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This study computes the gradient of a function of numerical solutions of ordinary differential equations (ODEs) with respect to the initial condition. The adjoint method computes the gradient approximately by solving the corresponding…

Numerical Analysis · Mathematics 2020-04-07 Takeru Matsuda , Yuto Miyatake

We propose a unified theoretical framework to examine the energy dissipation properties at all stages of explicit exponential Runge-Kutta (EERK) methods for gradient flow problems. The main part of the novel framework is to construct the…

Numerical Analysis · Mathematics 2024-10-10 Hong-lin Liao , Xuping Wang

The reliability and precision of numerically solving stochastic non-Markovian equations by standard numerical codes, more specifically, with the fourth-order Runge-Kutta routine for solving differential equations, is gauged by comparing the…

Statistical Mechanics · Physics 2009-12-23 R. L. S. Farias , Rudnei O. Ramos , L. A. da Silva

We consider the construction of semi-implicit linear multistep methods which can be applied to time dependent PDEs where the separation of scales in additive form, typically used in implicit-explicit (IMEX) methods, is not possible. As…

Numerical Analysis · Mathematics 2020-01-14 Giacomo Albi , Lorenzo Pareschi

When one wishes to numerically solve an initial value problem, it is customary to rewrite it as an equivalent first-order system to which a method, usually from the class of Runge-Kutta methods, is applied. Directly treating higher-order…

Numerical Analysis · Mathematics 2026-02-25 Loris Petronijevic

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

Stochastic variational integrators for constrained, stochastic mechanical systems are developed in this paper. The main results of the paper are twofold: an equivalence is established between a stochastic Hamilton-Pontryagin (HP) principle…

Numerical Analysis · Mathematics 2007-09-23 Nawaf Bou-Rabee , Houman Owhadi

When evolving in time the solution of a hyperbolic partial differential equation, it is often desirable to use high order strong stability preserving (SSP) time discretizations. These time discretizations preserve the monotonicity…

Numerical Analysis · Mathematics 2017-08-02 Sidafa Conde , Sigal Gottlieb , Zachary J. Grant , John N. Shadid

This paper extends the high-order entropy stable (ES) adaptive moving mesh finite difference schemes developed in [14] to the two- and three-dimensional (multi-component) compressible Euler equations with the stiffened equation of state.…

Numerical Analysis · Mathematics 2022-08-10 Shangting Li , Junming Duan , Huazhong Tang

Traditional time discretization methods use a single timestep for the entire system of interest and can perform poorly when the dynamics of the system exhibits a wide range of time scales. Multirate infinitesimal step (MIS) methods (Knoth…

Numerical Analysis · Mathematics 2022-02-03 Steven Roberts , Arash Sarshar , Adrian Sandu

We propose quantum methods for solving differential equations that are based on a gradual improvement of the solution via an iterative process, and are targeted at applications in fluid dynamics. First, we implement the Jacobi iteration on…

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

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

A wide range of physical phenomena exhibit auxiliary admissibility criteria, such as conservation of entropy or various energies, which arise implicitly under the exact solution of their governing PDEs. However, standard temporal schemes,…

Numerical Analysis · Mathematics 2024-01-29 Mohammad R. Najafian , Brian C. Vermeire

In this paper, a recently published method [Hussain, Ismail, Senua, Solving directly special fourth-order ordinary differential equations using Runge-Kutta type method, J. Comput. Appl. Math. 306 (2016) 179-199] for solving fourth-order…

Numerical Analysis · Mathematics 2016-11-01 Maciej Jaromin

Applied to the master equation, the usual numerical integration methods, such as Runge-Kutta, become inefficient when the rates associated with various transitions differ by several orders of magnitude. We introduce an integration scheme…

Statistical Mechanics · Physics 2009-11-07 Ronald Dickman

The non-differentiability of the singular nonlinearity (such as $f=\ln|u|^2$) at $u=0$ presents significant challenges in devising accurate and efficient numerical schemes for the logarithmic Schr\"{o}dinger equation (LogSE). To address…

Numerical Analysis · Mathematics 2024-11-14 Jingye Yan , Hong Zhang , Yabing Wei , Xu Qian

In this paper we generalize the polynomial time integration framework to additively partitioned initial value problems. The framework we present is general and enables the construction of many new families of additive integrators with…

Numerical Analysis · Mathematics 2023-01-02 Tommaso Buvoli , Ben S. Southworth

We introduce a second-order time discretization method for stiff kinetic equations. The method is asymptotic-preserving (AP) -- can capture the Euler limit without numerically resolving the small Knudsen number; and positivity-preserving --…

Numerical Analysis · Mathematics 2018-12-17 Jingwei Hu , Ruiwen Shu

Problems that feature significantly different time scales, where the stiff time-step restriction comes from a linear component, implicit-explicit (IMEX) methods alleviate this restriction if the concern is linear stability. However, where…

Numerical Analysis · Mathematics 2019-04-16 Leah Isherwood , Zachary J. Grant , Sigal Gottlieb