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A convolutional neural network can be constructed using numerical methods for solving dynamical systems, since the forward pass of the network can be regarded as a trajectory of a dynamical system. However, existing models based on…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Mai Zhu , Bo Chang , Chong Fu

In this paper we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for…

Numerical Analysis · Mathematics 2014-01-31 Tomasz M. Tyranowski , Mathieu Desbrun

This work constructs a new class of multirate schemes based on the recently developed generalized additive Runge-Kutta (GARK) methods (Sandu and Guenther, 2013). Multirate schemes use different step sizes for different components and for…

Numerical Analysis · Computer Science 2013-10-24 Michael Guenther , Adrian Sandu

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 present a novel and general methodology for building second-order finite volume implicit-explicit Runge-Kutta numerical schemes for solving two-dimensional financial parabolic PDEs with mixed derivatives. The methods achieve second-order…

Recently, the efficient numerical solution of Hamiltonian problems has been tackled by defining the class of energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs). Their derivation relies on the expansion of…

Numerical Analysis · Mathematics 2023-01-16 Pierluigi Amodio , Luigi Brugnano , Felice Iavernaro

A semiclassical formula for the coherent-state propagator requires the determination of specific classical paths inhabiting a complex phase-space through a Hamiltonian flux. Such trajectories are constrained to special boundary conditions…

Quantum Physics · Physics 2017-02-01 A. L. Xavier

In this paper, we present a novel class of high-order Runge--Kutta (RK) discontinuous Galerkin (DG) schemes for hyperbolic conservation laws. The new method extends beyond the traditional method of lines framework and utilizes…

Numerical Analysis · Mathematics 2024-02-26 Qifan Chen , Zheng Sun , Yulong Xing

We consider the efficient numerical solution of coupled dynamical systems, consisting of a small nonlinear part and a large linear time invariant part, possibly stemming from spatial discretization of an underlying partial differential…

Numerical Analysis · Mathematics 2018-11-27 Herbert Egger , Vsevolod Shashkov , Kersten Schmidt

In this paper, we develop a new type of Runge--Kutta (RK) discontinuous Galerkin (DG) method for solving hyperbolic conservation laws. Compared with the original RKDG method, the new method features improved compactness and allows simple…

Numerical Analysis · Mathematics 2024-02-26 Qifan Chen , Zheng Sun , Yulong Xing

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

A family of explicit 15-stage Runge-Kutta methods of order 10 is derived.

Numerical Analysis · Mathematics 2025-12-22 Misha Stepanov

In this work we show how to get advantage from the Riemann--Hilbert analysis in order to obtain information about the matrix orthogonal polynomials and functions of second kind associated with a weight matrix. We deduce properties for the…

Classical Analysis and ODEs · Mathematics 2023-06-01 Amílcar Branquinho , Ana Foulquié-Moreno , Assil Fradi , Manuel Mañas

In this work, we introduce high-order Basis-Update & Galerkin (BUG) integrators based on explicit Runge-Kutta methods for large-scale matrix differential equations. These dynamical low-rank integrators extend the BUG integrator to arbitrary…

Numerical Analysis · Mathematics 2026-01-27 Fabio Nobile , Sébastien Riffaud

A semi-implicit-explicit (semi-IMEX) Runge-Kutta (RK) method is proposed for the numerical integration of ordinary differential equations (ODEs) of the form $\mathbf{u}' = \mathbf{f}(t,\mathbf{u}) + G(t,\mathbf{u}) \mathbf{u}$, where…

Numerical Analysis · Mathematics 2025-04-15 Lingyun Ding

We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of (non-necessarily Hamiltonian) ordinary differential equations by means of Newton-like iterations. We pay particular…

Numerical Analysis · Mathematics 2017-03-23 Mikel Antoñana , Joseba Makazaga , Ander Murua

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

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

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

The 4-th order Runge-Kutta method in the complex plane is proposed for numerically advancing the solutions of a system of first order differential equations in one external invariant satisfied by the master integrals related to a Feynman…

High Energy Physics - Phenomenology · Physics 2009-11-07 M. Caffo , H. Czyz , E. Remiddi
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