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This paper is concerned with the asymptotic expansions of the amplitude of the solution of the Helmholtz equation. The original expansions were obtained using a pseudo-differential decomposition of the Dirichlet to Neumann operator. This…

Analysis of PDEs · Mathematics 2016-12-13 Souaad Lazergui , Yassine Boubendir

A recipe is presented for constructing band-limited superoscillating functions that exhibit arbitrarily high frequencies over arbitrarily long intervals.

Mathematical Physics · Physics 2019-07-02 Masud Mansuripur , Per K. Jakobsen

Runge-Kutta methods have an irreplaceable position among numerical methods designed to solve ordinary differential equations. Especially, implicit ones are suitable for approximating solutions of stiff initial value problems. We propose a…

Numerical Analysis · Mathematics 2024-12-13 Hana Mizerová , Katarína Tvrdá

A new method for the numerical solution of ODEs is presented. This approach is based on an approximate formulation of the Taylor methods that has a much easier implementation than the original Taylor methods, since only the functions in the…

Numerical Analysis · Mathematics 2025-01-30 Antonio Baeza , Sebastiano Boscarino , Pep Mulet , Giovanni Russo , David Zorío

We extend the ultraspherical spectral method to solving nonlinear ODE boundary value problems. We propose to use the inexact Newton-GMRES framework for which an effective preconditioner can be constructed and a fast Jacobian-vector…

Numerical Analysis · Mathematics 2023-07-03 Ouyuan Qin , Kuan Xu

In [11] and [5], an error estimate of optimal convergence rates and optimal error propagation (optimal^2) was given for the Runge-Kutta discontinuous Galerkin (RKDG) method solving the scalar nonlinear conservation laws in the case of…

Numerical Analysis · Mathematics 2013-12-10 Tong Sun , Adamou Fode

While quantum algorithms for solving large scale systems of linear equations offer potentially exponential speedups, their application has largely been confined to sparse matrices. This work extends the scope of these algorithms to a broad…

Quantum Physics · Physics 2026-02-27 Kun Tang , Jun Lai

Sampling with Markov chain Monte Carlo methods often amounts to discretizing some continuous-time dynamics with numerical integration. In this paper, we establish the convergence rate of sampling algorithms obtained by discretizing smooth…

Machine Learning · Statistics 2020-02-04 Xuechen Li , Denny Wu , Lester Mackey , Murat A. Erdogdu

Spectral data is routinely broadened in order to improve appearance, approximate a higher sampling level or model experimental measurement effects. While there has been extensive work in the signal processing field to develop efficient…

Materials Science · Physics 2023-09-22 Jessica Farmer , Adam J. Jackson

This paper introduces the Runge-Kutta Chebyshev descent method (RKCD) for strongly convex optimisation problems. This new algorithm is based on explicit stabilised integrators for stiff differential equations, a powerful class of numerical…

Optimization and Control · Mathematics 2020-06-30 Armin Eftekhari , Bart Vandereycken , Gilles Vilmart , Konstantinos C. Zygalakis

We design and analyse a new numerical method to solve ODE system based on the structural method. We compute approximations of solutions together with its derivatives up to order $K$ by solving an entire block corresponding to $R$ time…

Numerical Analysis · Mathematics 2025-08-05 S. Clain , M. T. Malheiro , G. J. Machado , R. Costa

We discuss the numerical solution of initial value problems for $\varepsilon^2\,\varphi''+a(x)\,\varphi=0$ in the highly oscillatory regime, i.e., with $a(x)>0$ and $0<\varepsilon\ll 1$. We analyze and implement an approximate solution…

Numerical Analysis · Mathematics 2024-11-08 Jannis Körner , Anton Arnold , Christian Klein , Jens Markus Melenk

This paper investigates the energy conservation properties of explicit Runge--Kutta (RK) time discretizations for autonomous skew-symmetric systems. For linear problems, we present a general framework for constructing RK methods in which…

Numerical Analysis · Mathematics 2026-05-12 Jinjie Liu , Moysey Brio

In [1] is proposed a simplified DeC method, that, when combined with the residual distribution (RD) framework, allows to construct a high order, explicit FE scheme with continuous approximation avoiding the inversion of the mass matrix for…

Numerical Analysis · Mathematics 2022-11-17 Rémi Abgrall , Elise Le Mélédo , Philipp Öffner , Davide Torlo

Algebraic Riccati equations with indefinite quadratic terms play an important role in applications related to robust controller design. While there are many established approaches to solve these in case of small-scale dense coefficients,…

Numerical Analysis · Mathematics 2023-01-13 Peter Benner , Jan Heiland , Steffen W. R. Werner

The parametric instability arising when ordinary differential equations (ODEs) are numerically integrated with Runge-Kutta-Nystr\"om (RKN) methods with varying step sizes is investigated. It is shown that when linear constant coefficient…

Numerical Analysis · Mathematics 2012-09-25 Robert Piché

ksmt is a CDCL-style calculus for solving non-linear constraints over real numbers involving polynomials and transcendental functions. In this paper we investigate properties of the ksmt calculus and show that it is a $\delta$-complete…

Logic in Computer Science · Computer Science 2021-04-28 Franz Brauße , Konstantin Korovin , Margarita V. Korovina , Norbert Th. Müller

In this paper we consider an approach to improve the performance of exponential Runge--Kutta integrators and Lawson schemes} in cases where the solution of a related, but usually much simpler, problem can be computed efficiently. While for…

Numerical Analysis · Mathematics 2023-10-20 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann

A wide range of numerical methods exists for computing polynomial approximations of solutions of ordinary differential equations based on Chebyshev series expansions or Chebyshev interpolation polynomials. We consider the application of…

Symbolic Computation · Computer Science 2014-07-11 Alexandre Benoit , Mioara Joldes , Marc Mezzarobba

Numerical simulation codes are very common tools to study complex phenomena, but they are often time-consuming and considered as black boxes. For some statistical studies (e.g. asset management, sensitivity analysis) or optimization…

Statistics Theory · Mathematics 2017-08-14 Vincent Moutoussamy , Simon Nanty , Benoît Pauwels