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Einstein's kinetic theory of the Brownian motion, based upon light water molecules continuously bombarding a heavy pollen, provided an explanation of diffusion from the Newtonian mechanics. Since the discovery of quantum mechanics it has…

Mathematical Physics · Physics 2010-09-07 Laszlo Erdos

We investigate the sedimentation of identical inertialess spherical particles in a Stokes fluid in the limit of many small particles. It is known that the presence of the particles leads to an increase of the effective viscosity of the…

Analysis of PDEs · Mathematics 2021-02-09 Richard M. Höfer , Richard Schubert

We develop an intrinsic geometric approach to calculus of variations on Wasserstein space. We show that the flows associated to the Schroedinger bridge with general prior, to Optimal Mass Transport and to the Madelung fluid can all be…

Mathematical Physics · Physics 2017-12-07 Giovanni Conforti , Michele Pavon

A comprehensive methodology for establishing the existence of gradient flows for cross-diffusion systems with respect to suitable energies is proposed. The approach is based on the construction of piecewise-in-time constant approximations…

Analysis of PDEs · Mathematics 2026-04-03 Mathias Dus , Ansgar Jüngel

In this paper we discuss the Wasserstein distance between the n-point motions of Harris flows whose covariance functions have compact support. We prove that it can be estimated by the diameters of their support provided the latter are…

Probability · Mathematics 2017-04-04 A. A. Dorogovtsev , V. V. Fomichov

We investigate the transport of inertial particles by cellular flows when advection dominates over inertia and diffusion, that is, for Stokes and P\'eclet numbers satisfying $\mathrm{St} \ll 1$ and $\mathrm{Pe} \gg 1$. Starting from the…

Fluid Dynamics · Physics 2020-05-26 Antoine Renaud , Jacques Vanneste

In this work, a second order smoothed particle hydrodynamics is derived for the study of relativistic heavy ion collisions. The hydrodynamical equation of motion is formulated in terms of the variational principle. In order to describe the…

Nuclear Theory · Physics 2017-10-11 Philipe Mota , Weixian Chen , Wei-Liang Qian

It is well known that nonlinear diffusion equations can be interpreted as a gradient flow in the space of probability measures equipped with the Euclidean Wasserstein distance. Under suitable convexity conditions on the nonlinearity, due to…

Analysis of PDEs · Mathematics 2014-02-13 François Bolley , José A. Carrillo

Score-based diffusion models have emerged as powerful tools in generative modeling, yet their theoretical foundations remain underexplored. In this work, we focus on the Wasserstein convergence analysis of score-based diffusion models.…

Machine Learning · Statistics 2025-02-10 Yifeng Yu , Lu Yu

This paper considers the problem of regression over distributions, which is becoming increasingly important in machine learning. Existing approaches often ignore the geometry of the probability space or are computationally expensive. To…

Machine Learning · Computer Science 2025-10-31 Maksim Maslov , Alexander Kugaevskikh , Matthew Ivanov

We consider advection of small inertial particles by a random fluid flow with a strong steady shear component. It is known that inertial particles suspended in a random flow can exhibit clusterization even if the flow is incompressible. We…

Chaotic Dynamics · Physics 2013-05-30 Grigory A. Sizov

Diffusion models are popular tools for generating new data samples, using a forward process that adds noise to data and a reverse process to denoise and produce samples. However, when the data distribution consists of n points, empirical…

Machine Learning · Statistics 2025-08-05 Yang Lyu , Tan Minh Nguyen , Yuchun Qian , Xin T. Tong

The paper studies the overdamped motion of Brownian particles in a tilted sawtooth potential. The dependencies of the diffusion coefficient and coherence level of Brownian transport on temperature, tilting force, and the shape of the…

Soft Condensed Matter · Physics 2009-11-10 E. Heinsalu , R. Tammelo , T. Ord

We introduce a time discretization for Wasserstein gradient flows based on the classical Backward Differentiation Formula of order two. The main building block of the scheme is the notion of geodesic extrapolation in the Wasserstein space,…

Analysis of PDEs · Mathematics 2023-11-20 Thomas Gallouët , Andrea Natale , Gabriele Todeschi

The primary choice to summarize a finite collection of random objects is by using measures of central tendency, such as mean and median. In the field of optimal transport, the Wasserstein barycenter corresponds to the Fr\'{e}chet or…

Methodology · Statistics 2025-09-03 Kisung You , Dennis Shung , Mauro Giuffrè

The mean field variational inference (MFVI) formulation restricts the general Bayesian inference problem to the subspace of product measures. We present a framework to analyze MFVI algorithms, which is inspired by a similar development for…

Machine Learning · Statistics 2022-10-21 Soumyadip Ghosh , Yingdong Lu , Tomasz Nowicki , Edith Zhang

Atmospheric water vapour is an essential ingredient of weather and climate. Key features of its distribution can be represented by kinematic models which treat it as a passive scalar advected by a prescribed flow and reacting through…

Atmospheric and Oceanic Physics · Physics 2017-06-29 Yue-Kin Tsang , Jacques Vanneste

Micro- and nano-swimmers moving in a fluid solvent confined by structures that produce entropic barriers are often described by overdamped active Brownian particle dynamics, where viscous effects are large and inertia plays no role.…

Soft Condensed Matter · Physics 2023-03-28 Narender Khatri , Raymond Kapral

We consider a family of fractional porous media equations, recently studied by Caffarelli and V\'azquez. We show the construction of a weak solution as Wasserstein gradient flow of a square fractional Sobolev norm. Energy dissipation…

Analysis of PDEs · Mathematics 2017-10-11 Stefano Lisini , Edoardo Mainini , Antonio Segatti

In this paper, we propose a new method to compute the solution of time-dependent Schr\"odinger equation (TDSE). Using push-forward maps and Wasserstein Hamiltonian flow, we reformulate the TDSE as a Hamiltonian system in terms of…

Numerical Analysis · Mathematics 2025-08-07 Hao Wu , Shu Liu , Xiaojing Ye , Haomin Zhou