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We study fluctuations of small noise multiscale diffusions around their homogenized deterministic limit. We derive quantitative rates of convergence of the fluctuation processes to their Gaussian limits in the appropriate Wasserstein metric…

Probability · Mathematics 2024-11-05 Solesne Bourguin , Konstantinos Spiliopoulos

We study a singular-limit problem arising in the modelling of chemical reactions. At finite {\epsilon} > 0, the system is described by a Fokker-Planck convection-diffusion equation with a double-well convection potential. This potential is…

Analysis of PDEs · Mathematics 2014-09-16 Steffen Arnrich , Alexander Mielke , Mark A. Peletier , Giuseppe Savaré , Marco Veneroni

We give a comprehensive description of Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals $\mathcal F_\nu := \text{MMD}_K^2(\cdot, \nu)$ towards given target measures $\nu$ on the real line, where we focus on the…

Analysis of PDEs · Mathematics 2025-12-05 Richard Duong , Viktor Stein , Robert Beinert , Johannes Hertrich , Gabriele Steidl

We introduce a new class of Wasserstein-type distances specifically designed to tackle questions concerning stability and convergence to equilibria for kinetic equations. Thanks to these new distances, we improve some classical estimates by…

Analysis of PDEs · Mathematics 2022-02-23 Mikaela Iacobelli

We give a sufficient condition under which the time-marginal law of $\mu$-reversible infinite interacting Brownian motions is characterised as the steepest gradient descent of the relative entropy in the Wasserstein space in the sense of…

Probability · Mathematics 2025-12-02 Kohei Suzuki

Starting with the relativistic Boltzmann equation where the collision term is generalized to include nonlocal effects via gradients of the phase-space distribution function, and using Grad's 14-moment approximation for the distribution…

Nuclear Theory · Physics 2013-05-23 Amaresh Jaiswal , Rajeev S. Bhalerao , Subrata Pal

We construct a new random probability measure on the sphere and on the unit interval which in both cases has a Gibbs structure with the relative entropy functional as Hamiltonian. It satisfies a quasi-invariance formula with respect to the…

Probability · Mathematics 2007-05-23 Max-K von Renesse , Karl-Theodor Sturm

We study the reknown deconvolution problem of recovering a distribution function from independent replicates (signal) additively contaminated with random errors (noise), whose distribution is known. We investigate whether a Bayesian…

Statistics Theory · Mathematics 2021-11-15 Judith Rousseau , Catia Scricciolo

We propose a variational finite volume scheme to approximate the solutions to Wasserstein gradient flows. The time discretization is based on an implicit linearization of the Wasserstein distance expressed thanks to Benamou-Brenier formula,…

Numerical Analysis · Mathematics 2019-07-22 Clément Cancès , Thomas O. Gallouët , Gabriele Todeschi

We revisit the variational characterization of diffusion as entropic gradient flux and provide for it a probabilistic interpretation based on stochastic calculus. It was shown by Jordan, Kinderlehrer, and Otto that, for diffusions of…

Probability · Mathematics 2020-03-24 Ioannis Karatzas , Walter Schachermayer , Bertram Tschiderer

We study the problem of quantifying how far an empirical distribution deviates from Gaussianity under the framework of optimal transport. By exploiting the cone geometry of the relative translation invariant quadratic Wasserstein space, we…

Machine Learning · Computer Science 2026-02-02 Binshuai Wang , Peng Wei

The problem of modeling the relationship between univariate distributions and one or more explanatory variables has found increasing interest. Traditional functional data methods cannot be applied directly to distributional data because of…

Methodology · Statistics 2025-02-04 Yidong Zhou , Hans-Georg Müller

We study diffusion of colloids on a fluid-fluid interface using particle simulations and fluctuating hydrodynamics. Diffusion on a two-dimensional interface with three-dimensional hydrodynamics is known to be anomalous, with the collective…

Statistical Mechanics · Physics 2018-08-01 R. P. Peláez , F. Balboa Usabiaga , S. Panzuela , Q. Xiao , R. Delgado-Buscalioni , A. Donev

We study an additive-noise approximation to Keller-Segel-Dean-Kawasaki dynamics, which is proposed as an approximate model to the fluctuating hydrodynamics of chemotactically interacting particles around their mean-field limit. As such, the…

Probability · Mathematics 2026-04-29 Adrian Martini , Avi Mayorcas

Contraction in Wasserstein 1-distance with explicit rates is established for generalized Hamiltonian Monte Carlo with stochastic gradients under possibly nonconvex conditions. The algorithms considered include splitting schemes of kinetic…

Probability · Mathematics 2024-09-16 Martin Chak , Pierre Monmarché

The Dean-Kawasaki equation - a strongly singular SPDE - is a basic equation of fluctuating hydrodynamics; it has been proposed in the physics literature to describe the fluctuations of the density of $N$ independent diffusing particles in…

Analysis of PDEs · Mathematics 2023-07-06 Federico Cornalba , Julian Fischer

It is well known that energy dissipation and finite size can deeply affect the dynamics of granular matter, often making usual hydrodynamic approaches problematic. Here we report on the experi-mental investigation of a small model system,…

Soft Condensed Matter · Physics 2023-10-31 Andrea Gnoli , Giorgio Pontuale , Andrea Puglisi , Alberto Petri

Diffusion-coagulation can be simply described by a dynamic where particles perform a random walk on a lattice and coalesce with probability unity when meeting on the same site. Such processes display non-equilibrium properties with strong…

Statistical Mechanics · Physics 2018-03-13 L. Turban , J. -Y. Fortin

The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability measures. It formulates the theoretical motivation resulting from the interpretation of fictitious adversary of robust…

Mathematical Finance · Quantitative Finance 2019-03-05 Yu Feng , Erik Schlögl

We consider discrete porous medium equations of the form \partial_t \rho_t = \Delta \phi(\rho_t), where \Delta is the generator of a reversible continuous time Markov chain on a finite set X, and \phi is an increasing function. We show that…

Functional Analysis · Mathematics 2012-12-06 Matthias Erbar , Jan Maas