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The way particles interact with turbulent structures, particularly in regions of high vorticity and strain rate, has been investigated in simulations of homogeneous turbulence and in simple flows which have a periodic or persistent…

Fluid Dynamics · Physics 2012-05-28 Michael W. Reeks

Reaction-diffusion systems driven far from thermodynamic equilibrium through the injection of energy can support multiple distinct spatial patterns that persist as long-lived dynamical phases. The stability of these metastable phases is not…

Statistical Mechanics · Physics 2026-03-13 Eric R. Heller , David T. Limmer

We theoretically investigate how information flows when two particles interact with each other. Understanding the physical mechanisms of directional information flow is crucial for advancing information thermodynamics and stochastic…

Statistical Mechanics · Physics 2026-03-12 Tenta Tani

The information processing capacity of a complex dynamical system is reflected in the partitioning of its state space into disjoint basins of attraction, with state trajectories in each basin flowing towards their corresponding attractor.…

Disordered Systems and Neural Networks · Physics 2007-05-23 Peter Krawitz , Ilya Shmulevich

Non-equilibrium fluctuations of various stochastic variables, such as work and entropy production, have been widely discussed recently in the context of large deviations, cumulants and fluctuation relations. Typically, one looks at the…

Statistical Mechanics · Physics 2016-08-03 Keiji Saito , Abhishek Dhar

This is a set of four lectures devoted to simple ideas about turbulent transport, a ubiquitous non-equilibrium phenomenon. In the course similar to that given by the author in 2006 in Warwick [45], we discuss lessons which have been learned…

Chaotic Dynamics · Physics 2008-06-12 Krzysztof Gawedzki

The rotational dynamics of anisotropic particles advected in a turbulent fluid flow are important in many industrial and natural setting. Particle rotations are controlled by small scale properties of turbulence that are nearly universal,…

Fluid Dynamics · Physics 2013-04-19 Shima Parsa , Enrico Calzavarini , Federico Toschi , Greg A. Voth

We calculate and verify with simulations the ratio between the average translational and rotational energies of systems with rough, inelastic particles, either forced or freely cooling. The ratio shows non-equipartition of energy. In…

Statistical Mechanics · Physics 2009-10-31 S. McNamara , S. Luding

We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent…

Fluid Dynamics · Physics 2016-04-28 Rodrigo M. Pereira , Christophe Garban , Laurent Chevillard

When very small particles are suspended in a fluid in motion, they tend to follow the flow. How such tracer particles are mixed, transported, and dispersed by turbulent flow has been successfully described by statistical models. Heavy…

Fluid Dynamics · Physics 2023-12-21 J. Bec , K. Gustavsson , B. Mehlig

The identification of cells and particles based on their transport properties in microfluidic devices is crucial for numerous applications in biology and medicine. Neutrally buoyant particles transported in microfluidic channels, migrate…

Stochastic thermodynamics provides the framework to analyze thermodynamic laws and quantities along individual trajectories of small but fully observable systems. If the observable level fails to capture all relevant degrees of freedom,…

Statistical Mechanics · Physics 2024-07-01 Julius Degünther , Jann van der Meer , Udo Seifert

Biological machines like molecular motors and enzymes operate in dynamic cycles representable as stochastic flows on networks. Current stochastic dynamics describes such flows on fixed networks. Here, we develop a scalable approach to…

Statistical Mechanics · Physics 2026-03-02 Ying-Jen Yang , Ken A. Dill

We introduce an index based on information theory to quantify the stationarity of a stochastic process.The index compares on the one hand the information contained in the increment at the time scale $\tau$ of the process at time $t$ with,…

Data Analysis, Statistics and Probability · Physics 2021-12-02 Carlos Granero-Belinchon , Stéphane G. Roux , Nicolas B. Garnier

While entropy changes are the usual subject of fluctuation theorems, we seek fluctuation relations involving time-symmetric quantities, namely observables that do not change sign if the trajectories are observed backward in time. We find…

Statistical Mechanics · Physics 2015-11-04 Marco Baiesi , Gianmaria Falasco

Diffusive transport of particles or, more generally, small objects is a ubiquitous feature of physical and chemical reaction systems. In configurations containing confining walls or constrictions transport is controlled both by the…

Statistical Mechanics · Physics 2009-01-22 P. Sekhar Burada , Peter Hanggi , Fabio Marchesoni , Gerhard Schmid , Peter Talkner

Modeling transformations between arbitrary data distributions is a fundamental scientific challenge, arising in applications like drug discovery and evolutionary simulation. While flow matching offers a natural framework for this task, its…

Machine Learning · Computer Science 2025-10-09 Shiye Su , Yuhui Zhang , Linqi Zhou , Rajesh Ranganath , Serena Yeung-Levy

At the macroscopic scale, many important models of collective motion fall into the class of kinematic flows for which both velocity and diffusion terms depend only on particle density. When total particle numbers are fixed and finite,…

Adaptation and Self-Organizing Systems · Physics 2022-04-12 Jeremy Worsfold , Tim Rogers , Paul Milewski

This article is an invitation. It is, first, an invitation to consider as a subject worthy of attention the wide range of situations where small discrete elements, either bubbles, droplets or solid particles, are embedded in turbulent…

Fluid Dynamics · Physics 2023-11-06 Jean-Pierre Minier , Christophe Henry

Reservoir computing systems are constructed using a driven dynamical system in which external inputs can alter the evolving states of a system. These paradigms are used in information processing, machine learning, and computation. A…

Neural and Evolutionary Computing · Computer Science 2023-04-26 G Manjunath , Juan-Pablo Ortega