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We consider stochastic dynamical systems defined by differential equations with a uniform random time delay. The latter equations are shown to be equivalent to deterministic higher-order differential equations: for an $n$-th order equation…

Statistical Mechanics · Physics 2011-10-11 P. L. Krapivsky , J. M. Luck , K. Mallick

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

Invariant foliations are complicated random sets useful for describing and understanding the qualitative behaviors of nonlinear dynamical systems. We will consider invariant foliations for stochastic partial differential equation with…

Dynamical Systems · Mathematics 2013-11-20 Zhongkai Guo

Stochastic averaging allows for the reduction of the dimension and complexity of stochastic dynamical systems with multiple time scales, replacing fast variables with statistically equivalent stochastic processes in order to analyze…

Probability · Mathematics 2015-02-25 William F. Thompson , Rachel A. Kuske , Adam H. Monahan

The theory of slow manifolds is an important tool in the study of deterministic dynamical systems, giving a practical method by which to reduce the number of relevant degrees of freedom in a model, thereby often resulting in a considerable…

Statistical Mechanics · Physics 2013-07-01 George W A Constable , Alan J McKane , Tim Rogers

We consider a reaction-diffusion equation on a network subjected to dynamic boundary conditions, with time delayed behaviour, also allowing for multiplicative Gaussian noise perturbations. Exploiting semigroup theory, we rewrite the…

Probability · Mathematics 2017-02-17 Francesco Cordoni , Luca Di Persio

Modelling stochastic systems has many important applications. Normal form coordinate transforms are a powerful way to untangle interesting long term macroscale dynamics from detailed microscale dynamics. We explore such coordinate…

Dynamical Systems · Mathematics 2009-11-13 A. J. Roberts

We present a theoretical analysis of some popular adaptive Stochastic Gradient Descent (SGD) methods in the small learning rate regime. Using the stochastic modified equations framework introduced by Li et al., we derive effective…

Machine Learning · Statistics 2025-09-29 Luca Callisti , Marco Romito , Francesco Triggiano

A multiscale analysis of 1D stochastic bistable reaction-diffusion equations with additive noise is carried out w.r.t. travelling waves within the variational approach to stochastic partial differential equations. It is shown with explicit…

Probability · Mathematics 2019-02-11 Jennifer Krüger , Wilhelm Stannat

We consider multiscale stochastic dynamical systems. In this article an \emph{intermediate} reduced model is obtained for a slow-fast system with fast mode driven by white noise. First, the reduced stochastic system on exponentially…

Mathematical Physics · Physics 2009-03-10 W. Wang , A. J. Roberts

Stochastic boundary conditions for interactions with a particle reservoir are discussed in many-particle systems. We introduce the boundary conditions with the injection rate and the momentum distribution of particles coming from a particle…

Statistical Mechanics · Physics 2017-04-26 Tooru Taniguchi , Shin-ichi Sawada

This paper is concerned with the large deviation principle of the non-local fractional stochastic reaction-diffusion equation with a polynomial drift of arbitrary degree driven by multiplicative noise defined on unbounded domains. We first…

Probability · Mathematics 2023-05-23 Bixiang Wang

We study the wellposedness and pathwise regularity of semilinear non-autonomous parabolic evolution equations with boundary and interior noise in an $L^p$ setting. We obtain existence and uniqueness of mild and weak solutions. The boundary…

Probability · Mathematics 2010-01-14 Roland Schnaubelt , Mark Veraar

We study a system whose dynamics are governed by predictions of its future states. A general formalism and concrete examples are presented. We find that the dynamical characteristics depend on how to shape the predictions as well as on how…

Other Condensed Matter · Physics 2015-06-25 Toru Ohira

We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time dynamical modelling. The work has high emphasis on the stochastic part of the differential equation, also…

Machine Learning · Statistics 2020-06-29 Martin Jørgensen , Marc Peter Deisenroth , Hugh Salimbeni

The influence of small random perturbations on a deterministic dynamical system with a locally stable equilibrium is considered. The perturbed system is described by the It\^{o} stochastic differential equation. It is assumed that the noise…

Mathematical Physics · Physics 2016-02-18 Oskar Sultanov

In this work we study permanence of hyperbolicity for autonomous differential equations under nonautonomous random/stochastic perturbations. For the linear case, we study robustness and existence of exponential dichotomies for nonautonomous…

Analysis of PDEs · Mathematics 2021-04-06 Tomás Caraballo , Alexandre N. de Carvalho , José A. Langa , Alexandre N. Oliveira-Sousa

We consider a 2-dimensional stochastic differential equation in polar coordinates depending on several parameters. We show that if these parameters belong to a specific regime then the deterministic system explodes in finite time, but the…

Dynamical Systems · Mathematics 2022-06-17 Matti Leimbach , Jonathan C. Mattingly , Michael Scheutzow

This paper is devoted to the study of hyperbolic systems of linear partial differential equations perturbed by a Brownian motion. The existence and uniqueness of solutions are proved by an energy method. The specific features of this class…

Probability · Mathematics 2021-09-29 Adnan Aboulalaa

Noise-induced transitions between multistable states happen in a multitude of systems, such as species extinction in biology, protein folding, or tipping points in climate science. Large deviation theory is the rigorous language to describe…

Probability · Mathematics 2024-09-27 Paolo Bernuzzi , Tobias Grafke