English
Related papers

Related papers: Local large deviations for randomly forced nonline…

200 papers

We show a finite-time large deviation principle (LDP) for "Dyson type" diffusion processes, including Dyson Brownian motion on the circle, for a fixed number of particles as the coupling parameter $\beta=8/\kappa$ tends to $\infty$. We also…

Probability · Mathematics 2025-08-28 Osama Abuzaid , Vivian Olsiewski Healey , Eveliina Peltola

Local differential privacy (LDP) has become a central topic in data privacy research, offering strong privacy guarantees by perturbing user data at the source and removing the need for a trusted curator. However, the noise introduced by LDP…

Machine Learning · Computer Science 2026-03-04 Caihong Qin , Yang Bai

We explore an asymptotic behavior of densities of sums of independent random variables that are convoluted with a small continuous noise.

Probability · Mathematics 2019-01-11 Sergey G. Bobkov , Arnaud Marsiglietti

In this paper, we investigate the use of a mass lumped fully explicit time stepping scheme for the discretisation of the wave equation with underlying material parameters that vary at arbitrarily fine scales. We combine the leapfrog scheme…

Numerical Analysis · Mathematics 2021-09-08 Sjoerd Geevers , Roland Maier

This article is the first of two in which we develop a geometric framework for analysing silent and anisotropic big bang singularities. The results of the present article concern the asymptotic behaviour of solutions to linear systems of…

General Relativity and Quantum Cosmology · Physics 2021-10-20 Hans Ringström

Stability is a key property of both forward models and inverse problems, and depends on the norms considered in the relevant function spaces. For instance, stability estimates for hyperbolic partial differential equations are often based on…

Analysis of PDEs · Mathematics 2026-04-13 Rima Alaifari , Giovanni S. Alberti , Tandri Gauksson

In this work, we present the convergence analysis of one-point large deviations rate functions (LDRFs) of the spatial finite difference method (FDM) for stochastic wave equations with small noise, which is essentially about the asymptotical…

Numerical Analysis · Mathematics 2022-09-20 Diancong Jin , Jialin Hong , Derui Sheng

We prove a sample path large deviation principle (LDP) with sub-linear speed for unbounded functionals of certain Markov chains induced by the Lindley recursion. The LDP holds in the Skorokhod space $\mathbb{D}[0,T]$ equipped with the…

Probability · Mathematics 2023-10-03 Mihail Bazhba , Jose Blanchet , Chang-Han Rhee , Bert Zwart

We give a short analytic proof of local large deviations for i.i.d. random variables in the domain of a multivariate $\alpha$-stable law, $\alpha\in(0,1)\cup(1,2]$. Our method simultaneously covers lattice and nonlattice distributions (and…

Probability · Mathematics 2022-02-15 Ian Melbourne , Dalia Terhesiu

In this paper, we establish the large deviation principle for 3D stochastic primitive equations with small perturbation multiplicative noise. The proof is mainly based on the weak convergence approach.

Probability · Mathematics 2016-06-14 Zhao Dong , Jianliang Zhai , Rangrang Zhang

The authors consider non-autonomous dynamical behavior of wave-type evolutionary equations with nonlinear damping and critical nonlinearity. These type of waves equations are formulated as non-autonomous dynamical systems (namely,…

Dynamical Systems · Mathematics 2009-11-11 Chunyou Sun , Daomin Cao , Jinqiao Duan

This paper explores the exponential stability of two nonlinear wave equations coupled through their velocities. The analysis is divided into two main cases. First, we consider a system where one equation is damped, while the other…

Analysis of PDEs · Mathematics 2025-07-11 Alhabib Moumni , Cristina Pignotti , Jawad Salhi , Mouhcine Tilioua

The maximum principle forms an important qualitative property of second order elliptic equations, therefore its discrete analogues, the so-called discrete maximum principles (DMPs) have drawn much attention. In this paper DMPs are…

Numerical Analysis · Mathematics 2018-07-05 János Karátson , Balázs Kovács , Sergey Korotov

In this paper, we study the asymptotic stability of two wave equations coupled by velocities of anti-symmetric type via only one damping. We adopt the frequency domain method to prove that the system with smooth initial data is…

Analysis of PDEs · Mathematics 2020-11-24 Yan Cui , Zhiqiang Wang

We take the point of view of a particle performing random walk with bounded jumps on $\mathbb{Z}^d$ in a stationary and ergodic random environment. We prove the quenched large deviation principle (LDP) for the pair empirical measure of the…

Probability · Mathematics 2008-12-17 Atilla Yilmaz

We revisit the one-dimensional model of the symmetric simple exclusion process slowly coupled with two unequal reservoirs at the boundaries. In its non-equilibrium stationary state, the large deviations functions of density and current have…

Statistical Mechanics · Physics 2024-08-07 Soumyabrata Saha , Tridib Sadhu

We prove local energy decay for the damped wave equation on R^d. The problem which we consider is given by a long range metric perturbation of the Euclidean Laplacian with a short range absorption index. Under a geometric control assumption…

Mathematical Physics · Physics 2014-03-04 Jean-Marc Bouclet , Julien Royer

In this paper we consider a multi-dimensional damped semiliear wave equation with dynamic boundary conditions, related to the Kelvin-Voigt damping. We firstly prove the local existence by using the Faedo-Galerkin approximations combined…

Analysis of PDEs · Mathematics 2008-10-31 Stéphane Gerbi , Belkacem Said-Houari

We explore the relation between fast waves, damping and imposed noise for different scalings by considering the singularly perturbed stochastic nonlinear wave equations \nu u_{tt}+u_t=\D u+f(u)+\nu^\alpha\dot{W} on a bounded spatial domain.…

Analysis of PDEs · Mathematics 2011-09-15 Wei Wang , Yan Lv , A. J. Roberts

Differentially Private Stochastic Gradient Descent (DP-SGD) has been widely used for solving optimization problems with privacy guarantees in machine learning and statistics. Despite this, a systematic non-asymptotic convergence analysis…

Methodology · Statistics 2025-07-10 Enze Shi , Jinhan Xie , Bei Jiang , Linglong Kong , Xuming He
‹ Prev 1 8 9 10 Next ›