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A few novel radial basis function (RBF) discretization schemes for partial differential equations are developed in this study. For boundary-type methods, we derive the indirect and direct symmetric boundary knot methods. Based on the…

Numerical Analysis · Mathematics 2025-10-20 W. Chen

Spectral methods for solving partial differential equations (PDEs) and stochastic partial differential equations (SPDEs) often use Fourier or polynomial spectral expansions on either uniform and non-uniform grids. However, while very widely…

Numerical Analysis · Mathematics 2025-07-30 Channa Hatharasinghe , Run Yan Teh , Jesse van Rhijn , Peter D. Drummond , Margaret D. Reid

Computationally efficient numerical methods for high-order approximations of convolution integrals involving weakly singular kernels find many practical applications including those in the development of fast quadrature methods for…

Numerical Analysis · Mathematics 2018-10-10 Akash Anand , Awanish Kumar Tiwari

We show that a rectangular collocation method, equivalent to evaluating all matrix elements with a quadrature-like scheme and using more points than basis functions, is an effective approach for solving the electronic Schr\"odinger equation…

Computational Physics · Physics 2021-12-08 Sergei Manzhos , Tucker Carrington

High-dimensional Partial Differential Equations (PDEs) are a popular mathematical modelling tool, with applications ranging from finance to computational chemistry. However, standard numerical techniques for solving these PDEs are typically…

Numerical Analysis · Mathematics 2023-11-22 Weiqi Wang , Simone Brugiapaglia

Integration operational matrix methods based on Zernike polynomials are used to determine approximate solutions of a class of non-homogeneous partial differential equations (PDEs) of first and second order. Due to the nature of the Zernike…

Analysis of PDEs · Mathematics 2022-07-18 Kanti Bhushan Datta , Somantika Datta

In this letter we apply a method recently devised in \cite{aapla03} to find precise approximate solutions to a certain class of nonlinear differential equations. The analysis carried out in \cite{aapla03} is refined and results of much…

Mathematical Physics · Physics 2009-11-10 Paolo Amore , Hector Montes Lamas

In this paper we propose an algorithm for the numerical solution of arbitrary differential equations of fractional order. The algorithm is obtained by using the following decomposition of the differential equation into a system of…

Numerical Analysis · Mathematics 2025-10-20 Leszczynski Jacek , Ciesielski Mariusz

Identifying computational tasks suitable for (future) quantum computers is an active field of research. Here we explore utilizing quantum computers for the purpose of solving differential equations. We consider two approaches: (i) basis…

Quantum Physics · Physics 2021-07-14 Benjamin Zanger , Christian B. Mendl , Martin Schulz , Martin Schreiber

Differential equations are a powerful tool to tackle Feynman integrals. In this talk we discuss recent progress, where the method of differential equations has been applied to Feynman integrals which are not expressible in terms of multiple…

High Energy Physics - Phenomenology · Physics 2017-12-14 Luise Adams , Christian Bogner , Ekta Chaubey , Armin Schweitzer , Stefan Weinzierl

Results of research of possibility of transformation of a difference equation into a system of the first-order difference equation are presented. In contrast to the method used previously, an unknown grid function is split into two new…

General Mathematics · Mathematics 2017-03-29 M. I. Ayzatsky

A very simple and accurate numerical method which is applicable to systems of differentio-integral equations with quite general boundary conditions has been devised. Although the basic idea of this method stems from the Keller Box method,…

Fluid Dynamics · Physics 2014-09-30 Jian-Jun Shu , Graham Wilks

A general class of functionally-fitted explicit pseudo two-step Runge-Kutta-Nystr\"{o}m (FEPTRKN) methods for solving second-order initial value problems has been studied. These methods can be considered generalized explicit pseudo two-step…

Numerical Analysis · Mathematics 2014-10-17 N. S. Hoang

We develop continuous-stage Runge-Kutta-Nystr\"{o}m (csRKN) methods for solving second order ordinary differential equations (ODEs) in this paper. The second order ODEs are commonly encountered in various fields and some of them can be…

Numerical Analysis · Mathematics 2016-02-05 Wensheng Tang , Jingjing Zhang

In this paper, we introduce some analytical techniques to solve some classes of second order differential equations. Such classes of differential equations arise in describing some mathematical problems in Physics and Engineering.

Classical Analysis and ODEs · Mathematics 2017-06-08 Rami AlAhmad , Mohammadkheer Al-Jararha

We extend the piecewise orthogonal collocation method to computing periodic solutions of coupled renewal and delay differential equations. Through a rigorous error analysis, we prove convergence of the relevant finite-element method and…

Numerical Analysis · Mathematics 2023-05-23 Alessia andò , Dimitri Breda

We consider the application of implicit and linearly implicit (Rosenbrock-type) peer methods to matrix-valued ordinary differential equations. In particular the differential Riccati equation (DRE) is investigated. For the Rosenbrock-type…

Numerical Analysis · Mathematics 2018-07-26 Peter Benner , Norman Lang

This paper establishes and analyzes a second-order accurate numerical scheme for the nonlinear partial integrodifferential equation with a weakly singular kernel. In the time direction, we apply the Crank-Nicolson method for the time…

Numerical Analysis · Mathematics 2022-09-07 Wenlin Qiu , Xu Xiao , Kexin Li

This paper describes in detail the implementation of a finite element technique for solving the compressible Navier-Stokes equations that is provably robust and demonstrates excellent performance on modern computer hardware. The method is…

Numerical Analysis · Mathematics 2022-02-02 Jean-Luc Guermond , Martin Kronbichler , Matthias Maier , Bojan Popov , Ignacio Tomas

Policy gradient methods are a powerful family of reinforcement learning algorithms for continuous control that optimize a policy directly. However, standard first-order methods often converge slowly. Second-order methods can accelerate…

Systems and Control · Electrical Eng. & Systems 2025-11-05 Amirreza Valaei , Arash Bahari Kordabad , Sadegh Soudjani
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