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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…

We show in this paper that third- and fourth-order low storage Runge-Kutta algorithms can be built specifically for quadratic nonlinear operators, at the expense of roughly doubling the time needed for evaluating the temporal derivatives.…

Fluid Dynamics · Physics 2008-08-14 Marc E. Brachet , Pablo D. Mininni , Duane L. Rosenberg , Annick Pouquet

We provide a note on continuous-stage Runge-Kutta methods (csRK) for solving initial value problems of first-order ordinary differential equations. Such methods, as an interesting and creative extension of traditional Runge-Kutta (RK)…

Numerical Analysis · Mathematics 2018-05-28 Wensheng Tang

In this paper, we apply the Paired-Explicit Runge-Kutta (P-ERK) schemes by Vermeire et. al. (2019, 2022) to dynamically partitioned systems arising from adaptive mesh refinement. The P-ERK schemes enable multirate time-integration with no…

Numerical Analysis · Mathematics 2024-07-09 Daniel Doehring , Michael Schlottke-Lakemper , Gregor J. Gassner , Manuel Torrilhon

We develop continuous-stage Runge-Kutta methods based on weighted orthogonal polynomials in this paper. There are two main highlighted merits for developing such methods: Firstly, we do not need to study the tedious solution of…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

This work focuses on the numerical study of a recently published class of Runge-Kutta methods designed for mixed-precision arithmetic. We employ the methods in solving partial differential equations on modern hardware. In particular we…

Numerical Analysis · Mathematics 2024-12-24 Ivo Dravins , Marcel Koch , Victoria Griehl , Katharina Kormann

In this paper a new Runge-Kutta type scheme is introduced for nonlinear stochastic partial differential equations (SPDEs) with multiplicative trace class noise. The proposed scheme converges with respect to the computational effort with a…

Numerical Analysis · Mathematics 2012-04-03 Xiaojie Wang , Siqing Gan

Motivated by studies on fully discrete numerical schemes for linear hyperbolic conservation laws, we present a framework on analyzing the strong stability of explicit Runge-Kutta (RK) time discretizations for semi-negative autonomous linear…

Numerical Analysis · Mathematics 2018-11-28 Zheng Sun , Chi-Wang Shu

Exponential Runge--Kutta methods have shown to be competitive for the time integration of stiff semilinear parabolic PDEs. The current construction of stiffly accurate exponential Runge--Kutta methods, however, relies on a convergence…

Numerical Analysis · Mathematics 2020-09-29 Vu Thai Luan

This work introduces a new class of Runge-Kutta methods for solving nonlinearly partitioned initial value problems. These new methods, named nonlinearly partitioned Runge-Kutta (NPRK), generalize existing additive and component-partitioned…

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

One can elucidate integrability properties of ordinary differential equations (ODEs) by knowing the existence of second integrals (also known as weak integrals or Darboux polynomials for polynomial ODEs). However, little is known about how…

Numerical Analysis · Mathematics 2021-05-25 Benjamin K Tapley

Variational space-time formulations for Partial Differential Equations have been of great interest in the last decades. While it is known that implicit time marching schemes have variational structure, the Galerkin formulation of explicit…

Numerical Analysis · Mathematics 2018-06-21 Judit Muñoz-Matute , David Pardo , Victor M. Calo , Elisabete Alberdi

Fully implicit Runge-Kutta (IRK) methods have many desirable accuracy and stability properties as time integration schemes, but high-order IRK methods are not commonly used in practice with large-scale numerical PDEs because of the…

Numerical Analysis · Mathematics 2021-10-07 Ben S. Southworth , Oliver Krzysik , Will Pazner

In this paper we derive and analyze the properties of explicit singly diagonal implicit Runge-Kutta (ESDIRK) integration methods. We discuss the principles for construction of Runge-Kutta methods with embedded methods of different order for…

Numerical Analysis · Mathematics 2018-03-06 John Bagterp Jørgensen , Morten Rode Kristensen , Per Grove Thomsen

Mixed precision Runge--Kutta methods have been recently developed and used for the time-evolution of partial differential equations. Two-derivative Runge--Kutta schemes may offer enhanced stability and accuracy properties compared to…

Numerical Analysis · Mathematics 2026-02-17 Sigal Gottlieb , Zachary J. Grant , Cesar Herrera

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

In this work we present a new class of Runge-Kutta (RK) methods for solving systems of hyperbolic equations with a particular structure, generalization of a wave-equation. The new methods are {\it partially implicit} in the sense that a…

Mathematical Physics · Physics 2016-11-10 Isabel Cordero-Carrión , Pablo Cerdá-Durán

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

High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The…

Numerical Analysis · Mathematics 2014-03-27 Sigal Gottlieb , Zachary J. Grant , Daniel Higgs

We present a computational framework for obtaining multidimensional phase-space solutions of systems of non-linear coupled differential equations, using high-order implicit Runge-Kutta Physics- Informed Neural Networks (IRK-PINNs) schemes.…

Machine Learning · Computer Science 2024-09-26 Álvaro Fernández Corral , Nicolás Mendoza , Armin Iske , Andrey Yachmenev , Jochen Küpper