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We consider in this work a system of two stochastic differential equations named the perturbed compositional gradient flow. By introducing a separation of fast and slow scales of the two equations, we show that the limit of the slow motion…

Probability · Mathematics 2018-07-26 Wenqing Hu , Chris Junchi Li

We study linear time fractional diffusion equations in divergence form of time order less than one. It is merely assumed that the coefficients are measurable and bounded, and that they satisfy a uniform parabolicity condition. As the main…

Analysis of PDEs · Mathematics 2010-11-13 Rico Zacher

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

Dispersion is a fundamental concept in statistics, yet standard approaches - especially via stochastic orders - face limitations in the discrete setting. In particular, the classical dispersive order, well-established for continuous…

Methodology · Statistics 2025-11-11 Andreas Eberl , Bernhard Klar , Alfonso Suárez-Llorens

In this paper, we study the asymptotic behavior of a fully-coupled slow-fast McKean-Vlasov stochastic system. Using the non-linear Poisson equation on Wasserstein space, we first establish the strong convergence in the averaging principle…

Probability · Mathematics 2022-07-14 Yun Li , Longjie Xie

In this paper, we study the asymptotic behavior of a semi-linear slow-fast stochastic partial differential equation with singular coefficients. Using the Poisson equation in Hilbert space, we first establish the strong convergence in the…

Probability · Mathematics 2021-06-09 Michael Röckner , Longjie Xie , Li Yang

We establish a weak-strong uniqueness principle for solutions to entropy-dissipating reaction-diffusion equations: As long as a strong solution to the reaction-diffusion equation exists, any weak solution and even any renormalized solution…

Analysis of PDEs · Mathematics 2017-03-03 Julian Fischer

In this paper we consider an acoustic problem of wave propagation through a discontinuous medium. The problem is reduced to the dissipative wave equation with distributional dissipation. We show that this problem has a so-called very weak…

Analysis of PDEs · Mathematics 2017-05-04 Juan Carlos Munoz , Michael Ruzhansky , Niyaz Tokmagambetov

We study stochastic perturbations of linear systems of the form $$ dv(t)+Av(t)dt = \epsilon P(v(t))dt+\sqrt{\epsilon}B(v(t)) dW (t), v\in\mathbb{R}^{D}, (*) $$ where $A$ is a linear operator with non-zero imaginary spectrum. It is assumed…

Dynamical Systems · Mathematics 2023-08-08 Guan Huang , Sergei Kuksin

We establish an averaging principle for a structural multiscale stochastic nonlinear fractional Schr\"odinger system on the one-dimensional torus driven by a multiplicative Wiener noise. The slow component is governed by a fractional…

Analysis of PDEs · Mathematics 2026-05-13 Manil T. Mohan , Debopriya Mukherjee , Sandip Roy

A large deviation principle is derived for stochastic partial differential equations with slow-fast components. The result shows that the rate function is exactly that of the averaged equation plus the fluctuating deviation which is a…

Probability · Mathematics 2010-01-28 Wei Wang , A. J. Roberts , Jinqiao Duan

In this paper, we are concerned with the dynamical behavior of the stochastic nonclassical parabolic equation, more precisely, it is shown that the inviscid limits of the stochastic nonclassical diffusion equations reduces to the stochastic…

Dynamical Systems · Mathematics 2017-03-09 Peng Gao

Chemical and biochemical reactions can exhibit surprisingly different behaviours, ranging from multiple steady-state solutions to oscillatory solutions and chaotic behaviours. These types of systems are often modelled by a system of…

Analysis of PDEs · Mathematics 2025-07-03 Erika Hausenblas , Michael A. Högele , Tesfalem A. Tegegn

This work concerns the nonlinear filtering problem of multiscale McKean-Vlasov stochastic systems where the whole systems depend on distributions of fast components. First of all, we prove that the slow component of the original system…

Probability · Mathematics 2023-11-27 Huijie Qiao , Wanlin Wei

We analyze the weak-coupling limit of the random Schr\"odinger equation with low frequency initial data and a slowly decorrelating random potential. For the probing signal with a sufficiently long wavelength, we prove a homogenization…

Mathematical Physics · Physics 2015-08-10 Yu Gu , Lenya Ryzhik

This paper studies distributed stochastic approximation algorithms based on broadcast gossip on communication networks represented by digraphs. Weak convergence of these algorithms is proved, and an associated ordinary differential equation…

Applications · Statistics 2016-09-05 Miloš S. Stanković , Nemanja Ilić , Srdjan S. Stanković

For a class of stochastic models with Gaussian and rough mean-reverting volatility that embeds the genuine rough Stein-Stein model, we study the weak approximation rate when using a Euler type scheme with integrated kernels. Our first…

Probability · Mathematics 2026-02-23 Aurélien Alfonsi , Ahmed Kebaier

We study a wave equation with a nonlocal time fractional damping term that models the effects of acoustic attenuation characterized by a frequency dependence power law. First we prove existence of a unique solution to this equation with…

Numerical Analysis · Mathematics 2021-03-26 Katherine Baker , Lehel Banjai

This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average of the fast variable and assuming the boundary…

Systems and Control · Computer Science 2018-09-24 Mohammad Deghat , Saeed Ahmadizadeh , Dragan Nesic , Chris Manzie

Diffusion approximation provides weak approximation for stochastic gradient descent algorithms in a finite time horizon. In this paper, we introduce new tools motivated by the backward error analysis of numerical stochastic differential…

Machine Learning · Computer Science 2019-09-05 Yuanyuan Feng , Tingran Gao , Lei Li , Jian-Guo Liu , Yulong Lu
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