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Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. In case of repeated observations of time series for several experimental units, it is often the case that some of the…

Methodology · Statistics 2024-09-06 Fernando Baltazar-Larios , Mogens Bladt , Michael Sørensen

Given a fluid equation with reduced Lagrangian $l$ which is a functional of velocity $\MM{u}$ and advected density $D$ given in Eulerian coordinates, we give a general method for semidiscretising the equations to give a canonical…

Numerical Analysis · Mathematics 2007-05-23 Colin Cotter

We construct sub-grid scale models of incompressible fluids by considering expectations of semi-martingale Lagrangian particle trajectories. Our construction is based on the Lagrangian decomposition of flow maps into mean and fluctuation…

Mathematical Physics · Physics 2025-04-15 Theo Diamantakis , Ruiao Hu

We present the first method to directly use a learned continuous Lagrangian to forecast the dynamics of systems governed by partial differential equations, exploiting the inherent conservative structure to achieve stable long-range…

Machine Learning · Computer Science 2026-05-11 Lyra Zhornyak , Eric Forgoston , M. Ani Hsieh

We develop an information-theoretic formulation of stochastic dynamics in which the fundamental stochastic variable is the total action connecting spacetime points, rather than individual paths. By maximizing Shannon entropy over a joint…

Stratified fluids composed of a sequence of alternate layers show interesting macroscopic properties, which may be quite different from those of the individual constituent fluids. On a macroscopic scale, such systems can be considered a…

Numerical Analysis · Mathematics 2026-01-30 Simone Chiocchetti , Giovanni Russo

We consider spatially extended conductance based neuronal models with noise described by a stochastic reaction diffusion equation with additive noise coupled to a control variable with multiplicative noise but no diffusion. We only assume a…

Probability · Mathematics 2020-01-16 Martin Sauer , Wilhelm Stannat

Stochastic thermodynamics is a developing theory for systems out of thermal equilibrium. It allows to formulate a wealth of nontrivial relations among thermodynamic quantities such as heat dissipation, excess work, and entropy production in…

Statistical Mechanics · Physics 2026-02-24 Benjamin Sorkin , Gil Ariel , Tomer Markovich

A recent proposal (see quant-ph/9803068) to simulate semiclassical corrections to classical dynamics by suitable classical stochastic fluctuations is applied to the specific instance of charged beam dynamics in particle accelerators. The…

Accelerator Physics · Physics 2007-05-23 Salvatore De Martino , Silvio De Siena , Fabrizio Illuminati

The explicit semi-Lagrangian method method for solution of Lagrangian transport equations as developed in [Natarajan and Jacobs, Computer and Fluids, 2020] is adopted for the solution of stochastic differential equations that is consistent…

Computational Physics · Physics 2021-07-07 H. Natarajan , P. P. Popov , G. B. Jacobs

Resetting a stochastic process is an important problem describing the evolution of physical, biological and other systems which are continually returned to their certain fixed point. We consider the motion of a subdiffusive particle with a…

Statistical Mechanics · Physics 2024-01-18 Aleksander A. Stanislavsky

In this paper we study the problem of computing the effective diffusivity for a particle moving in chaotic and stochastic flows. In addition we numerically investigate the residual diffusion phenomenon in chaotic advection. The residual…

Numerical Analysis · Mathematics 2017-11-28 Zhongjian Wang , Jack Xin , Zhiwen Zhang

The stochastic thermodynamics provides a framework for the description of systems that are out of thermodynamic equilibrium. It is based on the assumption that the elementary constituents are acted by random forces that generate a…

Statistical Mechanics · Physics 2020-06-26 Mário J. de Oliveira

The purpose of this paper is to examine the Lagrangian stochastic modeling of the fluid velocity seen by inertial particles in a nonhomogeneous turbulent flow. A new Langevin-type model, compatible with the transport equation of the drift…

Fluid Dynamics · Physics 2009-07-01 Boris Arcen , Anne Tanière

A discrete theory for implicit nonholonomic Lagrangian systems undergoing elastic collisions is developed. It is based on the discrete Lagrange-d'Alembert-Pontryagin variational principle and the dynamical equations thus obtained are the…

Dynamical Systems · Mathematics 2025-03-26 Álvaro Rodríguez Abella , Leonardo Colombo

We develop in this paper a new framework for discrete calculus of variations when the actions have densities involving an arbitrary discretization operator. We deduce the discrete Euler-Lagrange equations for piecewise continuous critical…

Optimization and Control · Mathematics 2011-06-28 Philippe Ryckelynck , Laurent Smoch

Modeling statistical properties of motion of a Lagrangian particle advected by a high-Reynolds-number flow is of much practical interest and complement traditional studies of turbulence made in Eulerian framework. The strong and nonlocal…

Statistical Mechanics · Physics 2007-05-23 A. K. Aringazin , M. I. Mazhitov

Mathematically modelling diffusive and advective transport of particles in heterogeneous layered media is important to many applications in computational, biological and medical physics. While deterministic continuum models of such…

Computational Physics · Physics 2024-09-16 Elliot J. Carr

A computational approach is introduced for the study of the rheological properties of complex fluids and soft materials. The approach allows for a consistent treatment of microstructure elastic mechanics, hydrodynamic coupling, thermal…

Soft Condensed Matter · Physics 2023-02-28 P. J. Atzberger

In this paper we propose a novel way to integrate time-evolving partial differential equations that contain nonlinear advection and stiff linear operators, combining exponential integration techniques and semi-Lagrangian methods. The…

Computational Physics · Physics 2019-11-05 Pedro da Silva Peixoto , Martin Schreiber
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