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This paper investigates the competitiveness of semi-implicit Runge-Kutta (RK) and spectral deferred correction (SDC) time-integration methods up to order six for incompressible Navier-Stokes problems in conjunction with a high-order…

Numerical Analysis · Mathematics 2022-10-03 Montadhar Guesmi , Martina Grotteschi , Jörg Stiller

In this paper, we propose Galerkin-Legendre spectral method with implicit Runge-Kutta method for solving the unsteady two-dimensional Schrodinger equation with nonhomogeneous Dirichlet boundary conditions and initial condition. We apply a…

Numerical Analysis · Mathematics 2018-11-12 Wenjie Liu , Boying Wu

The paper establishes the strong convergence rates of a spatio-temporal full discretization of the stochastic wave equation with nonlinear damping in dimension one and two. We discretize the SPDE by applying a spectral Galerkin method in…

Numerical Analysis · Mathematics 2024-12-30 Meng Cai , David Cohen , Xiaojie Wang

We present a collection of algorithms which utilize dimensional reduction to perform mesh refinement and study possibly singular solutions of time-dependent partial differential equations. The algorithms are inspired by constructions used…

Numerical Analysis · Mathematics 2007-06-21 Panagiotis Stinis

In this paper, we propose a numerical method to approximate the solution of the time-dependent Schr\"odinger equation with periodic boundary condition in a high-dimensional setting. We discretize space by using the Fourier pseudo-spectral…

Numerical Analysis · Mathematics 2019-05-20 Yuya Suzuki , Dirk Nuyens

A novel class of high-order linearly implicit energy-preserving integrating factor Runge-Kutta methods are proposed for the nonlinear Schr\"odinger equation. Based on the idea of the scalar auxiliary variable approach, the original equation…

Numerical Analysis · Mathematics 2021-12-07 Chaolong Jiang , Jin Cui , Xu Qian , Songhe Song

The context of this work is the development of first order total variation diminishing (TVD) implicit-explicit (IMEX) Runge-Kutta (RK) schemes as a basis of a Multidimensional Optimal Order detection (MOOD) approach to approximate the…

Numerical Analysis · Mathematics 2025-01-08 Victor Michel-Dansac , Andrea Thomann

This work proposes an efficient space-time two-grid compact difference (ST-TGCD) scheme for solving the two-dimensional (2D) viscous Burgers' equation subject to initial and periodic boundary conditions. The proposed approach combines a…

Numerical Analysis · Mathematics 2025-10-20 Xiangyi Peng , Lisen Ding , Wenlin Qiu

In this paper, we present a novel strategy to systematically construct linearly implicit energy-preserving schemes with arbitrary order of accuracy for Hamiltonian PDEs. Such novel strategy is based on the newly developed exponential scalar…

Numerical Analysis · Mathematics 2023-07-27 Yonghui Bo , Yushun Wang , Wenjun Cai

We present a methodology to construct efficient high-order in time accurate numerical schemes for a class of gradient flows with appropriate Lipschitz continuous nonlinearity. There are several ingredients to the strategy: the exponential…

Numerical Analysis · Mathematics 2021-02-23 Wenbin Chen , Shufen Wang , Xiaoming Wang

High order strong stability preserving (SSP) time discretizations are advantageous for use with spatial discretizations with nonlinear stability properties for the solution of hyperbolic PDEs. The search for high order strong stability…

Numerical Analysis · Mathematics 2016-03-24 Andrew J. Christieb , Sigal Gottlieb , Zachary J. Grant , David C. Seal

In this article we present a novel and general methodology for building second order finite volume implicit-explicit (IMEX) numerical schemes for solving two dimensional financial parabolic PDEs with mixed derivatives. In particular,…

The Trotter-Suzuki approximation leads to an efficient algorithm for solving the time-dependent Schr\"odinger equation. Using existing highly optimized CPU and GPU kernels, we developed a distributed version of the algorithm that runs…

Computational Physics · Physics 2013-03-06 Peter Wittek , Fernando M. Cucchietti

Deep generative models based on neural differential equations have quickly become the state-of-the-art for numerous generation tasks across many different applications. These models rely on ODE/SDE solvers which integrate from a prior…

Machine Learning · Computer Science 2026-02-20 Zander W. Blasingame , Chen Liu

Irksome is a library based on the Unified Form Language (UFL) that automates the application of Runge-Kutta time-stepping methods for finite element spatial discretizations of partial differential equations (PDEs). This paper describes…

Numerical Analysis · Mathematics 2025-08-29 Robert C. Kirby , Scott P. MacLachlan , Pablo D. Brubeck

The accurate description of the non-linear response of many-electron systems to strong-laser fields remains a major challenge. Methods that bypass the unfavorable exponential scaling with particle number are required to address larger…

We develop two new sets of stable, rank-adaptive Dynamically Orthogonal Runge-Kutta (DORK) schemes that capture the high-order curvature of the nonlinear low-rank manifold. The DORK schemes asymptotically approximate the truncated singular…

Numerical Analysis · Mathematics 2023-08-08 Aaron Charous , Pierre F. J. Lermusiaux

We approximate the solution for the time dependent Schr\"odinger equation (TDSE) in two steps. We first use a pseudo-spectral collocation method that uses samples of functions on rank-1 or rank-r lattice points with unitary Fourier…

Numerical Analysis · Mathematics 2020-07-01 Yuya Suzuki , Gowri Suryanarayana , Dirk Nuyens

ADER (Arbitrary DERivative in space and time) methods for the time-evolution of hyperbolic conservation laws have recently generated a fair bit of interest. The ADER time update can be carried out in a single step, which is desirable in…

Computational Physics · Physics 2010-06-23 Dinshaw S. Balsara , Chad Meyer , Michael Dumbser , Huijing Du , Zhiliang Xu

We introduce a new class of multilevel, adaptive, dual-space methods for computing fast convolutional transforms. These methods can be applied to a broad class of kernels, from the Green's functions for classical partial differential…

Numerical Analysis · Mathematics 2023-09-12 Shidong Jiang , Leslie Greengard