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Many biological systems can be described by finite Markov models. A general method for simplifying master equations is presented that is based on merging adjacent states. The approach preserves the steady-state probability distribution and…

Biological Physics · Physics 2021-03-01 David Seiferth , Peter Sollich , Stefan Klumpp

This paper considers adiabatic reduction in both discrete and continuous models of stochastic gene expression. In gene expression models, the concept of bursting is a production of several molecules simultaneously and is generally…

Probability · Mathematics 2013-01-08 Romain Yvinec

We derive a simple closed analytical expression for the total entropy production along a single stochastic trajectory of a Brownian particle diffusing on a periodic potential under an external constant force. By numerical simulations we…

Statistical Mechanics · Physics 2015-06-25 A. Gomez-Marin , I. Pagonabarraga

We design 3D-printed motor-driven active particles and find that their dynamics can be characterized using the model of overdamped chiral active Brownian particles (ABPs), as demonstrated by measured angular statistics and translational…

Soft Condensed Matter · Physics 2025-02-28 Yuxuan Zhou , Maomao Ge , Ting Wang

The development of sophisticated experimental means to control nanoscale systems has motivated efforts to design driving protocols which minimize the energy dissipated to the environment. Computational models are a crucial tool in this…

Statistical Mechanics · Physics 2016-09-14 Todd R. Gingrich , Grant M. Rotskoff , Gavin E. Crooks , Phillip L. Geissler

Lyapunov exponents of dynamical systems are defined from the rates of divergence of nearby trajectories. For stochastic systems, one typically assumes that these trajectories are generated under the "same noise realization". The purpose of…

Statistical Mechanics · Physics 2016-04-20 Tanguy Laffargue , Julien Tailleur , Frédéric van Wijland

Transport phenomena are ubiquitous in nature and known to be important for various scientific domains. Examples can be found in physics, electrochemistry, heterogeneous catalysis, physiology, etc. To obtain new information about diffusive…

Probability · Mathematics 2007-05-23 Denis S. Grebenkov

We review a few representative examples of granular experiments or models where phase separation, accompanied by domain coarsening, is a relevant phenomenon. We first elucidate the intrinsic non-equilibrium, or athermal, nature of granular…

Statistical Mechanics · Physics 2015-04-29 Andrea Baldassarri , Andrea Puglisi , Alessandro Sarracino

Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been…

Probability · Mathematics 2020-01-08 Frédéric Legoll , Tony Lelièvre , Upanshu Sharma

Herein we develop a dynamical foundation for fractional Brownian Motion. A clear relation is established between the asymptotic behaviour of the correlation function and diffusion in a dynamical system. Then, assuming that scaling is…

chao-dyn · Physics 2008-02-03 R Mannella , P Grigolini , BJ West

The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This…

Statistical Mechanics · Physics 2017-03-08 Stefano Bo , Antonio Celani

Extensive time-series encoding the position of particles such as viruses, vesicles, or individual proteins are routinely garnered in single-particle tracking experiments or supercomputing studies. They contain vital clues on how viruses…

The large deviations analysis of solutions to stochastic differential equations and related processes is often based on approximation. The construction and justification of the approximations can be onerous, especially in the case where the…

Probability · Mathematics 2008-08-28 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

By and large the behavior of stochastic gradient is regarded as a challenging problem, and it is often presented in the framework of statistical machine learning. This paper offers a novel view on the analysis of on-line models of learning…

Machine Learning · Computer Science 2018-07-17 Giovanni Bellettini , Alessandro Betti , Marco Gori

We present the exact adiabatic theory for the dynamics of the inhomogeneous density distribution of a classical fluid. Erroneous particle number fluctuations of dynamical density functional theory are absent, both for canonical and grand…

Soft Condensed Matter · Physics 2016-05-25 Daniel de las Heras , Joseph M. Brader , Andrea Fortini , Matthias Schmidt

We study the motion of an overdamped particle connected to a thermal heat bath in the presence of an external periodic potential in one dimension. When we coarse-grain, i.e., bin the particle positions using bin sizes that are larger than…

Statistical Mechanics · Physics 2023-03-01 Lucianno Defaveri , Eli Barkai , David A. Kessler

In this article we discuss several aspects of the stochastic dynamics of spin models. The paper has two independent parts. Firstly, we explore a few properties of the multi-point correlations and responses of generic systems evolving in…

Statistical Mechanics · Physics 2009-11-10 Guilhem Semerjian , Leticia F. Cugliandolo , Andrea Montanari

We experimentally realize quasistatic adiabatic processes using a single optically-trapped micro- sphere immersed in water whose effective temperature is controlled by an external random electric field. A full energetic characterization of…

Statistical Mechanics · Physics 2015-06-03 Ignacio A. Martínez , Édgar Roldán , Luis Dinis , Dmitri Petrov , Raúl A. Rica

We present a mathematical theory of dynamical fluctuations for the hard sphere gas in the Boltzmann-Grad limit. We prove that: (1) fluctuations of the empirical measure from the solution of the Boltzmann equation, scaled with the square…

Analysis of PDEs · Mathematics 2022-08-26 Thierry Bodineau , Isabelle Gallagher , Laure Saint-Raymond , Sergio Simonella

We study a model of Brownian particles which are pumped with energy by means of a non-linear friction function, for which different types are discussed. A suitable expression for a non-linear, velocity-dependent friction function is derived…

Statistical Mechanics · Physics 2016-08-31 Udo Erdmann , Werner Ebeling , Lutz Schimansky-Geier , Frank Schweitzer