@misc{10481/107947,
year = {2026},
month = {1},
url = {https://hdl.handle.net/10481/107947},
abstract = {Polynomials known as Multiple Orthogonal Polynomials in a single variable are
polynomials that satisfy orthogonality conditions concerning multiple measures and
play a significant role in several applications such as Hermite-Padé approximation,
random matrix theory or integrable systems. However, this theory has only been
studied in the univariate case. In this paper, we present an introduction to Multiple
Orthogonality in one variable and its main properties, followed by some generalized
definitions of the two main types of multiple orthogonality, together with some
examples and extended results.},
organization = {MCIN/AEI/10.13039/501100011033 - Research Group GOYA-384 (PID2023-149117NB-I00, CEX2020-001105M)},
publisher = {Elsevier},
keywords = {Multiple orthogonal polynomials},
keywords = {Bivariate orthogonal polynomial vectors},
keywords = {Graded reverse lexicographic order},
title = {Multiple orthogonal polynomials of two real variables},
doi = {10.1016/j.jmaa.2025.129811},
author = {Fernández Rodríguez, Lidia and Villegas, Juan Antonio},
}