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© 2019 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 (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Inspired by ideas from umbral calculus and based on the two types of integrals occurring in the defining equations for the gamma and the reciprocal gamma functions, respectively, we develop a multi-variate version of umbral calculus and of the so-called umbral image technique. Besides providing a class of new formulae for generalized hypergeometric functions and an implementation of series manipulations for computing lacunary generating functions, our main application of these techniques is the study of Sobolev-Jacobi polynomials. Motivated by applications to theoretical chemistry, we moreover present a deep link between generalized normal-ordering techniques introduced by Gurappa and Panigrahi, two-variable Hermite polynomials and our integral-based series transforms. Notably, we thus calculate all K-tuple L-shifted lacunary exponential generating functions for a certain family of Sobolev-Jacobi (SJ) polynomials explicitly.

Details

Title
Operational Methods in the Study of Sobolev-Jacobi Polynomials
Author
Behr, Nicolas 1   VIAFID ORCID Logo  ; Dattoli, Giuseppe 2 ; Duchamp, Gérard H E 3 ; Licciardi, Silvia 2   VIAFID ORCID Logo  ; Penson, Karol A 4 

 Institut de Recherche en Informatique Fondamentale (IRIF), Université Paris-Diderot, F-75013 Paris, France 
 ENEA—Frascati Research Center, Via Enrico Fermi 45, 00044 Rome, Italy 
 Laboratoire d’Informatique de Paris-Nord (LIPN), CNRS UMR 7030, Université Paris 13, Sorbonne Paris Cité, F-93430 Villetaneuse, France 
 Laboratoire de Physique Theorique de la Matière Condensée (LPTMC), CNRS UMR 7600, Sorbonne Universités, Université Pierre et Marie Curie, F-75005 Paris, France 
First page
124
Publication year
2019
Publication date
2019
Publisher
MDPI AG
e-ISSN
22277390
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2548592737
Copyright
© 2019 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 (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.