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There has been recently a lot of interest in the analysis of the Stein gradient descent method, a deterministic sampling algorithm. It is based on a particle system moving along the gradient flow of the Kullback-Leibler divergence towards…

Analysis of PDEs · Mathematics 2023-12-29 José A. Carrillo , Jakub Skrzeczkowski

We study the numerical behaviour of a particle method for gradient flows involving linear and nonlinear diffusion. This method relies on the discretisation of the energy via non-overlapping balls centred at the particles. The resulting…

Analysis of PDEs · Mathematics 2016-12-07 J. A. Carrillo , Y. Huang , F. S. Patacchini , G. Wolansky

We establish a large deviation principle for time dependent trajectories (paths) of the empirical density of $N$ particles with long range interactions, for homogeneous systems. This result extends the classical kinetic theory that leads to…

Statistical Mechanics · Physics 2022-01-19 Ouassim Feliachi , Freddy Bouchet

Employing large deviation theory, we explore current fluctuations of underdamped Brownian motion for the paradigmatic example of a single particle in a one dimensional periodic potential. Two different approaches to the large deviation…

Statistical Mechanics · Physics 2018-03-12 Lukas P. Fischer , Patrick Pietzonka , Udo Seifert

We study a Schilder-type large deviation principle for sticky-reflected Brownian motion with boundary diffusion, both at the static and sample path level in the short-time limit. A sharp transition for the rate function occurs, depending on…

Analysis of PDEs · Mathematics 2025-01-22 Jean-Baptiste Casteras , Leonard Monsaingeon , Luca Nenna

In these lecture notes, we explore the mathematical preliminaries and foundational concepts that connect stochastic processes with partial differential equations. We begin by investigating Brownian motion, which serves as a model for random…

Probability · Mathematics 2025-09-15 Helder Rojas

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability…

Statistical Mechanics · Physics 2018-11-26 V. Sposini , A. V. Chechkin , F. Seno , G. Pagnini , R. Metzler

Although the dynamics of colloids in the vicinity of a solid interface has been widely characterized in the past, experimental studies of Brownian diffusion close to an air-water interface are rare and limited to particle-interface gap…

Soft Condensed Matter · Physics 2022-11-11 Stefano Villa , Christophe Blanc , Abdallah Daddi-Moussa-Ider , Antonio Stocco , Maurizio Nobili

Based on the theory of M-matrix and Perron-Frobenius theorem, we provide some criteria to justify the convergence of the regime-switching diffusion processes in Wasserstein distances. The cost function we used to define the Wasserstein…

Probability · Mathematics 2014-03-04 Jinghai Shao

We introduce and analyze a model for the transport of particles or energy in extended lattice systems. The dynamics of the model acts on a discrete phase space at discrete times but has nonetheless some of the characteristic properties of…

Mathematical Physics · Physics 2015-06-12 Raphael Lefevere

We consider a stochastic flow in which individual particles follow skew Brownian motions, with each one of these processes driven by the same Brownian motion. One does not have uniqueness for the solutions of the corresponding stochastic…

Probability · Mathematics 2007-05-23 Krzysztof Burdzy , Haya Kaspi

This thesis analyze the Wasserstein gradient flow of a functional defined as a double convolution of a non-smooth repulsive interaction potential. To be more precise, the potential under investigation has a -|x| behavior close to the…

Analysis of PDEs · Mathematics 2013-10-15 Giovanni A. Bonaschi

We consider a two-dimensional Hamiltonian system perturbed by a small diffusion term, whose coefficient is state-dependent and non-degenerate. As a result, the process consists of the fast motion along the level curves and slow motion…

Probability · Mathematics 2022-05-24 Shuo Yan

Score-based diffusion models currently constitute the state of the art in continuous generative modeling. These methods are typically formulated via overdamped or underdamped Ornstein--Uhlenbeck-type stochastic differential equations, in…

Machine Learning · Computer Science 2025-12-22 Herlock Rahimi

The meaning of thermodynamic descriptions is found in large-deviations scaling of the fluctuations probabilities. The primary large-deviations rate function is the entropy, which is the basis for both fluctuation theorems and for…

Statistical Mechanics · Physics 2015-05-27 Eric Smith

Consider a massive (inert) particle impinged from above by N Brownian particles that are instantaneously reflected upon collision with the inert particle. The velocity of the inert particle increases due to the influence of an external…

Probability · Mathematics 2022-12-28 Sayan Banerjee , Amarjit Budhiraja , Benjamin Estevez

We show that any positive, continuous, and bounded function can be realised as the diffusion coefficient of an evolution equation associated with a gradient interacting particle system. The proof relies on the construction of an appropriate…

Probability · Mathematics 2026-01-26 Gabriel S. Nahum

We consider a nonlinear fourth-order diffusion equation that arises in denoising of image densities. We propose an implicit time-stepping scheme that employs a primal-dual method for computing the subgradient of the total variation…

Numerical Analysis · Mathematics 2013-05-24 Martin Benning , Luca Calatroni , Bertram Düring , Carola-Bibiane Schönlieb

We consider a family of branching-selection particle systems in which particles branch at time dependent rate $r$ and are killed with a probability which is dependent on their rank via some function $\psi$. We show that, under fairly…

Probability · Mathematics 2026-05-07 Jacob Mercer

In the diffusive hydrodynamic limit for a symmetric interacting particle system (such as the exclusion process, the zero range process, the stochastic Ginzburg-Landau model, the energy exchange model), a possibly non-linear diffusion…

Probability · Mathematics 2017-05-01 Makiko Sasada