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The concepts of Generalized Parton Distributions (GPD) are reviewed in an introductory and phenomenological fashion. These distributions provide a rich and unifying picture of the nucleon structure. Their physical meaning is discussed. The…

High Energy Physics - Phenomenology · Physics 2009-11-07 Michel Garcon

Shifted partial derivative (SPD) methods are a central algebraic tool for circuit lower bounds, measuring the dimension of spaces of shifted derivatives of a polynomial. We develop the Shifted Partial Derivative Polynomial (SPDP) framework,…

Computational Complexity · Computer Science 2025-12-25 Darren J. Edwards

Darboux transformations for polynomial perturbations of a real multivariate measure are found. The 1D Christoffel formula is extended to the multidimensional realm: multivariate orthogonal polynomials are expressed in terms of last…

Classical Analysis and ODEs · Mathematics 2019-07-09 Gerardo Ariznabarreta , Manuel Mañas

We apply a symbolic approach of the general quadratic decomposition of polynomial sequences - presented in a previous article referenced herein - to polynomial sequences fulfilling specific orthogonal conditions towards two given…

Classical Analysis and ODEs · Mathematics 2020-01-07 Teresa Augusta Mesquita

We generalize some previous results on random polynomials in several complex variables. A standard setting is to consider random polynomials $H_n(z):=\sum_{j=1}^{m_n} a_jp_j(z)$ that are linear combinations of basis polynomials $\{p_j\}$…

Complex Variables · Mathematics 2024-01-29 Turgay Bayraktar , Tom Bloom , Norm Levenberg

The Dynamic-Mode Decomposition (DMD) is a well established data-driven method of finding temporally evolving linear-mode decompositions of nonlinear time series. Traditionally, this method presumes that all relevant dimensions are sampled…

Dynamical Systems · Mathematics 2021-01-13 Christopher W. Curtis , Daniel Jay Alford-Lago

Generalised parton distributions (GPDs) and transverse momentum dependent parton distributions (TMDs) describe complementary aspects of the three-dimensional structure of hadrons. We discuss their relation to each other and recall important…

High Energy Physics - Phenomenology · Physics 2016-06-22 Markus Diehl

Polynomial regression is a basic primitive in learning and statistics. In its most basic form the goal is to fit a degree $d$ polynomial to a response variable $y$ in terms of an $n$-dimensional input vector $x$. This is extremely…

Data Structures and Algorithms · Computer Science 2020-04-30 Sitan Chen , Raghu Meka

A key property of an algebraic variety is whether it is absolutely irreducible, meaning that it remains irreducible over the algebraic closure of its defining field, and determining absolute irreducibility is important in algebraic geometry…

Algebraic Geometry · Mathematics 2026-02-03 Carlos Agrinsoni , Heeralal Janwa , Moises Delgado

Differential properties for orthogonal polynomials in several variables are studied. We consider multivariate orthogonal polynomials whose gradients satisfy some quasi--orthogonality conditions. We obtain several characterizations for these…

Classical Analysis and ODEs · Mathematics 2007-05-23 M. Alvarez de Morales , L. Fernández , T. E. Pérez , M. A. Piñar

Generalized parton distributions (GPDs) are studied at the hadronic (nonperturbative) scale within different assumptions based on a relativistic constituent quark model. In particular, by means of a meson-cloud model we investigate the role…

High Energy Physics - Phenomenology · Physics 2009-11-11 S. Boffi , B. Pasquini , M. Traini

An analysis of high-dimensional data can offer a detailed description of a system but is often challenged by the curse of dimensionality. General dimensionality reduction techniques can alleviate such difficulty by extracting a few…

Methodology · Statistics 2021-09-28 Di Bo , Hoon Hwangbo , Vinit Sharma , Corey Arndt , Stephanie C. TerMaath

We derive a closed-form expression for the orthogonal polynomials associated with the general lognormal density. The result can be utilized to construct easily computable approximations for probability density function of a product of…

Information Theory · Computer Science 2016-11-17 Zhong Zheng , Lu Wei , Jyri Hämäläinen , Olav Tirkkonen

This paper presents a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduced-order models (ROMs) by embedding a high-dimensional system…

Numerical Analysis · Mathematics 2026-01-09 Jiaming Guo , Dunhui Xiao

This report presents a new, algorithmic approach to the distributions of the distance between two points distributed uniformly at random in various polygons, based on the extended Kinematic Measure (KM) from integral geometry. We first…

Computational Geometry · Computer Science 2016-02-11 Fei Tong , Jianping Pan

The task of approximating a function of d variables from its evaluations at a given number of points is ubiquitous in numerical analysis and engineering applications. When d is large, this task is challenged by the so-called curse of…

Numerical Analysis · Mathematics 2016-12-21 Albert Cohen , Giovanni Migliorati

In this work we develop arbitrary-order Discontinuous Skeletal Gradient Discretisations (DSGD) on general polytopal meshes. Discontinuous Skeletal refers to the fact that the globally coupled unknowns are broken polynomial on the mesh…

Numerical Analysis · Mathematics 2018-10-09 Daniele A. Di Pietro , Jérôme Droniou , Gianmarco Manzini

By using a generalization of Sturm-Liouville problems in discrete spaces, a basic class of symmetric orthogonal polynomials of a discrete variable with four free parameters, which generalizes all classical discrete symmetric orthogonal…

Classical Analysis and ODEs · Mathematics 2012-10-12 Mohammad Masjed-Jamei , Iván Area

The aim of the paper is twofold. Firstly, by using the constant rank level set theorem from differential geometry, we establish sharp upper bounds for the dimensions of the solution sets of polynomial variational inequalities under mild…

Optimization and Control · Mathematics 2020-01-28 Vu Trung Hieu

This paper introduces general methodologies for constructing closed-form solutions to linear constant-coefficient partial differential equations (PDEs) with polynomial right-hand sides in two and three spatial dimensions. Polynomial…

Numerical Analysis · Mathematics 2023-12-21 Thomas G. Anderson , Marc Bonnet , Luiz M. Faria , Carlos Pérez-Arancibia