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A pure and incompressible material is confined between two plates such that it is heated from below and cooled from above. When its melting temperature is comprised between these two imposed temperatures, an interface separating liquid and…

Fluid Dynamics · Physics 2020-02-11 Jhaswantsing Purseed , Benjamin Favier , Laurent Duchemin , Eric W. Hester

Diffusion models generate structure by progressively transforming noise into data, yet the mechanisms underlying this transition remain poorly understood. In this work, we show that pattern formation in trained diffusion models can be…

Machine Learning · Computer Science 2026-04-29 Luca Ambrogioni

Although coarse-grained models have been widely used to explain exotic phenomena in complex fluids, such as droplet formation in living cells, these conventional approaches often fail to capture the intricate microscopic degrees of freedom…

Soft Condensed Matter · Physics 2025-06-13 Masanari Shimada , Tetsuya J. Kobayashi

Non-uniform sampling arises when an experimenter does not have full control over the sampling characteristics of the process under investigation. Moreover, it is introduced intentionally in algorithms such as Bayesian optimization and…

Machine Learning · Statistics 2020-07-03 Stijn de Waele

With the traditional equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space in complex systems, which are separated into some metastable conformational regions by high free energy…

Soft Condensed Matter · Physics 2019-08-17 Cheng Yang , Biao Wan , Shun Xu , Yanting Wang , Xin Zhou

We explore the idea that non-equilibrium steady states breaking detailed balance are obtained by deforming trajectories (lines in space-time) that have been sampled in a reference system with stochastic dynamics obeying detailed balance,…

Statistical Mechanics · Physics 2018-04-17 Thomas Speck

We study the formation of coherent structures in a system with long-range interactions where particles moving on a circle interact through a repulsive cosine potential. Non equilibrium structures are shown to correspond to statistical…

Statistical Mechanics · Physics 2009-11-07 Julien Barre' , Freddy Bouchet , Thierry Dauxois , Stefano Ruffo

Symmetries represent a fundamental constraint for physical systems and relevant new phenomena often emerge as a consequence of their breaking. An important example is provided by space- and time-translational invariance in statistical…

Statistical Mechanics · Physics 2012-12-21 Matteo Marcuzzi , Andrea Gambassi , Michel Pleimling

The micropolar Rayleigh-B{\'e}nard convection system, which consists of Navier-Stokes equations, the angular momentum equation, and the heat equation, is a strongly nonlinear, coupled, and saddle point structural multiphysics system. A…

Numerical Analysis · Mathematics 2025-12-03 Ming Cui , Akang Hou , Xiaoyu Dong

We introduce a new formalism to study nonequilibrium steady-state currents in stochastic field theories. We show that generalizing the exterior derivative to functional spaces allows identifying the subspaces in which the system undergoes…

Statistical Mechanics · Physics 2022-09-30 Jérémy O'Byrne

Extending the famous Model B for the time evolution of a liquid mixture, we derive an approximate expression for the mobility matrix that couples the different mixture components. This approach is based on a single component fluid with…

Statistical Mechanics · Physics 2023-06-21 Maryam Akaberian , Filipe C Thewes , Peter Sollich , Matthias Krüger

We examine stochastic processes that are used to model nonequilibrium processes (e.g, pulling RNA or dragging colloids) and so deliberately violate detailed balance. We argue that by combining an information-theoretic measure of…

Statistical Mechanics · Physics 2009-11-13 R. A. Blythe

In this paper we investigate the applicability of non-equilibrium statistical mechanics to non-equilibrium damage phenomena. As an example, a fiber-bundle model with thermal noise and a fiber-bundle model with decay of fibers are…

Statistical Mechanics · Physics 2009-05-25 S. G. Abaimov

We discuss the non-equilibrium critical phenomena in liquids, and the models for these phenomena based on local equilibrium and extended scaling assumptions. Special situations are proposed for experimental tests of the theory.…

Statistical Mechanics · Physics 2009-10-31 Alexander Patashinski

Nonequilibrium complex systems are often effectively described by the mixture of different dynamics on different time scales. Superstatistics, which is "statistics of statistics" with two largely separated time scales, offers a consistent…

Statistical Mechanics · Physics 2015-05-18 Sumiyoshi Abe

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

Using large-scale parallel numerical simulations we explore spatiotemporal chaos in Rayleigh-B\'enard convection in a cylindrical domain with experimentally relevant boundary conditions. We use the variation of the spectrum of Lyapunov…

Chaotic Dynamics · Physics 2015-06-03 Alireza Karimi , Mark R. Paul

There are multiple ways in which a stochastic system can be out of statistical equilibrium. It might be subject to time-varying forcing; or be in a transient phase on its way towards equilibrium; it might even be in equilibrium without us…

Dynamical Systems · Mathematics 2019-07-08 Péter Koltai , Hao Wu , Frank Noé , Christof Schütte

A framework for deriving probabilistic data-driven closure models is proposed for coarse-grained numerical simulations of turbulence in statistically stationary state. The approach unites the ideal large-eddy simulation model and data…

Fluid Dynamics · Physics 2025-03-25 Sagy Ephrati

This paper details a developing artistic practice around an ongoing series of works called (un)stable equilibrium. These works are the product of using modern machine toolkits to train generative models without data, an approach akin to…

Machine Learning · Computer Science 2019-10-08 Terence Broad , Mick Grierson