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We consider a lattice gas on the discrete d-dimensional torus $(\mathbb{Z}/N\mathbb{Z})^d$ with a generic translation invariant, finite range interaction satisfying a uniform strong mixing condition. The lattice gas performs a Kawasaki…

Mathematical Physics · Physics 2013-02-13 Lorenzo Bertini , Alessandra Faggionato , Davide Gabrielli

We prove a large deviation principle for the sequence of push-forwards of empirical measures in the setting of Riesz potential interactions on compact subsets K in R^d with continuous external fields. Our results are valid for base measures…

Classical Analysis and ODEs · Mathematics 2016-10-27 Tom Bloom , Norman Levenberg , Franck Wielonsky

We discuss a method to solve models with long-range interactions in the microcanonical and canonical ensemble. The method closely follows the one introduced by Ellis, Physica D 133, 106 (1999), which uses large deviation techniques. We show…

Statistical Mechanics · Physics 2009-11-10 Julien Barre' , Freddy Bouchet , Thierry Dauxois , Stefano Ruffo

Large deviation functions are an essential tool in the statistics of rare events. Often they can be obtained by contraction from a so-called level 2 large deviation {\em functional} characterizing the empirical density of the underlying…

Statistical Mechanics · Physics 2016-08-24 Johannes Hoppenau , Daniel Nickelsen , Andreas Engel

Considering the interactions of two arbitrary particles, we obtain an internal energy expression of the complex system having long-range interactions. Based on the postulate of "equal-probability principle" for all microstates, the…

Statistical Mechanics · Physics 2017-01-19 Yanxiu Liu , Cheng Xu , Zhifu Huang , Bihong Lin , Jincan Chen

A numerical experiment of ideal stochastic motion of a particle subject to conservative forces and Gaussian noise reveals that the path probability depends exponentially on action. This distribution implies a fundamental principle…

Statistical Mechanics · Physics 2020-10-16 Qiuping A. Wang , Aziz El Kaabouchi

A set of core features is set forth as the essence of a thermodynamic description, which derive from large-deviation properties in systems with hierarchies of timescales, but which are \emph{not} dependent upon conservation laws or…

Statistical Mechanics · Physics 2020-10-28 Eric Smith

In this paper, a large deviation principle for the strong solution of the p-Laplace equation on unbounded domain driven by small multiplicative Brownian noise is established. The weak convergence approach and the localized time increment…

Probability · Mathematics 2024-08-28 Ananta K Majee

We consider homogeneous open quantum random walks on a lattice with finite dimensional local Hilbert space and we study in particular the position process of the quantum trajectories of the walk. We prove that the properly rescaled position…

Probability · Mathematics 2022-06-08 Raffaella Carbone , Federico Girotti , Anderson Melchor Hernandez

In this article we study the Dyson Bessel process, which describes the evolution of singular values of rectangular matrix Brownian motions, and prove a large deviation principle for its empirical particle density. We then use it to obtain…

Probability · Mathematics 2021-06-15 Alice Guionnet , Jiaoyang Huang

A Boussinesq model for the Benard convection under random influences is considered as a system of stochastic partial differential equations. This is a coupled system of stochastic Navier-Stokes equations and the transport equation for…

Probability · Mathematics 2009-05-12 Jinqiao Duan , Annie Millet

Using the theory of large deviations, macroscopic fluctuation theory provides a framework to understand the behaviour of non-equilibrium dynamics and steady states in diffusive systems. We extend this framework to a minimal model of…

Statistical Mechanics · Physics 2023-10-02 D. R. Michiel Renger , Upanshu Sharma

We establish a comprehensive sample path large deviation principle (LDP) for log-processes associated with multivariate time-inhomogeneous stochastic volatility models. Examples of models for which the new LDP holds include Gaussian models,…

Probability · Mathematics 2022-11-15 Archil Gulisashvili

In this paper, we introduce a mathematical apparatus that is relevant for understanding a dynamical system with small random perturbations and coupled with the so-called transmutation process -- where the latter jumps from one mode to…

Dynamical Systems · Mathematics 2017-09-15 Getachew K. Befekadu

Let $X$ be a L\'evy process with regularly varying L\'evy measure $\nu$. We obtain sample-path large deviations for scaled processes $\bar X_n(t) \triangleq X(nt)/n$ and obtain a similar result for random walks. Our results yield detailed…

Probability · Mathematics 2017-12-12 Chang-Han Rhee , Jose Blanchet , Bert Zwart

We analyze the dynamics of moderate fluctuations for macroscopic observables of the random field Curie Weiss model (i.e., standard Curie-Weiss model embedded in a site dependent, i.i.d. random environment). We obtain path space large…

Probability · Mathematics 2018-03-13 Francesca Collet , Richard C. Kraaij

By examining the deterministic limit of a general $\epsilon$-dependent generator for Markovian dynamics, which includes the continuous Fokker-Planck equations and discrete chemical master equations as two special cases, the intrinsic…

Probability · Mathematics 2021-10-27 Liu Hong , Hong Qian

The purpose of this paper is to ensure the conditions of G\"artner-Ellis Theorem for evaluations of the empirical measure. We show that up-to-date conditions for ensuring the convergence to a quasi-stationary distribution can be applied…

Probability · Mathematics 2020-04-21 Aurélien Velleret

We derive the spatially homogeneous Landau equation for Maxwellian molecules from a natural stochastic interacting particle system. More precisely, we control the relative entropy between the joint law of the particle system and the…

Analysis of PDEs · Mathematics 2024-10-01 José Antonio Carrillo , Xuanrui Feng , Shuchen Guo , Pierre-Emmanuel Jabin , Zhenfu Wang

The zig-zag process is a piecewise deterministic Markov process in position and velocity space. The process can be designed to have an arbitrary Gibbs type marginal probability density for its position coordinate, which makes it suitable…

Probability · Mathematics 2019-12-24 Joris Bierkens , Pierre Nyquist , Mikola C. Schlottke
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