Abstract
This paper offers a thorough examination of a unified class of Humbert’s polynomials in two variables, extending beyond well-known polynomial families such as Gegenbauer, Humbert, Legendre, Chebyshev, Pincherle, Horadam, Kinnsy, Horadam–Pethe, Djordjević, Gould, Milovanović, Djordjević, Pathan, and Khan polynomials. This study’s motivation stems from exploring polynomials that lack traditional nomenclature. This work presents various expansions for Humbert–Hermite polynomials, including those involving Hermite–Gegenbauer (or ultraspherical) polynomials and Hermite–Chebyshev polynomials. The proofs enhanced our understanding of the properties and interrelationships within this extended class of polynomials, offering valuable insights into their mathematical structure. This research consolidates existing knowledge while expanding the scope of Humbert’s polynomials, laying the groundwork for further investigation and applications in diverse mathematical fields.
Keywords:
Hermite polynomials; generalized humbert polynomials; generalized (p,q)-Fibonacci polynomials; generalized (p,q)-Lucas polynomials MSC:
0A115; 05A19; 11B39; 33C45; 33C55; 33C99
1. Introduction and Preliminaries
Special polynomials represent a distinctive class in mathematics, characterized by their inherent symmetries and unique properties that play pivotal roles in diverse mathematical areas. Their symmetrical structures often facilitate solving differential equations and analyzing orthogonal functions, making them tools for various fields. The symmetry inherent in these polynomials contributes to their wide-ranging applications, extending their utility to disciplines such as physics, engineering, and computer science, where they provide elegant solutions to complex problems.
Among the prominent examples of special polynomials are several well-known families. Legendre polynomials often appear in solving problems related to potential fields and wave equations, making them essential in electrostatics and quantum mechanics. Chebyshev polynomials are central to approximation theory and numerical analysis, particularly in minimizing errors in polynomial approximations. Hermite polynomials are crucial in quantum mechanics, especially in the study of the harmonic oscillator, where they describe the wave functions of quantum states. Humbert polynomials play an important role in combinatorial mathematics and the analysis of divided differences, contributing to the study of sequences and series. Appell polynomials are significant in the theory of special functions and modular forms, with applications extending to complex analysis and number theory. Touchard polynomials are instrumental in probability theory and combinatorics, particularly in the enumeration of permutations and partitions. These polynomials provide solutions to complex mathematical problems and are powerful tools for modeling and analysis across various scientific and engineering fields, where their inherent symmetry properties play a crucial role in simplifying computations and revealing underlying structures.
In 1965, Gould [1,2] made a significant contribution to the field of special functions by introducing a new class of polynomials, now referred to as Humbert polynomials, which he denoted as . His work thoroughly analyzed these polynomials, delving into their explicit mathematical expressions, recurrence relations, and higher-order derivatives. Additionally, Gould explored their operational expansions and the inverse relations associated with them, offering a comprehensive framework for understanding these polynomials’ behavior under various transformations and operations. Due to their ability to encompass several well-established families of polynomials through specific parameters, Humbert polynomials are particularly intriguing. For instance, when particular parameter values are selected, these polynomials can be reduced to Chebyshev, Gegenbauer, Kinney, Legendre, Liouville, or Pincherle polynomials. This unifying characteristic highlights the versatility of Humbert polynomials, making them a powerful tool in both theoretical research and practical applications.
The adaptability of the Humbert–Gould polynomials has attracted considerable attention from mathematicians, leading to a wealth of research aimed at expanding and generalizing their properties. Over the years, numerous scholars have contributed to this growing body of knowledge, bringing new insights and extensions to the original work. For example, Agarwal and Parihar [3] have provided valuable generalizations that broaden the scope of these polynomials in different mathematical contexts. Dilcher and Djordjević and their collaborators [4,5,6,7,8] have made significant strides in exploring the deeper properties of these polynomials, investigating their relationships with other special functions, and expanding their operational frameworks [9,10,11,12,13,14].
Researchers like He and Shiue [15,16] have furthered the understanding of Humbert–Gould polynomials by examining their applications in combinatorial mathematics and other areas. Horadam and their collaborators Mohan and Pethe have extensively studied these polynomials, focusing on their combinatorial aspects and connections to other mathematical structures. Khan and Pathan [17] have also played a key role in advancing the operational theory related to these polynomials, providing new methods for their manipulation and application [18,19,20,21].
Other notable contributions come from Milovanović and Djordjević [22], who have explored the algebraic properties of Humbert–Gould polynomials, and Dave [23], Liu [24], and Ma [25], who has worked on extending their applicability to various fields. Ramírez [26,27], Nalli and Haukkanen [28] Sinha [29], Shreshta [30], Wang, and the collaborative work of Wang and Wang [31,32] have all added to the rich tapestry of research surrounding these polynomials, each offering unique perspectives and insights that have furthered the mathematical community’s understanding of these versatile functions.
Therefore, Gould’s introduction of Humbert polynomials has opened up a vast area of mathematical inquiry, with numerous researchers building upon their foundational work. The ongoing exploration and generalization of these polynomials have deepened our understanding of their inherent properties and expanded their application across various domains, making them an essential subject of study in modern mathematics (see [1,2,12,13,15,24]).
The Humbert–Gould polynomials [1] are introduced via the generating function given by:
where is a positive integer, and the remaining parameters are generally free of restrictions. The explicit form of the polynomial is expressed as follows (see [1]):
where is the greatest integer.
In recent work, Wang and Wang [32] extended the concept by introducing generalized forms of the -Fibonacci and -Lucas polynomials. These are defined as follows.
Let be a fixed positive integer, and consider two polynomials and with real coefficients. The generalized -Fibonacci polynomials, denoted by and -Lucas polynomials , are defined through the generating functions (refer to [32]):
with the initial conditions , , . And
with the initial conditions , , .
The generating functions for the sequences and are given by the following expressions [32]:
and
These definitions imply the following relationship:
It is important to note that the sequences of polynomials and satisfy the same recurrence relation of order , yet they differ in their initial conditions. These sequences are sometimes referred to as the generalized Lucas u-polynomial and the generalized v-polynomial sequences, respectively.
The sequences and include several well-known polynomial sequences as particular cases. For example, when , these sequences simplify to the classical -Fibonacci polynomials and -Lucas polynomials (as defined in (see [19,21,26,27,31]. Further simplifications yield familiar polynomials associated with names such as Fibonacci, Lucas, Pell, Pell–Lucas, Jacobsthal, and Jacobsthal–Lucas, among others.
Recently, Wang and Wang [32] introduced the generalized the Humbert polynomials as the convolutions of Fibonacci polynomials.
Definition 1.
For each complex number r, the generalized convolved -Fibonacci polynomials, also known as the generalized Humbert polynomials , are defined by the generating function:
where θ is a positive integer.
This relationship underscores the connection between these generalized polynomial sequences and various well-known sequences in the mathematical literature.
The introduction of special functions with numerous indices and variables represents a noteworthy progression in the field of generalized special functions. These functions hold considerable importance, finding recognition in both practical applications and pure mathematical contexts. The demand for polynomials with multiple indices and variables arises from the necessity to address challenges across various mathematical disciplines, from the study of partial differential equations to abstract group theory. Recently, the polynomials represented by , known as multivariable Hermite Polynomials (MHP), were introduced in (see [33,34]) and are given by generating relation:
with the operational rule:
and series representation:
This paper is structured as follows. Section 2 delves into the introduction of the generalized multivariate Humbert–Hermite polynomials, denoted as . These polynomials are constructed by leveraging the framework of generalized -Fibonacci polynomials. We provide a comprehensive exploration of their mathematical properties, including but not limited to their generating relations, explicit forms, and notable identities. This section also examines the underlying algebraic structure and potential applications of these polynomials in various mathematical contexts.
Section 3 shifts focus to the analysis and derivation of various expansions related to Hermite polynomials. Specifically, we obtain expansions for the Hermite–Chebyshev and Hermite–Gegenbauer polynomials. This section systematically explores the connections between these classical orthogonal polynomials, providing detailed proofs and discussing the implications of these expansions in broader mathematical and applied fields. Through these expansions, we highlight how these polynomials can be expressed in terms of other well-known polynomial families, thereby enriching the theory and application of Hermite-related polynomials. The paper concludes with some remarks.
2. Generalized Multivariate Hermite–Humbert Polynomials
In this section, we present the introduction of generalized multivariate Hermite–Humbert polynomials, denoted as . These polynomials are developed within the framework of generalized -Fibonacci polynomials, which serve as the foundational building blocks. By extending the concept of the classic Hermite–Humbert polynomials into a multivariate setting, we aim to explore the deeper structural relationships and functional properties that emerge in this generalized form. The introduction of these polynomials is not merely a theoretical exercise; it represents a significant expansion in the field of polynomial theory, with potential applications in areas such as combinatorics, number theory, and the study of special functions. This work seeks to provide a robust mathematical foundation for these polynomials, facilitating further exploration and application in both pure and applied mathematics.
We begin by formally defining the generalized multivariate Hermite–Humbert polynomials , establishing the groundwork for a detailed examination of their properties. These properties include generating functions, recurrence relations, and identities that reveal the intricate connections between the multivariate Hermite–Humbert polynomials and the underlying -Fibonacci polynomials. By deriving and analyzing these properties, we aim to uncover the mathematical significance of these polynomials, demonstrating how they generalize classical results and contribute to the broader understanding of polynomial sequences. This section serves as a critical foundation for the subsequent analysis, providing the essential tools and definitions required for the in-depth exploration of these polynomials and their applications in later sections.
Definition 2.
For each complex number r, the generalized convolved -Fibonacci polynomials, also known as the generalized multivariate Hermite–Humbert polynomials , are defined by the generating function:
where θ is a positive integer, , and the other parameters are generally unrestricted.
Reduction to Known Results:
By setting in Equation , we obtain a known result by Wang and Wang [32]:
Furthermore, by taking , Equation reduces to another known result by Pathan and Khan [20].
Special Cases and Connections:
When , the polynomials become the generalized multivariate -Fibonacci polynomials , that is:
By adjusting the generating function in Equation with the substitutions , , and , where , we obtain:
where denotes the multivariate Humbert–Hermite–Gould polynomials. These polynomials can be further specialized into other polynomial families, such as the multivariate Hermite–Gegenbauer polynomials, Pincherle polynomials, and others, by appropriately choosing the parameters and c.
Polynomial Sequences and Representations:
By choosing particular values for , , and in Equation (12), we can generate different polynomial sequences, as illustrated in Table 1. Furthermore, using the definitions of and , we derive the following representation:
Table 1.
Special cases of the generalized multivariate Hermite–Humbert polynomials.
Some significant special cases of this representation are detailed below. By substituting into Equation (15), we derive additional relationships and transformations of these polynomials, which are as follows:
where are called the multivariate Hermite–Gegenbaurer polynomials:
where are called the multivariate Hermite–Chebyshev polynomials.
where denotes the multivariate Hermite–Legendre polynomials.
As a special case, if we set , , and in Equation (12), the generalized multivariate Humbert–Hermite polynomial simplifies to the Humbert–Hermite polynomial in one variable. Consequently, Equation (12) yields the following generating function:
Furthermore, the Hermite–Gegenbauer (or ultraspherical) polynomials (which are denoted as ) in one variable, for nonnegative integer r, are given by:
Letting and , respectively, in (17) gives:
where are Hermite–Legendre polynomials, and
where represents the Hermite–Chebyshev polynomials.
Next, we derive the explicit expressions for the generalized multivariate Hermite–Humbert polynomials. We start with the following theorem.
Theorem 1.
Let and . Then:
where
Proof.
From (12), we have:
Hence, we complete the proof of the theorem. □
Remark 1.
On setting in we get the known result of Wang and Wang [32].
Remark 2.
Adjusting , and replacing by in , we get:
Theorem 2.
Let and . Then:
where , .
Proof.
Let and in Equation (12) and we have:
Now:
From (23), we have:
By matching the coefficients of on both sides, we arrive at the desired result, Equation (22). □
Remark 3.
If we set in Equation (22), we get to know the result of Wang and Wang [32].
3. On Expansions of Multivariate Hermite–Chebyshev and Multivariate Hermite–Gegenbaurer Polynomials
In this section, we focus on proving several important theorems related to the expansions of multivariate Hermite–Gegenbauer and multivariate Hermite–Chebyshev polynomials in three variables. These expansions are crucial for understanding the deeper connections between various families of orthogonal polynomials and their applications in mathematical analysis and theoretical physics.
We begin our exploration by examining Equations (12) and (14), along with a specific case of (12) where and . The following equation:
is not just a mathematical expression, but a powerful tool that will be used to derive a series of subsidiary results in the following theorem. These results are significant because they offer insights into the structure and relationships of multivariate polynomials, which have broad implications in areas such as combinatorics, approximation theory, and mathematical physics.
Understanding these expansions allows us to bridge the gap between different polynomial families, providing a unified framework that can be applied to solve complex problems in various domains. The theorems we prove here are not only of theoretical interest but also pave the way for practical applications, making them a valuable addition to the existing body of knowledge in the field.
Theorem 3.
Let and . Then:
Proof.
Rewrite the (12) as:
Using (9), we can write:
Now:
Which completes the proof of the result. □
Remark 4.
Letting , in (25), we have the following.
Corollary 1.
For and , then:
Corollary 2.
For in (25) with and , then:
Theorem 4.
Let . Then:
Proof.
The definition of can be written as:
Using [35], we can write:
Hence, we complete the proof of the result. □
Remark 5.
Adjusting , , , in (28), it reduces to the known result of Batahan and Shehata [35].
Corollary 3.
For and , then:
Theorem 5.
Let . Then:
where
Proof.
By applying the power series expansion of and arranging the series appropriately, we obtain:
Additionally, we can express this as follows:
Now, by equating the coefficients of on both sides of the resulting equation, we obtain the desired result. □
Remark 6.
When setting and in Theorem 5, the result simplifies to:
In a similar manner, we can define the generalized -Lucas polynomials as follows:
Definition 3.
For any complex number r, the generalized convolved -Lucas polynomials, also referred to as the generalized multivariate Hermite–Humbert polynomials , are specified by:
where , , and the remaining parameters are generally unrestricted.
Theorem 6.
Let . Then:
Proof.
Utilizing expressions (9) and (33), it follows that:
By matching the coefficients of on both sides, we obtain Equation (35). □
Remark 7.
When is set in Theorem 6, the result simplifies to:
Theorem 7.
Let . Then:
Proof.
The expression (33) can be rewritten as:
By equating the coefficients of on both sides, we obtain Equation (37). □
Remark 8.
By setting in Theorem 7, the result simplifies to the following:
4. Conclusions
This paper has thoroughly investigated the generalized multivariable Humbert–Hermite polynomials, represented by the notation . Building on the generalized -Fibonacci polynomials, Section 2 has revealed key mathematical properties of these polynomials, including their generating relations, explicit forms, and significant identities. Additionally, the section has explored these polynomials’ algebraic structure and potential mathematical applications. Section 3 expanded the discussion by focusing on the derivation and analysis of expansions related to Hermite polynomials, particularly Hermite–Chebyshev and Hermite–Gegenbauer polynomials. This section has systematically examined the connections between these classical orthogonal polynomials, providing detailed proof and discussing the broader implications of these expansions. The ability to express these polynomials in terms of other well-known families enhances the theory and application of Hermite-related polynomials.
Future observations could focus on extending the derived expansions of Hermite-related polynomials, particularly Hermite–Chebyshev and Hermite–Gegenbauer polynomials, to more generalized families or multivariable settings. This could deepen the understanding of their orthogonal properties and recurrence relations in broader contexts. Additionally, exploring numerical methods for efficiently computing these expansions could be valuable, particularly in applications such as quantum mechanics or signal processing. Further research might uncover new combinatorial interpretations or connections between these polynomials and algebraic identities, enhancing their use in approximation theory, especially for solving differential equations and optimization problems.
Author Contributions
Conceptualization, N.A., H.N.Z., A.A., S.A.W. and W.A.K.; Data curation, N.A., H.N.Z. and A.A.; Formal analysis, S.A.W.; Funding acquisition, N.A., H.N.Z. and A.A.; Investigation, K.K., N.A., H.N.Z., A.A., S.A.W., F.G. and W.A.K.; Methodology, K.K., S.A.W. and W.A.K.; Project administration, S.A.W. and W.A.K.; Resources, N.A., H.N.Z., F.G. and A.A.; Software, S.A.W. and W.A.K.; Supervision, S.A.W. and W.A.K.; Validation, N.A., H.N.Z., A.A., S.A.W. and W.A.K.; Visualization, N.A., H.N.Z., A.A., S.A.W. and W.A.K.; Writing—original draft, K.K., S.A.W., W.A.K., H.N.Z. and F.G.; Writing—review and editing. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Research Deanship at the University of Ha’il, Saudi Arabia, through Project No. RG-23 206.
Data Availability Statement
Data are contained within the article.
Conflicts of Interest
The authors declare no competing interests.
References
- Gould, H.W. Inverse series relation and other expansions involving Humbert polynomials. Duke Math. J. 1965, 32, 697–711. [Google Scholar] [CrossRef]
- Gould, H.W.; Hooper, A.T. Operational formulas connected with two generalizations of Hermite polynomials. Duke Math. J. 1962, 29, 51–63. [Google Scholar] [CrossRef]
- Agarwal, R.; Parihar, H.S. On certain generalized polynomial system associated with Humbert polynomials. Sci. Ser. A Math. Sci. (N. S.) 2012, 23, 31–44. [Google Scholar]
- Dilcher, K. A generalization of Fibonacci polynomials and a representation of Gagenbauer polynomials of integer order. Fibonacci Quart. 1987, 25, 300–303. [Google Scholar] [CrossRef]
- Djorjević, G.B. A generalization of Gegenbauer polynomial with two variables. Indian J. Pure Appl. Math. 2024, in press. [Google Scholar]
- Djorjević, G.B. Polynomials related to generalized Chebyshev polynomials. Filomat 2009, 23, 279–290. [Google Scholar] [CrossRef]
- Djorjević, G.B.; Djordjevic, S.S. Convolutions of the generalized Morgan-Voyce polynomials. Appl. Math. Comput. 2015, 259, 106–115. [Google Scholar]
- Djorjević, G.B.; Srivastava, H.M. Incomplete generalized Jacobsthal and Jacobsthal-Lucas numbers. Math. Comput. Model. 2005, 42, 1049–1056. [Google Scholar] [CrossRef]
- Guan, H.; Khan, W.A.; Kizilates, C. On generalized bivariate (p,q)-Bernoulli-Fibonacci and generalized bivariate (p,q)-Bernoulli-Lucas polynomials. Symmetry 2023, 15, 943. [Google Scholar] [CrossRef]
- Andrews, L.C. Special Functions for Engineers and Mathematicians; Macmillan Co.: New York, NY, USA, 1985. [Google Scholar]
- Abramowitz, M.; Stegun, I.A. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables; Reprint of the 1972 Edition; Dover Publications, Inc.: New York, NY, USA, 1992. [Google Scholar]
- Bell, E.T. Exponential polynomials. Ann. Math. 1934, 35, 258–277. [Google Scholar] [CrossRef]
- Comtet, L. Advanced Combinatorics; D. Reidel Publishing Co.: Dordrecht, The Netherlands, 1974. [Google Scholar]
- Zhang, C.; Khan, W.A.; Kizilates, C. On (p,q)-Fibonacci and (p,q)-Lucas polynomials associated with Changhee numbers with their applications. Symmetry 2023, 15, 851. [Google Scholar] [CrossRef]
- He, T.-X.; Shiue, P.J.-S. On sequences of numbers and polynomials defined by linear recurrence relations of order 2. Int. J. Math. Math. Sci. 2009, 2009, 709386. [Google Scholar] [CrossRef]
- He, T.-X.; Shiue, P.J.-S. Sequences of non-Gegenbauer-Humbert polynomials meet the generalized Gegenebauer-Humbert polynomials. Int. Sch. Res. Netw. ISRN Algebra 2011, 2011, 268096. [Google Scholar] [CrossRef]
- Khan, W.A.; Pathan, M.A. On a class of Humbert-Hermite polynomials. Novi Sad J. Math. 2021, 51, 1–11. [Google Scholar]
- Cheon, G.-S.; Kim, H.; Shapiro, L.W. A generalization of Lucas polynomials sequence. Discret. Appl. Math. 2009, 157, 920–927. [Google Scholar] [CrossRef]
- Lee, G.; Asci, M. Some properties of the (p,q)-Fibonacci and (p,q)-Lucas polynomials. J. Appl. Math. 2012, 2012, 264842. [Google Scholar] [CrossRef]
- Pathan, M.A.; Khan, W.A. On a class of generalized Humberts-Hermite polynomials via generalized Fibonacci polynomials. Turk. J. Math. 2022, 46, 929–945. [Google Scholar] [CrossRef]
- Wang, J. Some new results for the (p,q)-Fibonacci and Lucas polynomials. Adv. Differ. Equ. 2014, 2014, 64. [Google Scholar] [CrossRef]
- Milovanović, G.V.; Djordjevixcx, G.B. On some properties of Humbert’s polynomials. Fibonacci Quart. 1987, 25, 356–360. [Google Scholar] [CrossRef]
- Dave, C.K. Another generalization of Gegenbauer polynomials. J. Indian Acad. Math. 1978, 2, 42–45. [Google Scholar]
- Liu, G. Formulas for convolution Fibonacci numbers and polynomials. Fibonacci Quart. 2002, 40, 352–357. [Google Scholar] [CrossRef]
- Ma, S.-M. Identities involving generalized Fibonacci-type polynomials. Appl. Math. Comput. 2011, 217, 9297–9301. [Google Scholar] [CrossRef]
- Ramírez, J.L. On convolved generalized Fibonacci and Lucas polynomials. Appl. Math. Comput. 2014, 229, 208–213. [Google Scholar] [CrossRef]
- Ramírez, J.L. Some properties of convolved k-Fibonacci numbers. ISRN Combin. 2013, 2013, 759641. [Google Scholar] [CrossRef][Green Version]
- Nalli, A.; Haukkanen, P. On generalized Fibonacci and Lucas polynomials. Chaos Solitons Fractals 2009, 42, 3179–3186. [Google Scholar] [CrossRef]
- Sinha, S.K. On a polynomial associated with Gegenbauer polynomials. Proc. Nat. Acad. Sci. India 1989, 59, 439–455. [Google Scholar]
- Shrestha, N.B. Polynomial associated with Legendre polynomials. Nepali Math. Sci. Rep. Triv. Univ. 1977, 2, 1. [Google Scholar]
- Wang, W.; Wang, H. Some results on convolved (p,q)-Fibonacci polynomials. Integral Transform. Spec. Funct. 2015, 26, 340–356. [Google Scholar] [CrossRef]
- Wang, W.; Wang, H. Generalized Humbert polynomials via generalized Fibonacci polynomials. Appl. Math. Comput. 2017, 307, 204–216. [Google Scholar] [CrossRef]
- Dattoli, G.; Torre, A. Exponential operators, quasi-monomials and generalized polynomials. Radiat. Phys. Chem. 2000, 57, 21–26. [Google Scholar] [CrossRef]
- Dattoli, G.; Maimo, G.; Torre, A.; Cesarano, C. Generalized Hermite polynomials and super-Gaussian forms. J. Math. Anal. Appl. 1996, 233, 597–609. [Google Scholar] [CrossRef]
- Batahan, R.S.; Shehata, A. Hermite-Chebyshev polynomials with their generalization form. J. Math. Sci. Adv. Appl. 2014, 29, 47–59. [Google Scholar]
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. |
© 2024 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 (https://creativecommons.org/licenses/by/4.0/).