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Generative diffusion models are extensively used in unsupervised and self-supervised machine learning with the aim to generate new samples from a probability distribution estimated with a set of known samples. They have demonstrated…

Fluid Dynamics · Physics 2026-01-28 Wilfried Genuist , Éric Savin , Filippo Gatti , Didier Clouteau

We consider general Markov processes with absorption and provide criteria ensuring the exponential convergence in total variation of the distribution of the process conditioned not to be absorbed. The first one is based on two-sided…

Probability · Mathematics 2018-01-18 Nicolas Champagnat , Koléhè Coulibaly-Pasquier , Denis Villemonais

We investigate coupled stochastic differential equations governing N non-negative continuous random variables that satisfy a conservation principle. In various fields a conservation law requires that a set of fluctuating variables be…

Probability · Mathematics 2014-03-06 J. Bakosi , J. R. Ristorcelli

An inhomogeneous Kaluza-Klein compactification of a higher dimensional spacetime may give rise to an effective 4d spacetime with distinct domains having different sizes of the extra dimensions. The domains are separated by domain walls…

High Energy Physics - Theory · Physics 2008-11-26 Nelson De Leon , John Morris

We consider a tight-binding Schroedinger equation with time dependent diagonal noise, given as a function of a Markov process. This model was considered previously by Kang and Schenker (J. Stat. Phys., 134(5-6):1005, arXiv:0808.2784), who…

Mathematical Physics · Physics 2015-12-11 Clark Musselman , Jeffrey Schenker

We consider diffusive lattice gases on a ring and analyze the stability of their density profiles conditionally to a current deviation. Depending on the current, one observes a phase transition between a regime where the density remains…

Statistical Mechanics · Physics 2009-11-11 T. Bodineau , B. Derrida

Consider a system of particles evolving as independent and identically distributed (i.i.d.) random walks. Initial fluctuations in the particle density get translated over time with velocity $\vec{v}$, the common mean velocity of the random…

Probability · Mathematics 2010-09-15 Rohini Kumar

We examine the Langevin diffusion confined to a closed, convex domain $D\subset\mathbb{R}^d$, represented as a reflected stochastic differential equation. We introduce a sequence of penalized stochastic differential equations and prove that…

Probability · Mathematics 2026-01-22 Tarika Mane , Amine Boukardagha

We are interested in studying the sensitivity of diffusion processes or their approximations by Markov Chains with respect to a perturbation of the coefficients.

Probability · Mathematics 2016-11-28 V. Konakov , A. Kozhina , S. Menozzi

We study singularities in the large deviation function of the time-averaged current of diffusive systems connected to two reservoirs. A set of conditions for the occurrence of phase transitions, both first and second order, are obtained by…

Statistical Mechanics · Physics 2022-08-31 Yongjoo Baek , Yariv Kafri , Vivien Lecomte

Large deviations quantify the occurrence of events that depart from the average behavior of a system. In this note we derive an exact expression for their moment generating function. This expression offers a new tool to investigate the…

Statistical Mechanics · Physics 2016-04-19 David Andrieux

We present general results on fluctuations and spatial correlations of the coarse-grained empirical density and current of Markovian diffusion in equilibrium or non-equilibrium steady states on all time scales. We unravel a deep connection…

Statistical Mechanics · Physics 2023-04-06 Cai Dieball , Aljaž Godec

We revisit functional central limit theorems for additive functionals of ergodic Markov diffusion processes. Translated in the language of partial differential equations of evolution, they appear as diffusion limits in the asymptotic…

Probability · Mathematics 2012-09-06 Patrick Cattiaux , Djalil Chafai , Arnaud Guillin

We consider the large deviations associated with the empirical mean of independent and identically distributed random variables under a subexponential moment condition. We show that non-trivial deviations are observable at a subexponential…

Probability · Mathematics 2025-07-22 Grégoire Ferré

The long time behavior of an absorbed Markov process is well described by the limiting distribution of the process conditioned to not be killed when it is observed. Our aim is to give an approximation's method of this limit, when the…

Probability · Mathematics 2009-05-25 Denis Villemonais

We study a general limiting framework for the convergence of sequences of additive functionals of diffusions to L\'evy subordinators, and provide explicit sufficient conditions that both ensure convergence and characterize the law of the…

Probability · Mathematics 2026-01-15 Thibaud Taillefumier , Gordan Zitkovic

This paper studies, in dimensions greater than two, stationary diffusion processes in random environment which are small, isotropic perturbations of Brownian motion satisfying a finite range dependence. Such processes were first considered…

Analysis of PDEs · Mathematics 2016-01-26 Benjamin J. Fehrman

We obtain the exact large deviation functions of the density profile and of the current, in the non-equilibrium steady state of a one dimensional symmetric simple exclusion process coupled to boundary reservoirs with slow rates. Compared to…

Statistical Mechanics · Physics 2021-02-03 Bernard Derrida , Ori Hirschberg , Tridib Sadhu

We construct diffusions with values in the nonnegative orthant, normal reflection along each of the axes, and two pairs of local drift/variance characteristics assigned according to rank; one of the variances is allowed to vanish, but not…

Probability · Mathematics 2014-01-29 Tomoyuki Ichiba , Ioannis Karatzas , Vilmos Prokaj

We study the small-time fluctuations for diffusion processes which are conditioned by their initial and final positions, under the assumptions that the diffusivity has a sub-Riemannian structure and that the drift vector field lies in the…

Probability · Mathematics 2018-08-28 Karen Habermann