framework to other special function operators (e.g., Wright or Fox–H functions).
- Investigate coefficient-related problems such as Hankel determinants, Bohr radii and inclusion relations for these geometrically defined subfamilies.
Author Contributions
Conceptualization, I.A., H.M.S., S.M.E.-D. and T.M.S.; Methodology, I.A., H.M.S., S.M.E.-D. and T.M.S.; Software, I.A., H.M.S., S.M.E.-D. and T.M.S.; Validation, I.A., H.M.S., S.M.E.-D. and T.M.S.; Formal analysis, I.A., H.M.S., S.M.E.-D. and T.M.S.; Investigation, I.A., H.M.S. and S.M.E.-D.; Resources, I.A., H.M.S., S.M.E.-D. and T.M.S.; Data curation, I.A., H.M.S., S.M.E.-D. and T.M.S.; Writing—original draft, I.A., H.M.S., S.M.E.-D. and T.M.S.; Writing—review & editing, I.A., H.M.S., S.M.E.-D. and T.M.S.; Visualization, I.A., H.M.S., S.M.E.-D. and T.M.S.; Supervision, I.A., H.M.S., S.M.E.-D. and T.M.S.; Project administration, I.A., H.M.S., S.M.E.-D. and T.M.S.; Funding acquisition, I.A., H.M.S., S.M.E.-D. and T.M.S. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP-RP26).
Data Availability Statement
No new data were created or analyzed in this study.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Duren, P.L. Univalent Functions; Grundlehren der Mathematischen Wissenschaften, Band 259; Springer: New York, NY, USA, 1983. [Google Scholar]
- Lewin, M. On a coefficient problem for bi-univalent functions. Proc. Amer. Math. Soc. 1967, 18, 63–68. [Google Scholar] [CrossRef]
- Brannan, D.A.; Taha, T.S. On some classes of bi-univalent functions. Studia Univ. Babeş-Bolyai Math. 1986, 31, 70–77. [Google Scholar]
- Brannan, D.A.; Clunie, J.G. Aspects of contemporary complex analysis. In Proceedings of the NATO Advanced Study Institute Held at University of Durhary; Academic Press: New York, NY, USA, 1979. [Google Scholar]
- Netenyahu, E. The minimal distance of the image boundary from the origin and the second coefficient of a univalent function in |z| < 1. Arch. Rational Mech. Anal. 1969, 32, 100–112. [Google Scholar] [CrossRef] [Scilit]
- Tan, D.L. Coefficient estimates for bi-univalent functions. Chin. Ann. Math. Ser. A 1984, 5, 559–568. [Google Scholar]
- Srivastava, H.M.; Mishra, A.K.; Gochhayat, P. Certain subclasses of analytic and bi-univalent functions. Appl. Math. Lett. 2010, 23, 1188–1192. [Google Scholar] [CrossRef] [Scilit]
- Bulut, S. Faber polynomial coefficient estimates for a comprehensive subclass of analytic bi-univalent functions. C.R. Acad. Sci. Paris Sér. 2014, I, 479–484. [Google Scholar] [CrossRef] [Scilit]
- Deniz, E. Certain subclasses of bi-univalent functions satisfying subordinate conditions. J. Class. Ana. 2013, 2, 49–60. [Google Scholar] [CrossRef] [Scilit]
- Frasin, B.A. Coefficient bounds for certain classes of bi-univalent functions. Hacet. J. Math. stat. 2014, 43, 383–389. [Google Scholar] [CrossRef] [Scilit]
- Frasin, B.A.; Aouf, M.K. New subclasses of bi-univalent functions. Appl. Math. 2011, 24, 1569–1573. [Google Scholar] [CrossRef] [Scilit]
- Tang, H.; Deng, G.; Li, S. Coefficient estimates for new subclasses of Ma-Minda bi-univalent functions. J. Inequalities Appl. 2013, 2013, 317. [Google Scholar] [CrossRef] [Scilit]
- Fekete, M.; Szegö, G. Eine Bemerkung Uber ungerade schlichte funktionen. J. Lond. Math. Soc. 1933, 89, 85–89. [Google Scholar] [CrossRef] [Scilit]
- Altınkaya, Ş.; Yalçın, S. Lucas polynomials and applications to an unified class of bi-univalent functions equipped with (P,Q)-derivative operators. TWMS J. Pure Appl. Math. 2020, 11, 100–108. [Google Scholar]
- Deniz, E.; Kamali, M.; Korkmaz, S. A certain subclass of bi-univalent functions associated with Bell numbers and q-Srivastava Attiya operator. AIMS Math. 2020, 5, 7259–7271. [Google Scholar] [CrossRef] [Scilit]
- Guney, H.O.; Murugusundaramoorthy, G.; Sokol, J. Certain subclasses of bi-univalent functions related to shell-like curves connected with Fibonacci numbers. Acta Univ. Sapientiae Math. 2018, 10, 70–84. [Google Scholar] [CrossRef] [Scilit]
- Orhan, H.; Mamatha, P.K.; Swamy, S.R.; Magesh, N.; Yamini, J. Certain classes of bi-univalent functions associated with the Horadam polynomials. Acta Univ. Sapientiae Math. 2021, 13, 258–272. [Google Scholar] [CrossRef] [Scilit]
- Swamy, S.R.; Yalcin, S. Coefficient bounds for regular and bi-univalent functions linked with Gegenbauer polynomials. Probl. Anal. Issues Anal. 2022, 11, 133–144. [Google Scholar] [CrossRef] [Scilit]
- Swamy, S.R.; Breaz, D.; Kala, V.; Mamatha, P.K.; Cotîrlă, L.-I.; Rapeanu, E. Initial Coefficient bounds analysis for novel subclasses of bi-univalent functions linked with Lucas-Balancing polynomials. Mathematics 2024, 12, 1325. [Google Scholar] [CrossRef] [Scilit]
- Yao, M.; Zhao, T.; Cao, J.; Li, J. Hierarchical Fuzzy Topological System for High-Dimensional Data Regression Problems. IEEE Trans. Fuzzy Syst. 2025, 33, 2084–2095. [Google Scholar] [CrossRef] [Scilit]
- Kocer, E.G.; Tuncez, S. Bazilevic Fibonacci and Lucas like polynomials. Gazi Univ. J. Sci. 2016, 29, 109–113. [Google Scholar]
- Yilmaz, N.; Aktas, I. On some new subclasses of bi-univalent functions defined by generalized bivariate Fibonacci polynomial. Afr. Mat. 2022, 33, 3–12. [Google Scholar]
- Catalani, M. Generalized Bivariate Fibonacci Polynomials. arXiv 2004, arXiv:math/0211366. [Google Scholar] [CrossRef] [Scilit]
- Aktas, I.; Hamarat, D. Generalized bivariate Fibonacci polynomial and two new subclasses of bi-univalent functions. Asian-Eur. J. Math. 2023, 16, 2350147. [Google Scholar] [CrossRef] [Scilit]
- Ozturk, R.; Aktas, I. Coefficient Estimate and Fekete-Szegö Problems for certain new subclasses of bi-univalent functions defined by generalized bivariate Fibonacci polynomial. Sahand Commun. Math. Anal. 2024, 21, 3. [Google Scholar]
- Zhang, C.; Liu, M.; Mohammadzadeh, A.; Taghavifar, H. A fractional adaptive type-2 fuzzy structural control system: Theoretical/experimental study. Structures 2024, 70, 107843. [Google Scholar] [CrossRef] [Scilit]
- Wang, D.; Zhang, C.; Li, J.; Zhu, L.; Zhou, B.; Zhou, Q.; Cheng, L.; Shuai, Z. A Novel Interval Power Flow Method Based on Hybrid Box-Ellipsoid Uncertain Sets. IEEE Trans. Power Syst. 2024, 39, 6111–6114. [Google Scholar] [CrossRef] [Scilit]
- Mittag-Leffler, M.G. Sur la représentation analytique d’une branche uniforme d’une fonction monogène. Acta Math. 1905, 29, 101–181. [Google Scholar] [CrossRef] [Scilit]
- Aouf, M.K.; Seoudy, T.M. Subclasses of p–valent functions involving a new operator containing the generalized Mittag–Leffler function. Mediterr. J. Math. 2018, 15, 181. [Google Scholar] [CrossRef] [Scilit]
- Noreen, S.; Raza, M.; Liu, J.-L.; Arif, M. Geometric Properties of Normalized Mittag-Leffler Functions. Symmetry 2019, 11, 45. [Google Scholar] [CrossRef] [Scilit]
- Srivastava, H.M.; El-Deeb, S.M. Fuzzy Differential Subordinations Based upon the Mittag–Leffler Type Borel Distribution. Symmetry 2021, 13, 1023. [Google Scholar] [CrossRef] [Scilit]
- Attiya, A.A.; Seoudy, T.M.; Albaid, A. Third-order differential subordination for meromorphic functions associated with generalized Mittag-Leffler function. Fractal Fract. 2023, 7, 175. [Google Scholar] [CrossRef] [Scilit]
- Wong, R.S.C.; Zhao, Y.-Q. Exponential asymptotics of the Mittag-Leffler function. Constr. Approx. 2002, 18, 355–385. [Google Scholar] [CrossRef] [Scilit]
- Mittag-Leffler, G.M. Sur la nouvelle fonction Eα(x). Comptes Rendus Acad. Sci. 1903, 137, 554–558. [Google Scholar]
- Ali, T.A.A.; Xiao, Z.; Jiang, H.; Li, B. A class of digital integrators based on trigonometric quadrature rules. IEEE Trans. Ind. Electron. 2024, 71, 6128–6138. [Google Scholar] [CrossRef] [Scilit]
- Srivastava, H.M.; Tomovski, Z. Fractional calculus with an integral operator containing a generalized Mittag-Leffler function in the kernel. Appl. Math. Comput. 2009, 211, 198–210. [Google Scholar] [CrossRef] [Scilit]
- Attiya, A.A. Some applications of Mittag-Leffler function in the unit disk. Filomat 2016, 30, 2075–2081. [Google Scholar] [CrossRef] [Scilit]
- Livingston, A.E. On the radius of univalence of certain analytic functions. Proc. Am. Math. Soc. 1996, 17, 352–357. [Google Scholar] [CrossRef]
- Alexander, J.W. Functions which map the interior of the unit circle upon simple regions. Ann. Math. 1915, 17, 12–22. [Google Scholar] [CrossRef] [Scilit]
- Biernacki, M. Sur l’intégrale des fonctions univalentes. Bull. Acad. Polon. Sci. Sér. Sci. Math. Astr. Phys. 1960, 8, 29–34. [Google Scholar]
- Yang, J.; Liu, Y.; Lu, X.; Wang, T. An adaptive measurement-based substructure identification framework for dynamic response reconstruction. Mech. Syst. Signal Process. 2025, 239, 113277. [Google Scholar] [CrossRef] [Scilit]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.