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This letter proposes a predictor-corrector method to strike a balance between simulation accuracy and efficiency by appropriately tuning the numerical integration step length of a power system time-domain simulation. Numerical tests…

Computational Engineering, Finance, and Science · Computer Science 2019-02-07 Yiming Cai , Junbo Zhang , Weizhou Yu

We consider a class of linear Vlasov partial differential equations driven by Wiener noise. Different types of stochastic perturbations are treated: additive noise, multiplicative It\^o and Stratonovich noise, and transport noise. We…

Numerical Analysis · Mathematics 2024-03-01 Charles-Edouard Bréhier , David Cohen

In this paper, we consider the application of exponential integrators to problems that are advection dominated, either on the entire or on a subset of the domain. In this context, we compare Leja and Krylov based methods to compute the…

Numerical Analysis · Mathematics 2024-10-17 Lukas Einkemmer , Trung-Hau Hoang , Alexander Ostermann

Viewing optimization methods as numerical integrators for ordinary differential equations (ODEs) provides a thought-provoking modern framework for studying accelerated first-order optimizers. In this literature, acceleration is often…

Optimization and Control · Mathematics 2021-02-24 Peiyuan Zhang , Antonio Orvieto , Hadi Daneshmand , Thomas Hofmann , Roy Smith

We change a previous time-stepping algorithm for solving a multi-scale Vlasov-Poisson system within a Particle-In-Cell method, in order to do accurate long time simulations. As an exponential integrator, the new scheme allows to use large…

Numerical Analysis · Mathematics 2015-06-19 Emmanuel Frenod , Sever Hirstoaga , Mathieu Lutz

This article deals with the numerical integration in time of nonlinear Schr\"odinger equations. The main application is the numerical simulation of rotating Bose-Einstein condensates. The authors perform a change of unknown so that the…

Analysis of PDEs · Mathematics 2017-01-31 Christophe Besse , Guillaume Dujardin , Ingrid Lacroix-Violet

Discrete variational methods show excellent performance in numerical simulations of mechanical systems. In this paper, we adapt discrete variational integrators for the case of mechanical systems with double-bracket dissipation. In…

Numerical Analysis · Mathematics 2026-04-30 Anthony Bloch , Sebastián J. Ferraro , David Martín de Diego , Shreyas Bharadwaj

This paper deals with the error analysis of the trapezoidal rule for the computation of Fourier type integrals, based on two double exponential transformations. The theory allows to construct algorithms in which the steplength and the…

Numerical Analysis · Mathematics 2023-08-03 Eleonora Denich , Paolo Novati

We propose Poisson integrators for the numerical integration of separable Poisson systems. We analyze three situations in which the Poisson systems are separated in three ways and the Poisson integrators can be constructed by using the…

Numerical Analysis · Mathematics 2022-11-09 Beibei Zhu , Lun Ji , Aiqing Zhu , Yifa Tang

Seismic imaging is a major challenge in geophysics with broad applications. It involves solving wave propagation equations with absorbing boundary conditions (ABC) multiple times. This drives the need for accurate and efficient numerical…

Numerical Analysis · Mathematics 2024-01-30 Fernando V. Ravelo , Martin Schreiber , Pedro S. Peixoto

For electromagnetic transient (EMT) simulation of a power system, a state-space-based approach needs to solve state-space EMT equations by using numerical integration methods, e.g., the Euler method, Runge-Kutta methods, and…

Systems and Control · Electrical Eng. & Systems 2023-02-21 Min Xiong , Rui Yao , Yang Liu , Kai Sun , Feng Qiu

A quantitative definition of numerical stiffness for initial value problems is proposed. Exponential integrators can effectively integrate linearly stiff systems, but they become expensive when the linear coefficient is a matrix, especially…

Numerical Analysis · Mathematics 2023-05-23 Thoma Zoto , John C. Bowman

Differentiable simulators promise faster computation time for reinforcement learning by replacing zeroth-order gradient estimates of a stochastic objective with an estimate based on first-order gradients. However, it is yet unclear what…

Machine Learning · Computer Science 2022-08-23 H. J. Terry Suh , Max Simchowitz , Kaiqing Zhang , Russ Tedrake

The efficient simulation of models defined in terms of stochastic differential equations (SDEs) depends critically on an efficient integration scheme. In this article, we investigate under which conditions the integration schemes for…

Computational Physics · Physics 2016-08-16 G. De Fabritiis , M. Serrano , P. Español , P. V. Coveney

We present a methodology for numerically integrating ordinary differential equations containing rapidly oscillatory terms. This challenge is distinct from that for differential equations which have rapidly oscillatory solutions: here the…

Numerical Analysis · Mathematics 2013-05-23 J. E. Bunder , A. J. Roberts

Matrix Riccati differential equations arise in many different areas and are particular important within the field of control theory. In this paper we consider numerical integration for large-scale systems of stiff matrix Riccati…

Numerical Analysis · Mathematics 2019-08-20 Dongping Li

The Obreshkov method is a single-step multi-derivative method used in the numerical solution of differential equations and has been used in recent years in efficient circuit simulation. It has been shown that it can be made of arbitrary…

Numerical Analysis · Mathematics 2021-02-08 Emad Gad

The Alekseev-Gr{\"o}bner lemma is combined with the theory of modified equations to obtain an \emph{a priori} estimate for the global error of numerical integrators. This estimate is correct up to a remainder term of order $h^{2p}$, where…

Numerical Analysis · Mathematics 2025-10-20 Jitse Niesen

This work proposes a suite of numerical techniques to facilitate the design of structure-preserving integrators for nonlinear dynamics. The celebrated LaBudde-Greenspan integrator and various energy-momentum schemes adopt a difference…

Numerical Analysis · Mathematics 2023-05-17 Ju Liu

A research frontier has emerged in scientific computation, wherein numerical error is regarded as a source of epistemic uncertainty that can be modelled. This raises several statistical challenges, including the design of statistical…

Machine Learning · Statistics 2017-10-19 François-Xavier Briol , Chris. J. Oates , Mark Girolami , Michael A. Osborne , Dino Sejdinovic