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Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of…

Mathematical Software · Computer Science 2017-07-17 Andrea Vandin

The neural ordinary differential equation (ODE) framework has emerged as a powerful tool for developing accelerated surrogate models of complex physical systems governed by partial differential equations (PDEs). A popular approach for PDE…

Fluid Dynamics · Physics 2025-03-26 Ashish S. Nair , Shivam Barwey , Pinaki Pal , Jonathan F. MacArt , Troy Arcomano , Romit Maulik

Neural operators, which emerge as implicit solution operators of hidden governing equations, have recently become popular tools for learning responses of complex real-world physical systems. Nevertheless, the majority of neural operator…

Machine Learning · Computer Science 2023-01-31 Ning Liu , Yue Yu , Huaiqian You , Neeraj Tatikola

Various many-body models are treated, which describe $N$ points confined to move on a plane circle. Their Newtonian equations of motion ("accelerations equal forces") are integrable, i. e. they allow the explicit exhibition of $N$ constants…

Mathematical Physics · Physics 2014-07-09 Oksana Bihun , Francesco Calogero

Modern applications of robotics typically involve a robot control system with an inner PI (proportional-integral) or PID (proportional-integral-derivative) control loop and an outer user-specified control loop. The existing outer loop…

Systems and Control · Computer Science 2021-12-14 Hanlei Wang , Wei Ren , Chien Chern Cheah , Yongchun Xie , Shangke Lyu

A new methodology is developed to integrate numerically the equations of motion for classical many-body systems in molecular dynamics simulations. Its distinguishable feature is the possibility to preserve, independently on the size of the…

Statistical Mechanics · Physics 2009-10-31 I. P. Omelyan , I. M. Mryglod , R. Folk

The recursive Newton-Euler Algorithm (RNEA) is a popular technique for computing the dynamics of robots. RNEA can be framed as a differentiable computational graph, enabling the dynamics parameters of the robot to be learned from data via…

Forecasting system behaviour near and across bifurcations is crucial for identifying potential shifts in dynamical systems. While machine learning has recently been used to learn critical transitions and bifurcation structures from data,…

Machine Learning · Computer Science 2025-11-14 Eva van Tegelen , George van Voorn , Ioannis Athanasiadis , Peter van Heijster

Identifying dynamical systems from experimental data is a notably difficult task. Prior knowledge generally helps, but the extent of this knowledge varies with the application, and customized models are often needed. Neural ordinary…

Systems and Control · Electrical Eng. & Systems 2023-01-13 Mona Buisson-Fenet , Valery Morgenthaler , Sebastian Trimpe , Florent Di Meglio

In recent works we have used quantum tools in the analysis of the time evolution of several macroscopic systems. The main ingredient in our approach is the self-adjoint Hamiltonian $H$ of the system $\Sc$. This Hamiltonian quite often, and…

Quantum Physics · Physics 2019-10-23 Fabio Bagarello

New techniques for evaluating the closed time path action for non-equilibrium quantum fields are presented. A derivative expansion is performed using a proper time kernel. Applications relevant to the scalar field theory of warm inflation…

High Energy Physics - Phenomenology · Physics 2009-11-07 Ian G Moss

The time derivative of the circulation of a vector field $\boldsymbol{A}$ over a moving and deforming closed curve, $\frac {\mathrm{d}}{\mathrm{d} t}\oint \boldsymbol{A} \cdot \mathrm{d} \boldsymbol{r}$, is computed in two ways, with and…

History and Philosophy of Physics · Physics 2020-06-08 Dragan V Redzic

We present a direct derivation of the typical time derivatives used in a continuum description of complex fluid flows, harnessing the principles of the kinematics of line elements. The evolution of the microstructural conformation tensor in…

Fluid Dynamics · Physics 2024-01-12 Howard A. Stone , Michael J. Shelley , Evgeniy Boyko

In this paper, we use the fractional calculus to discuss the fractional mechanics, where the time derivative is replaced with the fractional derivative of order $\nu$. We deal with the motion of a body in a resisting medium where the…

General Physics · Physics 2015-06-15 Won Sang Chung , Min Jung

It is well known that conservative mechanical systems exhibit local oscillatory behaviours due to their elastic and gravitational potentials, which completely characterise these periodic motions together with the inertial properties of the…

Optimization and Control · Mathematics 2023-06-26 Yannik Wotte , Sven Dummer , Nicolò Botteghi , Christoph Brune , Stefano Stramigioli , Federico Califano

A key ingredient to achieving intelligent behavior is physical understanding that equips robots with the ability to reason about the effects of their actions in a dynamic environment. Several methods have been proposed to learn dynamics…

Robotics · Computer Science 2020-01-24 David Millard , Eric Heiden , Shubham Agrawal , Gaurav S. Sukhatme

Probing the out-of-equilibrium dynamics of quantum matter has gained renewed interest owing to immense experimental progress in artifcial quantum systems. Dynamical quantum measures such as the growth of entanglement entropy (EE) and…

Disordered Systems and Neural Networks · Physics 2018-04-04 Pranjal Bordia , Fabien Alet , Pavan Hosur

We consider a general open system dynamics and we provide a recursive method to derive the associated non-Markovian master equation in a perturbative series. The approach relies on a momenta expansion of the open system evolution. Unlike…

Quantum Physics · Physics 2018-02-26 Giulio Gasbarri , Luca Ferialdi

We present an efficient variational integrator for multibody systems. Variational integrators reformulate the equations of motion for multibody systems as discrete Euler-Lagrange (DEL) equations, transforming forward integration into a…

Robotics · Computer Science 2018-02-06 Jeongseok Lee , C. Karen Liu , Frank C. Park , Siddhartha S. Srinivasa

We extend Noether's theorem to dynamical optimal control systems being under the action of nonconservative forces. A systematic way of calculating conservation laws for nonconservative optimal control problems is given. As a corollary, the…

Optimization and Control · Mathematics 2007-05-23 Gastao S. F. Frederico , Delfim F. M. Torres
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