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For reaction-diffusion equations in irregular domain with moving boundaries, the numerical stability constraints from the reaction and diffusion terms often require very restricted time step size, while complex geometries may lead to…

Numerical Analysis · Mathematics 2022-10-03 Shuang Liu , Xinfeng Liu

Simulation-based techniques such as variants of stochastic Runge-Kutta are the de facto approach for inference with stochastic differential equations (SDEs) in machine learning. These methods are general-purpose and used with parametric and…

Machine Learning · Computer Science 2021-11-01 Arno Solin , Ella Tamir , Prakhar Verma

Low-storage explicit Runge-Kutta schemes are particularly popular for the numerical integration of time-dependent partial differential equations based on the method-of-lines due to their efficiency and their reduced memory requirements. We…

Numerical Analysis · Mathematics 2026-04-07 Sergio Blanes , Alejandro Escorihuela-Tomàs

This work aims to construct an efficient and highly accurate numerical method to address the time singularity at $t=0$ involved in a class of time-fractional parabolic integro-partial differential equations in one and two dimensions. The…

Numerical Analysis · Mathematics 2024-09-27 Sudarshan Santra , Ratikanta Behera

This paper develops three high-order accurate discontinuous Galerkin (DG) methods for the one-dimensional (1D) and two-dimensional (2D) nonlinear Dirac (NLD) equations with a general scalar self-interaction. They are the Runge-Kutta DG…

Numerical Analysis · Mathematics 2020-11-03 Shu-Cun Li , Huazhong Tang

Systems of reaction-diffusion partial differential equations (RD-PDEs) are widely applied for modelling life science and physico-chemical phenomena. In particular, the coupling between diffusion and nonlinear kinetics can lead to the…

Numerical Analysis · Mathematics 2019-03-13 Maria Chiara D'Autilia , Ivonne Sgura , Valeria Simoncini

We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient…

Numerical Analysis · Mathematics 2014-01-09 David I. Ketcheson , Colin B. Macdonald , Steven J. Ruuth

We introduce a new class of arbitrary-order exponential time differencing methods based on spectral deferred correction (ETDSDC) and describe a simple procedure for initializing the requisite matrix functions. We compare the stability and…

Numerical Analysis · Mathematics 2020-11-03 Tommaso Buvoli

The purpose of this work is to describe in detail the development of the Spectral Difference Raviart-Thomas (SDRT) formulation for two and three-dimensional tensor-product elements and simplexes. Through the process, the authors establish…

Numerical Analysis · Mathematics 2021-05-19 Gonzalo Sáez-Mischlich , Javier Sierra-Ausín , Jérémie Gressier

The goal of this paper is to develop 2nd order Implicit-Explicit Runge-Kutta (IMEX-RK) finite volume (FV) schemes for solving 1d parabolic PDEs for option pricing, with possible nonlinearities in the source and advection terms. The spatial…

We explore a novel way to numerically resolve the scaling behavior of finite-time singularities in solutions of nonlinear parabolic PDEs. The Runge--Kutta--Legendre (RKL) and Runge--Kutta--Gegenbauer (RKG) super-time-stepping methods were…

Numerical Analysis · Mathematics 2025-09-24 Zheng Tan , Tariq D. Aslam , Andrea L. Bertozzi

This article is devoted to the construction of a new class of semi-Lagrangian (SL) schemes with implicit-explicit (IMEX) Runge-Kutta (RK) time stepping for PDEs involving multiple space-time scales. The semi-Lagrangian (SL) approach fully…

Numerical Analysis · Mathematics 2021-07-16 Walter Boscheri , Maurizio Tavelli , Lorenzo Pareschi

In this work, we develop a class of up to third-order energy-stable schemes for the Cahn--Hilliard equation. Building on Lawson's integrating factor Runge--Kutta method, which is widely used for stiff semilinear equations, we discuss its…

Numerical Analysis · Mathematics 2024-11-26 Haifeng Wang , Jingwei Sun , Hong Zhang , Xu Qian , Songhe Song

In this paper, we extend the Paired-Explicit Runge-Kutta schemes by Vermeire et. al. to fourth-order of consistency. Based on the order conditions for partitioned Runge-Kutta methods we motivate a specific form of the Butcher arrays which…

As a universal quantum mechanical approach to the dynamical many-body problem, the time-dependent density functional theory (TDDFT) might be inadequate to describe crucial observables that rely on two-body evolution behavior, like the…

Computational Physics · Physics 2025-11-17 Jiong-Hang Liang , Yunfeng Xiong

The application of Runge-Kutta schemes designed to enjoy a large region of absolute stability can significantly increase the efficiency of numerical methods for PDEs based on a method of lines approach. In this work we investigate the…

Numerical Analysis · Mathematics 2007-05-23 Fausto Cavalli , Giovanni Naldi , Gabriella Puppo , Matteo Semplice

This paper introduces a novel framework for the solution of (large-scale) Lyapunov and Sylvester equations derived from numerical integration methods. Suitable systems of ordinary differential equations are introduced. Low-rank…

Numerical Analysis · Mathematics 2021-04-13 Christian Bertram , Heike Faßbender

We present a class of high-order Eulerian-Lagrangian Runge-Kutta finite volume methods that can numerically solve Burgers' equation with shock formations, which could be extended to general scalar conservation laws. Eulerian-Lagrangian (EL)…

Numerical Analysis · Mathematics 2024-05-31 Jiajie Chen , Joseph Nakao , Jing-Mei Qiu , Yang Yang

Emerging tensor network techniques for solutions of Partial Differential Equations (PDEs), known for their ability to break the curse of dimensionality, deliver new mathematical methods for ultrafast numerical solutions of high-dimensional…

Numerical Analysis · Mathematics 2024-02-29 Dibyendu Adak , Duc P. Truong , Gianmarco Manzini , Kim Ø. Rasmussen , Boian S. Alexandrov

In this paper, Runge-Kutta-Gegenbauer (RKG) stability polynomials of arbitrarily high order of accuracy are introduced in closed form. The stability domain of RKG polynomials extends in the the real direction with the square of polynomial…

Numerical Analysis · Mathematics 2019-04-22 Stephen O'Sullivan