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Related papers: Exact Moment Scaling from Multiplicative Noise

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We consider a class of models describing an ensemble of identical interacting agents subject to multiplicative noise. In the thermodynamic limit, these systems exhibit continuous and discontinuous phase transitions in a, generally,…

Statistical Mechanics · Physics 2023-10-27 Niccolò Zagli , Grigorios A. Pavliotis , Valerio Lucarini , Alexander Alecio

Denoising diffusion models are a class of generative models which have recently achieved state-of-the-art results across many domains. Gradual noise is added to the data using a diffusion process, which transforms the data distribution into…

Machine Learning · Statistics 2024-06-28 Francisco Vargas , Teodora Reu , Anna Kerekes , Michael M Bronstein

This paper is concerned with the problem of regularization by noise of systems of reaction-diffusion equations with mass control. It is known that $\textit{strong}$ solutions to such systems of PDEs may blow-up in finite time. Moreover, for…

Analysis of PDEs · Mathematics 2023-11-30 Antonio Agresti

Evolution of a system of diffusing and proliferating mortal reactants is analyzed in the presence of randomly moving catalysts. While the continuum description of the problem predicts reactant extinction as the average growth rate becomes…

Soft Condensed Matter · Physics 2009-10-31 N. M. Shnerb , E. Bettelheim , Y. Louzoun , O. Agam , S. Solomon

Linear systems with many degrees of freedom containing multiplicative and additive noise are considered. The steady state probability distribution for equations of this kind is examined. With multiplicative white noise it is shown that…

chao-dyn · Physics 2009-10-22 J. M. Deutsch

Moment methods are classical approaches that approximate the mesoscopic radiative transfer equation by a system of macroscopic moment equations. An expansion in the angular variables transforms the original equation into a system of…

Mathematical Physics · Physics 2023-08-17 Martin Frank , Benjamin Seibold

In assemblies of globally coupled dynamical units, weak noise perturbing independently the individual units can cause anomalous dispersion in the synchronized cloud of the units in the phase space. When the noise-free dynamics of the…

Chaotic Dynamics · Physics 2016-09-07 Jun-nosuke Teramae , Yoshiki Kuramoto

Event correlation between aftershocks in the coherent noise model is studied by making use of natural time, which has recently been introduced in complex time-series analysis. It is found that the aging phenomenon and the associated scaling…

Statistical Mechanics · Physics 2009-11-10 Ugur Tirnakli , Sumiyoshi Abe

A finite size scaling theory, originally developed only for transitions to absorbing states [Phys. Rev. E {\bf 92}, 062126 (2015)], is extended to distinct sorts of discontinuous nonequilibrium phase transitions. Expressions for quantities…

Statistical Mechanics · Physics 2018-06-13 Marcelo M. de Oliveira , M. G. E. da Luz , Carlos E. Fiore

The effect of a change of noise amplitudes in overdamped diffusive systems is linked to their unperturbed behavior by means of a nonequilibrium fluctuation-response relation. This formula holds also for systems with state-independent…

Statistical Mechanics · Physics 2017-06-13 Cem Yolcu , Antoine Bérut , Gianmaria Falasco , Artyom Petrosyan , Sergio Ciliberto , Marco Baiesi

Along with recent diffusion models, randomized smoothing has become one of a few tangible approaches that offers adversarial robustness to models at scale, e.g., those of large pre-trained models. Specifically, one can perform randomized…

Machine Learning · Computer Science 2023-10-30 Jongheon Jeong , Jinwoo Shin

We present a multiscale approach to model diffusion in a crowded environment and its effect on the reaction rates. Diffusion in biological systems is often modeled by a discrete space jump process in order to capture the inherent noise of…

Subcellular Processes · Quantitative Biology 2016-03-18 Lina Meinecke

Diffusion generative models unlock new possibilities for inverse problems as they allow for the incorporation of strong empirical priors in scientific inference. Recently, diffusion models are repurposed for solving inverse problems using…

Many systems in nature and laboratories are far from equilibrium and exhibit significant fluctuations, invalidating the key assumptions of small fluctuations and short memory time in or near equilibrium. A full knowledge of Probability…

Statistical Mechanics · Physics 2017-11-15 Eun-jin Kim , Lucille-Marie Tenk`es , Rainer Hollerbach , Ovidiu Radulescu

We consider the response of a dynamical system driven by external adiabatic fluctuations. Based on the `adiabatic following approximation' we have made a systematic separation of time-scales to carry out an expansion in $\alpha |\mu|^{-1}$,…

Statistical Mechanics · Physics 2009-10-31 S. K. Banik , J. R. Chaudhuri , D. S. Ray

In this paper, we establish smoothness of moments of the solutions of discrete coagulation-diffusion systems. As key assumptions, we suppose that the coagulation coefficients grow at most sub-linearly and that the diffusion coefficients…

Analysis of PDEs · Mathematics 2015-11-19 Maxime Breden , Laurent Desvillettes , Klemens Fellner

We construct importance sampling schemes for stochastic differential equations with small noise and fast oscillating coefficients. Standard Monte Carlo methods perform poorly for these problems in the small noise limit. With multiscale…

Probability · Mathematics 2012-02-03 Paul Dupuis , Konstantinos Spiliopoulos , Hui Wang

The paper deals with the problem of large-time behaviour of trajectories for discrete-time dynamical systems driven by a random noise. Assuming that the phase space is finite-dimensional and compact, and the noise is a Markov process with a…

Probability · Mathematics 2025-07-15 Sergei Kuksin , Armen Shirikyan

We extend slow manifolds near a transcritical singularity in a fast-slow system given by the explicit Euler discretization of the corresponding continuous-time normal form. The analysis uses the blow-up method and direct trajectory-based…

Dynamical Systems · Mathematics 2019-07-16 Maximilian Engel , Christian Kuehn

Moment estimation for stochastic differential equations (SDEs) is fundamental to the formal reasoning and verification of stochastic dynamical systems, yet remains challenging and is rarely available in closed form. In this paper, we study…

Systems and Control · Electrical Eng. & Systems 2026-03-04 Shenghua Feng , Jie An , Naijun Zhan , Fanjiang Xu