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Recent large deviation results have provided general lower bounds for the fluctuations of time-integrated currents in the steady state of stochastic systems. A corollary are so-called thermodynamic uncertainty relations connecting precision…

Statistical Mechanics · Physics 2017-03-29 Juan P. Garrahan

The fluctuation-dissipation relation is calculated for a class of stochastic models obeying a master equation. The transition rates are assumed to obey detailed balance also in the presence of a field. It is shown that in general the linear…

Statistical Mechanics · Physics 2016-08-31 Gregor Diezemann

A calculational approach in fluid turbulence is presented. Use is made of the attracting nature of the fluid-dynamic dynamical system. An approximate approach is offerred that effectively propagates the statistics in time. Loss of…

Fluid Dynamics · Physics 2007-05-23 Edsel A. Ammons

We derive the distribution of particle currents for a system of interacting active Brownian particles in the long time limit using large deviation theory and a weighted many body expansion. We find the distribution is non-Gaussian, except…

Statistical Mechanics · Physics 2018-12-19 Trevor GrandPre , David T. Limmer

We propose a model of random diffusion to investigate flow fluctuations in complex networks. We derive an analytical law showing that the dependence of fluctuations with the mean traffic in a network is ruled by the delicate interplay of…

Physics and Society · Physics 2008-05-21 S. Meloni , J. Gomez-Gardenes , V. Latora , Y. Moreno

We derive here Lagrangian fluctuation-dissipation relations for advected scalars in wall-bounded flows. The relations equate the dissipation rate for either passive or active scalars to the variance of scalar inputs from the initial values,…

Fluid Dynamics · Physics 2017-10-13 Theodore D. Drivas , Gregory L. Eyink

We develop a fluctuation theory of connectivities for subcritical random cluster models. The theory is based on a comprehensive nonperturbative probabilistic description of long connected clusters in terms of essentially one-dimensional…

Probability · Mathematics 2008-08-28 Massimo Campanino , Dmitry Ioffe , Yvan Velenik

The relationships between reversible Carnot cycles, the absence of perpetual motion machines and the existence of a non-decreasing, globally unique entropy function forms the starting point of many textbook presentations of the foundations…

Statistical Mechanics · Physics 2015-05-14 O. J. E. Maroney

In this perspective we consider how modern statistical mechanics and response theory can be applied to understand the response of polar molecules to an applied electric field and the fluctuations in these systems. Results that are…

Statistical Mechanics · Physics 2024-01-08 Debra J. Searles , Stephen Sanderson

From single vehicle data a number of new empirical results concerning the density-dependence of the velocity distribution and its moments as well as the characteristics of their temporal fluctuations have been determined. These are utilized…

Statistical Mechanics · Physics 2009-10-31 Dirk Helbing

We derive an extended fluctuation relation for an open system coupled with two reservoirs under adiabatic one-cycle modulation. We confirm that the geometric phase caused by the Berry-Sintisyn-Nemenman curvature in the parameter space…

Statistical Mechanics · Physics 2020-07-15 Yuki Hino , Hisao Hayakawa

A statistical mechanical study of fluidized granular media is presented. Using a special energy injection mechanism, homogeneous fluidized stationary states are obtained. Molecular dynamics simulations and theoretical analysis of the…

Statistical Mechanics · Physics 2009-10-31 R. Soto , M. Mareschal

The article provides a unitary and complete solution to the fluctuation-dissipation relations for particle hydromechanics in a generic fluid, accounting for the hydrodynamic fluid-particle interactions (including arbitrary memory kernels in…

Statistical Mechanics · Physics 2024-12-30 Massimiliano Giona , Giuseppe Procopio , Chiara Pezzotti

We demonstrate several explicit duality mappings between elasticity of two-dimensional crystals and fracton tensor gauge theories, expanding on recent works by two of the present authors. We begin by dualizing the quantum elasticity theory…

Strongly Correlated Electrons · Physics 2019-11-01 Michael Pretko , Zhengzheng Zhai , Leo Radzihovsky

We introduce a model for a periodically driven electron pump that sequentially interact with an arbitrary number of heat and particle reservoirs. Exact expressions for the thermodynamic fluxes, such as entropy production and particle flows…

Statistical Mechanics · Physics 2021-09-03 Pedro E. Harunari , Carlos E. Fiore , Karel Proesmans

We find that in "two-photon"-like processes in the scalar $\varphi^3_E$ model and also in hadron-pair production arising from the collisions of a real (transversely polarized) and a highly virtual, longitudinally polarized, photon in QCD,…

High Energy Physics - Phenomenology · Physics 2008-11-27 I. V. Anikin , I. O. Cherednikov , N. G. Stefanis , O. V. Teryaev

For a system to qualify as a quantum fluid, quantum-statistical effects should operate in addition to quantum-mechanical ones. Here, we address the hitherto unexplored dynamical condition for the quantum-statistical effects to be…

Quantum Physics · Physics 2023-03-21 Alessio Zaccone , Kostya Trachenko

For a class of coalescing stochastic flows on the real line the existence of dual flows is proved. A stochastic flow and its dual are constructed as a forward and backward perfect cocycles over the same metric dynamical system. The metric…

Probability · Mathematics 2019-03-22 Georgii V. Riabov

The recent development of the theory of fluctuation relations has led to new insights into the ever-lasting question of how irreversible behavior emerges from time-reversal symmetric microscopic dynamics. We provide an introduction to…

Popular Physics · Physics 2011-12-20 Michele Campisi , Peter Hänggi

The notion of the stationary equilibrium ensemble has played a central role in statistical mechanics. In machine learning as well, training serves as generalized equilibration that drives the probability distribution of model parameters…

Machine Learning · Statistics 2018-12-24 Sho Yaida