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In this article, a family of two- and three-stage explicit multiquadric (MQ) and inverse multiquadric (IMQ) radial basis functions (RBFs) Runge-Kutta methods are introduced for solving ordinary differential equations. These methods are…

Numerical Analysis · Mathematics 2025-09-23 Shipra Mahata , Samala Rathan

Recent years have seen an increasing amount of research devoted to the development of so-called resonance-based methods for dispersive nonlinear partial differential equations. In many situations, this new class of methods allows for…

Numerical Analysis · Mathematics 2024-07-22 Georg Maierhofer , Katharina Schratz

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

We show that symplectic Runge-Kutta methods provide effective symplectic integrators for Hamiltonian systems with index one constraints. These include the Hamiltonian description of variational problems subject to position and velocity…

Numerical Analysis · Mathematics 2014-02-28 Robert I McLachlan , Klas Modin , Olivier Verdier , Matt Wilkins

In ordinary turbulence research it has been a long standing tradition to solve the equations in spectral space giving the best possible accuracy. This is indeed a natural choice for incompressible problems with periodic boundaries, but it…

Astrophysics · Physics 2009-11-07 A. Brandenburg , W. Dobler

We study the effect of global error control in the numerical solution of Hamiltonian systems. In particular, we apply the RKQ algorithm in the numerical solution of a Hamiltonian system. This algorithm is designed to provide stepwise…

Numerical Analysis · Mathematics 2011-12-01 J. S. C. Prentice

We develop a general framework for designing conservative numerical methods based on summation by parts operators and split forms in space, combined with relaxation Runge-Kutta methods in time. We apply this framework to create new classes…

Numerical Analysis · Mathematics 2021-03-09 Hendrik Ranocha , Dimitrios Mitsotakis , David I. Ketcheson

In this survey, we provide an in-depth investigation of exponential Runge-Kutta methods for the numerical integration of initial-value problems. These methods offer a valuable synthesis between classical Runge-Kutta methods, introduced more…

Numerical Analysis · Mathematics 2026-04-27 Alessia andò , Nicolò Cangiotti , Mattia Sensi

Many time-dependent differential equations are equipped with invariants. Preserving such invariants under discretization can be important, e.g., to improve the qualitative and quantitative properties of numerical solutions. Recently,…

Numerical Analysis · Mathematics 2023-11-27 Sebastian Bleecke , Hendrik Ranocha

Solutions of the Dirichlet and Robin boundary value problems for the multi-term variable-distributed order diffusion equation are studied. A priori estimates for the corresponding differential and difference problems are obtained by using…

Numerical Analysis · Mathematics 2014-01-31 A. A. Alikhanov

Cell collective migration plays a crucial role in a variety of physiological processes. In this work, we propose the Runge-Kutta random feature method to solve the nonlinear and strongly coupled multiphase flow problems of cells, in which…

Numerical Analysis · Mathematics 2024-12-10 Yangtao Deng , Qiaolin He

In this paper, we present a quadratic auxiliary variable approach to develop a new class of energy-preserving Runge-Kutta methods for the Korteweg-de Vries equation. The quadratic auxiliary variable approach is first proposed to reformulate…

Numerical Analysis · Mathematics 2021-10-29 Yue Chen , Yuezheng Gong , Qi Hong , Chuwu Wang

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 generalize the idea of relaxation time stepping methods in order to preserve multiple nonlinear conserved quantities of a dynamical system by projecting along directions defined by multiple time stepping algorithms. Similar to the…

Numerical Analysis · Mathematics 2023-02-13 Abhijit Biswas , David I. Ketcheson

We introduce a new class of Runge-Kutta type methods suitable for time stepping to propagate hyperbolic solutions within tent-shaped spacetime regions. Unlike standard Runge-Kutta methods, the new methods yield expected convergence…

Numerical Analysis · Mathematics 2020-02-28 Jay Gopalakrishnan , Joachim Schöberl , Christoph Wintersteiger

It is difficult to design high order numerical schemes which could preserve both the maximum bound property (MBP) and energy dissipation law for certain phase field equations. Strong stability preserving (SSP) Runge-Kutta methods have been…

Numerical Analysis · Mathematics 2022-03-10 Zhaohui Fu , Tao Tang , Jiang Yang

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

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

Explicit integrating factor Runge-Kutta methods are attractive and popular in developing high-order maximum bound principle preserving time-stepping schemes for Allen-Cahn type gradient flows. However, they always suffer from the…

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

A focus of recent research in quantum computing has been on developing quantum algorithms for differential equations solving using variational methods on near-term quantum devices. A promising approach involves variational algorithms, which…

Quantum Physics · Physics 2026-02-03 David Dechant , Liubov Markovich , Vedran Dunjko , Jordi Tura