Higher-order differential operators having bivariate orthogonal polynomials as eigenfunctions

We introduce a systematic method for constructing higher-order partial differential equations for which bivariate orthogonal polynomials are eigenfunctions. Using the framework of moment functionals, the approach is independent of the orthogonality domain’s geometry, enabling broad applicability across different polynomial families. Applications to classical weight functions on the unit disk and triangle modified by measures defined on lower-dimensional manifolds are presented.

Authors

Institutions

Publication Details

Journal
Results in Applied Mathematics
Published
2025-04-14
DOI
https://doi.org/10.1016/j.rinam.2025.100571
Primary Topic
Differential Equations and Numerical Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Higher-order differential operators having bivariate orthogonal polynomials as eigenfunctions

Misael E. Marriaga
Results in Applied Mathematics
Differential Equations and Numerical Methods
article

Higher-order differential operators having bivariate orthogonal polynomials as eigenfunctions

Misael E. Marriaga
article en

Abstract

We introduce a systematic method for constructing higher-order partial differential equations for which bivariate orthogonal polynomials are eigenfunctions. Using the framework of moment functionals, the approach is independent of the orthogonality domain’s geometry, enabling broad applicability across different polynomial families. Applications to classical weight functions on the unit disk and triangle modified by measures defined on lower-dimensional manifolds are presented.

Results in Applied MathematicsVol. 26
Universidad Rey Juan Carlos (ES)
Openalex Percentile: Top 89%
Differential Equations and Numerical Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.