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Related papers: Approximation theorems for Pascali systems

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Let $G_1, G_2 $ be domains in ${\mathbb R}^{n+1}$, $n \geq 2$, such that $G_1 \subset G_2$ and the domain $G_1$ have rather regular boundary. We investigate the problem of approximation of solutions to strongly uniformly $2m$-parabolic…

Analysis of PDEs · Mathematics 2024-10-15 P. Yu. Vilkov , A. A. Shlapunov

In this paper we discuss a framework for the polynomial approximation to the solution of initial value problems for differential equations. The framework, initially devised for the approximation of ordinary differential equations, is…

Numerical Analysis · Mathematics 2022-11-15 Luigi Brugnano , Gianluca Frasca-Caccia , Felice Iavernaro , Vincenzo Vespri

This paper presents an algorithm to simulate Gaussian random vectors whose precision matrix can be expressed as a polynomial of a sparse matrix. This situation arises in particular when simulating Gaussian Markov random fields obtained by…

Methodology · Statistics 2020-04-07 Mike Pereira , Nicolas Desassis

This paper offers a newly created integral approach for operators employing the orthogonal modified Laguerre polynomials and P\u{a}lt\u{a}nea basis. These operators approximate the functions over the interval $[0,\infty)$. Further, the…

Functional Analysis · Mathematics 2024-05-14 Kapil Kumar , Naokant Deo , Durvesh Kumar Verma

This paper develops a new direct approach to approximating suprema of general empirical processes by a sequence of suprema of Gaussian processes, without taking the route of approximating whole empirical processes in the sup-norm. We prove…

Probability · Mathematics 2014-08-19 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

In this note we study a quantitative version of Bernstein's approximation problem when the polynomials are dense in weighted spaces on the real line completing a result of S.~N.~Mergelyan (1960). We estimate in the logarithmic scale the…

Classical Analysis and ODEs · Mathematics 2022-11-28 Anna Kononova

We review the theory of optimal polynomial and rational Chebyshev approximations, and Zolotarev's formula for the sign function over the range (\epsilon \leq |z| \leq1). We explain how rational approximations can be applied to large sparse…

High Energy Physics - Lattice · Physics 2009-11-10 A. D. Kennedy

We develop a general convergence theory for adaptive discontinuous Galerkin methods for elliptic PDEs covering the popular SIPG, NIPG and LDG schemes as well as all practically relevant marking strategies. Another key feature of the…

Numerical Analysis · Mathematics 2020-09-07 Christian Kreuzer , Emmanuil H. Georgoulis

We prove a fundamental theorem for tropical partial differential equations, analogous to the fundamental theorem of tropical geometry in this context. We extend results from Aroca et al., Falkensteiner et al. and from Fink and Toghani for…

Algebraic Geometry · Mathematics 2026-04-17 Francesco Gallinaro , Stefano Mereta

We introduce a general framework for studying special subsets of rational points on an algebraic variety, termed $\mathcal{M}$-points. The notion of $\mathcal{M}$-points generalizes the concepts of integral points, Campana points and Darmon…

Algebraic Geometry · Mathematics 2024-09-12 Boaz Moerman

A Vitali-type theorem for vector lattice-valued modulars with respect to filter convergence is proved. Some applications are given to modular convergence theorems for moment operatorsin the vector lattice setting, and also for the Brownian…

Functional Analysis · Mathematics 2015-07-24 Antonio Boccuto , Domenico Candeloro , Anna Rita Sambucini

The generalized Langrangian mean theory provides exact equations for general wave-turbulence-mean flow interactions in three dimensions. For practical applications, these equations must be closed by specifying the wave forcing terms. Here…

Atmospheric and Oceanic Physics · Physics 2009-11-13 Fabrice Ardhuin , Nicolas Rascle , Kostas Belibassakis

We use the Stein-Chen method to prove new explicit inequalities for the total variation, Wasserstein and local distances between the distribution of a random diagonal sum of a Bernoulli matrix and a Poisson distribution. Approximation…

Probability · Mathematics 2024-09-04 Bero Roos

We combine the method of exchangeable pairs with Stein's method for functional approximation. As a result, we give a general linearity condition under which an abstract Gaussian approximation theorem for stochastic processes holds. We apply…

Probability · Mathematics 2020-10-22 Mikolaj J. Kasprzak

In this paper we survey the theory of holomorphic approximation, from the classical 19th century results of Runge and Weierstrass, continuing with the 20th century work of Oka and Weil, Mergelyan, Vitushkin and others, to the most recent…

Complex Variables · Mathematics 2020-06-16 John Erik Fornaess , Franc Forstneric , Erlend Fornaess Wold

In this paper we prove a version of Lie-B\"acklund theorem for overdetermined systems of scalar PDEs, whose general solution depends on 1 function of 1 variable. This generalizes the case of involutive system of the second order on the…

Differential Geometry · Mathematics 2013-05-31 Boris Kruglikov

We establish Marstrand-type as well as Besicovich-Federer-type projection theorems for closest-point projections onto hyperplanes in the normed space $\mathbb{R}^{n}$. In particular, we prove that if a norm on $\mathbb{R}^{n}$ is…

Metric Geometry · Mathematics 2018-09-05 Annina Iseli

Some properties of generalized convexity for sets and for functions are identified in case of the reliability polynomials of two dual minimal networks. A method of approximating the reliability polynomials of two dual minimal network is…

Discrete Mathematics · Computer Science 2021-12-14 Gabriela Cristescu , Vlad-Florin Dragoi , Sorin-Horatiu Hoara

We present two algorithms for constructing orthonormal bases of rational function vectors with respect to a discrete inner product, and discuss how to use them for a rational approximation problem. Building on the pencil-based formulation…

Numerical Analysis · Mathematics 2026-01-21 Robbe Vermeiren

Mean-field models approximate large stochastic systems by simpler differential equations that are supposed to approximate the mean of the larger system. It is generally assumed that as the stochastic systems get larger (i.e., more people or…

Probability · Mathematics 2016-03-01 Benjamin Armbruster
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