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Dynamics near and far away from thermal equilibrium is studied within the framework of Langevin equations. A stochasticity-dissipation relation is proposed to emphasize the equal importance of the stochastic and deterministic forces in…

Classical Physics · Physics 2007-05-23 P. Ao

Starting from a model that consists of a semiclassical spin coupled to two leads we present a microscopic derivation of the Langevin equation for the direction of the spin. For slowly-changing direction it takes on the form of the…

Mesoscale and Nanoscale Physics · Physics 2008-02-04 A. S. Nunez , R. A. Duine

We consider nonlinear filters for diffusion processes when the observation and signal noises are small and of the same order. As the noise intensities approach zero, the nonlinear filter can be approximated by a certain variational problem…

Probability · Mathematics 2022-10-19 Anugu Sumith Reddy , Amarjit Budhiraja , Amit Apte

We demonstrate that a Langevin equation that describes the motion of a Brownian particle under non-equilibrium conditions can be exactly transformed to a special equation that explicitly exhibits the response of the velocity to a time…

Statistical Mechanics · Physics 2009-11-11 Takahiro Harada , Kumiko Hayashi , Shin-ichi Sasa

The random batch method is advantageous in accelerating force calculations in particle simulations, but it poses a challenge of removing the artificial heating effect in application to the Langevin dynamics. We develop an approach to solve…

Computational Physics · Physics 2024-11-05 Zhenli Xu , Yue Zhao , Qi Zhou

This paper focuses on systems of nonlinear second-order stochastic differential equations with multi-scales. The motivation for our study stems from mathematical physics and statistical mechanics, for examples, Langevin dynamics and…

Probability · Mathematics 2024-04-08 Nhu N. Nguyen , George Yin

We investigate the probabilities of large deviations for the position of the front in a stochastic model of the reaction $X+Y \to 2X$ on the integer lattice in which $Y$ particles do not move while $X$ particles move as independent simple…

Probability · Mathematics 2008-07-16 Jean Bérard , Alejandro Ramírez

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

In this paper, we study an ordinary differential equation with a degenerate global attractor at the origin, to which we add a white noise with a small parameter that regulates its intensity. Under general conditions, for any fixed…

Probability · Mathematics 2025-05-27 Gerardo Barrera , Conrado da Costa , Milton Jara

In this paper, we study the large deviation principle of invariant measures of stochastic reaction-diffusion lattice systems driven by multiplicative noise. We first show that any limit of a sequence of invariant measures of the stochastic…

Probability · Mathematics 2024-05-07 Bixiang Wang

This paper investigates neutral-type McKean-Vlasov stochastic differential equations in which the drift and diffusion coefficients depend on both the segment process and its distribution. Under a one-sided Lipschitz condition on the drift…

Probability · Mathematics 2025-11-25 Zhaohang Wang , Junhao Hu , Chenggui Yuan

This article concerns the large deviations regime and the consequent solution of the Kramers problem for a two-time scale stochastic system driven by a common jump noise signal perturbed in small intensity $\varepsilon>0$ and with…

Probability · Mathematics 2022-07-15 Pedro Catuogno , André de Oliveira Gomes

We derive a large deviation principle for families of random variables in the basin of attraction of spectrally positive stable distributions by proving a uniform version of the Tauberian theorem for Laplace-Stieltjes transforms. The main…

Probability · Mathematics 2026-05-25 Giampaolo Cristadoro , Gaia Pozzoli

We propose a solution for linear inverse problems based on higher-order Langevin diffusion. More precisely, we propose pre-conditioned second-order and third-order Langevin dynamics that provably sample from the posterior distribution of…

Machine Learning · Statistics 2023-12-08 Nicolas Zilberstein , Ashutosh Sabharwal , Santiago Segarra

How condensed-matter simulations depend on the number of molecules being simulated ($N$) is sometimes itself a valuable piece of information. Liquid crystals provide a case in point. Light scattering and $2d$-IR experiments on…

Soft Condensed Matter · Physics 2024-12-20 Eleftherios Mainas , Richard M. Stratt

In this paper, we established the Freidlin-Wentzell type large deviation principles for first-order scalar conservation laws perturbed by small multiplicative noise. Due to the lack of the viscous terms in the stochastic equations, the…

Probability · Mathematics 2020-03-24 Zhao Dong , Jiang-Lun Wu , Rangrang Zhang , Tusheng Zhang

We study the heat equation on a half-space or on an exterior domain with a linear dynamical boundary condition. Our main aim is to establish the rate of convergence to solutions of the Laplace equation with the same dynamical boundary…

Analysis of PDEs · Mathematics 2019-01-03 Marek Fila , Kazuhiro Ishige , Tatsuki Kawakami , Johannes Lankeit

The large deviation principle is established for the distributions of a class of generalized stochastic porous media equations for both small noise and short time.

Probability · Mathematics 2007-05-23 Michael Röckner , Feng-Yu Wang , Liming Wu

In this paper, we establish a large deviation principle for stochastic evolution equations with reflection in an infinite dimensional ball. Weak convergence approach plays an important role.

Probability · Mathematics 2024-03-05 Zdzisław Brzeźniak , Qi Li , Tusheng Zhang

For stochastic wave equation, when the dissipative damping is a non-globally Lipschitz function of the velocity, there are few results on the long-time dynamics, in particular, the exponential ergodicity and strong law of large numbers, for…

Probability · Mathematics 2024-02-05 Meng Cai , Chuchu Chen , Jialin Hong , Tau Zhou