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Numerical computations have become a pillar of all modern quantitative sciences. Any computation involves modeling--even if often this step is not made explicit--and any model has to neglect details while still being physically accurate.…

Statistical Mechanics · Physics 2022-11-08 Thomas Speck

Recent advancements in generative modeling, particularly diffusion models, have opened new directions for time series modeling, achieving state-of-the-art performance in forecasting and synthesis. However, the reliance of diffusion-based…

Machine Learning · Computer Science 2025-05-13 Marcel Kollovieh , Marten Lienen , David Lüdke , Leo Schwinn , Stephan Günnemann

The nonequilibrium dynamics of a binary Lennard-Jones mixture in a simple shear flow is investigated by means of molecular dynamics simulations. The range of temperature investigated covers both the liquid, supercooled and glassy states,…

Soft Condensed Matter · Physics 2009-11-07 Ludovic Berthier , Jean-Louis Barrat

Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems is a fundamental yet challenging problem in many fields of science and engineering. Existing methods face significant obstacles: Gaussian-based filters struggle…

Numerical Analysis · Mathematics 2025-03-06 Xintong Wang , Xiaofei Guan , Ling Guo , Hao Wu

The generative paradigm has become increasingly important in machine learning and deep learning models. Among popular generative models are normalizing flows, which enable exact likelihood estimation by transforming a base distribution…

Machine Learning · Computer Science 2025-03-18 Naoufal El Bekri , Lucas Drumetz , Franck Vermet

Given a particle system obeying overdamped Langevin dynamics, we demonstrate that it is always possible to construct a thermodynamically consistent macroscopic model which obeys a gradient flow with respect to its non-equilibrium free…

Statistical Mechanics · Physics 2025-06-11 Travis Leadbetter , Prashant K. Purohit , Celia Reina

The study of complex systems is limited by the fact that only few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the systems behavior. In addition, empirical data typically…

Data Analysis, Statistics and Probability · Physics 2013-11-04 Matteo Marsili , Iacopo Mastromatteo , Yasser Roudi

Accurate prediction of electron temperature ($T_{\rm e}$) in non-equilibrium {plasma} flows is critical, yet hampered by inadequate models for electron heating from vibrationally excited states. Prior models often relied on ad-hoc scaling…

Plasma Physics · Physics 2025-09-23 Felipe Martin Rodriguez Fuentes , Bernard Parent

In this paper we propose a novel approach to construct macroscopic balance equations and constitutive equations describing various irreversible phenomena. It is based on the general principles of non-equilibrium thermodynamics and consists…

Statistical Mechanics · Physics 2014-11-27 Liu Hong , Zaibao Yang , Yi Zhu , Wen-An Yong

In this paper, a coupling lattice Boltzmann (LB) model for simulating thermal flows on the standard D2Q9 lattice is developed in the framework of the double-distribution-function (DDF) approach in which the viscous heat dissipation and…

Computational Physics · Physics 2012-02-07 Q. Li , K. H. Luo , Y. L. He , Y. J. Gao , W. Q. Tao

To describe the nonequilibrium states of a system we introduce a new thermodynamic parameter - the lifetime (the first passage time) of a system. The statistical distributions that can be obtained out of the mesoscopic description…

Chemical Physics · Physics 2007-05-23 V. V. Ryazanov

In the present thesis, we study the heat flow in mesoscopic one-dimensional transport systems. Using the analysis of full counting statistics, we calculate the cumulant generating function of the particle and heat flows and prove its…

Statistical Mechanics · Physics 2015-04-22 Kaoru Yamamoto

Two fundamental problems in unsupervised learning are efficient inference for latent-variable models and robust density estimation based on large amounts of unlabeled data. Algorithms for the two tasks, such as normalizing flows and…

Machine Learning · Statistics 2018-08-02 Changyou Chen , Chunyuan Li , Liqun Chen , Wenlin Wang , Yunchen Pu , Lawrence Carin

People are well aware that, inherently, certain small-scale nonchaotic particle movements are not governed by thermodynamics. Usually, such phenomena are studied by kinetic theory and their energy properties are considered "trivial". In…

Statistical Mechanics · Physics 2025-08-05 Yu Qiao , Zhaoru Shang

The aim of this work is to analyze the entropy, entropy flux and entropy supply rate of granular fluids within the frameworks of the Boltzmann equation and continuum thermodynamics. It is shown that the entropy inequality for a granular gas…

Statistical Mechanics · Physics 2010-11-17 Gilberto M. Kremer

We present a novel approach to kinetic theory modeling enabling the simulation of a generic, real gas presented by its corresponding equation of state. The model is based on mass, momentum and energy conservation, and unlike the lattice…

Fluid Dynamics · Physics 2020-02-25 Ehsan Reyhanian , Benedikt Dorschner , Ilya Karlin

A way to construct Boltzmann entropy, i.e., the entropy as a function of a microscopic pure state, for quantum field systems is proposed. Operators that shift the field in wavevector space are used in the construction. By employing an…

Statistical Mechanics · Physics 2020-03-25 Kyo Yoshida

Lack of knowledge about the detailed many-particle motion on the microscopic scale is a key issue in any theoretical description of a macroscopic experiment. For systems at or close to thermal equilibrium, statistical mechanics provides a…

Statistical Mechanics · Physics 2016-03-03 Peter Reimann

The problem of energy conservation in the lattice Boltzmann method is solved. A novel model with energy conservation is derived from Boltzmann's kinetic theory. It is demonstrated that the full thermo-hydrodynamics pertinent to the…

Statistical Mechanics · Physics 2007-05-23 S. Ansumali , I. V. Karlin

Thermodynamic properties can be in principle derived from the partition function, which, in many-atom systems, is hard to evaluate as it involves a sum on the accessible microscopic states. Recently, the partition function has been computed…