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We study Runge-Kutta methods for rough differential equations which can be used to calculate solutions to stochastic differential equations driven by processes that are rougher than a Brownian motion. We use a Taylor series representation…

Numerical Analysis · Mathematics 2020-03-31 Martin Redmann , Sebastian Riedel

We consider the construction of semi-implicit linear multistep methods which can be applied to time dependent PDEs where the separation of scales in additive form, typically used in implicit-explicit (IMEX) methods, is not possible. As…

Numerical Analysis · Mathematics 2020-01-14 Giacomo Albi , Lorenzo Pareschi

In order to solve continuous-time optimal control problems, direct methods transcribe the infinite-dimensional problem to a nonlinear program (NLP) using numerical integration methods. In cases where the integration error can be manipulated…

Optimization and Control · Mathematics 2025-03-18 Jakob Harzer , Jochem De Schutter , Moritz Diehl

From the point of view of statistical mechanics, a full characterisation of a molecular system requires the experimental determination of its possible states, their populations and the respective interconversion rates. Well-established…

Computational Physics · Physics 2020-06-02 Z. Faidon Brotzakis , Michele Vendruscolo , Peter. G. Bolhuis

High-performance autonomy often must operate at the boundaries of safety. When external agents are present in a system, the process of ensuring safety without sacrificing performance becomes extremely difficult. In this paper, we present an…

Robotics · Computer Science 2021-10-05 Stanley Bak , Johannes Betz , Abhinav Chawla , Hongrui Zheng , Rahul Mangharam

In the paper explicit functional continuous Runge-Kutta and Runge-Kutta-Nystr\"om methods for retarded functional differential equations are considered. New methods for first order equations as well as for second order equations of the…

Numerical Analysis · Mathematics 2018-06-25 Alexey S. Eremin

Extended Stability Runge-Kutta (ESRK) methods are crucial for solving large-scale computational problems in science and engineering, including weather forecasting, aerodynamic analysis, and complex biological modelling. However, balancing…

Machine Learning · Computer Science 2025-06-27 Gavin Lee Goodship , Luis Miralles-Pechuan , Stephen O'Sullivan

The numerical efficiency of different schemes for solving the Liouville-von Neumann equation within multilevel Redfield theory has been studied. Among the tested algorithms are the well-known Runge-Kutta scheme in two different…

Chemical Physics · Physics 2009-11-06 Ivan Kondov , Ulrich Kleinekathoefer , Michael Schreiber

Transient stability assessment of power systems needs to account for increased risk from uncertainties due to the integration of renewables and distributed generators. The uncertain operating condition of the power grid hinders reliable…

Dynamical Systems · Mathematics 2017-05-04 Dongchan Lee , Konstantin Turitsyn

The residual-based variational multiscale (VMS) formulation has achieved remarkable success in large-eddy simulation of turbulent flows. However, its temporal discretization has largely remained limited to second-order implicit schemes. The…

Fluid Dynamics · Physics 2025-12-09 Yujie Sun , Chi Ding , Ju Liu

Delayed processes are ubiquitous throughout biology. These delays may arise through maturation processes or as the result of complex multi-step networks, and mathematical models with distributed delays are increasingly used to capture the…

Populations and Evolution · Quantitative Biology 2024-10-15 Tyler Cassidy

Runge-Kutta methods are a popular class of numerical methods for solving ordinary differential equations. Every Runge-Kutta method is characterized by two basic parameters: its order, which measures the accuracy of the solution it produces,…

Numerical Analysis · Mathematics 2019-11-04 David K. Zhang

The construction of efficient methods for uncertainty quantification in kinetic equations represents a challenge due to the high dimensionality of the models: often the computational costs involved become prohibitive. On the other hand,…

Numerical Analysis · Mathematics 2021-12-03 Giacomo Dimarco , Liu Liu , Lorenzo Pareschi , Xueyu Zhu

Maximum bound principle (MBP) is an important property for a large class of semilinear parabolic equations, in the sense that the time-dependent solution of the equation with appropriate initial and boundary conditions and nonlinear…

Numerical Analysis · Mathematics 2021-04-21 Jingwei Li , Xiao Li , Lili Ju , Xinlong Feng

Most studies in multiparameter estimation assume the dynamics is fixed and focus on identifying the optimal probe state and the optimal measurements. In practice, however, controls are usually available to alter the dynamics, which provides…

Quantum Physics · Physics 2017-10-30 Jing Liu , Haidong Yuan

In this paper we present tools for applied researchers that re-purpose off-the-shelf methods from the computer-science field of machine learning to create a "discovery engine" for data from randomized controlled trials (RCTs). The applied…

Machine Learning · Statistics 2019-05-13 Jens Ludwig , Sendhil Mullainathan , Jann Spiess

In this master thesis we have compared different second order stabilized explicit Runge-Kutta methods when applied to the incompressible Navier-Stokes equations by means of a projection method and a differential algebraic approach. We…

Numerical Analysis · Mathematics 2022-03-30 Giacomo Rosilho de Souza

A recently developed high-order implicit shock tracking (HOIST) framework for resolving discontinuous solutions of inviscid, steady conservation laws [41, 43] is extended to the unsteady case. Central to the framework is an optimization…

Numerical Analysis · Mathematics 2022-01-26 Andrew Shi , Per-Olof Persson , Matthew Zahr

This work establishes a solution to the problem of assessing the capacity of multi-object assemblies to withstand external forces without becoming unstable. Our physically-grounded approach handles arbitrary structures made from rigid…

Robotics · Computer Science 2025-06-25 Philippe Nadeau , Jonathan Kelly

A general purpose, modular program package for the integration of large number of independent ordinary differential equation systems capable of using professional graphics cards is presented. The available numerical schemes are the explicit…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-10 Ferenc Hegedűs