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We study Linear Response Theory and Entropic Fluctuations of finite dimensional non-equilibrium repeated interaction systems (RIS). More precisely, in a situation where the temperatures of the probes can take a finite number of different…

Mathematical Physics · Physics 2020-10-28 J. F. Bougron , L. Bruneau

We consider a general class of non-gradient hypoelliptic Langevin diffusions and study two related questions. The first one is large deviations for hypoelliptic multiscale diffusions. The second one is small mass asymptotics of the…

Probability · Mathematics 2017-02-24 Wenqing Hu , Konstantinos Spiliopoulos

We study determinantal random point processes on a compact complex manifold X associated to an Hermitian metric on a line bundle over X and a probability measure on X. Physically, this setup describes a free fermion gas on X subject to a…

Complex Variables · Mathematics 2011-06-27 Robert J. Berman

We consider temporal models of rapidly changing Markovian networks modulated by time-evolving spatially dependent kernels that define rates for edge formation and dissolution. Alternatively, these can be viewed as Markovian networks with…

Probability · Mathematics 2025-06-11 Shankar Bhamidi , Amarjit Budhiraja , Souvik Ray

We consider an irreducible continuous time Markov chain on a finite state space and with time periodic jump rates and prove the joint large deviation principle for the empirical measure and flow and the joint large deviation principle for…

Probability · Mathematics 2018-10-17 L. Bertini , R. Chetrite , A. Faggionato , D. Gabrielli

We consider a collection of weakly interacting diffusion processes moving in a two-scale locally periodic environment. We study the large deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2022-11-03 Zachary Bezemek , Konstantinos Spiliopoulos

Self-interacting jump processes (SIJPs) describe systems with non-Markovian stochastic dynamics in which transition rates depend on empirical observables of the process, which gives rise to long-range memory and feedback. We derive the…

Statistical Mechanics · Physics 2026-03-23 Francesco Coghi , Juan P. Garrahan

For parabolic stochastic partial differential equations (SPDEs), we show that the numerical methods, including the spatial spectral Galerkin method and further the full discretization via the temporal accelerated exponential Euler method,…

Numerical Analysis · Mathematics 2021-06-22 Chuchu Chen , Ziheng Chen , Jialin Hong , Diancong Jin

We consider the stationary measure of the asymmetric simple exclusion process (ASEP) on a finite interval in $\mathbb{Z}$ with open boundaries. Fixing all the jump rates and letting the system size approach infinity, the height profile of…

Probability · Mathematics 2024-12-18 Milind Hegde , Zongrui Yang

We study two problems. First, we consider the large deviation behavior of empirical measures of certain diffusion processes as, simultaneously, the time horizon becomes large and noise becomes vanishingly small. The law of large numbers…

Probability · Mathematics 2023-09-14 Amarjit Budhiraja , Pavlos Zoubouloglou

We show that a modification of the proof of our paper [CvELNR18], in the spirit of [FP81], shows delocalisation in the long-range Discrete Gaussian Chain, and generalisations thereof, for any decay power $\alpha>2$ and at all temperatures.…

Probability · Mathematics 2024-06-26 Loren Coquille , Aernout C. D. van Enter , Arnaud Le Ny , Wioletta M. Ruszel

We consider discrete time Markov chains with Polish state space. The large deviations principle for empirical measures of a Markov chain can equivalently be stated in Laplace principle form, which builds on the convex dual pair of relative…

Probability · Mathematics 2026-01-14 Stephan Eckstein

Hamiltonian dynamics describing conservative systems naturally preserves the standard notion of phase-space volume, a result known as the Liouville's theorem which is central to the formulation of classical statistical mechanics. In this…

Mathematical Physics · Physics 2026-01-06 Aritra Ghosh

We obtain asymptotic expansions for the large deviation principle (LDP) for continuous time stochastic processes with weakly dependent increments. As a key example, we show that additive functionals of solutions of stochastic differential…

Probability · Mathematics 2021-04-06 Kasun Fernando , Pratima Hebbar

The article obtains large deviation asymptotic for sub-critical communication networks modelled as signal-interference-noise-ratio(SINR) random networks. To achieve this, we define the empirical power measure and the empirical connectivity…

Probability · Mathematics 2021-04-14 E. Sakyi-Yeboah , P. S. Andam , L. Asiedu , K. Doku-Amponsah

We study large deviations in the Langevin dynamics, with damping of order $\e^{-1}$ and noise of order $1$, as $\e\downarrow 0$. The damping coefficient is assumed to be state dependent. We proceed first with a change of time and then, we…

Probability · Mathematics 2015-09-30 Sandra Cerrai , Mark Freidlin

We derive a large deviation principle for random permutations induced by probability measures of the unit square, called permutons. These permutations are called $\mu$-random permutations. We also introduce and study a new general class of…

Probability · Mathematics 2023-04-04 Jacopo Borga , Sayan Das , Sumit Mukherjee , Peter Winkler

One says that the local large deviation principle (LLDP) is satisfied for a family of random vectors $\{\zeta_T\}_{T\ge 0}$ in $\mathbb R^d,$ $d\ge 1,$ if there exists a function $D:\mathbb R^d\to [0,\infty],$ $D\not \equiv \infty,$ such…

Probability · Mathematics 2026-04-27 Konstantin Borovkov

We utilize the weak convergence method to establish the Freidlin--Wentzell large deviations principle (LDP) for stochastic delay differential equations (SDDEs) with super-linearly growing coefficients, which covers a large class of cases…

Probability · Mathematics 2022-01-04 Diancong Jin , Ziheng Chen , Tau Zhou

Letting~$N=\left\{N(t), t\geq0\right\}$ be a standard Poisson process, Stroock~ \cite{Stroock-1981} constructed a family of continuous processes by $$\Theta_{\epsilon}(t)=\int_0^t\theta_{\epsilon}(r)dr, \ \ \ \ \ 0 \le t \le 1,$$ where…

Probability · Mathematics 2022-06-06 Hui Jiang , Lihu Xu , Qingshan Yang