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This paper is devoted to examining the stability of Runge-Kutta methods for solving nonlinear Volterra delay-integro-differential-algebraic equations (DIDAEs) with constant delay. Hybrid numerical schemes combining Runge-Kutta methods and…

Numerical Analysis · Mathematics 2025-08-19 Gehao Wang , Yuexin Yu

We establish essentially optimal bounds on the complexity of initial-value problems in the randomized and quantum settings. For this purpose we define a sequence of new algorithms whose error/cost properties improve from step to step. These…

Quantum Physics · Physics 2007-05-23 Boleslaw Kacewicz

We propose a new probabilistic scheme which combines deep learning techniques with high order schemes for backward stochastic differential equations belonging to the class of Runge-Kutta methods to solve high-dimensional semi-linear…

Numerical Analysis · Mathematics 2023-01-02 Jean-François Chassagneux , Junchao Chen , Noufel Frikha

The main objective of this series of papers is to explore the entire landscape of numerical methods for fast nonlinear Fourier transformation (NFT) within the class of integrators known as the exponential integrators. In this paper, we…

Numerical Analysis · Mathematics 2018-12-13 Vishal Vaibhav

This study introduces the reader to the theory of approximating the solution(s) of a non-linear, second order, ordinary differential equation (ODE) with piecewise polynomial functions by using the collocation method. It then focuses on the…

Numerical Analysis · Mathematics 2018-05-09 J Hamish M Darbyshire

We consider quadrature formulas of high order in time based on Radau-type, L-stable implicit Runge-Kutta schemes to solve time dependent stiff PDEs. Instead of solving a large nonlinear system of equations, we develop a method that performs…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Matthew Emmett

The Nystr\"om method is a popular low-rank approximation technique for large matrices that arise in kernel methods and convex optimization. Yet, when the data exhibits heavy-tailed spectral decay, the effective dimension of the problem…

Data Structures and Algorithms · Computer Science 2025-07-22 Sachin Garg , Michał Dereziński

A new format for commutator-free Lie group methods is proposed based on explicit classical Runge-Kutta schemes. In this format exponentials are reused at every stage and the storage is required only for two quantities: the right hand side…

Numerical Analysis · Mathematics 2025-06-12 Alexei Bazavov

The nonlinear gyrokinetic equations describe plasma turbulence in laboratory and astrophysical plasmas. To solve these equations, massively parallel codes have been developed and run on present-day supercomputers. This paper describes…

Computational Physics · Physics 2014-03-31 H. Doerk , F. Jenko

Rational methods are intended to time integrate linear homogeneous problems. However, their scope can be extended so as to cover linear nonhomogeneous problems. In this paper the integration of semilinear problems is considered. The…

Numerical Analysis · Mathematics 2025-09-23 Carlos Arranz-Simón , Begoña Cano , César Palencia

In this paper, a family of arbitrarily high-order structure-preserving exponential Runge-Kutta methods are developed for the nonlinear Schr\"odinger equation by combining the scalar auxiliary variable approach with the exponential…

Numerical Analysis · Mathematics 2020-09-15 Jin Cui , Zhuangzhi Xu , Yushun Wang , Chaolong Jiang

Multirate integration is an increasingly relevant tool that enables scientists to simulate multiphysics systems. Existing multirate methods are designed for equations whose fast and slow variables can be linearly separated using additive or…

Numerical Analysis · Mathematics 2025-04-07 Tommaso Buvoli , Brian K. Tran , Ben S. Southworth

We show that existing Runge-Kutta methods for ordinary differential equations (odes) can be modified to solve stochastic differential equations (sdes) with strong solutions provided that appropriate changes are made to the way stepsizes are…

Quantum Physics · Physics 2007-09-30 Joshua Wilkie , Murat Cetinbas

A methodology that can generate the optimal coefficients of a numerical method with the use of an artificial neural network is presented in this work. The network can be designed to produce a finite difference algorithm that solves a…

Neural and Evolutionary Computing · Computer Science 2013-09-20 Angelos A. Anastassi

Recently, the class of Runge-Kutta type methods named Fractional HBVMs (FHBVMs) has been introduced for the numerical solution of initial value problems of fractional differential equations, and a corresponding Matlab software has been…

Numerical Analysis · Mathematics 2025-07-29 Luigi Brugnano , Gianmarco Gurioli , Felice Iavernaro , Mikk Vikerpuur

Extended Stability Runge-Kutta (ESRK) methods are crucial for solving large-scale computational problems in science and engineering, including weather forecasting, aerodynamic analysis, and complex biological modelling. However, balancing…

Machine Learning · Computer Science 2025-06-27 Gavin Lee Goodship , Luis Miralles-Pechuan , Stephen O'Sullivan

The object of the present paper is to extend the third-order iterative method for solving nonlinear equations into systems of nonlinear equations. Since our motive is to develop the method which improve the order of convergence of Newton's…

Numerical Analysis · Mathematics 2013-09-24 Anuradha Singh , J. P. Jaiswa

Recently, the efficient numerical solution of Hamiltonian problems has been tackled by defining the class of energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs). Their derivation relies on the expansion of…

Numerical Analysis · Mathematics 2023-01-16 Pierluigi Amodio , Luigi Brugnano , Felice Iavernaro

We show how the error term for the Trapezium Rule can be estimated, by solving an initial value problem using a Runge-Kutta method. The error term can then be added to the Trapezium approximation, yielding a much more accurate result. We…

Numerical Analysis · Mathematics 2023-06-13 J. S. C. Prentice

It is well known that symplectic Runge-Kutta and Partitioned Runge-Kutta methods exactly preserve {\em quadratic} first integrals (invariants of motion) of the system being integrated. While this property is often seen as a mere curiosity…

Numerical Analysis · Mathematics 2015-06-22 J. M. Sanz-Serna