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The macroscopic behavior of the solution of a coupled system of partial differential equations arising in the modeling of reaction-diffusion processes in periodic porous media is analyzed. Our mathematical model can be used for studying…

Analysis of PDEs · Mathematics 2019-06-19 G. Cardone , C. Perugia , C. Timofte

In this paper, we explore osmotic transport by means of molecular dynamics (MD) simulations. We first consider osmosis through a membrane, and investigate the reflection coefficient of an imperfectly semi-permeable membrane, in the dilute…

Mesoscale and Nanoscale Physics · Physics 2017-05-18 Hiroaki Yoshida , Sophie Marbach , Lydéric Bocquet

Particles diffusing near interfaces face anisotropic resistance to motion due to hydrodynamic interactions. While this has been extensively studied near \textit{hard} interfaces since the works of Lorentz and Brenner, our understanding of…

Soft Condensed Matter · Physics 2026-03-03 Ali Mohammadi , Zhen Li , Sophie Marbach , Micheline Abbas

Solvation is a notoriously difficult and nagging problem for the rigorous theoretical description of chemistry in the liquid phase. Successes and failures of various approaches ranging from implicit solvation modeling through dielectric…

Chemical Physics · Physics 2020-04-01 Gregor N. Simm , Paul L. Türtscher , Markus Reiher

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

The vertical upwelling/diffusion model (VUDM) has historically played a key role in shaping our ideas about how the heat balance is achieved in the ocean. Its has been and is still widely used in many applications ranging from the…

Fluid Dynamics · Physics 2017-08-08 Remi Tailleux , Antoine Hochet , David Ferreira , Till Kuhlbrodt , Jonathan Gregory

This article introduces a novel framework for developing quantum algorithms for the Lattice Boltzmann Method (LBM) applied to the advection-diffusion equation. We formulate the collision-streaming evolution of the LBM as a compact…

Mathematical Physics · Physics 2026-02-11 Yuan He , Yuan Yu , Yue Yu

Several competing artificial compressibility methods for the incompressible flow equations are examined using the high-order flux reconstruction method. The established artificial compressibility method (ACM) of \citet{Chorin1967} is…

Partial differential equations (PDEs) on surfaces arise in a wide range of applications. The closest point method (Ruuth and Merriman, J. Comput. Phys. 227(3):1943-1961, [2008]) is a recent embedding method that has been used to solve a…

Numerical Analysis · Mathematics 2019-11-04 A. Petras , S. J. Ruuth

We study dynamics emergent from a two-dimensional reaction--diffusion process modelled via a finite lattice dynamical system, as well as an analogous PDE system, involving spatially nonlocal interactions. These models govern the evolution…

Tissues and Organs · Quantitative Biology 2018-11-14 Andrew L. Krause , Dmitry Beliaev , Robert A. Van Gorder , Sarah L. Waters

Accounting for geometry-induced changes in the electronic distribution in molecular simulation is important for capturing effects such as charge flow, charge anisotropy and polarization. Multipolar force fields have demonstrated their…

Chemical Physics · Physics 2022-07-01 Eric D. Boittier , Mike Devereux , Markus Meuwly

Volume-filling cross-diffusion equations for the components of a tissue structure are formally derived from mass conservation laws and force balances for the interphase pressures and viscous drag forces in a multiphase approach. The…

Analysis of PDEs · Mathematics 2026-04-03 Ansgar Jüngel , Cordula Reisch , Sara Xhahysa

This master thesis introduces the idea of dynamic cutoffs in molecular dynamics simulations, based on the distance between particles and the interface, and presents a solution for detecting interfaces in real-time. Our dynamic cutoff method…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-12 Paul Springer

This work presents a comprehensive framework for enhanced diffusion modeling in fluid-structure interactions by combining the Immersed Boundary Method (IBM) with stochastic trajectories and high-order spectral boundary conditions. Using…

Analysis of PDEs · Mathematics 2024-10-31 Rômulo Damasclin Chaves dos Santos , Jorge Henrique de Oliveira Sales

Lattice Boltzmann models are briefly introduced together with references to methods used to predict their ability for simulations of systems described by partial differential equations that are first order in time and low order in space…

Numerical Analysis · Mathematics 2024-11-15 Pierre Lallemand , François Dubois , Li-shi Luo

Diffusion models have demonstrated exceptional performances in various fields of generative modeling, but suffer from slow sampling speed due to their iterative nature. While this issue is being addressed in continuous domains, discrete…

Machine Learning · Computer Science 2025-05-12 Satoshi Hayakawa , Yuhta Takida , Masaaki Imaizumi , Hiromi Wakaki , Yuki Mitsufuji

We introduce Linearly Constrained Diffusion Implicit Models (CDIM), a fast and accurate approach to solving noisy linear inverse problems using diffusion models. Traditional diffusion-based inverse methods rely on numerous projection steps…

Machine Learning · Computer Science 2025-12-01 Vivek Jayaram , Ira Kemelmacher-Shlizerman , Steven M. Seitz , John Thickstun

The solution of partial differential equations (PDEs) on complex domains often presents a significant computational challenge by requiring the generation of fitted meshes. The Diffuse Domain Method (DDM) is an alternative which reformulates…

Numerical Analysis · Mathematics 2026-05-13 Luke Benfield , Andreas Dedner

The efficient resolution of Bayesian inverse problems remains challenging due to the high computational cost of traditional sampling methods. In this paper, we propose a novel framework that integrates Conditional Flow Matching (CFM) with a…

Machine Learning · Computer Science 2025-05-20 Daniil Sherki , Ivan Oseledets , Ekaterina Muravleva

Particle-based methods are a practical tool in computational fluid dynamics, and novel types of methods have been proposed. However, widely developed Lagrangian-type formulations suffer from the nonuniform distribution of particles, which…

Fluid Dynamics · Physics 2025-03-26 Takeharu Matsuda , Satoshi Ii