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The invariance for the equation of fast diffusion in the 2D coordinate space has been proved, and its reduction to the 1D (with respect to the spatial variable) analog is demonstrated. On the basis of these results, new exact…

Mathematical Physics · Physics 2007-05-23 E. I. Semenov

Superluminal propagation is an intrinsic problem in the diffusion equation and has not been effectively addressed for a long time. In this work, a rigorous solution to this issue is obtained under the assumption that particles undergo a…

High Energy Astrophysical Phenomena · Physics 2025-06-25 Xing-Jian Lv , Xiao-Jun Bi , Kun Fang , Peng-Fei Yin , Meng-Jie Zhao

A Riemannian metric bundle G(M) is a fiber bundle over a smooth manifold M, whose fibers are the spaces of symmetric, positive-definite bilinear forms on the tangent spaces of M, which represent the Rieman?nian metrics. In this work, we aim…

Differential Geometry · Mathematics 2023-04-17 Shouvik Datta Choudhury

We present a general mechanistic model of mass diffusion for a composite sphere placed in a large ambient medium. The multi-layer problem is described by a system of diffusion equations coupled via interlayer boundary conditions such as…

Medical Physics · Physics 2018-01-17 Elliot J. Carr , Giuseppe Pontrelli

Diffusion models achieve state-of-the-art performance in various generation tasks. However, their theoretical foundations fall far behind. This paper studies score approximation, estimation, and distribution recovery of diffusion models,…

Machine Learning · Computer Science 2023-02-15 Minshuo Chen , Kaixuan Huang , Tuo Zhao , Mengdi Wang

In this paper we develop a model to describe the diffusion process in a porous medium. For the observed decrease in current yield, we propose other causes than difference in diffusivity, which we consider unaltered by the porous medium. The…

Chemical Physics · Physics 2012-05-10 P. C. T. DÁjello , G. L. Nunes , J. J. Piacentini , L. Lauck

Given a Kaehlerian holomorphic fiber bundle whose fiber is a compact homogeneous Kaehler manifold, we describe the perturbed Hermitian-Einstein equations relative to certain holomorphic vector bundles. With respect to special metrics on the…

Differential Geometry · Mathematics 2007-05-23 Steven B. Bradlow , James F. Glazebrook , Franz W. Kamber

Reflectionless potentials following the prescription of Kay and Moses allow for total transmission of incoming waves of any kinetic energy. The optical analogue of such potentials occur as dielectric stratified media that can offer null…

A new solution to the mono-dimensional diffusion equation for time-variable first kind boundary condition is presented where the time-variable function at the surface is derived proposing a surface saturation model. This solution may be…

Materials Science · Physics 2022-12-08 Guglielmo Macrelli

What is the optimal way to approximate a high-dimensional diffusion process by one in which the coordinates are independent? This paper presents a construction, called the \emph{independent projection}, which is optimal for two natural…

Probability · Mathematics 2024-10-10 Daniel Lacker

High-dimensional data are often assumed to lie on lower-dimensional manifolds. We study how to construct diffusion processes on this data manifold using only point cloud samples and without access to charts, projections, or other geometric…

Machine Learning · Computer Science 2026-05-21 Victor Kawasaki-Borruat , Clara Grotehans , Pierre Vandergheynst , Adam Gosztolai

The advection-diffusion equation can be approximated by a one-dimensional diffusion equation in Lagrangian coordinates along the directions of compression of fluid elements (the stable manifold). This result holds in any number of…

Chaotic Dynamics · Physics 2009-11-07 Jean-Luc Thiffeault

In this note, we demonstrated for the first time that one can derive an expression for the effective diffusion coefficient, equal to the Lifson-Jackson formula, using a subsequent homogenization of the 1D reaction-diffusion-advection…

Chemical Physics · Physics 2016-08-03 Steffen Martens

We establish the zero-diffusion limit for both continuous and discrete aggregation models over convex and bounded domains. Compared with a similar zero-diffusion limit derived in [44], our approach is different and relies on a coupling…

Analysis of PDEs · Mathematics 2018-09-07 Razvan C. Fetecau , Hui Huang , Daniel Messenger , Weiran Sun

Mixing a passive scalar field by stirring can be measured in a variety of ways including tracer particle dispersion, via the flux-gradient relationship, or by suppression of scalar concentration variations in the presence of inhomogeneous…

Fluid Dynamics · Physics 2010-11-08 Zhi Lin , Katarína Bodová , Charles R. Doering

This paper introduces a novel, robust, and computationally efficient framework for high-quality quadrilateral mesh generation on general two-dimensional domains. The core of the proposed approach is a novel method for computing cross fields…

Numerical Analysis · Mathematics 2026-05-28 Jingwen Dai , Zhonghua Qiao , Dong Wang

Optical micro-manipulation techniques has evolved into powerful tools to efficiently steer the motion of microscopical particles on periodic and quasi-periodic potentials, driven by the external electromagnetic field. Here, the dynamics of…

Atomic Physics · Physics 2018-11-13 Aliezer Martínez-Mesa , Llinersy Uranga Piña

The fiber bundle model is essentially an array of elements that break when sufficient load is applied on them. With a local loading mechanism, this can serve as a model for a one-dimensional interface separating the broken and unbroken…

Statistical Mechanics · Physics 2016-11-09 Soumyajyoti Biswas , Lucas Goehring

An upper bound on the mixing efficiency is derived for a passive scalar under the influence of advection and diffusion with a body source. For a given stirring velocity field, the mixing efficiency is measured in terms of an equivalent…

Fluid Dynamics · Physics 2007-12-12 Jean-Luc Thiffeault , Charles R. Doering , John D. Gibbon

Recent advances in diffusion models have demonstrated their remarkable ability to capture complex image distributions, but the geometric properties of the learned data manifold remain poorly understood. We address this gap by introducing a…

Machine Learning · Computer Science 2025-10-13 Simone Azeglio , Arianna Di Bernardo