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Symplectic schemes are powerful methods for numerically integrating Hamiltonian systems, and their long-term accuracy and fidelity have been proved both theoretically and numerically. However direct applications of standard symplectic…

Plasma Physics · Physics 2019-06-26 Jianyuan Xiao , Hong Qin

A high order finite difference method is proposed for unstructured meshes to simulate compressible inviscid/viscous flows with/without discontinuities. In this method, based on the strong form equation, the divergence of the flux on each…

Numerical Analysis · Mathematics 2021-09-08 Zeyuan Zhou , Mei-Yuan Zhen , Kun Qu , Jin-Sheng Cai

This paper proposes an implicit family of sub-step integration algorithms grounded in the explicit singly diagonally implicit Runge-Kutta (ESDIRK) method. The proposed methods achieve third-order consistency per sub-step and thus the…

Numerical Analysis · Mathematics 2025-06-05 Jinze Li , Hua Li , Kaiping Yu , Rui Zhao

We consider the numerical integration of non-autonomous separable parabolic equations using high order splitting methods with complex coefficients (methods with real coefficients of order greater than two necessarily have negative…

Numerical Analysis · Mathematics 2014-05-20 Muaz Seydaoğlu , Sergio Blanes

In this work, in order to obtain higher-order schemes for solving forward backward stochastic differential equations, we adopt the high-order multi-step method in [W. Zhao, Y. Fu and T. Zhou, SIAM J. Sci. Comput., 36(4) (2014),…

Numerical Analysis · Mathematics 2020-10-06 Long Teng , Weidong Zhao

We have proposed new algorithms for the numerical integration of the equations of motion for classical spin systems. In close analogy to symplectic integrators for Hamiltonian equations of motion used in Molecular Dynamics these algorithms…

Statistical Mechanics · Physics 2009-10-31 M. Krech , Alex Bunker , D. P. Landau

We propose a third-order numerical integrator based on the Neumann series and the Filon quadrature, designed mainly for highly oscillatory partial differential equations. The method can be applied to equations that exhibit small or moderate…

Numerical Analysis · Mathematics 2024-06-21 Rafał Perczyński , Grzegorz Madejski

We construct numerical integrators for Hamiltonian problems that may advantageously replace the standard Verlet time-stepper within Hybrid Monte Carlo and related simulations. Past attempts have often aimed at boosting the order of accuracy…

Numerical Analysis · Mathematics 2015-04-10 Sergio Blanes , Fernando Casas , J. M. Sanz-Serna

In this article we describe a new Hermite series based sequential estimator for the Spearman rank correlation coefficient and provide algorithms applicable in both the stationary and non-stationary settings. To treat the non-stationary…

Methodology · Statistics 2021-07-07 Michael Stephanou , Melvin Varughese

It is often unnoticed that the predominant way to use collocation methods is fundamentally flawed when applied to optimal control in robotics. Such methods assume that the system dynamics is given by a first order ODE, whereas robots are…

Robotics · Computer Science 2023-02-20 Siro Moreno-Martín , Lluís Ros , Enric Celaya

We show that a recently discovered fourth order symplectic algorithm, which requires one evaluation of force gradient in addition to three evaluations of the force, when iterated to higher order, yielded algorithms that are far superior to…

Computational Physics · Physics 2009-11-06 Siu A. Chin , Donald W. Kidwell

An approach is proposed to improve the efficiency of fourth-order algorithms for numerical integration of the equations of motion in molecular dynamics simulations. The approach is based on an extension of the decomposition scheme by…

Statistical Mechanics · Physics 2009-11-07 Igor Omelyan , Ihor Mryglod , Reinhard Folk

We present high-order compact schemes for a linear second-order parabolic partial differential equation (PDE) with mixed second-order derivative terms in two spatial dimensions. The schemes are applied to option pricing PDE for a family of…

Computational Finance · Quantitative Finance 2016-11-02 Bertram Düring , Christof Heuer

We present an algorithm named "Chamomile Scheme". The scheme is fully optimized for calculating gravitational interactions on the latest programmable Graphics Processing Unit (GPU), NVIDIA GeForce8800GTX, which has (a) small but fast shared…

Astrophysics · Physics 2007-05-23 Tsuyoshi Hamada , Toshiaki Iitaka

In this paper, a class of high-order compact finite difference Hermite scheme is presented for the simulation of double-diffusive convection. To maintain linear stability, the convective fluxes are split into positive and negative parts,…

Numerical Analysis · Mathematics 2025-06-25 Jianqing Yang , Jianxian Qiu

We present a novel method for efficient direct integration of gravitational N-body systems with a large variation in characteristic time scales. The method is based on a recursive and adaptive partitioning of the system based on the…

Instrumentation and Methods for Astrophysics · Physics 2014-10-08 Jürgen Jänes , Federico I. Pelupessy , Simon F. Portegies Zwart

We present a method for efficient differentiable simulation of articulated bodies. This enables integration of articulated body dynamics into deep learning frameworks, and gradient-based optimization of neural networks that operate on…

Machine Learning · Computer Science 2021-09-17 Yi-Ling Qiao , Junbang Liang , Vladlen Koltun , Ming C. Lin

Hermite polynomials and functions have extensive applications in scientific and engineering problems. Although it is recognized that employing the scaled Hermite functions rather than the standard ones can remarkably enhance the…

Numerical Analysis · Mathematics 2026-05-06 Hao Hu , Haijun Yu

We propose new linear combinations of compositions of a basic second-order scheme with appropriately chosen coefficients to construct higher order numerical integrators for differential equations. They can be considered as a generalization…

Numerical Analysis · Mathematics 2024-04-25 Sergio Blanes , Fernando Casas , Luke Shaw

Despite their frequent slow convergence, proximal gradient schemes are widely used in large-scale optimization tasks due to their tremendous stability, scalability, and ease of computation. In this paper, we develop and investigate a…

Computation · Statistics 2025-08-19 Nicholas C. Henderson , Ravi Varadhan