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Recent investigations of turbulent circulation fluctuations have uncovered substantial insights into the statistical organization of flow structures and revealed unexpected geometric features of turbulent intermittency. Of particular…

A fundamental challenge is to understand nonequilibrium statistical mechanics starting from microscopic chaos in the equations of motion of a many-particle system. In this review we summarize recent theoretical advances along these lines.…

Chaotic Dynamics · Physics 2010-01-04 R. Klages

For optimizing a non-convex function in finite dimension, a method is to add Brownian noise to a gradient descent, allowing for transitions between basins of attractions of different minimizers. To adapt this for optimization over a space…

Probability · Mathematics 2025-05-13 Pierre Germain , Pierre Monmarché

.Stochastic models based on random diffusivities, such as the diffusing-diffusivity approach, are popular concepts for the description of non-Gaussian diffusion in heterogeneous media. Studies of these models typically focus on the moments…

Statistical Mechanics · Physics 2020-08-26 V. Sposini , D. S. Grebenkov , R. Metzler , G. Oshanin , F. Seno

This work considers the distribution of inertial particles in turbulence using the point-particle approximation. We demonstrate that the random point process formed by the positions of particles in space is a Poisson point process with…

Fluid Dynamics · Physics 2017-07-26 Lukas Schmidt , Itzhak Fouxon , Markus Holzner

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

A paradigm for isothermal, mechanical rectification of stochastic fluctuations is introduced in this paper. The central idea is to transform energy injected by random perturbations into rigid-body rotational kinetic energy. The prototype…

Probability · Mathematics 2007-10-18 Nawaf Bou-Rabee , Houman Owhadi

Motion under stochastic resetting serves to model a myriad of processes in physics and beyond, but in most cases studied to date resetting to the origin was assumed to take zero time or a time decoupled from the spatial position at the…

Statistical Mechanics · Physics 2020-10-27 Arnab Pal , Łukasz Kuśmierz , Shlomi Reuveni

Persistence, defined as the probability that a fluctuating signal has not reached a threshold up to a given observation time, plays a crucial role in the theory of random processes. It quantifies the kinetics of processes as varied as phase…

Statistical Mechanics · Physics 2022-10-12 N. Levernier , T. V. Mendes , O. Bénichou , R. Voituriez , T. Guérin

This work is a numerical experiment of stochastic motion of conservative Hamiltonian system or weakly damped Brownian particles. The objective is to prove the existence of path probability and to compute its values. By observing a large…

Statistical Mechanics · Physics 2012-02-09 Lin Tongling , Pujos Cyril , Ou Congjie , Bi Wenping , Calvayrac Florent , Wang Qiuping A

We study the stochastic dynamics of a particle with two distinct motility states. Each one is characterized by two parameters: one represents the average speed and the other represents the persistence quantifying the tendency to maintain…

Statistical Mechanics · Physics 2021-07-16 M. Reza Shaebani , Heiko Rieger

We address the reachability problem for continuous-time stochastic dynamic systems. Our objective is to present a unified framework that characterizes the reachable set of a dynamic system in the presence of both stochastic disturbances and…

Systems and Control · Electrical Eng. & Systems 2024-09-04 Saber Jafarpour , Zishun Liu , Yongxin Chen

Turbulence closure for the weakly nonlinear stochastic waves requires, besides weak nonlinearity, randomness in both the phases and the amplitudes of the Fourier modes. This randomness, once present initially, must remain over the nonlinear…

Mathematical Physics · Physics 2007-05-23 Yeontaek Choi , Yuri V. Lvov , Sergey Nazarenko

Entropy production in stochastic mechanical systems is examined here with strict bounds on its rate. Stochastic mechanical systems include pure diffusions in Euclidean space or on Lie groups, as well as systems evolving on phase space for…

Mathematical Physics · Physics 2022-01-12 Gregory S. Chirikjian

The classical statistics of turbulence are shown to be not specific to turbulence and can be derived from a solution for recurring unsteady state viscous flow. Care must be exercised in using them to make deductions about turbulence…

Fluid Dynamics · Physics 2010-01-14 Trinh Khanh Tuoc

In our recent works we proposed a theory of turbulence in inertial gas flow via the mean field effect of an intermolecular potential. We found that, in inertial flow, turbulence indeed spontaneously develops from a laminar initial…

Fluid Dynamics · Physics 2022-12-14 Rafail V. Abramov

This paper uses dynamical invariants to describe the evolution of collisionless systems subject to time-dependent gravitational forces without resorting to maximum-entropy probabilities. We show that collisionless relaxation can be viewed…

Astrophysics of Galaxies · Physics 2015-06-03 Jorge Peñarrubia

Spontaneous stochasticity is a modern paradigm for turbulent transport at infinite Reynolds numbers. It suggests that tracer particles advected by rough turbulent flows and subject to additional thermal noise, remain non-deterministic in…

Fluid Dynamics · Physics 2023-06-21 André Luís Peixoto Considera , Simon Thalabard

This paper attempts to make feasible the evolutionary emergence of novelty in a supposedly deterministic world which behavior is associated with those of the mathematical dynamical systems. The work was motivated by the observation of…

Adaptation and Self-Organizing Systems · Physics 2024-06-26 R. Herrero , F. Pi , J. Rius , G. Orriols

Analytical (rational) mechanics is the mathematical structure of Newtonian deterministic dynamics developed by D'Alembert, Langrange, Hamilton, Jacobi, and many other luminaries of applied mathematics. Diffusion as a stochastic process of…

Mathematical Physics · Physics 2012-09-03 Hao Ge , Hong Qian