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Using a solvable model, the two-dimensional two-component plasma, we study a Coulomb gas confined in a disk and in an annulus with boundaries that can adsorb some of the negative particles of the system. We obtain explicit analytic…

Statistical Mechanics · Physics 2007-05-23 Lina Merchan , Gabriel Tellez

This paper is devoted to the study of some nonlinear parabolic equations with discontinuous diffusion intensities. Such problems appear naturally in physical and biological models. Our analysis is based on variational techniques and in…

Analysis of PDEs · Mathematics 2021-02-09 Dohyun Kwon , Alpár Richárd Mészáros

We study the diffusion-limited process $A+A\to A$ in one dimension, with finite reaction rates. We develop an approximation scheme based on the method of Inter-Particle Distribution Functions (IPDF), which was formerly used for the exact…

Condensed Matter · Physics 2016-08-31 Dexin Zhong , Daniel ben-Avraham

We study a driven many particle system comprising of two identical lanes of finite lengths. On one lane, particles hop diffusively with a bias in a specific direction. On the other lane, particles hop in a specific direction obeying mutual…

Statistical Mechanics · Physics 2015-06-03 Bappa Saha , Sutapa Mukherji

A new approach to the modeling of nonfree particle diffusion is presented. The approach uses a general setup based on geometric graphs (networks of curves), which means that particle diffusion in anything from arrays of barriers and pore…

Statistical Mechanics · Physics 2018-04-05 Niels Buhl

We consider a two-dimensional singularly perturbed transmission problem with two different diffusion coefficients, in a domain with smooth (analytic) boundary. The solution will contain boundary layers only in the part of the domain where…

Analysis of PDEs · Mathematics 2011-04-06 Serge Nicaise , Xenophontos Christos

Porous and heterogeneous materials are found in many applications from composites, membranes, chemical reactors, and other engineered materials to biological matter and natural subsurface structures. In this work we propose an integrated…

Computational Physics · Physics 2019-09-15 Gianluca Boccardo , Eleonora Crevacore , Alberto Passalacqua , Matteo Icardi

While diffusion models have shown great success in image generation, their noise-inverting generative process does not explicitly consider the structure of images, such as their inherent multi-scale nature. Inspired by diffusion models and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Severi Rissanen , Markus Heinonen , Arno Solin

A general method of solving the drift kinetic equation is developed for an axisymmetric magnetic field. Expanding a distribution function in general moments a set of ordinary differential equations are obtained. Successively expanding the…

Plasma Physics · Physics 2023-04-11 Jeong-Young Ji , Eric D. Held , J. Andrew Spencer , Yong-Su Na

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

Hypothesis:Diffusion in confinement is an important fundamental problem with significant implications for applications of supported liquid phases. However, resolving the spatially dependent diffusion coefficient, parallel and perpendicular…

We demonstrate a method for filtering images defined on curved surfaces embedded in 3D. Applications are noise removal and the creation of artistic effects. Our approach relies on in-surface diffusion: we formulate Weickert's edge/coherence…

Numerical Analysis · Mathematics 2014-04-08 Emma Naden , Thomas März , Colin B. Macdonald

A new diffuse interface model for a two-phase flow of two incompressible fluids with different densities is introduced using methods from rational continuum mechanics. The model fulfills local and global dissipation inequalities and is…

Fluid Dynamics · Physics 2011-04-08 H. Abels , H. Garcke , G. Grün

Fusing probabilistic information is a fundamental task in signal and data processing with relevance to many fields of technology and science. In this work, we investigate the fusion of multiple probability density functions (pdfs) of a…

Signal Processing · Electrical Eng. & Systems 2023-01-20 Günther Koliander , Yousef El-Laham , Petar M. Djurić , Franz Hlawatsch

A diffused-interface approach based on the Allen-Cahn phase field equation is developed within a high-order Discontinuous Galerkin framework. The interface capturing technique is based on the balance between explicit diffusion and…

Fluid Dynamics · Physics 2023-06-09 Niccolò Tonicello , Matthias Ihme

We present an ``equation-free'' multiscale approach to the simulation of unsteady diffusion in a random medium. The diffusivity of the medium is modeled as a random field with short correlation length, and the governing equations are cast…

Numerical Analysis · Mathematics 2007-05-23 Dongbin Xiu , Ioannis Kevrekidis

An approximation to the solution of a stochastic parabolic equation is constructed using the Galerkin approximation followed by the Wiener Chaos decomposition. The result is applied to the nonlinear filtering problem for the time…

Probability · Mathematics 2007-06-13 Sergey V. Lototsky

We introduce closed-form transition density expansions for multivariate affine jump-diffusion processes. The expansions rely on a general approximation theory which we develop in weighted Hilbert spaces for random variables which possess…

Statistics Theory · Mathematics 2016-01-07 Damir Filipović , Eberhard Mayerhofer , Paul Schneider

We consider diffusion processes in media with pockets of large diffusivity. The asymptotic behavior of such processes is described when the diffusion coefficients in the pockets tend to infinity. The limiting process is identified as a…

Probability · Mathematics 2017-10-11 Mark Freidlin , Leonid Koralov , Alexander Wentzell

Diffusion models have emerged as powerful generative tools with applications in computer vision and scientific machine learning (SciML), where they have been used to solve large-scale probabilistic inverse problems. Traditionally, these…

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