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Nonlinear Fokker-Planck equations play a major role in modeling large systems of interacting particles with a proved effectiveness in describing real world phenomena ranging from classical fields such as fluids and plasma to social and…

Numerical Analysis · Mathematics 2023-11-23 Giacomo Dimarco , Lorenzo Pareschi , Mattia Zanella

This paper reports on a macroscopic fluctuation theory developed over the last ten years in collaboration with L. Bertini, A. De Sole, D. Gabrielli and C. Landim. This theory has been inspired by and tested on stochastic models of…

Statistical Mechanics · Physics 2015-05-18 Giovanni Jona-Lasinio

The stochastic quantization of dissipative systems is discussed. It is shown that in order to stochastically quantize a system with dissipation, one has to restrict the Fourier transform of the space-time variable to the positive half…

High Energy Physics - Theory · Physics 2009-10-28 Rodanthy Tzani

An open question in the field of non-equilibrium statistical physics is whether there exists a unique way through which non-equilibrium systems equilibrate irrespective of how far they are away from equilibrium. To answer this question we…

Statistical Mechanics · Physics 2014-03-14 P. Barat , A. Giri , Nilangshu K. Das , M. Bhattacharya , A. Dutta

Recent experimental and theoretical works have shown that giant fluctuations are present during diffusion in liquid systems. We use linearized fluctuating hydrodynamics to calculate the net mass transfer due to these non equilibrium…

Statistical Mechanics · Physics 2009-10-31 Doriano Brogioli , Alberto Vailati

It has been generally recognized that stochasticity can play an important role in the information processing accomplished by reaction networks in biological cells. Most treatments of that stochasticity employ Gaussian noise even though it…

Molecular Networks · Quantitative Biology 2015-05-30 Neda Bostani , David A. Kessler , Nadav M. Shnerb , Wouter-Jan Rappel , Herbert Levine

Fluctuations arising in nonlinear dissipative systems (diode, transistors, chemical reaction, etc.) subject to an external drive (voltage, chemical potential, etc.) are well known to elude any simple characterization such as the…

Statistical Mechanics · Physics 2023-07-10 Jean-Charles Delvenne , Léopold Van Brandt

Fluctuations in small biological systems can be crucial for their function. Large-deviation theory characterizes such rare events from the perspective of stochastic processes. In most cases it is very difficult to directly determine the…

Statistical Mechanics · Physics 2013-12-03 Artur Wachtel

When the complete understanding of a complex system is not available, as, e.g., for systems considered in the real-world, we need a top-down approach to complexity. In this approach one may start with the desire to understand general…

Statistical Mechanics · Physics 2019-05-22 Joachim Peinke , Mohammad Reza Rahimi Tabar , Matthias Wächter

We propose a method for approximating the large deviation rate function of time-integrated observables of diffusion processes, used in statistical physics to characterize the fluctuations of nonequilibrium systems. The method is based on…

Statistical Mechanics · Physics 2026-01-15 Pelerine Tsobgni Nyawo , Hugo Touchette

The fluctuation theorem characterizes the distribution of the dissipation in nonequilibrium systems and proves that the average dissipation will be positive. For a large system with no external source of fluctuation, fluctuations in…

Statistical Mechanics · Physics 2018-12-18 Guillaume Michel , Debra J. Searles

In this paper we study macroscopic density equations in which the diffusion coefficient depends on a weighted spatial average of the density itself. We show that large differences (not present in the local density-dependence case) appear…

Statistical Mechanics · Physics 2009-11-11 Cristobal Lopez

Complex systems are characterized by a huge number of degrees of freedom often interacting in a non-linear manner. In many cases macroscopic states, however, can be characterized by a small number of order parameters that obey stochastic…

Data Analysis, Statistics and Probability · Physics 2012-02-20 David Kleinhans

In the hydrodynamic theory, the non-equilibrium dynamics of a many-body system is approximated, at large scales of space and time, by irreversible relaxation to local entropy maximisation. This results in a convective equation corrected by…

Statistical Mechanics · Physics 2025-12-02 Friedrich Hübner , Leonardo Biagetti , Jacopo De Nardis , Benjamin Doyon

Aim of this note is to analyse branching Brownian motion within the class of models introduced in the recent paper [4] and called chemical diffusion master equations. These models provide a description for the probabilistic evolution of…

Probability · Mathematics 2024-01-23 Alberto Lanconelli , Berk Tan Perçin

The Langevin equation is a common tool to model diffusion at a single-particle level. In non-homogeneous environments, such as aqueous two-phase systems or biological condensates with different diffusion coefficients in different phases,…

The complex dynamics of physical systems can often be modeled with stochastic differential equations. However, computational constraints inhibit the estimation of dynamics from large time-series datasets. I present a method for estimating…

Data Analysis, Statistics and Probability · Physics 2023-11-02 William Davis

Given a reaction-advection-diffusion system modelling the sulphation phenomenon, we derive a single regularised non-conservative and path-dependent nonlinear partial differential equation and propose a probabilistic interpretation via a…

Probability · Mathematics 2025-10-14 Daniela Morale , Leonardo Tarquini , Stefania Ugolini

We propose exact results for the full counting statistics, or the scaled cumulant generating function, pertaining to the transfer of arbitrary conserved quantities across an interface in homogeneous integrable models out of equilibrium. We…

Statistical Mechanics · Physics 2020-01-22 Jason Myers , M. J. Bhaseen , Rosemary J. Harris , Benjamin Doyon

We introduce a guided stochastic sampling method that augments sampling from diffusion models with physics-based guidance derived from partial differential equation (PDE) residuals and observational constraints, ensuring generated samples…

Machine Learning · Computer Science 2026-05-28 Andrew Millard , Fredrik Lindsten , Zheng Zhao
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