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We study the large-scale dynamics of the solution to a nonlinear stochastic heat equation (SHE) in dimensions $d \geq 3$ with long-range dependence. This equation is driven by multiplicative Gaussian noise, which is white in time and…

Probability · Mathematics 2025-01-16 Luca Gerolla , Martin Hairer , Xue-Mei Li

In this paper we present a general framework in which one can rigorously study the effect of spatio-temporal noise on traveling waves, stationary patterns and oscillations that are invariant under the action of a finite-dimensional set of…

Dynamical Systems · Mathematics 2020-06-24 James MacLaurin

We provide a generalized formulation of fluctuating hydrodynamics for the far-from-equilibrium noisy medium. As an example, we consider a noisy plasma experiencing Bjorken expansion, for which the leading order evolution is captured by…

Nuclear Theory · Physics 2022-06-28 Zenan Chen , Derek Teaney , Li Yan

This note is devoted to a discussion of the potential links and differences between three topics: regularization by noise, convex integration, spontaneous stochasticity. All of them deal with the effect on large scales of a small-scale…

Probability · Mathematics 2024-08-13 Franco Flandoli , Marco Rehmeier

The hydrodynamical model of the collective behavior of animals consists of the Euler equation with additional non-local forcing terms representing the repulsive and attractive forces among individuals. This paper deals with the system…

Analysis of PDEs · Mathematics 2021-07-01 Pavel Ludvik , Vaclav Macha

We derive the second-order hydrodynamic equation and the microscopic formulae of the relaxation times as well as the transport coefficients systematically from the relativistic Boltzmann equation. Our derivation is based on a novel…

High Energy Physics - Phenomenology · Physics 2016-02-01 Kyosuke Tsumura , Yuta Kikuchi , Teiji Kunihiro

Hydrodynamic behavior is a general feature of interacting systems with many degrees of freedom constrained by conservation laws. To date hydrodynamic scaling in relativistic quantum systems has been observed in many high energy settings,…

High Energy Physics - Phenomenology · Physics 2009-11-07 Luis M. A. Bettencourt , Fred Cooper , Karen Pao

We present a finite difference method to solve a new type of nonlocal hydrodynamic equations that arise in the theory of spatially inhomogeneous Bloch oscillations in semiconductor superlattices. The hydrodynamic equations describe the…

Mesoscale and Nanoscale Physics · Physics 2012-05-08 M. Álvaro , M. Carretero , L. L. Bonilla

We introduce a lattice random walk discretisation scheme for stochastic differential equations (SDEs) that samples binary or ternary increments at each step, suppressing complex drift and diffusion computations to simple 1 or 2 bit random…

Numerical Analysis · Mathematics 2026-02-18 Samuel Duffield , Maxwell Aifer , Denis Melanson , Zach Belateche , Patrick J. Coles

Minimax optimization problems have attracted a lot of attention over the past few years, with applications ranging from economics to machine learning. While advanced optimization methods exist for such problems, characterizing their…

Machine Learning · Computer Science 2024-02-21 Enea Monzio Compagnoni , Antonio Orvieto , Hans Kersting , Frank Norbert Proske , Aurelien Lucchi

Instability and rupture dynamics of a liquid nano-thread, subjected to external hydrodynamic perturbations, are captured by a stochastic lubrication equation (SLE) incorporating thermal fluctuations via Gaussian white noise. Linear…

Fluid Dynamics · Physics 2024-11-20 Zhao Zhang , Chengxi Zhao , Ting Si

Discovering the underlying relationships among variables from temporal observations has been a longstanding challenge in numerous scientific disciplines, including biology, finance, and climate science. The dynamics of such systems are…

Machine Learning · Computer Science 2024-05-07 Benjie Wang , Joel Jennings , Wenbo Gong

Hydrodynamic equations (HDEQs) are derived which describe spatio-temporal evolutions of the electron temperature and the chemical potential of two-dimensional systems in strong magnetic fields in states with large diagonal resistivity…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 Hiroshi Akera

A simple exactly solvable kinetic model for the non-linear inelastic hard sphere Boltzmann equation is used to explore the relevance of hydrodynamics for a granular gas. The equation predicts a non-trivial homogeneous cooling state (HCS),…

Soft Condensed Matter · Physics 2007-05-23 Aparna Baskaran , James W. Dufty

Many time series are effectively generated by a combination of deterministic continuous flows along with discrete jumps sparked by stochastic events. However, we usually do not have the equation of motion describing the flows, or how they…

Machine Learning · Computer Science 2020-01-09 Junteng Jia , Austin R. Benson

This paper is concerned with developing and analyzing two novel implicit temporal discretization methods for the stochastic semilinear wave equations with multiplicative noise. The proposed methods are natural extensions of well-known…

Numerical Analysis · Mathematics 2024-08-26 Xiaobing Feng , Yukun Li , Liet Vo

We study the effects of hydrodynamic fluctuations in non-boost-invariant longitudinal expansion of matter formed in relativistic heavy ion collisions. We formulate the theory of thermal noise within second-order viscous hydrodynamics…

Nuclear Theory · Physics 2018-09-26 Chandrodoy Chattopadhyay , Subrata Pal

We consider the out-of-equilibrium dynamics of an interacting integrable system in the presence of an external dephasing noise. In the limit of large spatial correlation of the noise, we develop an exact description of the dynamics of the…

Statistical Mechanics · Physics 2020-10-21 Alvise Bastianello , Jacopo De Nardis , Andrea De Luca

The formation of the beam halo in charged particle accelerators is studied in the framework of a stochastic-hydrodynamic model for the collective motion of the particle beam. In such a stochastic-hydrodynamic theory the density and the…

Statistical Mechanics · Physics 2009-11-10 Nicola Cufaro Petroni , Salvatore De Martino , Silvio De Siena , Fabrizio Illuminati

Stochastic differential equations (SDEs) and stochastic partial differential equations (SPDEs) are fundamental for modeling stochastic dynamics across the natural sciences and modern machine learning. Learning their solution operators with…

Machine Learning · Computer Science 2026-01-30 Dai Shi , Lequan Lin , Andi Han , Luke Thompson , José Miguel Hernández-Lobato , Zhiyong Wang , Junbin Gao
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