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We formulate a class of velocity-free finite-particle methods for mass transport problems based on a time-discrete incremental variational principle that combines entropy and the cost of particle transport, as measured by the Wasserstein…

Computational Physics · Physics 2023-05-10 Anna Pandolfi , Laurent Stainier , Michael Ortiz

We formulate a numerical method to solve the porous medium type equation with fractional diffusion \[ \frac{\partial u}{\partial t}+(-\Delta)^{\sigma/2} (u^m)=0 \] posed for $x\in \mathbb{R}^N$, $t>0$, with $m\geq 1$, $\sigma \in (0,2)$,…

Numerical Analysis · Mathematics 2013-07-10 Félix del Teso , Juan Luis Vázquez

The problem of diffusion in a porous medium with a spatially varying porosity is considered. The particular microstructure analyzed comprises a collection of impenetrable spheres, though the methods developed are general. Two different…

Fluid Dynamics · Physics 2017-10-12 Maria Bruna , S. Jonathan Chapman

We formulate a finite-particle method of mass transport that accounts for general mixed boundary conditions. The particle method couples a geometrically-exact treatment of advection; Wasserstein gradient-flow dynamics; and a…

Numerical Analysis · Mathematics 2025-03-05 Anna Pandolfi , Ignacio Romero , Michael Ortiz

The question of optimally approximating an arbitrary probability measure in the Wasserstein distance by a discrete one with uniform weights is considered. Estimates are obtained for the optimal approximation distance, with an explicit rate…

Probability · Mathematics 2026-04-14 Benjamin Seeger

We consider degenerate diffusion equations of the form $\partial_tp_t = \Delta f(p_t)$ on a bounded domain and subject to no-flux boundary conditions, for a class of nonlinearities $f$ that includes the porous medium equation. We derive for…

Probability · Mathematics 2022-10-31 Donghan Kim , Lane Chun Yeung

We consider a Vlasov-Fokker-Planck equation governing the evolution of the density of interacting and diffusive matter in the space of positions and velocities. We use a probabilistic interpretation to obtain convergence towards equilibrium…

Probability · Mathematics 2013-09-19 Francois Bolley , Arnaud Guillin , Florent Malrieu

In this paper, we establish sharp upper and lower bounds on the convergence rate of the empirical measures of point processes under the Wasserstein distance. To this end, we first introduce a new metric on the space of counting measures…

Statistics Theory · Mathematics 2026-04-28 Dongzhou Huang , Tianyi Jiang , Haonan Wang

In this paper, we provide a convergence rate for particle approximations of a class of second-order PDEs on Wasserstein space. We show that, up to some error term, the infinite-dimensional inf(sup)-convolution of the finite-dimensional…

Analysis of PDEs · Mathematics 2025-01-15 Erhan Bayraktar , Ibrahim Ekren , Xin Zhang

This paper presents a Wasserstein attraction approach for solving dynamic mass transport problems over networks. In the transport problem over networks, we start with a distribution over the set of nodes that needs to be "transported" to a…

Optimization and Control · Mathematics 2022-04-28 Ferran Arqué , César A. Uribe , Carlos Ocampo-Martinez

We design a deterministic particle method for the solution of the spatially homogeneous Landau equation with uncertainty. The deterministic particle approximation is based on the reformulation of the Landau equation as a formal gradient…

Numerical Analysis · Mathematics 2023-12-13 Rafael Bailo , José Antonio Carrillo , Andrea Medaglia , Mattia Zanella

In this paper we consider the numerical approximation of a general second order semi-linear parabolic partial differential equation. Equations of this type arise in many contexts, such as transport in porous media. Using finite element…

Numerical Analysis · Mathematics 2020-11-18 Jean Daniel Mukam , Antoine Tambue

Particle-based variational inference offers a flexible way of approximating complex posterior distributions with a set of particles. In this paper we introduce a new particle-based variational inference method based on the theory of…

Machine Learning · Statistics 2019-05-16 Luca Ambrogioni , Umut Guclu , Marcel van Gerven

We derive the hydrodynamic limit of a kinetic equation with a stochastic, short range perturbation of the velocity operator. Under some mixing hypotheses on the stochastic perturbation, we establish a diffusion-approximation result: the…

Analysis of PDEs · Mathematics 2020-10-01 Nils Caillerie , Julien Vovelle

A finite element method with mass-lumping and flux upwinding, is formulated for solving the immiscible two-phase flow problem in porous media. The method approximates directly the wetting phase pressure and saturation, which are the primary…

Numerical Analysis · Mathematics 2020-01-27 Girault Vivette , Riviere Beatrice , Cappanera Loic

We study a deterministic particle scheme to solve a scalar balance equation with nonlocal interaction and nonlinear mobility used to model congested dynamics. The main novelty with respect to "Radici-Stra [SIAM J. Math. Anal. 55.3 (2023)]"…

Analysis of PDEs · Mathematics 2024-11-13 Emanuela Radici , Federico Stra

We discuss transport equations resulting from relativistic diffusions in the proper time. We show that a solution of the transport equation can be obtained from the solution of the diffusion equation by means of an integration over the…

High Energy Physics - Theory · Physics 2009-11-19 Z. Haba

In this paper, we investigate the construction of a diffusion process whose time-marginal densities are constrained to belong to a given set at all time. The construction is obtained from a penalization approximation to the constraint set,…

Probability · Mathematics 2017-04-20 Jean-Francois Jabir

We study a nonlinear multimarginal optimal transport problem arising in risk management, where the objective is to maximize a spectral risk measure of the pushforward of a coupling by a cost function. Although this problem is inherently…

Optimization and Control · Mathematics 2026-03-27 Adrien Cances , Quentin Mérigot , Luca Nenna

Optimal transport (OT) provides powerful tools for comparing probability measures in various types. The Wasserstein distance which arises naturally from the idea of OT is widely used in many machine learning applications. Unfortunately,…

Optimization and Control · Mathematics 2021-06-03 Shu Liu , Haodong Sun , Hongyuan Zha