English
Related papers

Related papers: Steady-State Equilibrium and Nonequilibrium Noisy …

200 papers

We present a simple analytical tool which gives an approximate insight into the stationary behavior of nonlinear systems undergoing the influence of a weak and rapid noise from one dominating source, e.g. the kinetic equations describing a…

Quantitative Methods · Quantitative Biology 2008-08-13 Anna Ochab-Marcinek

We construct and investigate Boolean networks that follow a given reliable trajectory in state space, which is insensitive to fluctuations in the updating schedule, and which is also robust against noise. Robustness is quantified as the…

Biological Physics · Physics 2010-12-02 Christoph Schmal , Tiago P. Peixoto , Barbara Drossel

One of the key features of non-equilibrium steady states (NESS) is the presence of nontrivial probability currents. We propose a general classification of NESS in which these currents play a central distinguishing role. As a corollary, we…

Statistical Mechanics · Physics 2009-11-13 R. K. P. Zia , B. Schmittmann

Non-equilibrium steady states (NESS) of Markov processes give rise to non-trivial cyclic probability fluxes. Cycle decompositions of the steady state offer an effective description of such fluxes. Here, we present an iterative cycle…

Regulatory networks describe the interactions between molecular or cellular regulators, like transcription factors and genes in gene regulatory networks, kinases and their receptors in signalling networks, or neurons in neural networks. A…

Molecular Networks · Quantitative Biology 2022-12-29 Niklas Bonacker , Johannes Berg

Intrinsic stochasticity can induce highly non-trivial effects on dynamical systems, including stochastic and coherence resonance, noise induced bistability, noise-induced oscillations, to name but a few. In this paper we revisit a mechanism…

Disordered Systems and Neural Networks · Physics 2018-07-17 Serena di Santo , Pablo Villegas , Raffaella Burioni , Miguel A. Muñoz

We study a generic family of nonlinear dynamics on undirected networks generalising linear consensus. We find a compact expression for its equilibrium points in terms of the topology of the network and classify their stability using the…

Dynamical Systems · Mathematics 2021-12-07 Marc Homs-Dones , Karel Devriendt , Renaud Lambiotte

Networked dynamical systems, i.e., systems of dynamical units coupled via nontrivial interaction topologies, constitute models of broad classes of complex systems, ranging from gene regulatory and metabolic circuits in our cells to…

Adaptation and Self-Organizing Systems · Physics 2024-03-12 Xiaozhu Zhang , Marc Timme

The dynamical organization in the presence of noise of a Boolean neural network with random connections is analyzed. For low levels of noise, the system reaches a stationary state in which the majority of its elements acquire the same…

Disordered Systems and Neural Networks · Physics 2007-05-23 Cristian Huepe , Maximino Aldana

In the 1980s it was theoretically predicted that correlations of various observables in a fluid in a non-equilibrium steady state (NESS) are extraordinarily long-ranged, extending, in a well-defined sense, over the size of the system. This…

Statistical Mechanics · Physics 2024-01-22 T. R. Kirkpatrick , D. Belitz , J. R. Dorfman

Further analysis and experimentation is carried out in this paper for a chaotic dynamic model, viz. the Nonlinear Dynamic State neuron (NDS). The analysis and experimentations are performed to further understand the underlying dynamics of…

Neural and Evolutionary Computing · Computer Science 2014-08-19 Mohammad Alhawarat , Waleed Nazih , Mohammad Eldesouki

A modified fluctuation-dissipation-theorem (MFDT) for a non-equilibrium steady state (NESS) is experimentally checked by studying the position fluctuations of a colloidal particle whose motion is confined in a toroidal optical trap. The…

The quasi-static evolution of steady states far from equilibrium is investigated from the point of view of quantum statistical mechanics. As a concrete example of a thermodynamic system, a two-level quantum dot coupled to several reservoirs…

Mathematical Physics · Physics 2009-11-11 Walid K. Abou Salem

A fundamental premise of statistical physics is that the particles in a physical system are interchangeable, and hence the state of each specific component is representative of the system as a whole. This assumption breaks down for complex…

Physics and Society · Physics 2025-12-16 Neil G. MacLaren , Baruch Barzel , Naoki Masuda

Predicting how systems respond to external perturbations far from equilibrium remains a fundamental challenge across physics, chemistry, and biology. We present a unified response framework for stochastic Markov dynamics that integrates…

Statistical Mechanics · Physics 2026-05-13 Jiming Zheng , Zhiyue Lu

The past twenty years have seen a resurgence of interest in nonequilibrium thermodynamics, thanks to advances in the theory of stochastic processes and in their thermodynamic interpretation. Fluctuation theorems provide fundamental…

Statistical Mechanics · Physics 2017-11-16 Robert Marsland , Jeremy England

We show that coupling together two closed thermodynamic systems that independently attain equilibrium may give rise to a nonequilibrium stationary state (NESS) with a persistent, non-vanishing current. We study a simple example that is…

Statistical Mechanics · Physics 2014-01-23 Hernán Larralde , David P. Sanders

In thermodynamic equilibrium, the fluctuation-dissipation theorem links thermal fluctuations and dissipation. Biological systems, however, are driven out of equilibrium by internal processes that produce additional, active fluctuations.…

Soft Condensed Matter · Physics 2026-01-29 Ashot Matevosyan , Frank Jülicher , Ricard Alert

The archetypal system demonstrating stochastic resonance is nothing more than a threshold triggered device. It consists of a periodic modulated input and noise. Every time an output crosses the threshold the signal is recorded. Such a…

Statistical Mechanics · Physics 2014-01-10 Krzysztof Szczepaniec , Bartlomiej Dybiec

When neural networks are trained from data to simulate the dynamics of physical systems, they encounter a persistent challenge: the long-time dynamics they produce are often unphysical or unstable. We analyze the origin of such…

Machine Learning · Computer Science 2024-06-21 Daniel Floryan