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Recent advances in data-driven modeling have shown that diffusion models can successfully generate synthetic Lagrangian trajectories in turbulent flows. Building on this progress, we extend the method to the joint generation of pairs of…

The lattice Boltzmann method (LBM) has gained increasing popularity in incompressible viscous flow simulations, but it uses many more variables than necessary. This defect was overcome by a recent approach that solves the more actual…

Fluid Dynamics · Physics 2021-06-02 Jun-Jie Huang

Thermal transport in classical fluids is analyzed in terms of a Higher-Order Generalized Hydrodynamics (or Mesoscopic Hydro-Thermodynamics), that is, depending on the evolution of the energy density and its fluxes of all orders. It is…

Statistical Mechanics · Physics 2020-04-16 Cloves G. Rodrigues , Carlos A. B. Silva , Jose Galvao Ramos , Roberto Luzzi

This paper proposes stochastic models for the analysis of ocean surface trajectories obtained from freely-drifting satellite-tracked instruments. The proposed time series models are used to summarise large multivariate datasets and infer…

Applications · Statistics 2017-03-16 Adam M. Sykulski , Sofia C. Olhede , Jonathan M. Lilly , Eric Danioux

We analyze the effect of temperature on the yielding transition of amorphous solids using different coarse-grained model approaches. On one hand we use an elasto-plastic model, with temperature introduced in the form of an Arrhenius…

Disordered Systems and Neural Networks · Physics 2021-11-12 Ezequiel E. Ferrero , Alejandro B. Kolton , Eduardo A. Jagla

The description of molecular motion by macroscopic hydrodynamics has a long and continuing history. The Stokes-Einstein relation between the diffusion coefficient of a solute and the solvent viscosity predicted using macroscopic continuum…

Disordered Systems and Neural Networks · Physics 2007-05-23 Xiaoyu Xia , Peter G. Wolynes

Accurately forecasting long-term atmospheric variables remains a defining challenge in meteorological science due to the chaotic nature of atmospheric systems. Temperature data represents a complex superposition of deterministic cyclical…

Machine Learning · Computer Science 2026-01-14 Shreyas Rajeev , Karthik Mudenahalli Ashoka , Amit Mallappa Tiparaddi

We introduce and analyze a model for the transport of particles or energy in extended lattice systems. The dynamics of the model acts on a discrete phase space at discrete times but has nonetheless some of the characteristic properties of…

Mathematical Physics · Physics 2015-06-12 Raphael Lefevere

In this contribution, we introduce a general class of car-following models with an input-state-output port-Hamiltonian structure. We derive stability conditions and long-term behavior of the finite system with periodic boundaries and…

Dynamical Systems · Mathematics 2025-02-04 Julia Ackermann , Matthias Ehrhardt , Thomas Kruse , Antoine Tordeux

The stochastic variational approach for geophysical fluid dynamics was introduced by Holm (Proc Roy Soc A, 2015) as a framework for deriving stochastic parameterisations for unresolved scales. This paper applies the variational stochastic…

Fluid Dynamics · Physics 2022-09-16 Colin Cotter , Dan Crisan , Darryl D. Holm , Wei Pan , Igor Shevchenko

We present a lattice-based numerical method to describe the non equilibrium behavior of a simple fluid under non-uniform spatial conditions. The evolution equation for the one-particle phase-space distribution function is derived starting…

Statistical Mechanics · Physics 2009-11-13 S. Melchionna , U. Marini Bettolo Marconi

A model for the large-scale circulation (LSC) dynamics of turbulent Rayleigh-Benard convection is presented. It consists of two stochastic ordinary differential equations motivated by the Navier-Stokes equation, one each for the strength…

Fluid Dynamics · Physics 2007-05-23 Eric Brown , Guenter Ahlers

Many scientific systems, such as cellular populations or economic cohorts, are naturally described by probability distributions that evolve over time. Predicting how such a system would have evolved under different forces or initial…

Machine Learning · Statistics 2026-03-26 Tristan Luca Saidi , Gonzalo Mena , Larry Wasserman , Florian Gunsilius

Direct Monte Carlo simulations of the Enskog-Boltzmann equation for a spatially uniform system of smooth inelastic spheres are performed. In order to reach a steady state, the particles are assumed to be under the action of an external…

Statistical Mechanics · Physics 2016-08-31 J. M. Montanero , A. Santos

In spin-lattice models with order parameter conserved, we generalize the idea of spin diffusion incorporating a variety factors as possible driving forces, including the external field and the temperature. The Kawasaki dynamics in the…

Statistical Mechanics · Physics 2007-05-23 Han Zhu , Jian-Yang Zhu

Thermodynamics serves as a universal means for studying physical systems from an energy perspective. In recent years, with the establishment of the field of stochastic and quantum thermodynamics, the ideas of thermodynamics have been…

Statistical Mechanics · Physics 2023-02-07 Tan Van Vu , Keiji Saito

This paper provides an introduction to some stochastic models of lattice gases out of equilibrium and a discussion of results of various kinds obtained in recent years. Although these models are different in their microscopic features, a…

Statistical Mechanics · Physics 2015-12-18 L. Bertini , A. De Sole , D. Gabrielli , G. Jona--Lasinio , C. Landim

In this paper, we investigate the recently developed lattice Boltzmann model for relativistic hydrodynamics. To this purpose, we perform simulations of shock waves in quark-gluon plasma in the low and high viscosities regime, using three…

High Energy Physics - Theory · Physics 2012-02-01 D. Hupp , M. Mendoza , I. Bouras , S. Succi , H. J. Herrmann

The inclusion of convection in stellar evolution models lacks realism, especially near convective-radiative interfaces. Furthermore, the interaction of convection with oscillations prevent us from accurately predicting seismic frequencies,…

Solar and Stellar Astrophysics · Physics 2025-10-31 J. Philidet , K. Belkacem

In this paper, we introduce a data-driven modeling approach for dynamics problems with latent variables. The state-space of the proposed model includes artificial latent variables, in addition to observed variables that can be fitted to a…

Optimization and Control · Mathematics 2024-06-19 Yushuang Luo , Xiantao Li , Wenrui Hao